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Sample records for techniques monte carlo

  1. Variational Monte Carlo Technique

    Indian Academy of Sciences (India)

    ias

    RESONANCE ⎜ August 2014. GENERAL ⎜ ARTICLE. Variational Monte Carlo Technique. Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. Keywords. Variational methods, Monte. Carlo techniques, harmonic os- cillators, quantum mechanical systems. Sukanta Deb is an. Assistant Professor in the.

  2. Variational Monte Carlo Technique

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...

  3. Variational Monte Carlo Technique

    Indian Academy of Sciences (India)

    ias

    nonprobabilistic) problem [5]. ... In quantum mechanics, the MC methods are used to simulate many-particle systems us- ing random ...... D Ceperley, G V Chester and M H Kalos, Monte Carlo simulation of a many-fermion study, Physical Review Vol.

  4. Monte Carlo techniques in radiation therapy

    CERN Document Server

    Verhaegen, Frank

    2013-01-01

    Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data. With Monte Carlo-based treatment planning tools now available from commercial vendors, a complete transition to Monte Carlo-based dose calculation methods in radiotherapy could likely take place in the next decade. Monte Carlo Techniques in Radiation Therapy explores the use of Monte Carlo methods for modeling various features of internal and external radiation sources, including light ion beams. The book-the first of its kind-addresses applications of the Monte Carlo particle transport simulation technique in radiation therapy, mainly focusing on external beam radiotherapy and brachytherapy. It presents the mathematical and technical aspects of the methods in particle transport simulations. The book also discusses the modeling of medical linacs and other irradiation devices; issues specific...

  5. Monte Carlo techniques for analyzing deep penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

    1985-01-01

    A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs

  6. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.

    2016-11-29

    These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations

  7. Monte Carlo techniques in diagnostic and therapeutic nuclear medicine

    International Nuclear Information System (INIS)

    Zaidi, H.

    2002-01-01

    Monte Carlo techniques have become one of the most popular tools in different areas of medical radiation physics following the development and subsequent implementation of powerful computing systems for clinical use. In particular, they have been extensively applied to simulate processes involving random behaviour and to quantify physical parameters that are difficult or even impossible to calculate analytically or to determine by experimental measurements. The use of the Monte Carlo method to simulate radiation transport turned out to be the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides. There is broad consensus in accepting that the earliest Monte Carlo calculations in medical radiation physics were made in the area of nuclear medicine, where the technique was used for dosimetry modelling and computations. Formalism and data based on Monte Carlo calculations, developed by the Medical Internal Radiation Dose (MIRD) committee of the Society of Nuclear Medicine, were published in a series of supplements to the Journal of Nuclear Medicine, the first one being released in 1968. Some of these pamphlets made extensive use of Monte Carlo calculations to derive specific absorbed fractions for electron and photon sources uniformly distributed in organs of mathematical phantoms. Interest in Monte Carlo-based dose calculations with β-emitters has been revived with the application of radiolabelled monoclonal antibodies to radioimmunotherapy. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the medical physics

  8. Introduction to Monte Carlo methods: sampling techniques and random numbers

    International Nuclear Information System (INIS)

    Bhati, Sharda; Patni, H.K.

    2009-01-01

    The Monte Carlo method describes a very broad area of science, in which many processes, physical systems and phenomena that are statistical in nature and are difficult to solve analytically are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions. As the number of individual events (called histories) is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. Assuming that the behavior of physical system can be described by probability density functions, then the Monte Carlo simulation can proceed by sampling from these probability density functions, which necessitates a fast and effective way to generate random numbers uniformly distributed on the interval (0,1). Particles are generated within the source region and are transported by sampling from probability density functions through the scattering media until they are absorbed or escaped the volume of interest. The outcomes of these random samplings or trials, must be accumulated or tallied in an appropriate manner to produce the desired result, but the essential characteristic of Monte Carlo is the use of random sampling techniques to arrive at a solution of the physical problem. The major components of Monte Carlo methods for random sampling for a given event are described in the paper

  9. Analysis of neutron-reflectometry data by Monte Carlo technique

    CERN Document Server

    Singh, S

    2002-01-01

    Neutron-reflectometry data is collected in momentum space. The real-space information is extracted by fitting a model for the structure of a thin-film sample. We have attempted a Monte Carlo technique to extract the structure of the thin film. In this technique we change the structural parameters of the thin film by simulated annealing based on the Metropolis algorithm. (orig.)

  10. A decorrelation technique for iterated source Monte Carlo calculations

    International Nuclear Information System (INIS)

    Nease, Brian R.; Dumonteil, Eric

    2010-01-01

    In Monte Carlo (MC) iterated source calculations, the distribution of starter neutrons in a given cycle is based on the distribution of fission sites from the previous cycle. The consequence is that the neutron distribution and corresponding tallies in one cycle are correlated to those in successive cycles. Most MC codes do not account for these correlations, resulting in underestimation of the real variance. In this work, we propose a technique to reduce the correlations between MC cycles by modifying the power iteration process. To achieve this objective, we have developed two new methods. The first method is an orthogonalization procedure that removes the eigenmode corresponding to the largest eigenvalue. Since this method relies on the availability of the k-eigenvalues and corresponding eigenmodes, we have developed the second method, which calculates an unbiased estimator of the fission matrix. This estimator is novel because it does not require saving the source distribution from previous cycles. In this paper, we first show how the correlations are related to the eigenmodes of the fission matrix, then develop the theory behind the unbiased fission matrix estimator, and, finally, develop the decorrelation technique. These methods were implemented into a small mono-energetic research code as well as the continuous-energy Tripoli4 Monte Carlo code. Many results are provided using both codes. (author)

  11. Monte Carlo techniques for real-time quantum dynamics

    International Nuclear Information System (INIS)

    Dowling, Mark R.; Davis, Matthew J.; Drummond, Peter D.; Corney, Joel F.

    2007-01-01

    The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the 'weight', and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The Monte-Carlo algorithms are applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed

  12. Application of biasing techniques to the contributon Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Dubi, A.; Gerstl, S.A.W.

    1980-01-01

    Recently, a new Monte Carlo Method called the Contribution Monte Carlo Method was developed. The method is based on the theory of contributions, and uses a new receipe for estimating target responses by a volume integral over the contribution current. The analog features of the new method were discussed in previous publications. The application of some biasing methods to the new contribution scheme is examined here. A theoretical model is developed that enables an analytic prediction of the benefit to be expected when these biasing schemes are applied to both the contribution method and regular Monte Carlo. This model is verified by a variety of numerical experiments and is shown to yield satisfying results, especially for deep-penetration problems. Other considerations regarding the efficient use of the new method are also discussed, and remarks are made as to the application of other biasing methods. 14 figures, 1 tables.

  13. The Use of Monte Carlo Techniques to Teach Probability.

    Science.gov (United States)

    Newell, G. J.; MacFarlane, J. D.

    1985-01-01

    Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…

  14. Codified Design of Steel Structures Using Monte Carlo Techniques

    Czech Academy of Sciences Publication Activity Database

    Marek, Pavel; Guštar, M.; Anagnos, T.

    1999-01-01

    Roč. 52, č. 1 (1999), s. 69-82 ISSN 0143-974X R&D Projects: GA ČR GA103/98/0215 Keywords : reliability * limit states * failure * probability * loading * resistance * service ability * Monte Carlo Subject RIV: JM - Building Engineering Impact factor: 0.341, year: 1999

  15. Error reduction techniques for Monte Carlo neutron transport calculations

    International Nuclear Information System (INIS)

    Ju, J.H.W.

    1981-01-01

    Monte Carlo methods have been widely applied to problems in nuclear physics, mathematical reliability, communication theory, and other areas. The work in this thesis is developed mainly with neutron transport applications in mind. For nuclear reactor and many other applications, random walk processes have been used to estimate multi-dimensional integrals and obtain information about the solution of integral equations. When the analysis is statistically based such calculations are often costly, and the development of efficient estimation techniques plays a critical role in these applications. All of the error reduction techniques developed in this work are applied to model problems. It is found that the nearly optimal parameters selected by the analytic method for use with GWAN estimator are nearly identical to parameters selected by the multistage method. Modified path length estimation (based on the path length importance measure) leads to excellent error reduction in all model problems examined. Finally, it should be pointed out that techniques used for neutron transport problems may be transferred easily to other application areas which are based on random walk processes. The transport problems studied in this dissertation provide exceptionally severe tests of the error reduction potential of any sampling procedure. It is therefore expected that the methods of this dissertation will prove useful in many other application areas

  16. Characterization of decommissioned reactor internals: Monte Carlo analysis technique

    International Nuclear Information System (INIS)

    Reid, B.D.; Love, E.F.; Luksic, A.T.

    1993-03-01

    This study discusses computer analysis techniques for determining activation levels of irradiated reactor component hardware to yield data for the Department of Energy's Greater-Than-Class C Low-Level Radioactive Waste Program. The study recommends the Monte Carlo Neutron/Photon (MCNP) computer code as the best analysis tool for this application and compares the technique to direct sampling methodology. To implement the MCNP analysis, a computer model would be developed to reflect the geometry, material composition, and power history of an existing shutdown reactor. MCNP analysis would then be performed using the computer model, and the results would be validated by comparison to laboratory analysis results from samples taken from the shutdown reactor. The report estimates uncertainties for each step of the computational and laboratory analyses; the overall uncertainty of the MCNP results is projected to be ±35%. The primary source of uncertainty is identified as the material composition of the components, and research is suggested to address that uncertainty

  17. A Monte Carlo simulation technique to determine the optimal portfolio

    Directory of Open Access Journals (Sweden)

    Hassan Ghodrati

    2014-03-01

    Full Text Available During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR, which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.

  18. Monte Carlo simulation of tomography techniques using the platform Gate

    International Nuclear Information System (INIS)

    Barbouchi, Asma

    2007-01-01

    Simulations play a key role in functional imaging, with applications ranging from scanner design, scatter correction, protocol optimisation. GATE (Geant4 for Application Tomography Emission) is a platform for Monte Carlo Simulation. It is based on Geant4 to generate and track particles, to model geometry and physics process. Explicit modelling of time includes detector motion, time of flight, tracer kinetics. Interfaces to voxellised models and image reconstruction packages improve the integration of GATE in the global modelling cycle. In this work Monte Carlo simulations are used to understand and optimise the gamma camera's performances. We study the effect of the distance between source and collimator, the diameter of the holes and the thick of the collimator on the spatial resolution, energy resolution and efficiency of the gamma camera. We also study the reduction of simulation's time and implement a model of left ventricle in GATE. (Author). 7 refs

  19. MORSE Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Cramer, S.N.

    1984-01-01

    The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described.

  20. MORSE Monte Carlo code

    International Nuclear Information System (INIS)

    Cramer, S.N.

    1984-01-01

    The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described

  1. Monte Carlo simulation techniques for predicting annual power production

    International Nuclear Information System (INIS)

    Cross, J.P.; Bulandr, P.J.

    1991-01-01

    As the owner and operator of a number of small to mid-sized hydroelectric sites, STS HydroPower has been faced with the need to accurately predict anticipated hydroelectric revenues over a period of years. The typical approach to this problem has been to look at each site from a mathematical deterministic perspective and evaluate the annual production from historic streamflows. Average annual production is simply taken to be the area under the flow duration curve defined by the operating and design characteristics of the selected turbines. Minimum annual production is taken to be a historic dry year scenario and maximum production is viewed as power generated under the most ideal of conditions. Such an approach creates two problems. First, in viewing the characteristics of a single site, it does not take into account the probability of such an event occurring. Second, in viewing all sites in a single organization's portfolio together, it does not reflect the varying flow conditions at the different sites. This paper attempts to address the first of these two concerns, that being the creation of a simulation model utilizing the Monte Carlo method at a single site. The result of the analysis is a picture of the production at the site that is both a better representation of anticipated conditions and defined probabilistically

  2. Household water use and conservation models using Monte Carlo techniques

    Directory of Open Access Journals (Sweden)

    R. Cahill

    2013-10-01

    Full Text Available The increased availability of end use measurement studies allows for mechanistic and detailed approaches to estimating household water demand and conservation potential. This study simulates water use in a single-family residential neighborhood using end-water-use parameter probability distributions generated from Monte Carlo sampling. This model represents existing water use conditions in 2010 and is calibrated to 2006–2011 metered data. A two-stage mixed integer optimization model is then developed to estimate the least-cost combination of long- and short-term conservation actions for each household. This least-cost conservation model provides an estimate of the upper bound of reasonable conservation potential for varying pricing and rebate conditions. The models were adapted from previous work in Jordan and are applied to a neighborhood in San Ramon, California in the eastern San Francisco Bay Area. The existing conditions model produces seasonal use results very close to the metered data. The least-cost conservation model suggests clothes washer rebates are among most cost-effective rebate programs for indoor uses. Retrofit of faucets and toilets is also cost-effective and holds the highest potential for water savings from indoor uses. This mechanistic modeling approach can improve understanding of water demand and estimate cost-effectiveness of water conservation programs.

  3. Markov Chain Monte Carlo

    Indian Academy of Sciences (India)

    . Keywords. Gibbs sampling, Markov Chain. Monte Carlo, Bayesian inference, stationary distribution, conver- gence, image restoration. Arnab Chakraborty. We describe the mathematics behind the Markov. Chain Monte Carlo method of ...

  4. Automated importance generation and biasing techniques for Monte Carlo shielding techniques by the TRIPOLI-3 code

    International Nuclear Information System (INIS)

    Both, J.P.; Nimal, J.C.; Vergnaud, T.

    1990-01-01

    We discuss an automated biasing procedure for generating the parameters necessary to achieve efficient Monte Carlo biasing shielding calculations. The biasing techniques considered here are exponential transform and collision biasing deriving from the concept of the biased game based on the importance function. We use a simple model of the importance function with exponential attenuation as the distance to the detector increases. This importance function is generated on a three-dimensional mesh including geometry and with graph theory algorithms. This scheme is currently being implemented in the third version of the neutron and gamma ray transport code TRIPOLI-3. (author)

  5. Monte Carlo methods

    CERN Document Server

    Kalos, Melvin H

    2008-01-01

    This introduction to Monte Carlo methods seeks to identify and study the unifying elements that underlie their effective application. Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research.The book focuses on two basic themes: The first is the importance of random walks as they occur both in natural stochastic systems and in their relationship to integral and differential equations. The second theme is that of variance reduction in general and importance sampling in particular as a technique for efficient use of the methods. Random walks are introduced with an elementary example in which the modeling of radiation transport arises directly from a schematic probabilistic description of the interaction of radiation with matter. Building on this example, the relationship between random walks and integral equations is outlined

  6. Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox

    DEFF Research Database (Denmark)

    Nonejad, Nima

    This paper details Particle Markov chain Monte Carlo techniques for analysis of unobserved component time series models using several economic data sets. PMCMC combines the particle filter with the Metropolis-Hastings algorithm. Overall PMCMC provides a very compelling, computationally fast...

  7. Application of artificial intelligence techniques to the acceleration of Monte Carlo transport calculations

    International Nuclear Information System (INIS)

    Maconald, J.L.; Cashwell, E.D.

    1978-09-01

    The techniques of learning theory and pattern recognition are used to learn splitting surface locations for the Monte Carlo neutron transport code MCN. A study is performed to determine default values for several pattern recognition and learning parameters. The modified MCN code is used to reduce computer cost for several nontrivial example problems

  8. Exploring Monte Carlo methods

    CERN Document Server

    Dunn, William L

    2012-01-01

    Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble

  9. Monte Carlo methods

    Directory of Open Access Journals (Sweden)

    Bardenet Rémi

    2013-07-01

    Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.

  10. Monte Carlo alpha calculation

    Energy Technology Data Exchange (ETDEWEB)

    Brockway, D.; Soran, P.; Whalen, P.

    1985-01-01

    A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.

  11. Monte Carlo Methods in Physics

    International Nuclear Information System (INIS)

    Santoso, B.

    1997-01-01

    Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained

  12. Handbook of Monte Carlo methods

    National Research Council Canada - National Science Library

    Kroese, Dirk P; Taimre, Thomas; Botev, Zdravko I

    2011-01-01

    ... in rapid succession, the staggering number of related techniques, ideas, concepts and algorithms makes it difficult to maintain an overall picture of the Monte Carlo approach. This book attempts to encapsulate the emerging dynamics of this field of study"--

  13. Finite element model updating using the shadow hybrid Monte Carlo technique

    Science.gov (United States)

    Boulkaibet, I.; Mthembu, L.; Marwala, T.; Friswell, M. I.; Adhikari, S.

    2015-02-01

    Recent research in the field of finite element model updating (FEM) advocates the adoption of Bayesian analysis techniques to dealing with the uncertainties associated with these models. However, Bayesian formulations require the evaluation of the Posterior Distribution Function which may not be available in analytical form. This is the case in FEM updating. In such cases sampling methods can provide good approximations of the Posterior distribution when implemented in the Bayesian context. Markov Chain Monte Carlo (MCMC) algorithms are the most popular sampling tools used to sample probability distributions. However, the efficiency of these algorithms is affected by the complexity of the systems (the size of the parameter space). The Hybrid Monte Carlo (HMC) offers a very important MCMC approach to dealing with higher-dimensional complex problems. The HMC uses the molecular dynamics (MD) steps as the global Monte Carlo (MC) moves to reach areas of high probability where the gradient of the log-density of the Posterior acts as a guide during the search process. However, the acceptance rate of HMC is sensitive to the system size as well as the time step used to evaluate the MD trajectory. To overcome this limitation we propose the use of the Shadow Hybrid Monte Carlo (SHMC) algorithm. The SHMC algorithm is a modified version of the Hybrid Monte Carlo (HMC) and designed to improve sampling for large-system sizes and time steps. This is done by sampling from a modified Hamiltonian function instead of the normal Hamiltonian function. In this paper, the efficiency and accuracy of the SHMC method is tested on the updating of two real structures; an unsymmetrical H-shaped beam structure and a GARTEUR SM-AG19 structure and is compared to the application of the HMC algorithm on the same structures.

  14. Source of statistical noises in the Monte Carlo sampling techniques for coherently scattered photons

    OpenAIRE

    Muhammad, Wazir; Lee, Sang Hoon

    2012-01-01

    Detailed comparisons of the predictions of the Relativistic Form Factors (RFFs) and Modified Form Factors (MFFs) and their advantages and shortcomings in calculating elastic scattering cross sections can be found in the literature. However, the issues related to their implementation in the Monte Carlo (MC) sampling for coherently scattered photons is still under discussion. Secondly, the linear interpolation technique (LIT) is a popular method to draw the integrated values of squared RFFs/MFF...

  15. Validation of variance reduction techniques in Mediso (SPIRIT DH-V) SPECT system by Monte Carlo

    International Nuclear Information System (INIS)

    Rodriguez Marrero, J. P.; Diaz Garcia, A.; Gomez Facenda, A.

    2015-01-01

    Monte Carlo simulation of nuclear medical imaging systems is a widely used method for reproducing their operation in a real clinical environment, There are several Single Photon Emission Tomography (SPECT) systems in Cuba. For this reason it is clearly necessary to introduce a reliable and fast simulation platform in order to obtain consistent image data. This data will reproduce the original measurements conditions. In order to fulfill these requirements Monte Carlo platform GAMOS (Geant4 Medicine Oriented Architecture for Applications) have been used. Due to the very size and complex configuration of parallel hole collimators in real clinical SPECT systems, Monte Carlo simulation usually consumes excessively high time and computing resources. main goal of the present work is to optimize the efficiency of calculation by means of new GAMOS functionality. There were developed and validated two GAMOS variance reduction techniques to speed up calculations. These procedures focus and limit transport of gamma quanta inside the collimator. The obtained results were asses experimentally in Mediso (SPIRIT DH-V) SPECT system. Main quality control parameters, such as sensitivity and spatial resolution were determined. Differences of 4.6% sensitivity and 8.7% spatial resolution were reported against manufacturer values. Simulation time was decreased up to 650 times. Using these techniques it was possible to perform several studies in almost 8 hours each. (Author)

  16. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay

    2017-04-24

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  17. Monte Carlo simulation for IRRMA

    International Nuclear Information System (INIS)

    Gardner, R.P.; Liu Lianyan

    2000-01-01

    Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors

  18. Timesaving techniques for decision of electron-molecule collisions in Monte Carlo simulation of electrical discharges

    International Nuclear Information System (INIS)

    Sugawara, Hirotake; Mori, Naoki; Sakai, Yosuke; Suda, Yoshiyuki

    2007-01-01

    Techniques to reduce the computational load for determination of electron-molecule collisions in Monte Carlo simulations of electrical discharges have been presented. By enhancing the detection efficiency of the no-collision case in the decision scheme of the collisional events, we can decrease the frequency of access to time-consuming subroutines to calculate the electron collision cross sections of the gas molecules for obtaining the collision probability. A benchmark test and an estimation to evaluate the present techniques have shown a practical timesaving efficiency

  19. An efficient interpolation technique for jump proposals in reversible-jump Markov chain Monte Carlo calculations

    Science.gov (United States)

    Farr, W. M.; Mandel, I.; Stevens, D.

    2015-06-01

    Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model selection, but it suffers from a fundamental difficulty and it requires jumps between model parameter spaces, but cannot efficiently explore both parameter spaces at once. Thus, a naive jump between parameter spaces is unlikely to be accepted in the Markov chain Monte Carlo (MCMC) algorithm and convergence is correspondingly slow. Here, we demonstrate an interpolation technique that uses samples from single-model MCMCs to propose intermodel jumps from an approximation to the single-model posterior of the target parameter space. The interpolation technique, based on a kD-tree data structure, is adaptive and efficient in modest dimensionality. We show that our technique leads to improved convergence over naive jumps in an RJMCMC, and compare it to other proposals in the literature to improve the convergence of RJMCMCs. We also demonstrate the use of the same interpolation technique as a way to construct efficient "global" proposal distributions for single-model MCMCs without prior knowledge of the structure of the posterior distribution, and discuss improvements that permit the method to be used in higher dimensional spaces efficiently.

  20. Monte Carlo codes and Monte Carlo simulator program

    International Nuclear Information System (INIS)

    Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.

    1990-03-01

    Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)

  1. Efficient data management techniques implemented in the Karlsruhe Monte Carlo code KAMCCO

    International Nuclear Information System (INIS)

    Arnecke, G.; Borgwaldt, H.; Brandl, V.; Lalovic, M.

    1974-01-01

    The Karlsruhe Monte Carlo Code KAMCCO is a forward neutron transport code with an eigenfunction and a fixed source option, including time-dependence. A continuous energy model is combined with a detailed representation of neutron cross sections, based on linear interpolation, Breit-Wigner resonances and probability tables. All input is processed into densely packed, dynamically addressed parameter fields and networks of pointers (addresses). Estimation routines are decoupled from random walk and analyze a storage region with sample records. This technique leads to fast execution with moderate storage requirements and without any I/O-operations except in the input and output stages. 7 references. (U.S.)

  2. Microwave transport in EBT distribution manifolds using Monte Carlo ray-tracing techniques

    International Nuclear Information System (INIS)

    Lillie, R.A.; White, T.L.; Gabriel, T.A.; Alsmiller, R.G. Jr.

    1983-01-01

    Ray tracing Monte Carlo calculations have been carried out using an existing Monte Carlo radiation transport code to obtain estimates of the microsave power exiting the torus coupling links in EPT microwave manifolds. The microwave power loss and polarization at surface reflections were accounted for by treating the microwaves as plane waves reflecting off plane surfaces. Agreement on the order of 10% was obtained between the measured and calculated output power distribution for an existing EBT-S toroidal manifold. A cost effective iterative procedure utilizing the Monte Carlo history data was implemented to predict design changes which could produce increased manifold efficiency and improved output power uniformity

  3. The Virtual Monte Carlo

    CERN Document Server

    Hrivnacova, I; Berejnov, V V; Brun, R; Carminati, F; Fassò, A; Futo, E; Gheata, A; Caballero, I G; Morsch, Andreas

    2003-01-01

    The concept of Virtual Monte Carlo (VMC) has been developed by the ALICE Software Project to allow different Monte Carlo simulation programs to run without changing the user code, such as the geometry definition, the detector response simulation or input and output formats. Recently, the VMC classes have been integrated into the ROOT framework, and the other relevant packages have been separated from the AliRoot framework and can be used individually by any other HEP project. The general concept of the VMC and its set of base classes provided in ROOT will be presented. Existing implementations for Geant3, Geant4 and FLUKA and simple examples of usage will be described.

  4. The electron transport problem sampling by Monte Carlo individual collision technique

    International Nuclear Information System (INIS)

    Androsenko, P.A.; Belousov, V.I.

    2005-01-01

    The problem of electron transport is of most interest in all fields of the modern science. To solve this problem the Monte Carlo sampling has to be used. The electron transport is characterized by a large number of individual interactions. To simulate electron transport the 'condensed history' technique may be used where a large number of collisions are grouped into a single step to be sampled randomly. Another kind of Monte Carlo sampling is the individual collision technique. In comparison with condensed history technique researcher has the incontestable advantages. For example one does not need to give parameters altered by condensed history technique like upper limit for electron energy, resolution, number of sub-steps etc. Also the condensed history technique may lose some very important tracks of electrons because of its limited nature by step parameters of particle movement and due to weakness of algorithms for example energy indexing algorithm. There are no these disadvantages in the individual collision technique. This report presents some sampling algorithms of new version BRAND code where above mentioned technique is used. All information on electrons was taken from Endf-6 files. They are the important part of BRAND. These files have not been processed but directly taken from electron information source. Four kinds of interaction like the elastic interaction, the Bremsstrahlung, the atomic excitation and the atomic electro-ionization were considered. In this report some results of sampling are presented after comparison with analogs. For example the endovascular radiotherapy problem (P2) of QUADOS2002 was presented in comparison with another techniques that are usually used. (authors)

  5. Development of self-learning Monte Carlo technique for more efficient modeling of nuclear logging measurements

    International Nuclear Information System (INIS)

    Zazula, J.M.

    1988-01-01

    The self-learning Monte Carlo technique has been implemented to the commonly used general purpose neutron transport code MORSE, in order to enhance sampling of the particle histories that contribute to a detector response. The parameters of all the biasing techniques available in MORSE, i.e. of splitting, Russian roulette, source and collision outgoing energy importance sampling, path length transformation and additional biasing of the source angular distribution are optimized. The learning process is iteratively performed after each batch of particles, by retrieving the data concerning the subset of histories that passed the detector region and energy range in the previous batches. This procedure has been tested on two sample problems in nuclear geophysics, where an unoptimized Monte Carlo calculation is particularly inefficient. The results are encouraging, although the presented method does not directly minimize the variance and the convergence of our algorithm is restricted by the statistics of successful histories from previous random walk. Further applications for modeling of the nuclear logging measurements seem to be promising. 11 refs., 2 figs., 3 tabs. (author)

  6. Markov Chain Monte Carlo

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.

  7. Monte Carlo calculations of nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Pieper, S.C. [Argonne National Lab., IL (United States). Physics Div.

    1997-10-01

    Nuclear many-body calculations have the complication of strong spin- and isospin-dependent potentials. In these lectures the author discusses the variational and Green`s function Monte Carlo techniques that have been developed to address this complication, and presents a few results.

  8. Optimizing Availability of a Framework in Series Configuration Utilizing Markov Model and Monte Carlo Simulation Techniques

    Directory of Open Access Journals (Sweden)

    Mansoor Ahmed Siddiqui

    2017-06-01

    Full Text Available This research work is aimed at optimizing the availability of a framework comprising of two units linked together in series configuration utilizing Markov Model and Monte Carlo (MC Simulation techniques. In this article, effort has been made to develop a maintenance model that incorporates three distinct states for each unit, while taking into account their different levels of deterioration. Calculations are carried out using the proposed model for two distinct cases of corrective repair, namely perfect and imperfect repairs, with as well as without opportunistic maintenance. Initially, results are accomplished using an analytical technique i.e., Markov Model. Validation of the results achieved is later carried out with the help of MC Simulation. In addition, MC Simulation based codes also work well for the frameworks that follow non-exponential failure and repair rates, and thus overcome the limitations offered by the Markov Model.

  9. Monte Carlo simulations of neutron scattering instruments

    International Nuclear Information System (INIS)

    Aestrand, Per-Olof; Copenhagen Univ.; Lefmann, K.; Nielsen, K.

    2001-01-01

    A Monte Carlo simulation is an important computational tool used in many areas of science and engineering. The use of Monte Carlo techniques for simulating neutron scattering instruments is discussed. The basic ideas, techniques and approximations are presented. Since the construction of a neutron scattering instrument is very expensive, Monte Carlo software used for design of instruments have to be validated and tested extensively. The McStas software was designed with these aspects in mind and some of the basic principles of the McStas software will be discussed. Finally, some future prospects are discussed for using Monte Carlo simulations in optimizing neutron scattering experiments. (R.P.)

  10. Peelle's pertinent puzzle using the Monte Carlo technique

    Energy Technology Data Exchange (ETDEWEB)

    Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Burr, Thomas [Los Alamos National Laboratory; Pan, Feng [Los Alamos National Laboratory

    2009-01-01

    We try to understand the long-standing problem of the Peelle's Pertinent Puzzle (PPP) using the Monte Carlo technique. We allow the probability density functions to be any kind of form to assume the impact of distribution, and obtain the least-squares solution directly from numerical simulations. We found that the standard least squares method gives the correct answer if a weighting function is properly provided. Results from numerical simulations show that the correct answer of PPP is 1.1 {+-} 0.25 if the common error is multiplicative. The thought-provoking answer of 0.88 is also correct, if the common error is additive, and if the error is proportional to the measured values. The least squares method correctly gives us the most probable case, where the additive component has a negative value. Finally, the standard method fails for PPP due to a distorted (non Gaussian) joint distribution.

  11. Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter

    Directory of Open Access Journals (Sweden)

    Yazhao Wang

    2014-01-01

    Full Text Available This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.

  12. Finding the Better of Two Similar Designs by Monte Carlo Techniques

    DEFF Research Database (Denmark)

    Becker, Peter W.

    1974-01-01

    . The fraction which meets or exceeds the criterion is called the yield. Monte Carlo techniques can be used to simulate the population of systems and thus to estimate the ranking of two designs. The first result presented in the paper is a derivation of the probability that one design is better than another......, along with confidence limits for that probability. If the two designs are topologically the same, i.e., they differ only in the nominal values and actual distributions of true parameter values, then the same set of random numbers can be used for one simulation of each design. Due to the similarity...... there may be a positive correlation between the 2 results which can then be used to narrow the confidence limits from the crude method mentioned above. The second result is a derivation of these narrow confidence limits....

  13. Monte Carlo techniques to analyse the electrical mismatch losses in large-scale photovoltaic generators

    Energy Technology Data Exchange (ETDEWEB)

    Iannone, F.; Sarno, A. [ENEA, Portici (Italy). Research Center; Noviello, G. [ENEA, Manfredonia (Italy). Mt. Aquilone Test-Side

    1998-02-01

    In large-scale photovoltaic generators, the arrangement of modules with different electrical characteristics could involve a considerable mismatch between the single components resulting in a power loss. This means the actual power is less than the sum of the maximum output powers of the individual PV modules, operating at the same irradiance-temperature conditions. To reduce the mismatch losses and to calculate it under operating conditions, a statistical approach based on Monte Carlo simulation techniques, has been developed and validated. The simulation model shows that it is possible to meet the required mismatch level, with a random arrangement, starting from a modules population characterized in terms of short circuit current, I{sub SC} and open circuit voltage V{sub OC}, by a probability density function with a imposed variance. The method has been successfully applied for a 100 kWp standard unit photovoltaic generator, the computational results have shown good agreement with the experimental data. (author)

  14. Wormhole Hamiltonian Monte Carlo

    Science.gov (United States)

    Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak

    2015-01-01

    In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function. PMID:25861551

  15. Wormhole Hamiltonian Monte Carlo.

    Science.gov (United States)

    Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak

    2014-07-31

    In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function.

  16. Monte Carlo Techniques for the Comprehensive Modeling of Isotopic Inventories in Future Nuclear Systems and Fuel Cycles. Final Report

    International Nuclear Information System (INIS)

    Paul P.H. Wilson

    2005-01-01

    The development of Monte Carlo techniques for isotopic inventory analysis has been explored in order to facilitate the modeling of systems with flowing streams of material through varying neutron irradiation environments. This represents a novel application of Monte Carlo methods to a field that has traditionally relied on deterministic solutions to systems of first-order differential equations. The Monte Carlo techniques were based largely on the known modeling techniques of Monte Carlo radiation transport, but with important differences, particularly in the area of variance reduction and efficiency measurement. The software that was developed to implement and test these methods now provides a basis for validating approximate modeling techniques that are available to deterministic methodologies. The Monte Carlo methods have been shown to be effective in reproducing the solutions of simple problems that are possible using both stochastic and deterministic methods. The Monte Carlo methods are also effective for tracking flows of materials through complex systems including the ability to model removal of individual elements or isotopes in the system. Computational performance is best for flows that have characteristic times that are large fractions of the system lifetime. As the characteristic times become short, leading to thousands or millions of passes through the system, the computational performance drops significantly. Further research is underway to determine modeling techniques to improve performance within this range of problems. This report describes the technical development of Monte Carlo techniques for isotopic inventory analysis. The primary motivation for this solution methodology is the ability to model systems of flowing material being exposed to varying and stochastically varying radiation environments. The methodology was developed in three stages: analog methods which model each atom with true reaction probabilities (Section 2), non-analog methods

  17. Fundamentals of Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-16

    This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

  18. Wormhole Hamiltonian Monte Carlo

    OpenAIRE

    Lan, S; Streets, J; Shahbaba, B

    2014-01-01

    Copyright © 2014, Association for the Advancement of Artificial Intelligence. In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, espe...

  19. Microcanonical Monte Carlo

    International Nuclear Information System (INIS)

    Creutz, M.

    1986-01-01

    The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena

  20. EDITORIAL: International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification

    Science.gov (United States)

    Verhaegen, Frank; Seuntjens, Jan

    2008-03-01

    Monte Carlo particle transport techniques offer exciting tools for radiotherapy research, where they play an increasingly important role. Topics of research related to clinical applications range from treatment planning, motion and registration studies, brachytherapy, verification imaging and dosimetry. The International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification took place in a hotel in Montreal in French Canada, from 29 May-1 June 2007, and was the third workshop to be held on a related topic, which now seems to have become a tri-annual event. About one hundred workers from many different countries participated in the four-day meeting. Seventeen experts in the field were invited to review topics and present their latest work. About half of the audience was made up by young graduate students. In a very full program, 57 papers were presented and 10 posters were on display during most of the meeting. On the evening of the third day a boat trip around the island of Montreal allowed participants to enjoy the city views, and to sample the local cuisine. The topics covered at the workshop included the latest developments in the most popular Monte Carlo transport algorithms, fast Monte Carlo, statistical issues, source modeling, MC treatment planning, modeling of imaging devices for treatment verification, registration and deformation of images and a sizeable number of contributions on brachytherapy. In this volume you will find 27 short papers resulting from the workshop on a variety of topics, some of them on very new stuff such as graphics processing units for fast computing, PET modeling, dual-energy CT, calculations in dynamic phantoms, tomotherapy devices, . . . . We acknowledge the financial support of the National Cancer Institute of Canada, the Institute of Cancer Research of the Canadian Institutes of Health Research, the Association Québécoise des Physicien(ne)s Médicaux Clinique, the Institute of Physics, and Medical

  1. Implementation of variance-reduction techniques for Monte Carlo nuclear logging calculations with neutron sources

    NARCIS (Netherlands)

    Maucec, M

    2005-01-01

    Monte Carlo simulations for nuclear logging applications are considered to be highly demanding transport problems. In this paper, the implementation of weight-window variance reduction schemes in a 'manual' fashion to improve the efficiency of calculations for a neutron logging tool is presented.

  2. Monte Carlo particle simulation and finite-element techniques for tandem mirror transport

    International Nuclear Information System (INIS)

    Rognlien, T.D.; Cohen, B.I.; Matsuda, Y.; Stewart, J.J. Jr.

    1985-12-01

    A description is given of numerical methods used in the study of axial transport in tandem mirrors owing to Coulomb collisions and rf diffusion. The methods are Monte Carlo particle simulations and direct solution to the Fokker-Planck equations by finite-element expansion. 11 refs

  3. Parallel Monte Carlo reactor neutronics

    International Nuclear Information System (INIS)

    Blomquist, R.N.; Brown, F.B.

    1994-01-01

    The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved

  4. Monte Carlo alpha deposition

    International Nuclear Information System (INIS)

    Talley, T.L.; Evans, F.

    1988-01-01

    Prior work demonstrated the importance of nuclear scattering to fusion product energy deposition in hot plasmas. This suggests careful examination of nuclear physics details in burning plasma simulations. An existing Monte Carlo fast ion transport code is being expanded to be a test bed for this examination. An initial extension, the energy deposition of fast alpha particles in a hot deuterium plasma, is reported. The deposition times and deposition ranges are modified by allowing nuclear scattering. Up to 10% of the initial alpha particle energy is carried to greater ranges and times by the more mobile recoil deuterons. 4 refs., 5 figs., 2 tabs

  5. On Micro VAX farms and shower libraries: Monte Carlo techniques developed for the D0 detector

    International Nuclear Information System (INIS)

    Raja, R.

    1988-01-01

    In order to predict correctly the effects of cracks and dead material in a nearly hermetic calorimeter, hadronic and electromagnetic showers need to be simulated accurately on a particle by particle basis. Tracking all the particles of all showers in the calorimeter leads to very large CPU times (typically 5 hours on a VAX780) for events at √(s) = 2TeV. Parametrizing the energy deposition of electromagnetic particles in showers with energy below 200 MeV results in event times of the order of 1 hour on a VAX780. This is still unacceptably large. The D0 collaboration then employed a farm of 16 MicroVax II's to get acceptable throughputs. The calorimeter hit patterns of each individual track was output, to be summed up by a later job. These individual hit patterns were entered into a random access shower library file, which was then used for subsequent Monte Carlo simulations. This shower library technique results in further speed-ups of a factor of 60 without degrading the quality of simulation significantly

  6. Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques

    International Nuclear Information System (INIS)

    Deasy, Joseph O.

    2000-01-01

    The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to-voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions. (author)

  7. Extended canonical Monte Carlo methods: Improving accuracy of microcanonical calculations using a reweighting technique

    Science.gov (United States)

    Velazquez, L.; Castro-Palacio, J. C.

    2015-03-01

    Velazquez and Curilef [J. Stat. Mech. (2010) P02002, 10.1088/1742-5468/2010/02/P02002; J. Stat. Mech. (2010) P04026, 10.1088/1742-5468/2010/04/P04026] have proposed a methodology to extend Monte Carlo algorithms that are based on canonical ensemble. According to our previous study, their proposal allows us to overcome slow sampling problems in systems that undergo any type of temperature-driven phase transition. After a comprehensive review about ideas and connections of this framework, we discuss the application of a reweighting technique to improve the accuracy of microcanonical calculations, specifically, the well-known multihistograms method of Ferrenberg and Swendsen [Phys. Rev. Lett. 63, 1195 (1989), 10.1103/PhysRevLett.63.1195]. As an example of application, we reconsider the study of the four-state Potts model on the square lattice L ×L with periodic boundary conditions. This analysis allows us to detect the existence of a very small latent heat per site qL during the occurrence of temperature-driven phase transition of this model, whose size dependence seems to follow a power law qL(L ) ∝(1/L ) z with exponent z ≃0 .26 ±0 .02. Discussed is the compatibility of these results with the continuous character of temperature-driven phase transition when L →+∞ .

  8. Source of statistical noises in the Monte Carlo sampling techniques for coherently scattered photons

    Science.gov (United States)

    Muhammad, Wazir; Lee, Sang Hoon

    2013-01-01

    Detailed comparisons of the predictions of the Relativistic Form Factors (RFFs) and Modified Form Factors (MFFs) and their advantages and shortcomings in calculating elastic scattering cross sections can be found in the literature. However, the issues related to their implementation in the Monte Carlo (MC) sampling for coherently scattered photons is still under discussion. Secondly, the linear interpolation technique (LIT) is a popular method to draw the integrated values of squared RFFs/MFFs (i.e. ) over squared momentum transfer (). In the current study, the role/issues of RFFs/MFFs and LIT in the MC sampling for the coherent scattering were analyzed. The results showed that the relative probability density curves sampled on the basis of MFFs are unable to reveal any extra scientific information as both the RFFs and MFFs produced the same MC sampled curves. Furthermore, no relationship was established between the multiple small peaks and irregular step shapes (i.e. statistical noise) in the PDFs and either RFFs or MFFs. In fact, the noise in the PDFs appeared due to the use of LIT. The density of the noise depends upon the interval length between two consecutive points in the input data table of and has no scientific background. The probability density function curves became smoother as the interval lengths were decreased. In conclusion, these statistical noises can be efficiently removed by introducing more data points in the data tables. PMID:22984278

  9. Monte Carlo technique applications in field of radiation dosimetry at ENEA radiation protection institute: A Review

    International Nuclear Information System (INIS)

    Gualdrini, G.F.; Casalini, L.; Morelli, B.

    1994-12-01

    The present report summarizes the activities concerned with numerical dosimetry as carried out at the Radiation Protection Institute of ENEA (Italian Agency for New Technologies, Energy and the Environment) on photon dosimetric quantities. The first part is concerned with MCNP Monte Carlo calculation of field parameters and operational quantities for the ICRU sphere with reference photon beams for the design of personal dosemeters. The second part is related with studies on the ADAM anthropomorphic phantom using the SABRINA and MCNP codes. The results of other Monte Carlo studies carried out on electron conversion factors for various tissue equivalent slab phantoms are about to be published in other ENEA reports. The report has been produced in the framework of the EURADOS WG4 (numerical dosimetry) activities within a collaboration between the ENEA Environmental Department and ENEA Energy Department

  10. Novel imaging and quality assurance techniques for ion beam therapy a Monte Carlo study

    CERN Document Server

    Rinaldi, I; Jäkel, O; Mairani, A; Parodi, K

    2010-01-01

    Ion beams exhibit a finite and well defined range in matter together with an “inverted” depth-dose profile, the so-called Bragg peak. These favourable physical properties may enable superior tumour-dose conformality for high precision radiation therapy. On the other hand, they introduce the issue of sensitivity to range uncertainties in ion beam therapy. Although these uncertainties are typically taken into account when planning the treatment, correct delivery of the intended ion beam range has to be assured to prevent undesired underdosage of the tumour or overdosage of critical structures outside the target volume. Therefore, it is necessary to define dedicated Quality Assurance procedures to enable in-vivo range verification before or during therapeutic irradiation. For these purposes, Monte Carlo transport codes are very useful tools to support the development of novel imaging modalities for ion beam therapy. In the present work, we present calculations performed with the FLUKA Monte Carlo code and pr...

  11. Fast sequential Monte Carlo methods for counting and optimization

    CERN Document Server

    Rubinstein, Reuven Y; Vaisman, Radislav

    2013-01-01

    A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the

  12. A Hybrid Approach to Simulate X-Ray Imaging Techniques, Combining Monte Carlo and Deterministic Algorithms

    Science.gov (United States)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-10-01

    In this paper, we propose a hybrid approach to simulate multiple scattering of photons in objects under X-ray inspection, without recourse to parallel computing and without any approximation sacrificing accuracy. Photon scattering is considered from two points of view: it contributes to X-ray imaging and to the dose absorbed by the patient. The proposed hybrid approach consists of a Monte Carlo stage followed by a deterministic phase, thus taking advantage of the complementarity between these two methods. In the first stage, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Then this set of scattering events is used to compute the energy imparted to the detector, with a deterministic algorithm based on a "forced detection" scheme. Regarding dose evaluation, we propose to assess separately the energy deposited by direct radiation (using a deterministic algorithm) and by scattered radiation (using our hybrid approach). The results obtained in a test case are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the required detector resolution and statistics). It is possible to simulate radiographic images virtually free from photon noise. In the case of dose evaluation, the hybrid approach appears particularly suitable to calculate the dose absorbed by regions of interest (rather than the entire irradiated organ) with computation time and statistical fluctuations considerably reduced in comparison with conventional Monte Carlo simulation.

  13. Monte Carlo simulation of experiments

    International Nuclear Information System (INIS)

    Opat, G.I.

    1977-07-01

    An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)

  14. Technical Note: On the efficiency of variance reduction techniques for Monte Carlo estimates of imaging noise.

    Science.gov (United States)

    Sharma, Diksha; Sempau, Josep; Badano, Aldo

    2018-02-01

    Monte Carlo simulations require large number of histories to obtain reliable estimates of the quantity of interest and its associated statistical uncertainty. Numerous variance reduction techniques (VRTs) have been employed to increase computational efficiency by reducing the statistical uncertainty. We investigate the effect of two VRTs for optical transport methods on accuracy and computing time for the estimation of variance (noise) in x-ray imaging detectors. We describe two VRTs. In the first, we preferentially alter the direction of the optical photons to increase detection probability. In the second, we follow only a fraction of the total optical photons generated. In both techniques, the statistical weight of photons is altered to maintain the signal mean. We use fastdetect2, an open-source, freely available optical transport routine from the hybridmantis package. We simulate VRTs for a variety of detector models and energy sources. The imaging data from the VRT simulations are then compared to the analog case (no VRT) using pulse height spectra, Swank factor, and the variance of the Swank estimate. We analyze the effect of VRTs on the statistical uncertainty associated with Swank factors. VRTs increased the relative efficiency by as much as a factor of 9. We demonstrate that we can achieve the same variance of the Swank factor with less computing time. With this approach, the simulations can be stopped when the variance of the variance estimates reaches the desired level of uncertainty. We implemented analytic estimates of the variance of Swank factor and demonstrated the effect of VRTs on image quality calculations. Our findings indicate that the Swank factor is dominated by the x-ray interaction profile as compared to the additional uncertainty introduced in the optical transport by the use of VRTs. For simulation experiments that aim at reducing the uncertainty in the Swank factor estimate, any of the proposed VRT can be used for increasing the relative

  15. Quantum Monte Carlo approaches for correlated systems

    CERN Document Server

    Becca, Federico

    2017-01-01

    Over the past several decades, computational approaches to studying strongly-interacting systems have become increasingly varied and sophisticated. This book provides a comprehensive introduction to state-of-the-art quantum Monte Carlo techniques relevant for applications in correlated systems. Providing a clear overview of variational wave functions, and featuring a detailed presentation of stochastic samplings including Markov chains and Langevin dynamics, which are developed into a discussion of Monte Carlo methods. The variational technique is described, from foundations to a detailed description of its algorithms. Further topics discussed include optimisation techniques, real-time dynamics and projection methods, including Green's function, reptation and auxiliary-field Monte Carlo, from basic definitions to advanced algorithms for efficient codes, and the book concludes with recent developments on the continuum space. Quantum Monte Carlo Approaches for Correlated Systems provides an extensive reference ...

  16. Application of an efficient materials perturbation technique to Monte Carlo photon transport calculations in borehole logging

    International Nuclear Information System (INIS)

    Picton, D.J.; Harris, R.G.; Randle, K.; Weaver, D.R.

    1995-01-01

    This paper describes a simple, accurate and efficient technique for the calculation of materials perturbation effects in Monte Carlo photon transport calculations. It is particularly suited to the application for which it was developed, namely the modelling of a dual detector density tool as used in borehole logging. However, the method would be appropriate to any photon transport calculation in the energy range 0.1 to 2 MeV, in which the predominant processes are Compton scattering and photoelectric absorption. The method enables a single set of particle histories to provide results for an array of configurations in which material densities or compositions vary. It can calculate the effects of small perturbations very accurately, but is by no means restricted to such cases. For the borehole logging application described here the method has been found to be efficient for a moderate range of variation in the bulk density (of the order of ±30% from a reference value) or even larger changes to a limited portion of the system (e.g. a low density mudcake of the order of a few tens of mm in thickness). The effective speed enhancement over an equivalent set of individual calculations is in the region of an order of magnitude or more. Examples of calculations on a dual detector density tool are given. It is demonstrated that the method predicts, to a high degree of accuracy, the variation of detector count rates with formation density, and that good results are also obtained for the effects of mudcake layers. An interesting feature of the results is that relative count rates (the ratios of count rates obtained with different configurations) can usually be determined more accurately than the absolute values of the count rates. (orig.)

  17. Monte Carlo Modeling of Dual and Triple Photon Energy Absorptiometry Technique

    Directory of Open Access Journals (Sweden)

    Alireza Kamali-Asl

    2007-12-01

    Full Text Available Introduction: Osteoporosis is a bone disease in which there is a reduction in the amount of bone mineral content leading to an increase in the risk of bone fractures. The affected individuals not only have to go through lots of pain and suffering but this disease also results in high economic costs to the society due to a large number of fractures.  A timely and accurate diagnosis of this disease makes it possible to start a treatment and thus preventing bone fractures as a result of osteoporosis. Radiographic methods are particularly well suited for in vivo determination of bone mineral density (BMD due to the relatively high x-ray absorption properties of bone mineral compared to other tissues. Materials and Methods: Monte Carlo simulation has been conducted to explore the possibilities of triple photon energy absorptiometry (TPA in the measurement of bone mineral content. The purpose of this technique is to correctly measure the bone mineral density in the presence of fatty and soft tissues. The same simulations have been done for a dual photon energy absorptiometry (DPA system and an extended DPA system. Results: Using DPA with three components improves the accuracy of the obtained result while the simulation results show that TPA system is not accurate enough to be considered as an adequate method for the measurement of bone mineral density. Discussion: The reason for the improvement in the accuracy is the consideration of fatty tissue in TPA method while having attenuation coefficient as a function of energy makes TPA an inadequate method. Conclusion: Using TPA method is not a perfect solution to overcome the problem of non uniformity in the distribution of fatty tissue.

  18. Metropolis Methods for Quantum Monte Carlo Simulations

    OpenAIRE

    Ceperley, D. M.

    2003-01-01

    Since its first description fifty years ago, the Metropolis Monte Carlo method has been used in a variety of different ways for the simulation of continuum quantum many-body systems. This paper will consider some of the generalizations of the Metropolis algorithm employed in quantum Monte Carlo: Variational Monte Carlo, dynamical methods for projector monte carlo ({\\it i.e.} diffusion Monte Carlo with rejection), multilevel sampling in path integral Monte Carlo, the sampling of permutations, ...

  19. Monte Carlo Technique Used to Model the Degradation of Internal Spacecraft Surfaces by Atomic Oxygen

    Science.gov (United States)

    Banks, Bruce A.; Miller, Sharon K.

    2004-01-01

    Atomic oxygen is one of the predominant constituents of Earth's upper atmosphere. It is created by the photodissociation of molecular oxygen (O2) into single O atoms by ultraviolet radiation. It is chemically very reactive because a single O atom readily combines with another O atom or with other atoms or molecules that can form a stable oxide. The effects of atomic oxygen on the external surfaces of spacecraft in low Earth orbit can have dire consequences for spacecraft life, and this is a well-known and much studied problem. Much less information is known about the effects of atomic oxygen on the internal surfaces of spacecraft. This degradation can occur when openings in components of the spacecraft exterior exist that allow the entry of atomic oxygen into regions that may not have direct atomic oxygen attack but rather scattered attack. Openings can exist because of spacecraft venting, microwave cavities, and apertures for Earth viewing, Sun sensors, or star trackers. The effects of atomic oxygen erosion of polymers interior to an aperture on a spacecraft were simulated at the NASA Glenn Research Center by using Monte Carlo computational techniques. A two-dimensional model was used to provide quantitative indications of the attenuation of atomic oxygen flux as a function of the distance into a parallel-walled cavity. The model allows the atomic oxygen arrival direction, the Maxwell Boltzman temperature, and the ram energy to be varied along with the interaction parameters of the degree of recombination upon impact with polymer or nonreactive surfaces, the initial reaction probability, the reaction probability dependence upon energy and angle of attack, degree of specularity of scattering of reactive and nonreactive surfaces, and the degree of thermal accommodation upon impact with reactive and non-reactive surfaces to be varied to allow the model to produce atomic oxygen erosion geometries that replicate actual experimental results from space. The degree of

  20. Parallelizing Monte Carlo with PMC

    International Nuclear Information System (INIS)

    Rathkopf, J.A.; Jones, T.R.; Nessett, D.M.; Stanberry, L.C.

    1994-11-01

    PMC (Parallel Monte Carlo) is a system of generic interface routines that allows easy porting of Monte Carlo packages of large-scale physics simulation codes to Massively Parallel Processor (MPP) computers. By loading various versions of PMC, simulation code developers can configure their codes to run in several modes: serial, Monte Carlo runs on the same processor as the rest of the code; parallel, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on other MPP processor(s); distributed, Monte Carlo runs in parallel across many processors of the MPP with the rest of the code running on a different machine. This multi-mode approach allows maintenance of a single simulation code source regardless of the target machine. PMC handles passing of messages between nodes on the MPP, passing of messages between a different machine and the MPP, distributing work between nodes, and providing independent, reproducible sequences of random numbers. Several production codes have been parallelized under the PMC system. Excellent parallel efficiency in both the distributed and parallel modes results if sufficient workload is available per processor. Experiences with a Monte Carlo photonics demonstration code and a Monte Carlo neutronics package are described

  1. Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques.

    Science.gov (United States)

    Kilinc, Deniz; Demir, Alper

    2017-08-01

    The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

  2. Lectures on Monte Carlo methods

    CERN Document Server

    Madras, Neal

    2001-01-01

    Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati

  3. Monte Carlo simulations for plasma physics

    International Nuclear Information System (INIS)

    Okamoto, M.; Murakami, S.; Nakajima, N.; Wang, W.X.

    2000-07-01

    Plasma behaviours are very complicated and the analyses are generally difficult. However, when the collisional processes play an important role in the plasma behaviour, the Monte Carlo method is often employed as a useful tool. For examples, in neutral particle injection heating (NBI heating), electron or ion cyclotron heating, and alpha heating, Coulomb collisions slow down high energetic particles and pitch angle scatter them. These processes are often studied by the Monte Carlo technique and good agreements can be obtained with the experimental results. Recently, Monte Carlo Method has been developed to study fast particle transports associated with heating and generating the radial electric field. Further it is applied to investigating the neoclassical transport in the plasma with steep gradients of density and temperatures which is beyong the conventional neoclassical theory. In this report, we briefly summarize the researches done by the present authors utilizing the Monte Carlo method. (author)

  4. Simulation and the Monte Carlo method

    CERN Document Server

    Rubinstein, Reuven Y

    2016-01-01

    Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as the transform likelihood ratio...

  5. Monte Carlo methods for particle transport

    CERN Document Server

    Haghighat, Alireza

    2015-01-01

    The Monte Carlo method has become the de facto standard in radiation transport. Although powerful, if not understood and used appropriately, the method can give misleading results. Monte Carlo Methods for Particle Transport teaches appropriate use of the Monte Carlo method, explaining the method's fundamental concepts as well as its limitations. Concise yet comprehensive, this well-organized text: * Introduces the particle importance equation and its use for variance reduction * Describes general and particle-transport-specific variance reduction techniques * Presents particle transport eigenvalue issues and methodologies to address these issues * Explores advanced formulations based on the author's research activities * Discusses parallel processing concepts and factors affecting parallel performance Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, Monte Carlo Methods for Particle Transport provides nuclear engineers and scientists with a practical guide ...

  6. Verifying interpretive criteria for bioaerosol data using (bootstrap) Monte Carlo techniques.

    Science.gov (United States)

    Spicer, R Christopher; Gangloff, Harry

    2008-02-01

    A number of interpretive descriptors have been proposed for bioaerosol data due to the lack of health-based numerical standards, but very few have been verified as to their ability to describe a suspect indoor environment. Culturable and nonculturable (spore trap) sampling using the bootstrap version of Monte Carlo simulation (BMC) at several sites during 2003-2006 served as a source of indoor and outdoor data to test various criteria with regard to their variability in characterizing an indoor or outdoor environment. The purpose was to gain some insight for the reliability of some of the interpretive criteria in use as well as to demonstrate the utility of BMC methods as a generalized technique for validation of various interpretive criteria for bioaerosols. The ratio of nonphylloplane (NP) fungi (total of Aspergillus and Penicillium) to phylloplane (P) fungi (total of Cladosporium, Alternaria, and Epicoccum), or NP/P, is a descriptor that has been used to identify "dominance" of nonphylloplane fungi (NP/P > 1.0), assumed to be indicative of a problematic indoor environment. However, BMC analysis of spore trap and culturable bioaerosol data using the NP/P ratio identified frequent dominance by nonphylloplane fungi in outdoor air. Similarly, the NP/P descriptor indicated dominance of nonphylloplane fungi in buildings with visible mold growth and/or known water intrusion with a frequency often in the range of 0.5 Fixed numerical criteria for spore trap data of 900 and 1300 spores/m(3) for total spores and 750 Aspergillus/Penicillium spores/m(3) exhibited similar variability, as did ratios of nonphylloplane to total fungi, phylloplane to total fungi, and indoor/outdoor ratios for total fungal spores. Analysis of bioaerosol data by BMC indicates that numerical levels or descriptors based on dominance of certain fungi are unreliable as criteria for characterizing a given environment. The utility of BMC analysis lies in its generalized application to test mathematically

  7. Adjoint electron Monte Carlo calculations

    International Nuclear Information System (INIS)

    Jordan, T.M.

    1986-01-01

    Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment

  8. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    time Technical Consultant to. Systat Software Asia-Pacific. (P) Ltd., in Bangalore, where the technical work for the development of the statistical software Systat takes place. His research interests have been in statistical pattern recognition and biostatistics. Keywords. Markov chain, Monte Carlo sampling, Markov chain Monte.

  9. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    ter of the 20th century, due to rapid developments in computing technology ... early part of this development saw a host of Monte ... These iterative. Monte Carlo procedures typically generate a random se- quence with the Markov property such that the Markov chain is ergodic with a limiting distribution coinciding with the ...

  10. Monte Carlo analysis of a control technique for a tunable white lighting system

    DEFF Research Database (Denmark)

    Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

    2017-01-01

    A simulated colour control mechanism for a multi-coloured LED lighting system is presented. The system achieves adjustable and stable white light output and allows for system-to-system reproducibility after application of the control mechanism. The control unit works using a pre-calibrated lookup...... peak wavelength, the LED rated luminous flux bin, the influence of the operating conditions, ambient temperature, driving current, and the spectral response of the colour sensor. The system performance is investigated by evaluating the outputs from the Monte Carlo simulation. The outputs show...... that the applied control system yields an uncertainty on the luminous flux of 2.5% within a 95% coverage interval which is a significant reduction from the 8% of the uncontrolled system. A corresponding uncertainty reduction in Δu´v´ is achieved from an average of 0.0193 to 0.00125 within 95% coverage range after...

  11. Validation and simulation of a regulated survey system through Monte Carlo techniques

    Directory of Open Access Journals (Sweden)

    Asier Lacasta Soto

    2015-07-01

    Full Text Available Channel flow covers long distances and obeys to variable temporal behaviour. It is usually regulated by hydraulic elements as lateralgates to provide a correct of water supply. The dynamics of this kind of flow is governed by a partial differential equations systemnamed shallow water model. They have to be complemented with a simplified formulation for the gates. All the set of equations forma non-linear system that can only be solved numerically. Here, an explicit upwind numerical scheme in finite volumes able to solveall type of flow regimes is used. Hydraulic structures (lateral gates formulation introduces parameters with some uncertainty. Hence,these parameters will be calibrated with a Monte Carlo algorithm obtaining associated coefficients to each gate. Then, they will bechecked, using real cases provided by the monitorizing equipment of the Pina de Ebro channel located in Zaragoza.

  12. Specialized Monte Carlo codes versus general-purpose Monte Carlo codes

    International Nuclear Information System (INIS)

    Moskvin, Vadim; DesRosiers, Colleen; Papiez, Lech; Lu, Xiaoyi

    2002-01-01

    The possibilities of Monte Carlo modeling for dose calculations and optimization treatment are quite limited in radiation oncology applications. The main reason is that the Monte Carlo technique for dose calculations is time consuming while treatment planning may require hundreds of possible cases of dose simulations to be evaluated for dose optimization. The second reason is that general-purpose codes widely used in practice, require an experienced user to customize them for calculations. This paper discusses the concept of Monte Carlo code design that can avoid the main problems that are preventing wide spread use of this simulation technique in medical physics. (authors)

  13. Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique

    Energy Technology Data Exchange (ETDEWEB)

    Sampson, Andrew; Le Yi; Williamson, Jeffrey F. [Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 (United States)

    2012-02-15

    Purpose: To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. Methods: CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, {Delta}D, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 {sup 125}I seeds. The breast case consisted of 87 Model-200 {sup 103}Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D{sub 90}, as well as for various anatomical regions. Results: Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 x 1 x 1 mm{sup 3} dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and

  14. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

    In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  15. Monte Carlo simulation of Markov unreliability models

    International Nuclear Information System (INIS)

    Lewis, E.E.; Boehm, F.

    1984-01-01

    A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)

  16. Shell model the Monte Carlo way

    International Nuclear Information System (INIS)

    Ormand, W.E.

    1995-01-01

    The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined

  17. Shell model the Monte Carlo way

    Energy Technology Data Exchange (ETDEWEB)

    Ormand, W.E.

    1995-03-01

    The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.

  18. Off-diagonal expansion quantum Monte Carlo.

    Science.gov (United States)

    Albash, Tameem; Wagenbreth, Gene; Hen, Itay

    2017-12-01

    We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

  19. Off-diagonal expansion quantum Monte Carlo

    Science.gov (United States)

    Albash, Tameem; Wagenbreth, Gene; Hen, Itay

    2017-12-01

    We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

  20. Monte carlo methods and models in finance and insurance

    CERN Document Server

    Korn, Ralf; Kroisandt, Gerald

    2010-01-01

    Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...

  1. Monte Carlo methods and models in finance and insurance

    CERN Document Server

    Korn, Ralf; Kroisandt, Gerald

    2010-01-01

    Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath-Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for standard simulation and the simulation of...

  2. Markov Chain Monte Carlo Methods-Simple Monte Carlo

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 8; Issue 4. Markov Chain Monte Carlo ... New York 14853, USA. Indian Statistical Institute 8th Mile, Mysore Road Bangalore 560 059, India. Systat Software Asia-Pacific (PI Ltd., Floor 5, 'C' Tower Golden Enclave, Airport Road Bangalore 560017, India.

  3. Discrete diffusion Monte Carlo for frequency-dependent radiative transfer

    Energy Technology Data Exchange (ETDEWEB)

    Densmore, Jeffrey D [Los Alamos National Laboratory; Kelly, Thompson G [Los Alamos National Laboratory; Urbatish, Todd J [Los Alamos National Laboratory

    2010-11-17

    Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique.

  4. Depth-of-interaction estimates in pixelated scintillator sensors using Monte Carlo techniques

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, Diksha [Division of Imaging, Diagnostics and Software Reliability, Center for Devices and Radiological Health, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD 20993 (United States); Sze, Christina; Bhandari, Harish; Nagarkar, Vivek [Radiation Monitoring Devices Inc., Watertown, MA (United States); Badano, Aldo, E-mail: aldo.badano@fda.hhs.gov [Division of Imaging, Diagnostics and Software Reliability, Center for Devices and Radiological Health, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD 20993 (United States)

    2017-01-01

    Image quality in thick scintillator detectors can be improved by minimizing parallax errors through depth-of-interaction (DOI) estimation. A novel sensor for low-energy single photon imaging having a thick, transparent, crystalline pixelated micro-columnar CsI:Tl scintillator structure has been described, with possible future application in small-animal single photon emission computed tomography (SPECT) imaging when using thicker structures under development. In order to understand the fundamental limits of this new structure, we introduce cartesianDETECT2, an open-source optical transport package that uses Monte Carlo methods to obtain estimates of DOI for improving spatial resolution of nuclear imaging applications. Optical photon paths are calculated as a function of varying simulation parameters such as columnar surface roughness, bulk, and top-surface absorption. We use scanning electron microscope images to estimate appropriate surface roughness coefficients. Simulation results are analyzed to model and establish patterns between DOI and photon scattering. The effect of varying starting locations of optical photons on the spatial response is studied. Bulk and top-surface absorption fractions were varied to investigate their effect on spatial response as a function of DOI. We investigated the accuracy of our DOI estimation model for a particular screen with various training and testing sets, and for all cases the percent error between the estimated and actual DOI over the majority of the detector thickness was ±5% with a maximum error of up to ±10% at deeper DOIs. In addition, we found that cartesianDETECT2 is computationally five times more efficient than MANTIS. Findings indicate that DOI estimates can be extracted from a double-Gaussian model of the detector response. We observed that our model predicts DOI in pixelated scintillator detectors reasonably well.

  5. Dose point kernel simulation for monoenergetic electrons and radionuclides using Monte Carlo techniques.

    Science.gov (United States)

    Wu, J; Liu, Y L; Chang, S J; Chao, M M; Tsai, S Y; Huang, D E

    2012-11-01

    Monte Carlo (MC) simulation has been commonly used in the dose evaluation of radiation accidents and for medical purposes. The accuracy of simulated results is affected by the particle-tracking algorithm, cross-sectional database, random number generator and statistical error. The differences among MC simulation software packages must be validated. This study simulated the dose point kernel (DPK) and the cellular S-values of monoenergetic electrons ranging from 0.01 to 2 MeV and the radionuclides of (90)Y, (177)Lu and (103 m)Rh, using Fluktuierende Kaskade (FLUKA) and MC N-Particle Transport Code Version 5 (MCNP5). A 6-μm-radius cell model consisting of the cell surface, cytoplasm and cell nucleus was constructed for cellular S-value calculation. The mean absolute percentage errors (MAPEs) of the scaled DPKs, simulated using FLUKA and MCNP5, were 7.92, 9.64, 4.62, 3.71 and 3.84 % for 0.01, 0.1, 0.5, 1 and 2 MeV, respectively. For the three radionuclides, the MAPEs of the scaled DPKs were within 5 %. The maximum deviations of S(N←N), S(N←Cy) and S(N←CS) for the electron energy larger than 10 keV were 6.63, 6.77 and 5.24 %, respectively. The deviations for the self-absorbed S-values and cross-dose S-values of the three radionuclides were within 4 %. On the basis of the results of this study, it was concluded that the simulation results are consistent between FLUKA and MCNP5. However, there is a minor inconsistency for low energy range. The DPK and the cellular S-value should be used as the quality assurance tools before the MC simulation results are adopted as the gold standard.

  6. Dosimetric study of prostate brachytherapy using techniques of Monte-Carlo simulation, experimental measurements and comparison with a treatment plan

    International Nuclear Information System (INIS)

    Teles, Pedro; Barros, Silvia; Vaz, Pedro; Goncalves, Isabel; Facure, Alessandro; Rosa, Luiz da; Santos, Maira; Pereira Junior, Pedro Paulo; Zankl, Maria

    2013-01-01

    Prostate Brachytherapy is a radiotherapy technique, which consists in inserting a number of radioactive seeds (containing, usually, the following radionuclides 125 l, 241 Am or 103 Pd ) surrounding or in the vicinity of, prostate tumor tissue . The main objective of this technique is to maximize the radiation dose to the tumor and minimize it in other tissues and organs healthy, in order to reduce its morbidity. The absorbed dose distribution in the prostate, using this technique is usually non-homogeneous and time dependent. Various parameters such as the type of seed, the attenuation interactions between them, their geometrical arrangement within the prostate, the actual geometry of the seeds,and further swelling of the prostate gland after implantation greatly influence the course of absorbed dose in the prostate and surrounding areas. Quantification of these parameters is therefore extremely important for dose optimization and improvement of their plans conventional treatment, which in many cases not fully take into account. The Monte Carlo techniques allow to study these parameters quickly and effectively. In this work, we use the program MCNPX and generic voxel phantom (GOLEM) where simulated different geometric arrangements of seeds containing 125 I, Amersham Health model of type 6711 in prostates of different sizes, in order to try to quantify some of the parameters. The computational model was validated using a phantom prostate cubic RW3 type , consisting of tissue equivalent, and thermoluminescent dosimeters. Finally, to have a term of comparison with a treatment real plan it was simulate a treatment plan used in a hospital of Rio de Janeiro, with exactly the same parameters, and our computational model. The results obtained in our study seem to indicate that the parameters described above may be a source of uncertainty in the correct evaluation of the dose required for actual treatment plans. The use of Monte Carlo techniques can serve as a complementary

  7. Monte Carlo strategies in scientific computing

    CERN Document Server

    Liu, Jun S

    2008-01-01

    This paperback edition is a reprint of the 2001 Springer edition This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians It can also be used as the textbook for a graduate-level course on Monte Carlo methods Many problems discussed in the alter chapters can be potential thesis topics for masters’ or PhD students in statistics or computer science departments Jun Liu is Professor of Statistics at Harvard University, with a courtesy Professor appointment at Harvard Biostatistics Department Professor Liu was the recipient of the 2002 COPSS Presidents' Award, the most prestigious one for sta...

  8. Exact Monte Carlo for molecules

    Energy Technology Data Exchange (ETDEWEB)

    Lester, W.A. Jr.; Reynolds, P.J.

    1985-03-01

    A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H2, and the singlet-triplet splitting in methylene are presented and discussed. 17 refs.

  9. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    Markov Chain Monte Carlo Methods. 2. The Markov Chain Case. K B Athreya, Mohan Delampady and T Krishnan. K B Athreya is a Professor at. Cornell University. His research interests include mathematical analysis, probability theory and its application and statistics. He enjoys writing for Resonance. His spare time is ...

  10. Markov Chain Monte Carlo Methods

    Indian Academy of Sciences (India)

    GENERAL ! ARTICLE. Markov Chain Monte Carlo Methods. 3. Statistical Concepts. K B Athreya, Mohan Delampady and T Krishnan. K B Athreya is a Professor at. Cornell University. His research interests include mathematical analysis, probability theory and its application and statistics. He enjoys writing for Resonance.

  11. Is Monte Carlo embarrassingly parallel?

    International Nuclear Information System (INIS)

    Hoogenboom, J. E.

    2012-01-01

    Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

  12. Patient dose study in chest radiographic examinations for different exposure techniques using Monte Carlo method and voxel phantom

    International Nuclear Information System (INIS)

    Correa, Samanda C.A.; Souza, Edmilson M.; Silva, Ademir X.; Lopes, Ricardo T.

    2007-01-01

    Monte Carlo code MCNPX coupled with an adult voxel female model (FAX) were used to investigate how radiation dose in chest radiographic examinations vary with antiscatter techniques (air gap and grid) and projection geometry (anterior-posterior - AP and posterior-anterior - PA) for different tube voltages. The radiation doses were evaluated in terms of organ and effective doses, for a fixed air kerma at the image detector. The results show that the effective dose for grid technique decreases with increasing tube voltage, while that for air gap great variations were not observed. Besides, the work also showed that doses are larger for AP projections and that use of the air gap is recommended in the place of the anti-scatter grids. (author)

  13. Monte Carlo - Advances and Challenges

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.

    2008-01-01

    Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature

  14. Monte Carlo method in neutron activation analysis

    International Nuclear Information System (INIS)

    Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.

    2009-01-01

    Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA

  15. Monte Carlo simulation of the microcanonical ensemble

    International Nuclear Information System (INIS)

    Creutz, M.

    1984-01-01

    We consider simulating statistical systems with a random walk on a constant energy surface. This combines features of deterministic molecular dynamics techniques and conventional Monte Carlo simulations. For discrete systems the method can be programmed to run an order of magnitude faster than other approaches. It does not require high quality random numbers and may also be useful for nonequilibrium studies. 10 references

  16. Monte Carlo simulations of elemental imaging using the neutron-associated particle technique.

    Science.gov (United States)

    Abel, Michael R; Nie, Linda H

    2018-02-06

    The purpose of this study is to develop and employ a Monte Carlo (MC) simulation model of associated particle neutron elemental imaging (APNEI) in order to determine the three-dimensional (3D) imaging resolution of such a system by examining relevant physical and technological parameters and to thereby begin to explore the range of clinical applicability of APNEI to fields such as medical diagnostics, intervention, and etiological research. The presented APNEI model was defined in MCNP by a Gaussian-distributed and isotropic surface source emitting deuterium + deuterium (DD) neutrons, iron as the target element, nine iron-containing voxels (1 cm 3 volume each) arranged in a 3-by-3 array as the interrogated volume of interest, and finally, by high-purity germanium (HPGe) gamma-ray detectors anterior and posterior to the 9-voxel array. The MCNP f8 pulse height tally was employed in conjunction with the PTRAC particle tracking function to not only determine the signal acquired from iron inelastic scatter gamma-rays but also to quantitate each of the nine target voxels' contribution to the overall iron signal - each detected iron inelastic scatter gamma-ray being traced to the source neutron which incited its emission. With the spatial, vector, and timing information of the series of events for each relevant neutron history as collected by PTRAC, realistic grayscale images of the distribution of iron concentration in the 9-voxel array were simulated in both the projective and depth dimensions. With an overall 225 ps timing resolution, 6.25 mm 2 imaging plate pixels assumed to have well localized scintillation, and a DD neutron, Gaussian-distributed source spot with a diameter of 2 mm, projective and depth resolutions of imaging resolution offered by APNEI of target elements such as iron lends itself to potential applications in disease diagnosis and treatment planning (high resolution) as well as to ordnance and contraband detection (low resolution). However

  17. Cancer risk assessment after exposure from natural radionuclides in soil using Monte Carlo techniques.

    Science.gov (United States)

    Zupunski, Ljubica; Spasić-Jokić, Vesna; Trobok, Mirjana; Gordanić, Vojin

    2010-11-01

    The purpose of this paper is to assess fatal cancer risk after external and internal (inhalation and ingestion) exposure from natural radionuclides in soil like (238)U, (232)Th, (40)K, and (226)Ra on the territory of Bela Crkva, Serbia. Although receiving doses are low from sources like natural radionuclides in soil, because of stochastic effects of ionizing radiation, risk for developing cancer exists and can be quantified. Concentrations of radionuclides from 80 soil samples are measured using HPGe detector. Fatal cancer risk is assessed from calculated ambient dose rate in the target organs of body due to external and internal exposure. Monte Carlo simulations are used to obtain conversion factors which are required to calculate absorbed dose rate in target organs. Assessed cancer risk for (238)U in the case of both inhalation and ingestion exposure is from 1.11 × 10(-6) to 24 × 10(-6) for minimal and maximal activity in soil samples, from 1.02 × 10(-6) to 23.3 × 10(-6) for exposure to (226)Ra, from 1.89 × 10(-6) to 50.3 × 10(-6) for exposure to (232)Th, and from 0.265 × 10(-6) to 9.83 × 10(-6) for exposure to (40)K. Overall risk from (40)K as external and internal source is from 0.8 × 10(-6) to 31.9 × 10(-6). Calculated cancer risks from both inhalation and ingestion exposure could be related to all tissues that are on the way of distribution of particles within the body but especially to deposition sites in the body. Assessed risks for fatal cancer development from inhaled and ingested natural radionuclides originating in soil are not increased.

  18. (U) Introduction to Monte Carlo Methods

    Energy Technology Data Exchange (ETDEWEB)

    Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-20

    Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.

  19. Monte Carlo Based Framework to Support HAZOP Study

    DEFF Research Database (Denmark)

    Danko, Matej; Frutiger, Jerome; Jelemenský, Ľudovít

    2017-01-01

    This study combines Monte Carlo based process simulation features with classical hazard identification techniques for consequences of deviations from normal operating conditions investigation and process safety examination. A Monte Carlo based method has been used to sample and evaluate different...... deviations in process parameters simultaneously, thereby bringing an improvement to the Hazard and Operability study (HAZOP), which normally considers only one at a time deviation in process parameters. Furthermore, Monte Carlo filtering was then used to identify operability and hazard issues including...

  20. Electron Irradiation of Conjunctival Lymphoma-Monte Carlo Simulation of the Minute Dose Distribution and Technique Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Brualla, Lorenzo, E-mail: lorenzo.brualla@uni-due.de [NCTeam, Strahlenklinik, Universitaetsklinikum Essen, Essen (Germany); Zaragoza, Francisco J.; Sempau, Josep [Institut de Tecniques Energetiques, Universitat Politecnica de Catalunya, Barcelona (Spain); Wittig, Andrea [Department of Radiation Oncology, University Hospital Giessen and Marburg, Philipps-University Marburg, Marburg (Germany); Sauerwein, Wolfgang [NCTeam, Strahlenklinik, Universitaetsklinikum Essen, Essen (Germany)

    2012-07-15

    Purpose: External beam radiotherapy is the only conservative curative approach for Stage I non-Hodgkin lymphomas of the conjunctiva. The target volume is geometrically complex because it includes the eyeball and lid conjunctiva. Furthermore, the target volume is adjacent to radiosensitive structures, including the lens, lacrimal glands, cornea, retina, and papilla. The radiotherapy planning and optimization requires accurate calculation of the dose in these anatomical structures that are much smaller than the structures traditionally considered in radiotherapy. Neither conventional treatment planning systems nor dosimetric measurements can reliably determine the dose distribution in these small irradiated volumes. Methods and Materials: The Monte Carlo simulations of a Varian Clinac 2100 C/D and human eye were performed using the PENELOPE and PENEASYLINAC codes. Dose distributions and dose volume histograms were calculated for the bulbar conjunctiva, cornea, lens, retina, papilla, lacrimal gland, and anterior and posterior hemispheres. Results: The simulated results allow choosing the most adequate treatment setup configuration, which is an electron beam energy of 6 MeV with additional bolus and collimation by a cerrobend block with a central cylindrical hole of 3.0 cm diameter and central cylindrical rod of 1.0 cm diameter. Conclusions: Monte Carlo simulation is a useful method to calculate the minute dose distribution in ocular tissue and to optimize the electron irradiation technique in highly critical structures. Using a voxelized eye phantom based on patient computed tomography images, the dose distribution can be estimated with a standard statistical uncertainty of less than 2.4% in 3 min using a computing cluster with 30 cores, which makes this planning technique clinically relevant.

  1. Monte Carlo applications to radiation shielding problems

    International Nuclear Information System (INIS)

    Subbaiah, K.V.

    2009-01-01

    transport in complex geometries is straightforward, while even the simplest finite geometries (e.g., thin foils) are very difficult to be dealt with by the transport equation. The main drawback of the Monte Carlo method lies in its random nature: all the results are affected by statistical uncertainties, which can be reduced at the expense of increasing the sampled population, and, hence, the computation time. Under special circumstances, the statistical uncertainties may be lowered by using variance-reduction techniques. Monte Carlo methods tend to be used when it is infeasible or impossible to compute an exact result with a deterministic algorithm. The term Monte Carlo was coined in the 1940s by physicists working on nuclear weapon projects in the Los Alamos National Laboratory

  2. Present status of transport code development based on Monte Carlo method

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki

    1985-01-01

    The present status of development in Monte Carlo code is briefly reviewed. The main items are the followings; Application fields, Methods used in Monte Carlo code (geometry spectification, nuclear data, estimator and variance reduction technique) and unfinished works, Typical Monte Carlo codes and Merits of continuous energy Monte Carlo code. (author)

  3. Shell model Monte Carlo methods

    International Nuclear Information System (INIS)

    Koonin, S.E.

    1996-01-01

    We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of γ-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs

  4. Monte Carlo Methods in ICF

    Science.gov (United States)

    Zimmerman, George B.

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.

  5. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, G.B.

    1997-01-01

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics

  6. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, George B.

    1997-01-01

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials

  7. Adaptive Multilevel Monte Carlo Simulation

    KAUST Repository

    Hoel, H

    2011-08-23

    This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).

  8. Extending canonical Monte Carlo methods

    International Nuclear Information System (INIS)

    Velazquez, L; Curilef, S

    2010-01-01

    In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model

  9. Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques

    Science.gov (United States)

    Golosio, Bruno; Schoonjans, Tom; Brunetti, Antonio; Oliva, Piernicola; Masala, Giovanni Luca

    2014-03-01

    The simulation of X-ray imaging experiments is often performed using deterministic codes, which can be relatively fast and easy to use. However, such codes are generally not suitable for the simulation of even slightly more complex experimental conditions, involving, for instance, first-order or higher-order scattering, X-ray fluorescence emissions, or more complex geometries, particularly for experiments that combine spatial resolution with spectral information. In such cases, simulations are often performed using codes based on the Monte Carlo method. In a simple Monte Carlo approach, the interaction position of an X-ray photon and the state of the photon after an interaction are obtained simply according to the theoretical probability distributions. This approach may be quite inefficient because the final channels of interest may include only a limited region of space or photons produced by a rare interaction, e.g., fluorescent emission from elements with very low concentrations. In the field of X-ray fluorescence spectroscopy, this problem has been solved by combining the Monte Carlo method with variance reduction techniques, which can reduce the computation time by several orders of magnitude. In this work, we present a C++ code for the general simulation of X-ray imaging and spectroscopy experiments, based on the application of the Monte Carlo method in combination with variance reduction techniques, with a description of sample geometry based on quadric surfaces. We describe the benefits of the object-oriented approach in terms of code maintenance, the flexibility of the program for the simulation of different experimental conditions and the possibility of easily adding new modules. Sample applications in the fields of X-ray imaging and X-ray spectroscopy are discussed. Catalogue identifier: AERO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERO_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland

  10. 3D dose imaging for arc therapy techniques by means of Fricke gel dosimetry and dedicated Monte Carlo simulations

    International Nuclear Information System (INIS)

    Valente, Mauro; Castellano, Gustavo; Sosa, Carlos

    2008-01-01

    Full text: Radiotherapy is one of the most effective techniques for tumour treatment and control. During the last years, significant developments were performed regarding both irradiation technology and techniques. However, accurate 3D dosimetric techniques are nowadays not commercially available. Due to their intrinsic characteristics, traditional dosimetric techniques like ionisation chamber, film dosimetry or TLD do not offer proper continuous 3D dose mapping. The possibility of using ferrous sulphate (Fricke) dosimeters suitably fixed to a gel matrix, along with dedicated optical analysis methods, based on light transmission measurements for 3D absorbed dose imaging in tissue-equivalent materials, has become great interest in radiotherapy. Since Gore et al. showed in 1984 that the oxidation of ferrous ions to ferric ions still happen even when fixing the ferrous sulphate solution to a gelatine matrix, important efforts have been dedicated in developing and improving real continuous 3D dosimetric systems based on Fricke solution. The purpose of this work is to investigate the capability and suitability of Fricke gel dosimetry for arc therapy irradiations. The dosimetric system is mainly composed by Fricke gel dosimeters, suitably shaped in form of thin layers and optically analysed by means of visible light transmission measurements, acquiring sample images just before and after irradiation by means of a commercial flatbed-like scanner. Image acquisition, conversion to matrices and further analysis are accomplished by means of dedicated developed software, which includes suitable algorithms for optical density differences calculation and corresponding absorbed dose conversion. Dedicated subroutines allow 3D dose imaging reconstruction from single layer information, by means of computer tomography-like algorithms. Also, dedicated Monte Carlo (PENELOPE) subroutines have been adapted in order to achieve accurate simulation of arc therapy irradiation techniques

  11. Projector Quantum Monte Carlo without minus-sign problem

    NARCIS (Netherlands)

    Frick, M.; Raedt, H. De

    Quantum Monte Carlo techniques often suffer from the so-called minus-sign problem. This paper explores a possibility to circumvent this fundamental problem by combining the Projector Quantum Monte Carlo method with the variational principle. Results are presented for the two-dimensional Hubbard

  12. Exponential convergence on a continuous Monte Carlo transport problem

    International Nuclear Information System (INIS)

    Booth, T.E.

    1997-01-01

    For more than a decade, it has been known that exponential convergence on discrete transport problems was possible using adaptive Monte Carlo techniques. An adaptive Monte Carlo method that empirically produces exponential convergence on a simple continuous transport problem is described

  13. On the Markov Chain Monte Carlo (MCMC) method

    Indian Academy of Sciences (India)

    In this article, we give an introduction to Monte Carlo techniques with special emphasis on. Markov Chain Monte Carlo (MCMC). Since the latter needs Markov chains with state space that is R or Rd and most text books on Markov chains do not discuss such chains, we have included a short appendix that gives basic ...

  14. Neutron point-flux calculation by Monte Carlo

    International Nuclear Information System (INIS)

    Eichhorn, M.

    1986-04-01

    A survey of the usual methods for estimating flux at a point is given. The associated variance-reducing techniques in direct Monte Carlo games are explained. The multigroup Monte Carlo codes MC for critical systems and PUNKT for point source-point detector-systems are represented, and problems in applying the codes to practical tasks are discussed. (author)

  15. ANALYSIS OF MONTE CARLO SIMULATION SAMPLING TECHNIQUES ON SMALL SIGNAL STABILITY OF WIND GENERATOR- CONNECTED POWER SYSTEM

    Directory of Open Access Journals (Sweden)

    TEMITOPE RAPHAEL AYODELE

    2016-04-01

    Full Text Available Monte Carlo simulation using Simple Random Sampling (SRS technique is popularly known for its ability to handle complex uncertainty problems. However, to produce a reasonable result, it requires huge sample size. This makes it to be computationally expensive, time consuming and unfit for online power system applications. In this article, the performance of Latin Hypercube Sampling (LHS technique is explored and compared with SRS in term of accuracy, robustness and speed for small signal stability application in a wind generator-connected power system. The analysis is performed using probabilistic techniques via eigenvalue analysis on two standard networks (Single Machine Infinite Bus and IEEE 16–machine 68 bus test system. The accuracy of the two sampling techniques is determined by comparing their different sample sizes with the IDEAL (conventional. The robustness is determined based on a significant variance reduction when the experiment is repeated 100 times with different sample sizes using the two sampling techniques in turn. Some of the results show that sample sizes generated from LHS for small signal stability application produces the same result as that of the IDEAL values starting from 100 sample size. This shows that about 100 sample size of random variable generated using LHS method is good enough to produce reasonable results for practical purpose in small signal stability application. It is also revealed that LHS has the least variance when the experiment is repeated 100 times compared to SRS techniques. This signifies the robustness of LHS over that of SRS techniques. 100 sample size of LHS produces the same result as that of the conventional method consisting of 50000 sample size. The reduced sample size required by LHS gives it computational speed advantage (about six times over the conventional method.

  16. Photon detection efficiency of laboratory-based x-ray phase contrast imaging techniques for mammography: a Monte Carlo study

    Science.gov (United States)

    Saghamanesh, S.; Aghamiri, S. M.; Kamali-Asl, A.; Yashiro, W.

    2017-09-01

    An important challenge in real-world biomedical applications of x-ray phase contrast imaging (XPCI) techniques is the efficient use of the photon flux generated by an incoherent and polychromatic x-ray source. This efficiency can directly influence dose and exposure time and ideally should not affect the superior contrast and sensitivity of XPCI. In this paper, we present a quantitative evaluation of the photon detection efficiency of two laboratory-based XPCI methods, grating interferometry (GI) and coded-aperture (CA). We adopt a Monte Carlo approach to simulate existing prototypes of those systems, tailored for mammography applications. Our simulations were validated by means of a simple experiment performed on a CA XPCI system. Our results show that the fraction of detected photons in the standard energy range of mammography are about 1.4% and 10% for the GI and CA techniques, respectively. The simulations indicate that the design of the optical components plays an important role in the higher efficiency of CA compared to the GI method. It is shown that the use of lower absorbing materials as the substrates for GI gratings can improve its flux efficiency by up to four times. Along similar lines, we also show that an optimized and compact configuration of GI could lead to a 3.5 times higher fraction of detected counts compared to a standard and non-optimised GI implementation.

  17. Monte Carlo modeling of eye iris color

    Science.gov (United States)

    Koblova, Ekaterina V.; Bashkatov, Alexey N.; Dolotov, Leonid E.; Sinichkin, Yuri P.; Kamenskikh, Tatyana G.; Genina, Elina A.; Tuchin, Valery V.

    2007-05-01

    Based on the presented two-layer eye iris model, the iris diffuse reflectance has been calculated by Monte Carlo technique in the spectral range 400-800 nm. The diffuse reflectance spectra have been recalculated in L*a*b* color coordinate system. Obtained results demonstrated that the iris color coordinates (hue and chroma) can be used for estimation of melanin content in the range of small melanin concentrations, i.e. for estimation of melanin content in blue and green eyes.

  18. Monte Carlo methods for shield design calculations

    International Nuclear Information System (INIS)

    Grimstone, M.J.

    1974-01-01

    A suite of Monte Carlo codes is being developed for use on a routine basis in commercial reactor shield design. The methods adopted for this purpose include the modular construction of codes, simplified geometries, automatic variance reduction techniques, continuous energy treatment of cross section data, and albedo methods for streaming. Descriptions are given of the implementation of these methods and of their use in practical calculations. 26 references. (U.S.)

  19. Antitwilight II: Monte Carlo simulations.

    Science.gov (United States)

    Richtsmeier, Steven C; Lynch, David K; Dearborn, David S P

    2017-07-01

    For this paper, we employ the Monte Carlo scene (MCScene) radiative transfer code to elucidate the underlying physics giving rise to the structure and colors of the antitwilight, i.e., twilight opposite the Sun. MCScene calculations successfully reproduce colors and spatial features observed in videos and still photos of the antitwilight taken under clear, aerosol-free sky conditions. Through simulations, we examine the effects of solar elevation angle, Rayleigh scattering, molecular absorption, aerosol scattering, multiple scattering, and surface reflectance on the appearance of the antitwilight. We also compare MCScene calculations with predictions made by the MODTRAN radiative transfer code for a solar elevation angle of +1°.

  20. Mean field simulation for Monte Carlo integration

    CERN Document Server

    Del Moral, Pierre

    2013-01-01

    In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Marko

  1. Status of Monte Carlo dose planning

    International Nuclear Information System (INIS)

    Mackie, T.R.

    1995-01-01

    Monte Carlo simulation will become increasing important for treatment planning for radiotherapy. The EGS4 Monte Carlo system, a general particle transport system, has been used most often for simulation tasks in radiotherapy although ETRAN/ITS and MCNP have also been used. Monte Carlo treatment planning requires that the beam characteristics such as the energy spectrum and angular distribution of particles emerging from clinical accelerators be accurately represented. An EGS4 Monte Carlo code, called BEAM, was developed by the OMEGA Project (a collaboration between the University of Wisconsin and the National Research Council of Canada) to transport particles through linear accelerator heads. This information was used as input to simulate the passage of particles through CT-based representations of phantoms or patients using both an EGS4 code (DOSXYZ) and the macro Monte Carlo (MMC) method. Monte Carlo computed 3-D electron beam dose distributions compare well to measurements obtained in simple and complex heterogeneous phantoms. The present drawback with most Monte Carlo codes is that simulation times are slower than most non-stochastic dose computation algorithms. This is especially true for photon dose planning. In the future dedicated Monte Carlo treatment planning systems like Peregrine (from Lawrence Livermore National Laboratory), which will be capable of computing the dose from all beam types, or the Macro Monte Carlo (MMC) system, which is an order of magnitude faster than other algorithms, may dominate the field

  2. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-05

    Multilevel Monte-Carlo methods provide a powerful computational technique for reducing the computational cost of estimating expectations for a given computational effort. They are particularly relevant for computational problems when approximate distributions are determined via a resolution parameter h, with h=0 giving the theoretical exact distribution (e.g. SDEs or inverse problems with PDEs). The method provides a benefit by coupling samples from successive resolutions, and estimating differences of successive expectations. We develop a methodology that brings Sequential Monte-Carlo (SMC) algorithms within the framework of the Multilevel idea, as SMC provides a natural set-up for coupling samples over different resolutions. We prove that the new algorithm indeed preserves the benefits of the multilevel principle, even if samples at all resolutions are now correlated.

  3. Status of Monte Carlo at Los Alamos

    International Nuclear Information System (INIS)

    Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.

    1980-05-01

    Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner

  4. Higgs production enhancement in P-P collisions using Monte Carlo techniques at √s = 13 TeV

    Directory of Open Access Journals (Sweden)

    Soleiman M.H.M.

    2017-01-01

    Full Text Available A precise estimation of the amount of enhancement in Higgs boson production through pp collisions at ultra-relativistic energies throughout promotion of the gluon distribution function inside the protons before the collision is presented here. The study is based mainly on the available Monte Carlo event generators (PYTHIA 8.2.9, SHERPA 2.1.0 running on PCs and CERNX-Machine, respectively, and using the extended invariant mass technique. Generated samples of 1000 events from PYTHIA 8.2.9 and SHERPA,2.1.0 at √s = 13 TeV are used in the investigation of the effect of replacing the parton distribution function (PDF on the Higgs production enhancement. The CTEQ66 and MSRTW2004nlo parton distribution functions are used alternatively on PYTHIA 8.2.9 and SHERPA 2.1.0 event generators in companion with the effects of allowing initial state and final state radiations (ISR and FSR to obtain evidence on the enhancement of the SM-Higgs production depending on the field theoretical model of SM. It is found that, the replacement of PDFs will lead to a significant change in the SM-Higgs production, and the effect of allowing or denying any of ISR or FSR is sound for the two event generators but may be unrealistic in PHYTIA 8.2.9.

  5. Higgs production enhancement in P-P collisions using Monte Carlo techniques at √s = 13 TeV

    Science.gov (United States)

    Soleiman, M. H. M.; Abdel-Aziz, S. S.; Sobhi, M. S. E.

    2017-06-01

    A precise estimation of the amount of enhancement in Higgs boson production through pp collisions at ultra-relativistic energies throughout promotion of the gluon distribution function inside the protons before the collision is presented here. The study is based mainly on the available Monte Carlo event generators (PYTHIA 8.2.9, SHERPA 2.1.0) running on PCs and CERNX-Machine, respectively, and using the extended invariant mass technique. Generated samples of 1000 events from PYTHIA 8.2.9 and SHERPA,2.1.0 at √s = 13 TeV are used in the investigation of the effect of replacing the parton distribution function (PDF) on the Higgs production enhancement. The CTEQ66 and MSRTW2004nlo parton distribution functions are used alternatively on PYTHIA 8.2.9 and SHERPA 2.1.0 event generators in companion with the effects of allowing initial state and final state radiations (ISR and FSR) to obtain evidence on the enhancement of the SM-Higgs production depending on the field theoretical model of SM. It is found that, the replacement of PDFs will lead to a significant change in the SM-Higgs production, and the effect of allowing or denying any of ISR or FSR is sound for the two event generators but may be unrealistic in PHYTIA 8.2.9.

  6. Monte Carlo Simulation of Alloy Design Techniques: Fracture and Welding Studied Using the BFS Method for Alloys

    Science.gov (United States)

    Bozzolo, Guillermo H.; Good, Brian; Noebe, Ronald D.; Honecy, Frank; Abel, Phillip

    1999-01-01

    Large-scale simulations of dynamic processes at the atomic level have developed into one of the main areas of work in computational materials science. Until recently, severe computational restrictions, as well as the lack of accurate methods for calculating the energetics, resulted in slower growth in the area than that required by current alloy design programs. The Computational Materials Group at the NASA Lewis Research Center is devoted to the development of powerful, accurate, economical tools to aid in alloy design. These include the BFS (Bozzolo, Ferrante, and Smith) method for alloys (ref. 1) and the development of dedicated software for large-scale simulations based on Monte Carlo- Metropolis numerical techniques, as well as state-of-the-art visualization methods. Our previous effort linking theoretical and computational modeling resulted in the successful prediction of the microstructure of a five-element intermetallic alloy, in excellent agreement with experimental results (refs. 2 and 3). This effort also produced a complete description of the role of alloying additions in intermetallic binary, ternary, and higher order alloys (ref. 4).

  7. Biased Monte Carlo optimization: the basic approach

    International Nuclear Information System (INIS)

    Campioni, Luca; Scardovelli, Ruben; Vestrucci, Paolo

    2005-01-01

    It is well-known that the Monte Carlo method is very successful in tackling several kinds of system simulations. It often happens that one has to deal with rare events, and the use of a variance reduction technique is almost mandatory, in order to have Monte Carlo efficient applications. The main issue associated with variance reduction techniques is related to the choice of the value of the biasing parameter. Actually, this task is typically left to the experience of the Monte Carlo user, who has to make many attempts before achieving an advantageous biasing. A valuable result is provided: a methodology and a practical rule addressed to establish an a priori guidance for the choice of the optimal value of the biasing parameter. This result, which has been obtained for a single component system, has the notable property of being valid for any multicomponent system. In particular, in this paper, the exponential and the uniform biases of exponentially distributed phenomena are investigated thoroughly

  8. The Kinetic Activation-Relaxation Technique: A Powerful Off-lattice On-the-fly Kinetic Monte Carlo Algorithm

    OpenAIRE

    El-Mellouhi, fedwa; Mousseau, Normand; Lewis, Laurent J.

    2008-01-01

    Many materials science phenomena, such as growth and self-organisation, are dominated by activated diffusion processes and occur on timescales that are well beyond the reach of standard-molecular dynamics simulations. Kinetic Monte Carlo (KMC) schemes make it possible to overcome this limitation and achieve experimental timescales. However, most KMC approaches proceed by discretizing the problem in space in order to identify, from the outset, a fixed set of barriers that are used throughout t...

  9. Monte Carlo Techniques for Calculations of Charge Deposition and Displacement Damage from Protons in Visible and Infrared Sensor Arrays

    Science.gov (United States)

    Marshall, Paul; Reed, Robert; Fodness, Bryan; Jordan, Tom; Pickel, Jim; Xapsos, Michael; Burke, Ed

    2004-01-01

    This slide presentation examines motivation for Monte Carlo methods, charge deposition in sensor arrays, displacement damage calculations, and future work. The discussion of charge deposition sensor arrays includes Si active pixel sensor APS arrays and LWIR HgCdTe FPAs. The discussion of displacement damage calculations includes nonionizing energy loss (NIEL), HgCdTe NIEL calculation results including variance, and implications for damage in HgCdTe detector arrays.

  10. Observation and modeling of biological colloids with neutron scattering techniques and Monte Carlo simulations

    NARCIS (Netherlands)

    Van Heijkamp, L.F.

    2011-01-01

    In this study non-invasive neutron scattering techniques are used on soft condensed matter, probing colloidal length scales. Neutrons penetrate deeply into matter and have a different interaction with hydrogen and deuterium, allowing for tunable contrast using light and heavy water as solvents. The

  11. Probabilistic techniques using Monte Carlo sampling for multi- component system diagnostics

    International Nuclear Information System (INIS)

    Aumeier, S.E.; Lee, J.C.; Akcasu, A.Z.

    1995-01-01

    We outline the structure of a new approach at multi-component system fault diagnostics which utilizes detailed system simulation models, uncertain system observation data, statistical knowledge of system parameters, expert opinion, and component reliability data in an effort to identify incipient component performance degradations of arbitrary number and magnitude. The technique involves the use of multiple adaptive Kalman filters for fault estimation, the results of which are screened using standard hypothesis testing procedures to define a set of component events that could have transpired. Latin Hypercube sample each of these feasible component events in terms of uncertain component reliability data and filter estimates. The capabilities of the procedure are demonstrated through the analysis of a simulated small magnitude binary component fault in a boiling water reactor balance of plant. The results show that the procedure has the potential to be a very effective tool for incipient component fault diagnosis

  12. Monte Carlo lattice program KIM

    International Nuclear Information System (INIS)

    Cupini, E.; De Matteis, A.; Simonini, R.

    1980-01-01

    The Monte Carlo program KIM solves the steady-state linear neutron transport equation for a fixed-source problem or, by successive fixed-source runs, for the eigenvalue problem, in a two-dimensional thermal reactor lattice. Fluxes and reaction rates are the main quantities computed by the program, from which power distribution and few-group averaged cross sections are derived. The simulation ranges from 10 MeV to zero and includes anisotropic and inelastic scattering in the fast energy region, the epithermal Doppler broadening of the resonances of some nuclides, and the thermalization phenomenon by taking into account the thermal velocity distribution of some molecules. Besides the well known combinatorial geometry, the program allows complex configurations to be represented by a discrete set of points, an approach greatly improving calculation speed

  13. Monte Carlo Simulation of Phase Transitions

    OpenAIRE

    村井, 信行; N., MURAI; 中京大学教養部

    1983-01-01

    In the Monte Carlo simulation of phase transition, a simple heat bath method is applied to the classical Heisenberg model in two dimensions. It reproduces the correlation length predicted by the Monte Carlo renor-malization group and also computed in the non-linear σ model

  14. Advanced Computational Methods for Monte Carlo Calculations

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-01-12

    This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.

  15. The MC21 Monte Carlo Transport Code

    International Nuclear Information System (INIS)

    Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H

    2007-01-01

    MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities

  16. Monte Carlo simulation in nuclear medicine

    International Nuclear Information System (INIS)

    Morel, Ch.

    2007-01-01

    The Monte Carlo method allows for simulating random processes by using series of pseudo-random numbers. It became an important tool in nuclear medicine to assist in the design of new medical imaging devices, optimise their use and analyse their data. Presently, the sophistication of the simulation tools allows the introduction of Monte Carlo predictions in data correction and image reconstruction processes. The availability to simulate time dependent processes opens up new horizons for Monte Carlo simulation in nuclear medicine. In a near future, these developments will allow to tackle simultaneously imaging and dosimetry issues and soon, case system Monte Carlo simulations may become part of the nuclear medicine diagnostic process. This paper describes some Monte Carlo method basics and the sampling methods that were developed for it. It gives a referenced list of different simulation software used in nuclear medicine and enumerates some of their present and prospective applications. (author)

  17. Joint Data Assimilation and Parameter Calibration in on-line groundwater modelling using Sequential Monte Carlo techniques

    Science.gov (United States)

    Ramgraber, M.; Schirmer, M.

    2017-12-01

    As computational power grows and wireless sensor networks find their way into common practice, it becomes increasingly feasible to pursue on-line numerical groundwater modelling. The reconciliation of model predictions with sensor measurements often necessitates the application of Sequential Monte Carlo (SMC) techniques, most prominently represented by the Ensemble Kalman Filter. In the pursuit of on-line predictions it seems advantageous to transcend the scope of pure data assimilation and incorporate on-line parameter calibration as well. Unfortunately, the interplay between shifting model parameters and transient states is non-trivial. Several recent publications (e.g. Chopin et al., 2013, Kantas et al., 2015) in the field of statistics discuss potential algorithms addressing this issue. However, most of these are computationally intractable for on-line application. In this study, we investigate to what extent compromises between mathematical rigour and computational restrictions can be made within the framework of on-line numerical modelling of groundwater. Preliminary studies are conducted in a synthetic setting, with the goal of transferring the conclusions drawn into application in a real-world setting. To this end, a wireless sensor network has been established in the valley aquifer around Fehraltorf, characterized by a highly dynamic groundwater system and located about 20 km to the East of Zürich, Switzerland. By providing continuous probabilistic estimates of the state and parameter distribution, a steady base for branched-off predictive scenario modelling could be established, providing water authorities with advanced tools for assessing the impact of groundwater management practices. Chopin, N., Jacob, P.E. and Papaspiliopoulos, O. (2013): SMC2: an efficient algorithm for sequential analysis of state space models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 75 (3), p. 397-426. Kantas, N., Doucet, A., Singh, S

  18. Calculation of absorbed fractions to human skeletal tissues due to alpha particles using the Monte Carlo and 3-d chord-based transport techniques

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, J.G. [Institute of Radiation Protection and Dosimetry, Av. Salvador Allende s/n, Recreio, Rio de Janeiro, CEP 22780-160 (Brazil); Watchman, C.J. [Department of Radiation Oncology, University of Arizona, Tucson, AZ, 85721 (United States); Bolch, W.E. [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL, 32611 (United States); Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611 (United States)

    2007-07-01

    Absorbed fraction (AF) calculations to the human skeletal tissues due to alpha particles are of interest to the internal dosimetry of occupationally exposed workers and members of the public. The transport of alpha particles through the skeletal tissue is complicated by the detailed and complex microscopic histology of the skeleton. In this study, both Monte Carlo and chord-based techniques were applied to the transport of alpha particles through 3-D micro-CT images of the skeletal microstructure of trabecular spongiosa. The Monte Carlo program used was 'Visual Monte Carlo-VMC'. VMC simulates the emission of the alpha particles and their subsequent energy deposition track. The second method applied to alpha transport is the chord-based technique, which randomly generates chord lengths across bone trabeculae and the marrow cavities via alternate and uniform sampling of their cumulative density functions. This paper compares the AF of energy to two radiosensitive skeletal tissues, active marrow and shallow active marrow, obtained with these two techniques. (authors)

  19. The Monte Carlo method the method of statistical trials

    CERN Document Server

    Shreider, YuA

    1966-01-01

    The Monte Carlo Method: The Method of Statistical Trials is a systematic account of the fundamental concepts and techniques of the Monte Carlo method, together with its range of applications. Some of these applications include the computation of definite integrals, neutron physics, and in the investigation of servicing processes. This volume is comprised of seven chapters and begins with an overview of the basic features of the Monte Carlo method and typical examples of its application to simple problems in computational mathematics. The next chapter examines the computation of multi-dimensio

  20. Determination of output factor for 6 MV small photon beam: comparison between Monte Carlo simulation technique and microDiamond detector

    International Nuclear Information System (INIS)

    Krongkietlearts, K; Tangboonduangjit, P; Paisangittisakul, N

    2016-01-01

    In order to improve the life's quality for a cancer patient, the radiation techniques are constantly evolving. Especially, the two modern techniques which are intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) are quite promising. They comprise of many small beam sizes (beamlets) with various intensities to achieve the intended radiation dose to the tumor and minimal dose to the nearby normal tissue. The study investigates whether the microDiamond detector (PTW manufacturer), a synthetic single crystal diamond detector, is suitable for small field output factor measurement. The results were compared with those measured by the stereotactic field detector (SFD) and the Monte Carlo simulation (EGSnrc/BEAMnrc/DOSXYZ). The calibration of Monte Carlo simulation was done using the percentage depth dose and dose profile measured by the photon field detector (PFD) of the 10×10 cm 2 field size with 100 cm SSD. Comparison of the values obtained from the calculations and measurements are consistent, no more than 1% difference. The output factors obtained from the microDiamond detector have been compared with those of SFD and Monte Carlo simulation, the results demonstrate the percentage difference of less than 2%. (paper)

  1. Monte Carlo method in radiation transport problems

    International Nuclear Information System (INIS)

    Dejonghe, G.; Nimal, J.C.; Vergnaud, T.

    1986-11-01

    In neutral radiation transport problems (neutrons, photons), two values are important: the flux in the phase space and the density of particles. To solve the problem with Monte Carlo method leads to, among other things, build a statistical process (called the play) and to provide a numerical value to a variable x (this attribution is called score). Sampling techniques are presented. Play biasing necessity is proved. A biased simulation is made. At last, the current developments (rewriting of programs for instance) are presented due to several reasons: two of them are the vectorial calculation apparition and the photon and neutron transport in vacancy media [fr

  2. Monte Carlo study of the multiquark systems

    International Nuclear Information System (INIS)

    Kerbikov, B.O.; Polikarpov, M.I.; Zamolodchikov, A.B.

    1986-01-01

    Random walks have been used to calculate the energies of the ground states in systems of N=3, 6, 9, 12 quarks. Multiquark states with N>3 are unstable with respect to the spontaneous dissociation into color singlet hadrons. The modified Green's function Monte Carlo algorithm which proved to be more simple and much accurate than the conventional few body methods have been employed. In contrast to other techniques, the same equations are used for any number of particles, while the computer time increases only linearly V, S the number of particles

  3. Present status and future prospects of neutronics Monte Carlo

    International Nuclear Information System (INIS)

    Gelbard, E.M.

    1990-01-01

    It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)

  4. Combinatorial nuclear level density by a Monte Carlo method

    International Nuclear Information System (INIS)

    Cerf, N.

    1994-01-01

    We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte Carlo simulation, making use of the Metropolis sampling scheme, allows a computationally fast estimate of the level density for many fermion systems in large shell model spaces. We emphasize the advantages of this Monte Carlo approach, particularly concerning the prediction of the spin and parity distributions of the excited states,and compare our results with those derived from a traditional combinatorial or a statistical method. Such a Monte Carlo technique seems very promising to determine accurate level densities in a large energy range for nuclear reaction calculations

  5. Diagrammatic Monte Carlo approach for diagrammatic extensions of dynamical mean-field theory: Convergence analysis of the dual fermion technique

    Science.gov (United States)

    Gukelberger, Jan; Kozik, Evgeny; Hafermann, Hartmut

    2017-07-01

    The dual fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations, however, neglect higher-order interaction vertices beyond two-particle scattering in the dual effective action and further truncate the diagrammatic expansion in the two-particle scattering vertex to a leading-order or ladder-type approximation. In this work, we compute the dual fermion expansion for the two-dimensional Hubbard model including all diagram topologies with two-particle interactions to high orders by means of a stochastic diagrammatic Monte Carlo algorithm. We benchmark the obtained self-energy against numerically exact diagrammatic determinant Monte Carlo simulations to systematically assess convergence of the dual fermion series and the validity of these approximations. We observe that, from high temperatures down to the vicinity of the DMFT Néel transition, the dual fermion series converges very quickly to the exact solution in the whole range of Hubbard interactions considered (4 ≤U /t ≤12 ), implying that contributions from higher-order vertices are small. As the temperature is lowered further, we observe slower series convergence, convergence to incorrect solutions, and ultimately divergence. This happens in a regime where magnetic correlations become significant. We find, however, that the self-consistent particle-hole ladder approximation yields reasonable and often even highly accurate results in this regime.

  6. Application of Monte Carlo techniques for standardless efficiency calibration of NaI(Tl) based gamma spectrometry system

    International Nuclear Information System (INIS)

    Verma, Amit K.; Anilkumar, S.; Narayani, K.; Babu, D.A.R.; Sharma, D.N.

    2012-01-01

    The gamma ray spectrometry technique is commonly used for the assessment of radioactivity in environmental matrices like water, soil, vegetation etc. The detector system used for gamma ray spectrometer should be calibrated for each geometry considered and for different gamma energies. It is very difficult to have radionuclide standards to cover all photon energies and also not feasible to make standard geometries for common applications. So there is a need to develop some computational techniques to determine absolute efficiencies of these detectors for practical geometries and for energies of common radioactive sources. A Monte Carlo based simulation method is proposed to study the response of the detector for various energies and geometries. From the simulated spectrum it is possible to calculate the efficiency of the gamma energy for the particular geometry modeled. The efficiency calculated by this method has to be validated experimentally using standard sources in laboratory conditions for selected geometries. For the present work simulation studies were under taken for the 3″ x 3″ NaI(Tl) detector based gamma spectrometry system set up in our laboratory. In order to see the effectiveness of the method for the low level radioactivity measurement it is planned to use low active standard source of 40 K in cylindrical container geometry for our work. Suitable detector and geometry model was developed using KCI standard of the same size, composition, density and radionuclide contents. Simulation data generated was compared with the experimental spectral data taken for a counting period of 20000 sec and 50000 sec. The peak areas obtained from the simulated spectra were compared with that of experimental spectral data. It was observed that the count rate (9.03 cps) in the simulated peak area is in agreement with that of the experimental peak area count rates (8.44 cps and 8.4 cps). The efficiency of the detector calculated by this method offers an alternative

  7. Monte Carlo simulations on SIMD computer architectures

    International Nuclear Information System (INIS)

    Burmester, C.P.; Gronsky, R.; Wille, L.T.

    1992-01-01

    In this paper algorithmic considerations regarding the implementation of various materials science applications of the Monte Carlo technique to single instruction multiple data (SIMD) computer architectures are presented. In particular, implementation of the Ising model with nearest, next nearest, and long range screened Coulomb interactions on the SIMD architecture MasPar MP-1 (DEC mpp-12000) series of massively parallel computers is demonstrated. Methods of code development which optimize processor array use and minimize inter-processor communication are presented including lattice partitioning and the use of processor array spanning tree structures for data reduction. Both geometric and algorithmic parallel approaches are utilized. Benchmarks in terms of Monte Carl updates per second for the MasPar architecture are presented and compared to values reported in the literature from comparable studies on other architectures

  8. Multiscale Monte Carlo equilibration: Pure Yang-Mills theory

    Science.gov (United States)

    Endres, Michael G.; Brower, Richard C.; Detmold, William; Orginos, Kostas; Pochinsky, Andrew V.

    2015-12-01

    We present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

  9. Monte Carlo method for solving a parabolic problem

    Directory of Open Access Journals (Sweden)

    Tian Yi

    2016-01-01

    Full Text Available In this paper, we present a numerical method based on random sampling for a parabolic problem. This method combines use of the Crank-Nicolson method and Monte Carlo method. In the numerical algorithm, we first discretize governing equations by Crank-Nicolson method, and obtain a large sparse system of linear algebraic equations, then use Monte Carlo method to solve the linear algebraic equations. To illustrate the usefulness of this technique, we apply it to some test problems.

  10. Monte carlo simulation for soot dynamics

    KAUST Repository

    Zhou, Kun

    2012-01-01

    A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

  11. Monte Carlo approaches to light nuclei

    International Nuclear Information System (INIS)

    Carlson, J.

    1990-01-01

    Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of 16 O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs

  12. Monte Carlo approaches to light nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Carlson, J.

    1990-01-01

    Significant progress has been made recently in the application of Monte Carlo methods to the study of light nuclei. We review new Green's function Monte Carlo results for the alpha particle, Variational Monte Carlo studies of {sup 16}O, and methods for low-energy scattering and transitions. Through these calculations, a coherent picture of the structure and electromagnetic properties of light nuclei has arisen. In particular, we examine the effect of the three-nucleon interaction and the importance of exchange currents in a variety of experimentally measured properties, including form factors and capture cross sections. 29 refs., 7 figs.

  13. Importance iteration in MORSE Monte Carlo calculations

    International Nuclear Information System (INIS)

    Kloosterman, J.L.; Hoogenboom, J.E.

    1994-02-01

    An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example, which shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation. (orig.)

  14. Adaptive Markov Chain Monte Carlo

    KAUST Repository

    Jadoon, Khan

    2016-08-08

    A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.

  15. Advanced computers and Monte Carlo

    International Nuclear Information System (INIS)

    Jordan, T.L.

    1979-01-01

    High-performance parallelism that is currently available is synchronous in nature. It is manifested in such architectures as Burroughs ILLIAC-IV, CDC STAR-100, TI ASC, CRI CRAY-1, ICL DAP, and many special-purpose array processors designed for signal processing. This form of parallelism has apparently not been of significant value to many important Monte Carlo calculations. Nevertheless, there is much asynchronous parallelism in many of these calculations. A model of a production code that requires up to 20 hours per problem on a CDC 7600 is studied for suitability on some asynchronous architectures that are on the drawing board. The code is described and some of its properties and resource requirements ae identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resource requirements are identified to compare with corresponding properties and resources of some asynchronous multiprocessor architectures. Arguments are made for programer aids and special syntax to identify and support important asynchronous parallelism. 2 figures, 5 tables

  16. A MONTE CARLO COMPARISON OF PAAAM_ETRIC AND ...

    African Journals Online (AJOL)

    kernel nonparametric method is proposed and developed for estimating low flow quantiles. Ba&ed on annual minimum low flow data and Monte Carlo. Si•ulation Experiments, the proposed model is eotnpand with ... Carlo simulation technique using the criteria of the descriptive ability and predictive ability of a model.

  17. A fundamental study using Monte-Carlo simulation technique on the effect on the earthquake response of subsurface layers caused by uncertainy of soil properties

    International Nuclear Information System (INIS)

    Hata, Akihito; Shiba, Yukio

    2009-01-01

    The standard for Probabilistic Safety Assessment of Nuclear Power Plant on earthquakes published by Atomic Energy Society of Japan in 2007 states that the effect of uncertainy of soil properties on the earthquake response of subsurface layers should be assessed with conducting Monte-Carlo simulations of equivalent linear analysis. This paper presents a fundamental study on the effect of uncertainty of dynamic soil properties on the earthquake response with equivalent linear approach. A series of Monte-Carlo simulations of earthquake response analysis of a simple one-dimensional soil layer model have been conducted, where uncertainty of initial shear modulus G 0 , strain dependency of G/G 0 -γ and h-γ are considered. Through a series of simulations, it is demonstrated that although the average of maximum response of the subsurface top layer increases as input earthquake motion increases, the coefficient of variance of them does not necessarily increases, and that G/G 0 -γ relationship is the most influential factor among the concerned parameters. And also, it is shown that the maximum response of ground surface plotted against the peak frequency of the frequency response function calculated with equivalent linear analysis under converged condition, distributes around the response spectrum curve of the input earthquake motion so that the maximum response can be roughly estimated from the response spectrum curve. Finally, applicability of two-point-estimate technique is examined with being compared with Monte-Carlo simulation results. (author)

  18. 11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

    CERN Document Server

    Nuyens, Dirk

    2016-01-01

    This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.

  19. Monte Carlo methods for the self-avoiding walk

    International Nuclear Information System (INIS)

    Janse van Rensburg, E J

    2009-01-01

    The numerical simulation of self-avoiding walks remains a significant component in the study of random objects in lattices. In this review, I give a comprehensive overview of the current state of Monte Carlo simulations of models of self-avoiding walks. The self-avoiding walk model is revisited, and the motivations for Monte Carlo simulations of this model are discussed. Efficient sampling of self-avoiding walks remains an elusive objective, but significant progress has been made over the last three decades. The model still poses challenging numerical questions however, and I review specific Monte Carlo methods for improved sampling including general Monte Carlo techniques such as Metropolis sampling, umbrella sampling and multiple Markov Chain sampling. In addition, specific static and dynamic algorithms for walks are presented, and I give an overview of recent innovations in this field, including algorithms such as flatPERM, flatGARM and flatGAS. (topical review)

  20. Hybrid Monte Carlo methods in computational finance

    NARCIS (Netherlands)

    Leitao Rodriguez, A.

    2017-01-01

    Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the

  1. Monte Carlo code development in Los Alamos

    International Nuclear Information System (INIS)

    Carter, L.L.; Cashwell, E.D.; Everett, C.J.; Forest, C.A.; Schrandt, R.G.; Taylor, W.M.; Thompson, W.L.; Turner, G.D.

    1974-01-01

    The present status of Monte Carlo code development at Los Alamos Scientific Laboratory is discussed. A brief summary is given of several of the most important neutron, photon, and electron transport codes. 17 references. (U.S.)

  2. Monte Carlo Algorithms for Linear Problems

    OpenAIRE

    Dimov, Ivan

    2000-01-01

    MSC Subject Classification: 65C05, 65U05. Monte Carlo methods are a powerful tool in many fields of mathematics, physics and engineering. It is known, that these methods give statistical estimates for the functional of the solution by performing random sampling of a certain chance variable whose mathematical expectation is the desired functional. Monte Carlo methods are methods for solving problems using random variables. In the book [16] edited by Yu. A. Shreider one can find the followin...

  3. Multilevel Monte Carlo in Approximate Bayesian Computation

    KAUST Repository

    Jasra, Ajay

    2017-02-13

    In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte Carlo (MLMC). A sequential Monte Carlo version of the approach is developed and it is shown under some assumptions that for a given level of mean square error, this method for ABC has a lower cost than i.i.d. sampling from the most accurate ABC approximation. Several numerical examples are given.

  4. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

    KAUST Repository

    Ben Issaid, Chaouki

    2015-01-07

    Experimental design is very important since experiments are often resource-exhaustive and time-consuming. We carry out experimental design in the Bayesian framework. To measure the amount of information, which can be extracted from the data in an experiment, we use the expected information gain as the utility function, which specifically is the expected logarithmic ratio between the posterior and prior distributions. Optimizing this utility function enables us to design experiments that yield the most informative data for our purpose. One of the major difficulties in evaluating the expected information gain is that the integral is nested and can be high dimensional. We propose using Multilevel Monte Carlo techniques to accelerate the computation of the nested high dimensional integral. The advantages are twofold. First, the Multilevel Monte Carlo can significantly reduce the cost of the nested integral for a given tolerance, by using an optimal sample distribution among different sample averages of the inner integrals. Second, the Multilevel Monte Carlo method imposes less assumptions, such as the concentration of measures, required by Laplace method. We test our Multilevel Monte Carlo technique using a numerical example on the design of sensor deployment for a Darcy flow problem governed by one dimensional Laplace equation. We also compare the performance of the Multilevel Monte Carlo, Laplace approximation and direct double loop Monte Carlo.

  5. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef

    2016-01-06

    We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence, O(TOL-2).

  6. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef

    2015-01-07

    We propose and analyze a novel Multi-Index Monte Carlo (MIMC) method for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The MIMC method is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Inspired by Giles’s seminal work, instead of using first-order differences as in MLMC, we use in MIMC high-order mixed differences to reduce the variance of the hierarchical differences dramatically. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be of Total Degree (TD) type. When using such sets, MIMC yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence.

  7. Quantum Monte Carlo for atoms and molecules

    International Nuclear Information System (INIS)

    Barnett, R.N.

    1989-11-01

    The diffusion quantum Monte Carlo with fixed nodes (QMC) approach has been employed in studying energy-eigenstates for 1--4 electron systems. Previous work employing the diffusion QMC technique yielded energies of high quality for H 2 , LiH, Li 2 , and H 2 O. Here, the range of calculations with this new approach has been extended to include additional first-row atoms and molecules. In addition, improvements in the previously computed fixed-node energies of LiH, Li 2 , and H 2 O have been obtained using more accurate trial functions. All computations were performed within, but are not limited to, the Born-Oppenheimer approximation. In our computations, the effects of variation of Monte Carlo parameters on the QMC solution of the Schroedinger equation were studied extensively. These parameters include the time step, renormalization time and nodal structure. These studies have been very useful in determining which choices of such parameters will yield accurate QMC energies most efficiently. Generally, very accurate energies (90--100% of the correlation energy is obtained) have been computed with single-determinant trail functions multiplied by simple correlation functions. Improvements in accuracy should be readily obtained using more complex trial functions

  8. REVIEW: Fifty years of Monte Carlo simulations for medical physics

    Science.gov (United States)

    Rogers, D. W. O.

    2006-07-01

    Monte Carlo techniques have become ubiquitous in medical physics over the last 50 years with a doubling of papers on the subject every 5 years between the first PMB paper in 1967 and 2000 when the numbers levelled off. While recognizing the many other roles that Monte Carlo techniques have played in medical physics, this review emphasizes techniques for electron-photon transport simulations. The broad range of codes available is mentioned but there is special emphasis on the EGS4/EGSnrc code system which the author has helped develop for 25 years. The importance of the 1987 Erice Summer School on Monte Carlo techniques is highlighted. As an illustrative example of the role Monte Carlo techniques have played, the history of the correction for wall attenuation and scatter in an ion chamber is presented as it demonstrates the interplay between a specific problem and the development of tools to solve the problem which in turn leads to applications in other areas. This paper is dedicated to W Ralph Nelson and to the memory of Martin J Berger, two men who have left indelible marks on the field of Monte Carlo simulation of electron-photon transport.

  9. Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments

    International Nuclear Information System (INIS)

    Pevey, Ronald E.

    2005-01-01

    Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL

  10. Bayesian statistics and Monte Carlo methods

    Science.gov (United States)

    Koch, K. R.

    2018-03-01

    The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

  11. Successful vectorization - reactor physics Monte Carlo code

    International Nuclear Information System (INIS)

    Martin, W.R.

    1989-01-01

    Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)

  12. MO-F-CAMPUS-I-03: GPU Accelerated Monte Carlo Technique for Fast Concurrent Image and Dose Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Becchetti, M; Tian, X; Segars, P; Samei, E [Clinical Imaging Physics Group, Department of Radiology, Duke University Me, Durham, NC (United States)

    2015-06-15

    Purpose: To develop an accurate and fast Monte Carlo (MC) method of simulating CT that is capable of correlating dose with image quality using voxelized phantoms. Methods: A realistic voxelized phantom based on patient CT data, XCAT, was used with a GPU accelerated MC code for helical MDCT. Simulations were done with both uniform density organs and with textured organs. The organ doses were validated using previous experimentally validated simulations of the same phantom under the same conditions. Images acquired by tracking photons through the phantom with MC require lengthy computation times due to the large number of photon histories necessary for accurate representation of noise. A substantial speed up of the process was attained by using a low number of photon histories with kernel denoising of the projections from the scattered photons. These FBP reconstructed images were validated against those that were acquired in simulations using many photon histories by ensuring a minimal normalized root mean square error. Results: Organ doses simulated in the XCAT phantom are within 10% of the reference values. Corresponding images attained using projection kernel smoothing were attained with 3 orders of magnitude less computation time compared to a reference simulation using many photon histories. Conclusion: Combining GPU acceleration with kernel denoising of scattered photon projections in MC simulations allows organ dose and corresponding image quality to be attained with reasonable accuracy and substantially reduced computation time than is possible with standard simulation approaches.

  13. Monte Carlo and detector simulation in OOP

    International Nuclear Information System (INIS)

    Atwood, W.B.; Blankenbecler, R.; Kunz, P.; Burnett, T.; Storr, K.M.

    1990-01-01

    Object-Oriented Programming techniques are explored with an eye towards applications in High Energy Physics codes. Two prototype examples are given: MCOOP (a particle Monte Carlo generator) and GISMO (a detector simulation/analysis package). The OOP programmer does no explicit or detailed memory management nor other bookkeeping chores; hence, the writing, modification, and extension of the code is considerably simplified. Inheritance can be used to simplify the class definitions as well as the instance variables and action methods of each class; thus the work required to add new classes, parameters, or new methods is minimal. The software industry is moving rapidly to OOP since it has been proven to improve programmer productivity, and promises even more for the future by providing truly reusable software. The High Energy Physics community clearly needs to follow this trend

  14. Angular biasing in implicit Monte-Carlo

    International Nuclear Information System (INIS)

    Zimmerman, G.B.

    1994-01-01

    Calculations of indirect drive Inertial Confinement Fusion target experiments require an integrated approach in which laser irradiation and radiation transport in the hohlraum are solved simultaneously with the symmetry, implosion and burn of the fuel capsule. The Implicit Monte Carlo method has proved to be a valuable tool for the two dimensional radiation transport within the hohlraum, but the impact of statistical noise on the symmetric implosion of the small fuel capsule is difficult to overcome. We present an angular biasing technique in which an increased number of low weight photons are directed at the imploding capsule. For typical parameters this reduces the required computer time for an integrated calculation by a factor of 10. An additional factor of 5 can also be achieved by directing even smaller weight photons at the polar regions of the capsule where small mass zones are most sensitive to statistical noise

  15. A Monte Carlo learning/biasing experiment with intelligent random numbers

    International Nuclear Information System (INIS)

    Booth, T.E.

    1986-01-01

    A Monte Carlo learning and biasing technique that does its learning and biasing in the random number space rather than the physical phase space is described. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed

  16. Investigation of Reduction of the Uncertainty of Monte Carlo Dose Calculations in Oncor® Clinical Linear Accelerator Simulation Using the DBS Variance Reduction Technique in Monte Carlo Code BEAMnrc

    Directory of Open Access Journals (Sweden)

    Amin Asadi

    2017-10-01

    Full Text Available Purpose: To study the benefits of Directional Bremsstrahlung Splitting (DBS dose variance reduction technique in BEAMnrc Monte Carlo (MC code for Oncor® linac at 6MV and 18MV energies. Materials and Method: A MC model of Oncor® linac was built using BEAMnrc MC Code and verified by the measured data for 6MV and 18MV energies of various field sizes. Then Oncor® machine was modeled running DBS technique, and the efficiency of total fluence and spatial fluence for electron and photon, the efficiency of dose variance reduction of MC calculations for PDD on the central beam axis and lateral dose profile across the nominal field was measured and compared. Result: With applying DBS technique, the total fluence of electron and photon increased in turn 626.8 (6MV and 983.4 (6MV, and 285.6 (18MV and 737.8 (18MV, the spatial fluence of electron and photon improved in turn 308.6±1.35% (6MV and 480.38±0.43% (6MV, and 153±0.9% (18MV and 462.6±0.27% (18MV. Moreover, by running DBS technique, the efficiency of dose variance reduction for PDD MC dose calculations before maximum dose point and after dose maximum point enhanced 187.8±0.68% (6MV and 184.6±0.65% (6MV, 156±0.43% (18MV and 153±0.37% (18MV, respectively, and the efficiency of MC calculations for lateral dose profile remarkably on the central beam axis and across the treatment field raised in turn 197±0.66% (6MV and 214.6±0.73% (6MV, 175±0.36% (18MV and 181.4±0.45% (18MV. Conclusion: Applying dose variance reduction technique of DBS for modeling Oncor® linac with using BEAMnrc MC Code surprisingly improved the fluence of electron and photon, and it therefore enhanced the efficiency of dose variance reduction for MC calculations. As a result, running DBS in different kinds of MC simulation Codes might be beneficent in reducing the uncertainty of MC calculations. 

  17. Accelerated GPU based SPECT Monte Carlo simulations.

    Science.gov (United States)

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-07

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational

  18. Accelerated GPU based SPECT Monte Carlo simulations

    Science.gov (United States)

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-01

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency

  19. Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations

    DEFF Research Database (Denmark)

    Kamran, Faisal; Andersen, Peter E.

    2015-01-01

    profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...

  20. closed-shell variational quantum monte carlo simulation for the ...

    African Journals Online (AJOL)

    Vincent

    presented. The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock. (RHF) scheme. The components dependence of the electric dipole moment from the QMC technique is studied with a single determinant Slater-Jastrow trial wave-function obtained from the ...

  1. Utilising Monte Carlo Simulation for the Valuation of Mining Concessions

    Directory of Open Access Journals (Sweden)

    Rosli Said

    2005-12-01

    Full Text Available Valuation involves the analyses of various input data to produce an estimated value. Since each input is itself often an estimate, there is an element of uncertainty in the input. This leads to uncertainty in the resultant output value. It is argued that a valuation must also convey information on the uncertainty, so as to be more meaningful and informative to the user. The Monte Carlo simulation technique can generate the information on uncertainty and is therefore potentially useful to valuation. This paper reports on the investigation that has been conducted to apply Monte Carlo simulation technique in mineral valuation, more specifically, in the valuation of a quarry concession.

  2. Adiabatic optimization versus diffusion Monte Carlo methods

    Science.gov (United States)

    Jarret, Michael; Jordan, Stephen P.; Lackey, Brad

    2016-10-01

    Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .

  3. Random Numbers and Monte Carlo Methods

    Science.gov (United States)

    Scherer, Philipp O. J.

    Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

  4. Monte Carlo simulation of continuous-space crystal growth

    International Nuclear Information System (INIS)

    Dodson, B.W.; Taylor, P.A.

    1986-01-01

    We describe a method, based on Monte Carlo techniques, of simulating the atomic growth of crystals without the discrete lattice space assumed by conventional Monte Carlo growth simulations. Since no lattice space is assumed, problems involving epitaxial growth, heteroepitaxy, phonon-driven mechanisms, surface reconstruction, and many other phenomena incompatible with the lattice-space approximation can be studied. Also, use of the Monte Carlo method circumvents to some extent the extreme limitations on simulated timescale inherent in crystal-growth techniques which might be proposed using molecular dynamics. The implementation of the new method is illustrated by studying the growth of strained-layer superlattice (SLS) interfaces in two-dimensional Lennard-Jones atomic systems. Despite the extreme simplicity of such systems, the qualitative features of SLS growth seen here are similar to those observed experimentally in real semiconductor systems

  5. Simulation of transport equations with Monte Carlo

    International Nuclear Information System (INIS)

    Matthes, W.

    1975-09-01

    The main purpose of the report is to explain the relation between the transport equation and the Monte Carlo game used for its solution. The introduction of artificial particles carrying a weight provides one with high flexibility in constructing many different games for the solution of the same equation. This flexibility opens a way to construct a Monte Carlo game for the solution of the adjoint transport equation. Emphasis is laid mostly on giving a clear understanding of what to do and not on the details of how to do a specific game

  6. Self-learning Monte Carlo (dynamical biasing)

    International Nuclear Information System (INIS)

    Matthes, W.

    1981-01-01

    In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)

  7. Monte Carlo electron/photon transport

    International Nuclear Information System (INIS)

    Mack, J.M.; Morel, J.E.; Hughes, H.G.

    1985-01-01

    A review of nonplasma coupled electron/photon transport using Monte Carlo method is presented. Remarks are mainly restricted to linerarized formalisms at electron energies from 1 keV to 1000 MeV. Applications involving pulse-height estimation, transport in external magnetic fields, and optical Cerenkov production are discussed to underscore the importance of this branch of computational physics. Advances in electron multigroup cross-section generation is reported, and its impact on future code development assessed. Progress toward the transformation of MCNP into a generalized neutral/charged-particle Monte Carlo code is described. 48 refs

  8. A keff calculation method by Monte Carlo

    International Nuclear Information System (INIS)

    Shen, H; Wang, K.

    2008-01-01

    The effective multiplication factor (k eff ) is defined as the ratio between the number of neutrons in successive generations, which definition is adopted by most Monte Carlo codes (e.g. MCNP). Also, it can be thought of as the ratio of the generation rate of neutrons by the sum of the leakage rate and the absorption rate, which should exclude the effect of the neutron reaction such as (n, 2n) and (n, 3n). This article discusses the Monte Carlo method for k eff calculation based on the second definition. A new code has been developed and the results are presented. (author)

  9. Monte Carlo Treatment Planning for Advanced Radiotherapy

    DEFF Research Database (Denmark)

    Cronholm, Rickard

    This Ph.d. project describes the development of a workflow for Monte Carlo Treatment Planning for clinical radiotherapy plans. The workflow may be utilized to perform an independent dose verification of treatment plans. Modern radiotherapy treatment delivery is often conducted by dynamically...... modulating the intensity of the field during the irradiation. The workflow described has the potential to fully model the dynamic delivery, including gantry rotation during irradiation, of modern radiotherapy. Three corner stones of Monte Carlo Treatment Planning are identified: Building, commissioning...

  10. Monte Carlo dose distributions for radiosurgery

    International Nuclear Information System (INIS)

    Perucha, M.; Leal, A.; Rincon, M.; Carrasco, E.

    2001-01-01

    The precision of Radiosurgery Treatment planning systems is limited by the approximations of their algorithms and by their dosimetrical input data. This fact is especially important in small fields. However, the Monte Carlo methods is an accurate alternative as it considers every aspect of particle transport. In this work an acoustic neurinoma is studied by comparing the dose distribution of both a planning system and Monte Carlo. Relative shifts have been measured and furthermore, Dose-Volume Histograms have been calculated for target and adjacent organs at risk. (orig.)

  11. Radiation shielding techniques and applications. 4. Two-Phase Monte Carlo Approach to Photon Streaming Through Three-Legged Penetrations

    International Nuclear Information System (INIS)

    White, Travis; Hack, Joe; Nathan, Steve; Barnett, Marvin

    2001-01-01

    solutions for scattering of neutrons through multi-legged penetrations are readily available in the literature; similar analytical solutions for photon scattering through penetrations, however, are not. Therefore, computer modeling must be relied upon to perform our analyses. The computer code typically used by Westinghouse SMS in the evaluation of photon transport through complex geometries is the MCNP Monte Carlo computer code. Yet, geometries of this nature can cause problems even with the Monte Carlo codes. Striking a balance between how the code handles bulk transport through the wall with transport through the penetration void, particularly with the use of typical variance reduction methods, is difficult when trying to ensure that all the important regions of the model are sampled appropriately. The problem was broken down into several roughly independent cases. First, scatter through the penetration was considered. Second, bulk transport through the hot leg of the duct and then through the remaining thickness of wall was calculated to determine the amount of supplemental shielding required in the wall. Similar analyses were performed for the middle and cold legs of the penetration. Finally, additional external shielding from radiation streaming through the duct was determined for cases where the minimum offset distance was not feasible. Each case was broken down further into two phases. In the first phase of each case, photons were transported from the source material to an area at the face of the wall, or the opening of the duct, where photon energy and angular distributions were tallied, representing the source incident on the wall or opening. Then, a simplified model for each case was developed and analyzed using the data from the first phase and the new source term. (authors)

  12. Use of Monte Carlo Methods in brachytherapy; Uso del metodo de Monte Carlo en braquiterapia

    Energy Technology Data Exchange (ETDEWEB)

    Granero Cabanero, D.

    2015-07-01

    The Monte Carlo method has become a fundamental tool for brachytherapy dosimetry mainly because no difficulties associated with experimental dosimetry. In brachytherapy the main handicap of experimental dosimetry is the high dose gradient near the present sources making small uncertainties in the positioning of the detectors lead to large uncertainties in the dose. This presentation will review mainly the procedure for calculating dose distributions around a fountain using the Monte Carlo method showing the difficulties inherent in these calculations. In addition we will briefly review other applications of the method of Monte Carlo in brachytherapy dosimetry, as its use in advanced calculation algorithms, calculating barriers or obtaining dose applicators around. (Author)

  13. On the use of stochastic approximation Monte Carlo for Monte Carlo integration

    KAUST Repository

    Liang, Faming

    2009-03-01

    The stochastic approximation Monte Carlo (SAMC) algorithm has recently been proposed as a dynamic optimization algorithm in the literature. In this paper, we show in theory that the samples generated by SAMC can be used for Monte Carlo integration via a dynamically weighted estimator by calling some results from the literature of nonhomogeneous Markov chains. Our numerical results indicate that SAMC can yield significant savings over conventional Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, for the problems for which the energy landscape is rugged. © 2008 Elsevier B.V. All rights reserved.

  14. Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules

    CERN Document Server

    Lester, William A; Reynolds, PJ

    1994-01-01

    This book presents the basic theory and application of the Monte Carlo method to the electronic structure of atoms and molecules. It assumes no previous knowledge of the subject, only a knowledge of molecular quantum mechanics at the first-year graduate level. A working knowledge of traditional ab initio quantum chemistry is helpful, but not essential.Some distinguishing features of this book are: Clear exposition of the basic theory at a level to facilitate independent study. Discussion of the various versions of the theory: diffusion Monte Carlo, Green's function Monte Carlo, and release n

  15. Optimization of the Kinetic Activation-Relaxation Technique, an off-lattice and self-learning kinetic Monte-Carlo method

    International Nuclear Information System (INIS)

    Joly, Jean-François; Béland, Laurent Karim; Brommer, Peter; Mousseau, Normand; El-Mellouhi, Fedwa

    2012-01-01

    We present two major optimizations for the kinetic Activation-Relaxation Technique (k-ART), an off-lattice self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search THAT has been successfully applied to study a number of semiconducting and metallic systems. K-ART is parallelized in a non-trivial way: A master process uses several worker processes to perform independent event searches for possible events, while all bookkeeping and the actual simulation is performed by the master process. Depending on the complexity of the system studied, the parallelization scales well for tens to more than one hundred processes. For dealing with large systems, we present a near order 1 implementation. Techniques such as Verlet lists, cell decomposition and partial force calculations are implemented, and the CPU time per time step scales sublinearly with the number of particles, providing an efficient use of computational resources.

  16. Monte Carlo simulation of neutron counters for safeguards applications

    International Nuclear Information System (INIS)

    Looman, Marc; Peerani, Paolo; Tagziria, Hamid

    2009-01-01

    MCNP-PTA is a new Monte Carlo code for the simulation of neutron counters for nuclear safeguards applications developed at the Joint Research Centre (JRC) in Ispra (Italy). After some preliminary considerations outlining the general aspects involved in the computational modelling of neutron counters, this paper describes the specific details and approximations which make up the basis of the model implemented in the code. One of the major improvements allowed by the use of Monte Carlo simulation is a considerable reduction in both the experimental work and in the reference materials required for the calibration of the instruments. This new approach to the calibration of counters using Monte Carlo simulation techniques is also discussed.

  17. Estimation of flux distributions with Monte Carlo functional expansion tallies

    International Nuclear Information System (INIS)

    Griesheimer, D. P.; Martin, W. R.; Holloway, J. P.

    2005-01-01

    Monte Carlo methods provide a powerful technique for estimating the average radiation flux in a volume (or across a surface) in cases where analytical solutions may not be possible. Unfortunately, Monte Carlo simulations typically provide only integral results and do not offer any further details about the distribution of the flux with respect to space, angle, time or energy. In the functional expansion tally (FET) a Monte Carlo simulation is used to estimate the functional expansion coefficients for flux distributions with respect to an orthogonal set of basis functions. The expansion coefficients are then used in post-processing to reconstruct a series approximation to the true distribution. Discrete event FET estimators are derived and their application in estimating radiation flux or current distributions is demonstrated. Sources of uncertainty in the FET are quantified and estimators for the statistical and truncation errors are derived. Numerical results are presented to support the theoretical development. (authors)

  18. Biases in Monte Carlo eigenvalue calculations

    Energy Technology Data Exchange (ETDEWEB)

    Gelbard, E.M.

    1992-12-01

    The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

  19. Biases in Monte Carlo eigenvalue calculations

    Energy Technology Data Exchange (ETDEWEB)

    Gelbard, E.M.

    1992-01-01

    The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

  20. Monte Carlo method for random surfaces

    International Nuclear Information System (INIS)

    Berg, B.

    1985-01-01

    Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)

  1. Computer system for Monte Carlo experimentation

    International Nuclear Information System (INIS)

    Grier, D.A.

    1986-01-01

    A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language

  2. Workshop: Monte Carlo computational performance benchmark - Contributions

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.; Petrovic, B.; Martin, W.R.; Sutton, T.; Leppaenen, J.; Forget, B.; Romano, P.; Siegel, A.; Hoogenboom, E.; Wang, K.; Li, Z.; She, D.; Liang, J.; Xu, Q.; Qiu, Y.; Yu, J.; Sun, J.; Fan, X.; Yu, G.; Bernard, F.; Cochet, B.; Jinaphanh, A.; Jacquet, O.; Van der Marck, S.; Tramm, J.; Felker, K.; Smith, K.; Horelik, N.; Capellan, N.; Herman, B.

    2013-01-01

    This series of slides is divided into 3 parts. The first part is dedicated to the presentation of the Monte-Carlo computational performance benchmark (aims, specifications and results). This benchmark aims at performing a full-size Monte Carlo simulation of a PWR core with axial and pin-power distribution. Many different Monte Carlo codes have been used and their results have been compared in terms of computed values and processing speeds. It appears that local power values mostly agree quite well. The first part also includes the presentations of about 10 participants in which they detail their calculations. In the second part, an extension of the benchmark is proposed in order to simulate a more realistic reactor core (for instance non-uniform temperature) and to assess feedback coefficients due to change of some parameters. The third part deals with another benchmark, the BEAVRS benchmark (Benchmark for Evaluation And Validation of Reactor Simulations). BEAVRS is also a full-core PWR benchmark for Monte Carlo simulations

  3. Monte Carlo determination of heteroepitaxial misfit structures

    DEFF Research Database (Denmark)

    Baker, J.; Lindgård, Per-Anker

    1996-01-01

    We use Monte Carlo simulations to determine the structure of KBr overlayers on a NaCl(001) substrate, a system with large (17%) heteroepitaxial misfit. The equilibrium relaxation structure is determined for films of 2-6 ML, for which extensive helium-atom scattering data exist for comparison...

  4. Dynamic bounds coupled with Monte Carlo simulations

    NARCIS (Netherlands)

    Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.

    2011-01-01

    For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper

  5. Atomistic Monte Carlo simulation of lipid membranes

    DEFF Research Database (Denmark)

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....

  6. Design and analysis of Monte Carlo experiments

    NARCIS (Netherlands)

    Kleijnen, Jack P.C.; Gentle, J.E.; Haerdle, W.; Mori, Y.

    2012-01-01

    By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to

  7. Scalable Domain Decomposed Monte Carlo Particle Transport

    Energy Technology Data Exchange (ETDEWEB)

    O' Brien, Matthew Joseph [Univ. of California, Davis, CA (United States)

    2013-12-05

    In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

  8. An analysis of Monte Carlo tree search

    CSIR Research Space (South Africa)

    James, S

    2017-02-01

    Full Text Available Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in recent years. Despite the vast amount of research into MCTS, the effect of modifications on the algorithm, as well as the manner...

  9. Parallel processing Monte Carlo radiation transport codes

    International Nuclear Information System (INIS)

    McKinney, G.W.

    1994-01-01

    Issues related to distributed-memory multiprocessing as applied to Monte Carlo radiation transport are discussed. Measurements of communication overhead are presented for the radiation transport code MCNP which employs the communication software package PVM, and average efficiency curves are provided for a homogeneous virtual machine

  10. Monte Carlo studies of uranium calorimetry

    International Nuclear Information System (INIS)

    Brau, J.; Hargis, H.J.; Gabriel, T.A.; Bishop, B.L.

    1985-01-01

    Detailed Monte Carlo calculations of uranium calorimetry are presented which reveal a significant difference in the responses of liquid argon and plastic scintillator in uranium calorimeters. Due to saturation effects, neutrons from the uranium are found to contribute only weakly to the liquid argon signal. Electromagnetic sampling inefficiencies are significant and contribute substantially to compensation in both systems. 17 references

  11. Coded aperture optimization using Monte Carlo simulations

    International Nuclear Information System (INIS)

    Martineau, A.; Rocchisani, J.M.; Moretti, J.L.

    2010-01-01

    Coded apertures using Uniformly Redundant Arrays (URA) have been unsuccessfully evaluated for two-dimensional and three-dimensional imaging in Nuclear Medicine. The images reconstructed from coded projections contain artifacts and suffer from poor spatial resolution in the longitudinal direction. We introduce a Maximum-Likelihood Expectation-Maximization (MLEM) algorithm for three-dimensional coded aperture imaging which uses a projection matrix calculated by Monte Carlo simulations. The aim of the algorithm is to reduce artifacts and improve the three-dimensional spatial resolution in the reconstructed images. Firstly, we present the validation of GATE (Geant4 Application for Emission Tomography) for Monte Carlo simulations of a coded mask installed on a clinical gamma camera. The coded mask modelling was validated by comparison between experimental and simulated data in terms of energy spectra, sensitivity and spatial resolution. In the second part of the study, we use the validated model to calculate the projection matrix with Monte Carlo simulations. A three-dimensional thyroid phantom study was performed to compare the performance of the three-dimensional MLEM reconstruction with conventional correlation method. The results indicate that the artifacts are reduced and three-dimensional spatial resolution is improved with the Monte Carlo-based MLEM reconstruction.

  12. Back propagation and Monte Carlo algorithms for neural network computations

    International Nuclear Information System (INIS)

    Junczys, R.; Wit, R.

    1996-01-01

    Results of teaching procedures for neural network for two different algorithms are presented. The first one is based on the well known back-propagation technique, the second is an adopted version of the Monte Carlo global minimum seeking method. Combination of these two, different in nature, approaches provides promising results. (author) nature, approaches provides promising results. (author)

  13. A Monte Carlo adapted finite element method for dislocation ...

    Indian Academy of Sciences (India)

    P Zakian

    2017-10-10

    Oct 10, 2017 ... simulations are proposed. Various comparisons are examined to illustrate the capability of both methods for random simulation of faults. Keywords. Monte Carlo simulation; stochastic modeling; split node technique; finite element method; earthquake fault dislocation. 1. Introduction. In material science, a ...

  14. Closed-shell variational quantum Monte Carlo simulation for the ...

    African Journals Online (AJOL)

    Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... From our result, though the VQMC method showed much fluctuation, the technique calculated the electric dipole moment of hydrazine molecule as 2.0 D, which is in closer ...

  15. K-Antithetic Variates in Monte Carlo Simulation | Nasroallah | Afrika ...

    African Journals Online (AJOL)

    Abstract. Standard Monte Carlo simulation needs prohibitive time to achieve reasonable estimations. for untractable integrals (i.e. multidimensional integrals and/or intergals with complex integrand forms). Several statistical technique, called variance reduction methods, are used to reduce the simulation time. In this note ...

  16. Uncertainty analysis in Monte Carlo criticality computations

    International Nuclear Information System (INIS)

    Qi Ao

    2011-01-01

    Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.

  17. Novel Quantum Monte Carlo Approaches for Quantum Liquids

    Science.gov (United States)

    Rubenstein, Brenda M.

    Quantum Monte Carlo methods are a powerful suite of techniques for solving the quantum many-body problem. By using random numbers to stochastically sample quantum properties, QMC methods are capable of studying low-temperature quantum systems well beyond the reach of conventional deterministic techniques. QMC techniques have likewise been indispensible tools for augmenting our current knowledge of superfluidity and superconductivity. In this thesis, I present two new quantum Monte Carlo techniques, the Monte Carlo Power Method and Bose-Fermi Auxiliary-Field Quantum Monte Carlo, and apply previously developed Path Integral Monte Carlo methods to explore two new phases of quantum hard spheres and hydrogen. I lay the foundation for a subsequent description of my research by first reviewing the physics of quantum liquids in Chapter One and the mathematics behind Quantum Monte Carlo algorithms in Chapter Two. I then discuss the Monte Carlo Power Method, a stochastic way of computing the first several extremal eigenvalues of a matrix too memory-intensive to be stored and therefore diagonalized. As an illustration of the technique, I demonstrate how it can be used to determine the second eigenvalues of the transition matrices of several popular Monte Carlo algorithms. This information may be used to quantify how rapidly a Monte Carlo algorithm is converging to the equilibrium probability distribution it is sampling. I next present the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm. This algorithm generalizes the well-known Auxiliary-Field Quantum Monte Carlo algorithm for fermions to bosons and Bose-Fermi mixtures. Despite some shortcomings, the Bose-Fermi Auxiliary-Field Quantum Monte Carlo algorithm represents the first exact technique capable of studying Bose-Fermi mixtures of any size in any dimension. In Chapter Six, I describe a new Constant Stress Path Integral Monte Carlo algorithm for the study of quantum mechanical systems under high pressures. While

  18. Therapeutic Applications of Monte Carlo Calculations in Nuclear Medicine

    International Nuclear Information System (INIS)

    Coulot, J

    2003-01-01

    Monte Carlo techniques are involved in many applications in medical physics, and the field of nuclear medicine has seen a great development in the past ten years due to their wider use. Thus, it is of great interest to look at the state of the art in this domain, when improving computer performances allow one to obtain improved results in a dramatically reduced time. The goal of this book is to make, in 15 chapters, an exhaustive review of the use of Monte Carlo techniques in nuclear medicine, also giving key features which are not necessary directly related to the Monte Carlo method, but mandatory for its practical application. As the book deals with therapeutic' nuclear medicine, it focuses on internal dosimetry. After a general introduction on Monte Carlo techniques and their applications in nuclear medicine (dosimetry, imaging and radiation protection), the authors give an overview of internal dosimetry methods (formalism, mathematical phantoms, quantities of interest). Then, some of the more widely used Monte Carlo codes are described, as well as some treatment planning softwares. Some original techniques are also mentioned, such as dosimetry for boron neutron capture synovectomy. It is generally well written, clearly presented, and very well documented. Each chapter gives an overview of each subject, and it is up to the reader to investigate it further using the extensive bibliography provided. Each topic is discussed from a practical point of view, which is of great help for non-experienced readers. For instance, the chapter about mathematical aspects of Monte Carlo particle transport is very clear and helps one to apprehend the philosophy of the method, which is often a difficulty with a more theoretical approach. Each chapter is put in the general (clinical) context, and this allows the reader to keep in mind the intrinsic limitation of each technique involved in dosimetry (for instance activity quantitation). Nevertheless, there are some minor remarks to

  19. Simulation study on the behavior of X-rays and gamma rays in an inhomogeneous medium using the Monte Carlo technique

    International Nuclear Information System (INIS)

    Murase, Kenya; Kataoka, Masaaki; Kawamura, Masashi; Tamada, Shuji; Hamamoto, Ken

    1989-01-01

    A computer program based on the Monte Carlo technique was developed for the analysis of the behavior of X-rays and gamma rays in an inhomogeneous medium. The statistical weight of a photon was introduced and the survival biasing method was used for reducing the statistical error. This computer program has the mass energy absorption and attenuation coefficients for 69 tissues and organs as a database file, and can be applied to various cases of inhomogeneity. The simulation and experimental results of the central axis percent-depth dose in an inhomogeneous phantom were in good agreement. This computer program will be useful for analysis on the behavior of X-rays and gamma rays in an inhomogeneous medium consisting of various tissues and organs, not only in radiotherapy treatment planning but also in diagnostic radiology and in the field treating radiation protection. (author)

  20. minimum thresholds of monte carlo cycles for nigerian empirical

    African Journals Online (AJOL)

    2012-11-03

    Nov 3, 2012 ... Abstract. Monte Carlo simulation has proven to be an effective means of incorporating reliability analysis into the ... Monte Carlo simulation cycle of 2, 500 thresholds were enough to be used to provide sufficient repeatability for ... rameters using Monte Carlo method with the aid of. MATrixLABoratory.

  1. Propagation of Statistical and Nuclear Data Uncertainties in Monte-Carlo Burn-up Calculations

    OpenAIRE

    García Herranz, Nuria; Cabellos de Francisco, Oscar Luis; Sanz Gonzalo, Javier; Juan Ruiz, Jesús; Kuijper, Jim C.

    2008-01-01

    Two methodologies to propagate the uncertainties on the nuclide inventory in combined Monte Carlo-spectrum and burn-up calculations are presented, based on sensitivity/uncertainty and random sampling techniques (uncertainty Monte Carlo method). Both enable the assessment of the impact of uncertainties in the nuclear data as well as uncertainties due to the statistical nature of the Monte Carlo neutron transport calculation. The methodologies are implemented in our MCNP–ACAB system, which comb...

  2. Neutron analysis of spent fuel storage installation using parallel computing and advance discrete ordinates and Monte Carlo techniques

    International Nuclear Information System (INIS)

    Shedlock, D.; Haghighat, A.

    2005-01-01

    In the United States, the Nuclear Waste Policy Act of 1982 mandated centralised storage of spent nuclear fuel by 1988. However, the Yucca Mountain project is currently scheduled to start accepting spent nuclear fuel in 2010. Since many nuclear power plants were only designed for ∼10 y of spent fuel pool storage, >35 plants have been forced into alternate means of spent fuel storage. In order to continue operation and make room in spent fuel pools, nuclear generators are turning towards independent spent fuel storage installations (ISFSIs). Typical vertical concrete ISFSIs are ∼6.1 m high and 3.3 m in diameter. The inherently large system, and the presence of thick concrete shields result in difficulties for both Monte Carlo (MC) and discrete ordinates (S N ) calculations. MC calculations require significant variance reduction and multiple runs to obtain a detailed dose distribution. S N models need a large number of spatial meshes to accurately model the geometry and high quadrature orders to reduce ray effects, therefore, requiring significant amounts of computer memory and time. The use of various differencing schemes is needed to account for radial heterogeneity in material cross sections and densities. Two P 3 , S 12 , discrete ordinate, PENTRAN (parallel environment neutral-particle Transport) models were analysed and different MC models compared. A multigroup MCNP model was developed for direct comparison to the S N models. The biased A 3MCNP (automated adjoint accelerated MCNP) and unbiased (MCNP) continuous energy MC models were developed to assess the adequacy of the CASK multigroup (22 neutron, 18 gamma) cross sections. The PENTRAN S N results are in close agreement (5%) with the multigroup MC results; however, they differ by ∼20-30% from the continuous-energy MC predictions. This large difference can be attributed to the expected difference between multigroup and continuous energy cross sections, and the fact that the CASK library is based on the

  3. Lecture 1. Monte Carlo basics. Lecture 2. Adjoint Monte Carlo. Lecture 3. Coupled Forward-Adjoint calculations

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.

    2000-01-01

    The Monte Carlo method is a statistical method to solve mathematical and physical problems using random numbers. The principle of the methods will be demonstrated for a simple mathematical problem and for neutron transport. Various types of estimators will be discussed, as well as generally applied variance reduction methods like splitting, Russian roulette and importance biasing. The theoretical formulation for solving eigenvalue problems for multiplying systems will be shown. Some reflections will be given about the applicability of the Monte Carlo method, its limitations and its future prospects for reactor physics calculations. Adjoint Monte Carlo is a Monte Carlo game to solve the adjoint neutron (or photon) transport equation. The adjoint transport equation can be interpreted in terms of simulating histories of artificial particles, which show properties of neutrons that move backwards in history. These particles will start their history at the detector from which the response must be estimated and give a contribution to the estimated quantity when they hit or pass through the neutron source. Application to multigroup transport formulation will be demonstrated Possible implementation for the continuous energy case will be outlined. The inherent advantages and disadvantages of the method will be discussed. The Midway Monte Carlo method will be presented for calculating a detector response due to a (neutron or photon) source. A derivation will be given of the basic formula for the Midway Monte Carlo method The black absorber technique, allowing for a cutoff of particle histories when reaching the midway surface in one of the calculations will be derived. An extension of the theory to coupled neutron-photon problems is given. The method will be demonstrated for an oil well logging problem, comprising a neutron source in a borehole and photon detectors to register the photons generated by inelastic neutron scattering. (author)

  4. Monte Carlo simulations for heavy ion dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Geithner, O.

    2006-07-26

    Water-to-air stopping power ratio (s{sub w,air}) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s{sub w,air}, the influence of fragments and I-values on s{sub w,air} for carbon ion beams was investigated. The value of s{sub w,air} deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)

  5. Monte Carlo simulations for heavy ion dosimetry

    International Nuclear Information System (INIS)

    Geithner, O.

    2006-01-01

    Water-to-air stopping power ratio (s w,air ) calculations for the ionization chamber dosimetry of clinically relevant ion beams with initial energies from 50 to 450 MeV/u have been performed using the Monte Carlo technique. To simulate the transport of a particle in water the computer code SHIELD-HIT v2 was used which is a substantially modified version of its predecessor SHIELD-HIT v1. The code was partially rewritten, replacing formerly used single precision variables with double precision variables. The lowest particle transport specific energy was decreased from 1 MeV/u down to 10 keV/u by modifying the Bethe- Bloch formula, thus widening its range for medical dosimetry applications. Optional MSTAR and ICRU-73 stopping power data were included. The fragmentation model was verified using all available experimental data and some parameters were adjusted. The present code version shows excellent agreement with experimental data. Additional to the calculations of stopping power ratios, s w,air , the influence of fragments and I-values on s w,air for carbon ion beams was investigated. The value of s w,air deviates as much as 2.3% at the Bragg peak from the recommended by TRS-398 constant value of 1.130 for an energy of 50 MeV/u. (orig.)

  6. Parallel Monte Carlo Simulation of Aerosol Dynamics

    Directory of Open Access Journals (Sweden)

    Kun Zhou

    2014-02-01

    Full Text Available A highly efficient Monte Carlo (MC algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process. Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI. The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles.

  7. Parallel Monte Carlo simulation of aerosol dynamics

    KAUST Repository

    Zhou, K.

    2014-01-01

    A highly efficient Monte Carlo (MC) algorithm is developed for the numerical simulation of aerosol dynamics, that is, nucleation, surface growth, and coagulation. Nucleation and surface growth are handled with deterministic means, while coagulation is simulated with a stochastic method (Marcus-Lushnikov stochastic process). Operator splitting techniques are used to synthesize the deterministic and stochastic parts in the algorithm. The algorithm is parallelized using the Message Passing Interface (MPI). The parallel computing efficiency is investigated through numerical examples. Near 60% parallel efficiency is achieved for the maximum testing case with 3.7 million MC particles running on 93 parallel computing nodes. The algorithm is verified through simulating various testing cases and comparing the simulation results with available analytical and/or other numerical solutions. Generally, it is found that only small number (hundreds or thousands) of MC particles is necessary to accurately predict the aerosol particle number density, volume fraction, and so forth, that is, low order moments of the Particle Size Distribution (PSD) function. Accurately predicting the high order moments of the PSD needs to dramatically increase the number of MC particles. 2014 Kun Zhou et al.

  8. Monte Carlo Particle Transport: Algorithm and Performance Overview

    International Nuclear Information System (INIS)

    Gentile, N.; Procassini, R.; Scott, H.

    2005-01-01

    Monte Carlo methods are frequently used for neutron and radiation transport. These methods have several advantages, such as relative ease of programming and dealing with complex meshes. Disadvantages include long run times and statistical noise. Monte Carlo photon transport calculations also often suffer from inaccuracies in matter temperature due to the lack of implicitness. In this paper we discuss the Monte Carlo algorithm as it is applied to neutron and photon transport, detail the differences between neutron and photon Monte Carlo, and give an overview of the ways the numerical method has been modified to deal with issues that arise in photon Monte Carlo simulations

  9. Status of Monte Carlo at Los Alamos

    International Nuclear Information System (INIS)

    Thompson, W.L.; Cashwell, E.D.

    1980-01-01

    At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time

  10. Monte Carlo simulation of gas Cerenkov detectors

    International Nuclear Information System (INIS)

    Mack, J.M.; Jain, M.; Jordan, T.M.

    1984-01-01

    Theoretical study of selected gamma-ray and electron diagnostic necessitates coupling Cerenkov radiation to electron/photon cascades. A Cerenkov production model and its incorporation into a general geometry Monte Carlo coupled electron/photon transport code is discussed. A special optical photon ray-trace is implemented using bulk optical properties assigned to each Monte Carlo zone. Good agreement exists between experimental and calculated Cerenkov data in the case of a carbon-dioxide gas Cerenkov detector experiment. Cerenkov production and threshold data are presented for a typical carbon-dioxide gas detector that converts a 16.7 MeV photon source to Cerenkov light, which is collected by optics and detected by a photomultiplier

  11. No-compromise reptation quantum Monte Carlo

    International Nuclear Information System (INIS)

    Yuen, W K; Farrar, Thomas J; Rothstein, Stuart M

    2007-01-01

    Since its publication, the reptation quantum Monte Carlo algorithm of Baroni and Moroni (1999 Phys. Rev. Lett. 82 4745) has been applied to several important problems in physics, but its mathematical foundations are not well understood. We show that their algorithm is not of typical Metropolis-Hastings type, and we specify conditions required for the generated Markov chain to be stationary and to converge to the intended distribution. The time-step bias may add up, and in many applications it is only the middle of a reptile that is the most important. Therefore, we propose an alternative, 'no-compromise reptation quantum Monte Carlo' to stabilize the middle of the reptile. (fast track communication)

  12. Multilevel Monte Carlo Approaches for Numerical Homogenization

    KAUST Repository

    Efendiev, Yalchin R.

    2015-10-01

    In this article, we study the application of multilevel Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the homogenized solutions. This is accomplished within MLMC by considering different sizes of representative volumes (RVEs). Many inexpensive computations with the smallest RVE size are combined with fewer expensive computations performed on larger RVEs. Likewise, when it comes to homogenized solutions, different levels of coarse-grid meshes are used to solve the homogenized equation. We show that, by carefully selecting the number of realizations at each level, we can achieve a speed-up in the computations in comparison to a standard Monte Carlo method. Numerical results are presented for both one-dimensional and two-dimensional test-cases that illustrate the efficiency of the approach.

  13. Introduction to the Monte Carlo methods

    International Nuclear Information System (INIS)

    Uzhinskij, V.V.

    1993-01-01

    Codes illustrating the use of Monte Carlo methods in high energy physics such as the inverse transformation method, the ejection method, the particle propagation through the nucleus, the particle interaction with the nucleus, etc. are presented. A set of useful algorithms of random number generators is given (the binomial distribution, the Poisson distribution, β-distribution, γ-distribution and normal distribution). 5 figs., 1 tab

  14. Handbook of Markov chain Monte Carlo

    CERN Document Server

    Brooks, Steve

    2011-01-01

    ""Handbook of Markov Chain Monte Carlo"" brings together the major advances that have occurred in recent years while incorporating enough introductory material for new users of MCMC. Along with thorough coverage of the theoretical foundations and algorithmic and computational methodology, this comprehensive handbook includes substantial realistic case studies from a variety of disciplines. These case studies demonstrate the application of MCMC methods and serve as a series of templates for the construction, implementation, and choice of MCMC methodology.

  15. Replica Exchange for Reactive Monte Carlo Simulations

    Czech Academy of Sciences Publication Activity Database

    Turner, C.H.; Brennan, J.K.; Lísal, Martin

    2007-01-01

    Roč. 111, č. 43 (2007), s. 15706-15715 ISSN 1932-7447 R&D Projects: GA ČR GA203/05/0725; GA AV ČR 1ET400720409; GA AV ČR 1ET400720507 Institutional research plan: CEZ:AV0Z40720504 Keywords : monte carlo * simulation * reactive system Subject RIV: CF - Physical ; Theoretical Chemistry

  16. Applications of Maxent to quantum Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Silver, R.N.; Sivia, D.S.; Gubernatis, J.E. (Los Alamos National Lab., NM (USA)); Jarrell, M. (Ohio State Univ., Columbus, OH (USA). Dept. of Physics)

    1990-01-01

    We consider the application of maximum entropy methods to the analysis of data produced by computer simulations. The focus is the calculation of the dynamical properties of quantum many-body systems by Monte Carlo methods, which is termed the Analytical Continuation Problem.'' For the Anderson model of dilute magnetic impurities in metals, we obtain spectral functions and transport coefficients which obey Kondo Universality.'' 24 refs., 7 figs.

  17. Monte Carlo methods for preference learning

    DEFF Research Database (Denmark)

    Viappiani, P.

    2012-01-01

    Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....

  18. General purpose code for Monte Carlo simulations

    International Nuclear Information System (INIS)

    Wilcke, W.W.

    1983-01-01

    A general-purpose computer called MONTHY has been written to perform Monte Carlo simulations of physical systems. To achieve a high degree of flexibility the code is organized like a general purpose computer, operating on a vector describing the time dependent state of the system under simulation. The instruction set of the computer is defined by the user and is therefore adaptable to the particular problem studied. The organization of MONTHY allows iterative and conditional execution of operations

  19. The lund Monte Carlo for jet fragmentation

    International Nuclear Information System (INIS)

    Sjoestrand, T.

    1982-03-01

    We present a Monte Carlo program based on the Lund model for jet fragmentation. Quark, gluon, diquark and hadron jets are considered. Special emphasis is put on the fragmentation of colour singlet jet systems, for which energy, momentum and flavour are conserved explicitly. The model for decays of unstable particles, in particular the weak decay of heavy hadrons, is described. The central part of the paper is a detailed description on how to use the FORTRAN 77 program. (Author)

  20. Autocorrelations in hybrid Monte Carlo simulations

    International Nuclear Information System (INIS)

    Schaefer, Stefan; Virotta, Francesco

    2010-11-01

    Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)

  1. Topological zero modes in Monte Carlo simulations

    International Nuclear Information System (INIS)

    Dilger, H.

    1994-08-01

    We present an improvement of global Metropolis updating steps, the instanton hits, used in a hybrid Monte Carlo simulation of the two-flavor Schwinger model with staggered fermions. These hits are designed to change the topological sector of the gauge field. In order to match these hits to an unquenched simulation with pseudofermions, the approximate zero mode structure of the lattice Dirac operator has to be considered explicitly. (orig.)

  2. Monte Carlo simulation of Touschek effect

    Directory of Open Access Journals (Sweden)

    Aimin Xiao

    2010-07-01

    Full Text Available We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian-distributed beam or for a general beam whose distribution function is given. In addition, scattered electrons can be tracked through the beam line and the local beam-loss rate and beam halo information recorded.

  3. Vectorization of phase space Monte Carlo code in FACOM vector processor VP-200

    International Nuclear Information System (INIS)

    Miura, Kenichi

    1986-01-01

    This paper describes the vectorization techniques for Monte Carlo codes in Fujitsu's Vector Processor System. The phase space Monte Carlo code FOWL is selected as a benchmark, and scalar and vector performances are compared. The vectorized kernel Monte Carlo routine which contains heavily nested IF tests runs up to 7.9 times faster in vector mode than in scalar mode. The overall performance improvement of the vectorized FOWL code over the original scalar code reaches 3.3. The results of this study strongly indicate that supercomputer can be a powerful tool for Monte Carlo simulations in high energy physics. (Auth.)

  4. Generalized hybrid Monte Carlo - CMFD methods for fission source convergence

    International Nuclear Information System (INIS)

    Wolters, Emily R.; Larsen, Edward W.; Martin, William R.

    2011-01-01

    In this paper, we generalize the recently published 'CMFD-Accelerated Monte Carlo' method and present two new methods that reduce the statistical error in CMFD-Accelerated Monte Carlo. The CMFD-Accelerated Monte Carlo method uses Monte Carlo to estimate nonlinear functionals used in low-order CMFD equations for the eigenfunction and eigenvalue. The Monte Carlo fission source is then modified to match the resulting CMFD fission source in a 'feedback' procedure. The two proposed methods differ from CMFD-Accelerated Monte Carlo in the definition of the required nonlinear functionals, but they have identical CMFD equations. The proposed methods are compared with CMFD-Accelerated Monte Carlo on a high dominance ratio test problem. All hybrid methods converge the Monte Carlo fission source almost immediately, leading to a large reduction in the number of inactive cycles required. The proposed methods stabilize the fission source more efficiently than CMFD-Accelerated Monte Carlo, leading to a reduction in the number of active cycles required. Finally, as in CMFD-Accelerated Monte Carlo, the apparent variance of the eigenfunction is approximately equal to the real variance, so the real error is well-estimated from a single calculation. This is an advantage over standard Monte Carlo, in which the real error can be underestimated due to inter-cycle correlation. (author)

  5. A dual resolution measurement based Monte Carlo simulation technique for detailed dose analysis of small volume organs in the skull base region

    International Nuclear Information System (INIS)

    Yeh, Chi-Yuan; Tung, Chuan-Jung; Chao, Tsi-Chain; Lin, Mu-Han; Lee, Chung-Chi

    2014-01-01

    The purpose of this study was to examine dose distribution of a skull base tumor and surrounding critical structures in response to high dose intensity-modulated radiosurgery (IMRS) with Monte Carlo (MC) simulation using a dual resolution sandwich phantom. The measurement-based Monte Carlo (MBMC) method (Lin et al., 2009) was adopted for the study. The major components of the MBMC technique involve (1) the BEAMnrc code for beam transport through the treatment head of a Varian 21EX linear accelerator, (2) the DOSXYZnrc code for patient dose simulation and (3) an EPID-measured efficiency map which describes non-uniform fluence distribution of the IMRS treatment beam. For the simulated case, five isocentric 6 MV photon beams were designed to deliver a total dose of 1200 cGy in two fractions to the skull base tumor. A sandwich phantom for the MBMC simulation was created based on the patient's CT scan of a skull base tumor [gross tumor volume (GTV)=8.4 cm 3 ] near the right 8th cranial nerve. The phantom, consisted of a 1.2-cm thick skull base region, had a voxel resolution of 0.05×0.05×0.1 cm 3 and was sandwiched in between 0.05×0.05×0.3 cm 3 slices of a head phantom. A coarser 0.2×0.2×0.3 cm 3 single resolution (SR) phantom was also created for comparison with the sandwich phantom. A particle history of 3×10 8 for each beam was used for simulations of both the SR and the sandwich phantoms to achieve a statistical uncertainty of <2%. Our study showed that the planning target volume (PTV) receiving at least 95% of the prescribed dose (VPTV95) was 96.9%, 96.7% and 99.9% for the TPS, SR, and sandwich phantom, respectively. The maximum and mean doses to large organs such as the PTV, brain stem, and parotid gland for the TPS, SR and sandwich MC simulations did not show any significant difference; however, significant dose differences were observed for very small structures like the right 8th cranial nerve, right cochlea, right malleus and right semicircular

  6. Continuous energy Monte Carlo method based lattice homogeinzation

    International Nuclear Information System (INIS)

    Li Mancang; Yao Dong; Wang Kan

    2014-01-01

    Based on the Monte Carlo code MCNP, the continuous energy Monte Carlo multi-group constants generation code MCMC has been developed. The track length scheme has been used as the foundation of cross section generation. The scattering matrix and Legendre components require special techniques, and the scattering event method has been proposed to solve this problem. Three methods have been developed to calculate the diffusion coefficients for diffusion reactor core codes and the Legendre method has been applied in MCMC. To the satisfaction of the equivalence theory, the general equivalence theory (GET) and the superhomogenization method (SPH) have been applied to the Monte Carlo method based group constants. The super equivalence method (SPE) has been proposed to improve the equivalence. GET, SPH and SPE have been implemented into MCMC. The numerical results showed that generating the homogenization multi-group constants via Monte Carlo method overcomes the difficulties in geometry and treats energy in continuum, thus provides more accuracy parameters. Besides, the same code and data library can be used for a wide range of applications due to the versatility. The MCMC scheme can be seen as a potential alternative to the widely used deterministic lattice codes. (authors)

  7. On an efficient multiple time step Monte Carlo simulation of the SABR model

    NARCIS (Netherlands)

    A. Leitao Rodriguez (Álvaro); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractIn this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl.

  8. On an efficient multiple time step Monte Carlo simulation of the SABR model

    NARCIS (Netherlands)

    Leitao Rodriguez, A.; Grzelak, L.A.; Oosterlee, C.W.

    2017-01-01

    In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math.

  9. A zero-variance based scheme for Monte Carlo criticality simulations

    NARCIS (Netherlands)

    Christoforou, S.

    2010-01-01

    The ability of the Monte Carlo method to solve particle transport problems by simulating the particle behaviour makes it a very useful technique in nuclear reactor physics. However, the statistical nature of Monte Carlo implies that there will always be a variance associated with the estimate

  10. Global Monte Carlo Simulation with High Order Polynomial Expansions

    International Nuclear Information System (INIS)

    William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin

    2007-01-01

    The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as 'local' piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi's method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source convergence

  11. Calculation of extrapolation curves in the 4π(LS)β-γ coincidence technique with the Monte Carlo code Geant4.

    Science.gov (United States)

    Bobin, C; Thiam, C; Bouchard, J

    2016-03-01

    At LNE-LNHB, a liquid scintillation (LS) detection setup designed for Triple to Double Coincidence Ratio (TDCR) measurements is also used in the β-channel of a 4π(LS)β-γ coincidence system. This LS counter based on 3 photomultipliers was first modeled using the Monte Carlo code Geant4 to enable the simulation of optical photons produced by scintillation and Cerenkov effects. This stochastic modeling was especially designed for the calculation of double and triple coincidences between photomultipliers in TDCR measurements. In the present paper, this TDCR-Geant4 model is extended to 4π(LS)β-γ coincidence counting to enable the simulation of the efficiency-extrapolation technique by the addition of a γ-channel. This simulation tool aims at the prediction of systematic biases in activity determination due to eventual non-linearity of efficiency-extrapolation curves. First results are described in the case of the standardization (59)Fe. The variation of the γ-efficiency in the β-channel due to the Cerenkov emission is investigated in the case of the activity measurements of (54)Mn. The problem of the non-linearity between β-efficiencies is featured in the case of the efficiency tracing technique for the activity measurements of (14)C using (60)Co as a tracer. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Radiotherapy Monte Carlo simulation using cloud computing technology

    International Nuclear Information System (INIS)

    Poole, C.M.; Cornelius, I.; Trapp, J.V.; Langton, C.M.

    2012-01-01

    Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

  13. Study of TXRF experimental system by Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T., E-mail: ricardo@lin.ufrj.br [Nuclear Instrumentation Laboratory, Nuclear Engineering Program/COPPE Federal University of Rio de Janeiro (UFRJ), RJ (Brazil); Anjos, Marcelino J., E-mail: marcelin@uerj.br [State University of Rio de Janeiro (UERJ/IFADT/DFAT), RJ (Brazil); Conti, Claudio C., E-mail: ccconti@ird.gov.br [Instituto de Radioprotecao e Dosimetria, (IRD/CNEN-RJ), Rio de janeiro, RJ (Brazil)

    2011-07-01

    The Total-Reflection X-ray Fluorescence (TXRF) technique offers unique possibilities to study the concentrations of a wide range of trace elements in various types of samples. Besides that, the TXRF technique is widely used to study the trace elements in biological, medical and environmental samples due to its multielemental character as well as simplicity of sample preparation and quantification methods used. In general the TXRF experimental setup is not simple and might require substantial experimental efforts. On the other hand, in recent years, experimental TXRF portable systems have been developed. It has motivated us to develop our own TXRF portable system. In this work we presented a first step in order to optimize a TXRF experimental setup using Monte Carlo simulation by MCNP code. The results found show that the Monte Carlo simulation method can be used to investigate the development of a TXRF experimental system before its assembly. (author)

  14. A Monte Carlo program for generating hadronic final states

    International Nuclear Information System (INIS)

    Angelini, L.; Pellicoro, M.; Nitti, L.; Preparata, G.; Valenti, G.

    1991-01-01

    FIRST is a computer program to generate final states from high energy hadronic interactions using the Monte Carlo technique. It is based on a theoretical model in which the high degree of universality in such interactions is related with the existence of highly excited quark-antiquark bound states, called fire-strings. The program handles the decay of both fire-strings and unstable particles produced in the intermediate states. (orig.)

  15. Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations

    OpenAIRE

    Roberto S. Flowers-Cano; Ruperto Ortiz-Gómez; Jesús Enrique León-Jiménez; Raúl López Rivera; Luis A. Perera Cruz

    2018-01-01

    Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP), bias-corrected bootstrap (BC), accelerated bias-corrected bootstrap (BCA) and a modified version of the standard bootstrap (MSB). Different simulation scenarios were analyzed. In some cases, the mother distributi...

  16. Investigating the impossible: Monte Carlo simulations

    International Nuclear Information System (INIS)

    Kramer, Gary H.; Crowley, Paul; Burns, Linda C.

    2000-01-01

    Designing and testing new equipment can be an expensive and time consuming process or the desired performance characteristics may preclude its construction due to technological shortcomings. Cost may also prevent equipment being purchased for other scenarios to be tested. An alternative is to use Monte Carlo simulations to make the investigations. This presentation exemplifies how Monte Carlo code calculations can be used to fill the gap. An example is given for the investigation of two sizes of germanium detector (70 mm and 80 mm diameter) at four different crystal thicknesses (15, 20, 25, and 30 mm) and makes predictions on how the size affects the counting efficiency and the Minimum Detectable Activity (MDA). The Monte Carlo simulations have shown that detector efficiencies can be adequately modelled using photon transport if the data is used to investigate trends. The investigation of the effect of detector thickness on the counting efficiency has shown that thickness for a fixed diameter detector of either 70 mm or 80 mm is unimportant up to 60 keV. At higher photon energies, the counting efficiency begins to decrease as the thickness decreases as expected. The simulations predict that the MDA of either the 70 mm or 80 mm diameter detectors does not differ by more than a factor of 1.15 at 17 keV or 1.2 at 60 keV when comparing detectors of equivalent thicknesses. The MDA is slightly increased at 17 keV, and rises by about 52% at 660 keV, when the thickness is decreased from 30 mm to 15 mm. One could conclude from this information that the extra cost associated with the larger area Ge detectors may not be justified for the slight improvement predicted in the MDA. (author)

  17. Monte Carlo eigenfunction strategies and uncertainties

    International Nuclear Information System (INIS)

    Gast, R.C.; Candelore, N.R.

    1974-01-01

    Comparisons of convergence rates for several possible eigenfunction source strategies led to the selection of the ''straight'' analog of the analytic power method as the source strategy for Monte Carlo eigenfunction calculations. To insure a fair game strategy, the number of histories per iteration increases with increasing iteration number. The estimate of eigenfunction uncertainty is obtained from a modification of a proposal by D. B. MacMillan and involves only estimates of the usual purely statistical component of uncertainty and a serial correlation coefficient of lag one. 14 references. (U.S.)

  18. Atomistic Monte Carlo simulation of lipid membranes

    DEFF Research Database (Denmark)

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...

  19. MBR Monte Carlo Simulation in PYTHIA8

    Science.gov (United States)

    Ciesielski, R.

    We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.

  20. Markov chains analytic and Monte Carlo computations

    CERN Document Server

    Graham, Carl

    2014-01-01

    Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies.A detailed and rigorous presentation of Markov chains with discrete time and state space.An appendix presenting probabilistic notions that are nec

  1. Score Bounded Monte-Carlo Tree Search

    Science.gov (United States)

    Cazenave, Tristan; Saffidine, Abdallah

    Monte-Carlo Tree Search (MCTS) is a successful algorithm used in many state of the art game engines. We propose to improve a MCTS solver when a game has more than two outcomes. It is for example the case in games that can end in draw positions. In this case it improves significantly a MCTS solver to take into account bounds on the possible scores of a node in order to select the nodes to explore. We apply our algorithm to solving Seki in the game of Go and to Connect Four.

  2. by means of FLUKA Monte Carlo method

    Directory of Open Access Journals (Sweden)

    Ermis Elif Ebru

    2015-01-01

    Full Text Available Calculations of gamma-ray mass attenuation coefficients of various detector materials (crystals were carried out by means of FLUKA Monte Carlo (MC method at different gamma-ray energies. NaI, PVT, GSO, GaAs and CdWO4 detector materials were chosen in the calculations. Calculated coefficients were also compared with the National Institute of Standards and Technology (NIST values. Obtained results through this method were highly in accordance with those of the NIST values. It was concluded from the study that FLUKA MC method can be an alternative way to calculate the gamma-ray mass attenuation coefficients of the detector materials.

  3. Pseudo-extended Markov chain Monte Carlo

    OpenAIRE

    Nemeth, Christopher; Lindsten, Fredrik; Filippone, Maurizio; Hensman, James

    2017-01-01

    Sampling from the posterior distribution using Markov chain Monte Carlo (MCMC) methods can require an exhaustive number of iterations to fully explore the correct posterior. This is often the case when the posterior of interest is multi-modal, as the MCMC sampler can become trapped in a local mode for a large number of iterations. In this paper, we introduce the pseudo-extended MCMC method as an approach for improving the mixing of the MCMC sampler in complex posterior distributions. The pseu...

  4. Diffusion quantum Monte Carlo for molecules

    International Nuclear Information System (INIS)

    Lester, W.A. Jr.

    1986-07-01

    A quantum mechanical Monte Carlo method has been used for the treatment of molecular problems. The imaginary-time Schroedinger equation written with a shift in zero energy [E/sub T/ - V(R)] can be interpreted as a generalized diffusion equation with a position-dependent rate or branching term. Since diffusion is the continuum limit of a random walk, one may simulate the Schroedinger equation with a function psi (note, not psi 2 ) as a density of ''walks.'' The walks undergo an exponential birth and death as given by the rate term. 16 refs., 2 tabs

  5. Optical properties measurement of laser coagulated tissues with double integrating sphere and inverse Monte Carlo technique in the wavelength range from 350 to 2100 nm

    Science.gov (United States)

    Honda, Norihiro; Nanjo, Takuya; Ishii, Katsunori; Awazu, Kunio

    2012-03-01

    In laser medicine, the accurate knowledge about the optical properties (absorption coefficient; μa, scattering coefficient; μs, anisotropy factor; g) of laser irradiated tissues is important for the prediction of light propagation in tissues, since the efficacy of laser treatment depends on the photon propagation within the irradiated tissues. Thus, it is likely that the optical properties of tissues at near-ultraviolet, visible and near-infrared wavelengths will be more important due to more biomedical applications of lasers will be developed. For improvement of the laser induced thermotherapy, the optical property change during laser treatment should be considered in the wide wavelength range. For estimation of the optical properties of the biological tissues, the optical properties measurement system with a double integrating sphere setup and an inverse Monte Carlo technique was developed. The optical properties of chicken muscle tissue were measured in the native state and after laser coagulation using the optical properties measurement system in the wavelength range from 350 to 2100 nm. A CO2 laser was used for laser coagulation. After laser coagulation, the reduced scattering coefficient of the tissue increased. And, the optical penetration depth decreased. For improvement of the treatment depth during laser coagulation, a quantitative procedure using the treated tissue optical properties for determination of the irradiation power density following light penetration decrease might be important in clinic.

  6. Monte Carlo criticality analysis for dissolvers with neutron poison

    International Nuclear Information System (INIS)

    Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.

    1987-01-01

    Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)

  7. A one-dimensional lattice-gas model for simulating diffusion in channel pores with side pockets: The analytical approach and kinetic Monte Carlo technique

    Czech Academy of Sciences Publication Activity Database

    Tarasenko, Alexander; Jastrabík, Lubomír

    2012-01-01

    Roč. 152, APR (2012), s. 134-140 ISSN 1387-1811 R&D Projects: GA TA ČR TA01010517 Institutional research plan: CEZ:AV0Z10100522 Keywords : lattice-gas systems * diffusion * Monte Carlo simulations Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.365, year: 2012 http://dx.doi.org/10.1016/j.micromeso.2011.11.046

  8. Wielandt acceleration for MCNP5 Monte Carlo eigenvalue calculations

    International Nuclear Information System (INIS)

    Brown, F.

    2007-01-01

    Monte Carlo criticality calculations use the power iteration method to determine the eigenvalue (k eff ) and eigenfunction (fission source distribution) of the fundamental mode. A recently proposed method for accelerating convergence of the Monte Carlo power iteration using Wielandt's method has been implemented in a test version of MCNP5. The method is shown to provide dramatic improvements in convergence rates and to greatly reduce the possibility of false convergence assessment. The method is effective and efficient, improving the Monte Carlo figure-of-merit for many problems. In addition, the method should eliminate most of the underprediction bias in confidence intervals for Monte Carlo criticality calculations. (authors)

  9. Odd-flavor Simulations by the Hybrid Monte Carlo

    CERN Document Server

    Takaishi, Tetsuya; Takaishi, Tetsuya; De Forcrand, Philippe

    2001-01-01

    The standard hybrid Monte Carlo algorithm is known to simulate even flavors QCD only. Simulations of odd flavors QCD, however, can be also performed in the framework of the hybrid Monte Carlo algorithm where the inverse of the fermion matrix is approximated by a polynomial. In this exploratory study we perform three flavors QCD simulations. We make a comparison of the hybrid Monte Carlo algorithm and the R-algorithm which also simulates odd flavors systems but has step-size errors. We find that results from our hybrid Monte Carlo algorithm are in agreement with those from the R-algorithm obtained at very small step-size.

  10. Monte Carlo simulations for instrumentation at SINQ

    International Nuclear Information System (INIS)

    Filges, U.; Ronnow, H.M.; Zsigmond, G.

    2006-01-01

    The Paul Scherrer Institut (PSI) operates a spallation source SINQ equipped with 11 different neutron scattering instruments. Beside the optimization of the existing instruments, the extension with new instruments and devices are continuously done at PSI. For design and performance studies different Monte Carlo packages are used. Presently two major projects are in an advanced stage of planning. These are the new thermal neutron triple-axis spectrometer Enhanced Intensity and Greater Energy Range (EIGER) and the ultra-cold neutron source (UCN-PSI). The EIGER instrument design is focused on an optimal signal-to-background ratio. A very important design part was to realize a monochromator shielding which covers best shielding characteristic, low background production and high instrument functionality. The Monte Carlo package MCNPX was used to find the best choice. Due to the sharp energy distribution of ultra-cold neutrons (UCN) which can be Doppler-shifted towards cold neutron energies, a UCN phase space transformation (PST) device could produce highly monochromatic cold and very cold neutrons (VCN). The UCN-PST instrumentation project running at PSI is very timely since a new-generation superthermal spallation source of UCN is under construction at PSI with a UCN density of 3000-4000 n cm -3 . Detailed numerical simulations have been carried out to optimize the UCN density and flux. Recent results on numerical simulations of an UCN-PST-based source of highly monochromatic cold neutrons and VCN are presented

  11. Monte Carlo simulation for radiographic applications

    International Nuclear Information System (INIS)

    Tillack, G.R.; Bellon, C.

    2003-01-01

    Standard radiography simulators are based on the attenuation law complemented by built-up-factors (BUF) to describe the interaction of radiation with material. The assumption of BUF implies that scattered radiation reduces only the contrast in radiographic images. This simplification holds for a wide range of applications like weld inspection as known from practical experience. But only a detailed description of the different underlying interaction mechanisms is capable to explain effects like mottling or others that every radiographer has experienced in practice. The application of Monte Carlo models is capable to handle primary and secondary interaction mechanisms contributing to the image formation process like photon interactions (absorption, incoherent and coherent scattering including electron-binding effects, pair production) and electron interactions (electron tracing including X-Ray fluorescence and Bremsstrahlung production). It opens up possibilities like the separation of influencing factors and the understanding of the functioning of intensifying screen used in film radiography. The paper discusses the opportunities in applying the Monte Carlo method to investigate special features in radiography in terms of selected examples. (orig.) [de

  12. Multilevel Monte Carlo simulation of Coulomb collisions

    Energy Technology Data Exchange (ETDEWEB)

    Rosin, M.S., E-mail: msr35@math.ucla.edu [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Department of Mathematics and Science, Pratt Institute, Brooklyn, NY 11205 (United States); Ricketson, L.F. [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Dimits, A.M. [Lawrence Livermore National Laboratory, L-637, P.O. Box 808, Livermore, CA 94511-0808 (United States); Caflisch, R.E. [Mathematics Department, University of California at Los Angeles, Los Angeles, CA 90036 (United States); Institute for Pure and Applied Mathematics, University of California at Los Angeles, Los Angeles, CA 90095 (United States); Cohen, B.I. [Lawrence Livermore National Laboratory, L-637, P.O. Box 808, Livermore, CA 94511-0808 (United States)

    2014-10-01

    We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε, the computational cost of the method is O(ε{sup −2}) or O(ε{sup −2}(lnε){sup 2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε{sup −3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10{sup −5}. We discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.

  13. Parallel Monte Carlo Search for Hough Transform

    Science.gov (United States)

    Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.

    2017-10-01

    We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.

  14. Self-test Monte Carlo method

    International Nuclear Information System (INIS)

    Ohta, Shigemi

    1996-01-01

    The Self-Test Monte Carlo (STMC) method resolves the main problems in using algebraic pseudo-random numbers for Monte Carlo (MC) calculations: that they can interfere with MC algorithms and lead to erroneous results, and that such an error often cannot be detected without known exact solution. STMC is based on good randomness of about 10 10 bits available from physical noise or transcendental numbers like π = 3.14---. Various bit modifiers are available to get more bits for applications that demands more than 10 10 random bits such as lattice quantum chromodynamics (QCD). These modifiers are designed so that a) each of them gives a bit sequence comparable in randomness as the original if used separately from each other, and b) their mutual interference when used jointly in a single MC calculation is adjustable. Intermediate data of the MC calculation itself are used to quantitatively test and adjust the mutual interference of the modifiers in respect of the MC algorithm. STMC is free of systematic error and gives reliable statistical error. Also it can be easily implemented on vector and parallel supercomputers. (author)

  15. Algorithms for Monte Carlo calculations with fermions

    International Nuclear Information System (INIS)

    Weingarten, D.

    1985-01-01

    We describe a fermion Monte Carlo algorithm due to Petcher and the present author and another due to Fucito, Marinari, Parisi and Rebbi. For the first algorithm we estimate the number of arithmetic operations required to evaluate a vacuum expectation value grows as N 11 /msub(q) on an N 4 lattice with fixed periodicity in physical units and renormalized quark mass msub(q). For the second algorithm the rate of growth is estimated to be N 8 /msub(q) 2 . Numerical experiments are presented comparing the two algorithms on a lattice of size 2 4 . With a hopping constant K of 0.15 and β of 4.0 we find the number of operations for the second algorithm is about 2.7 times larger than for the first and about 13 000 times larger than for corresponding Monte Carlo calculations with a pure gauge theory. An estimate is given for the number of operations required for more realistic calculations by each algorithm on a larger lattice. (orig.)

  16. Monte Carlo simulations on a 9-node PC cluster

    International Nuclear Information System (INIS)

    Gouriou, J.

    2001-01-01

    Monte Carlo simulation methods are frequently used in the fields of medical physics, dosimetry and metrology of ionising radiation. Nevertheless, the main drawback of this technique is to be computationally slow, because the statistical uncertainty of the result improves only as the square root of the computational time. We present a method, which allows to reduce by a factor 10 to 20 the used effective running time. In practice, the aim was to reduce the calculation time in the LNHB metrological applications from several weeks to a few days. This approach includes the use of a PC-cluster, under Linux operating system and PVM parallel library (version 3.4). The Monte Carlo codes EGS4, MCNP and PENELOPE have been implemented on this platform and for the two last ones adapted for running under the PVM environment. The maximum observed speedup is ranging from a factor 13 to 18 according to the codes and the problems to be simulated. (orig.)

  17. Engineering local optimality in quantum Monte Carlo algorithms

    Science.gov (United States)

    Pollet, Lode; Van Houcke, Kris; Rombouts, Stefan M. A.

    2007-08-01

    Quantum Monte Carlo algorithms based on a world-line representation such as the worm algorithm and the directed loop algorithm are among the most powerful numerical techniques for the simulation of non-frustrated spin models and of bosonic models. Both algorithms work in the grand-canonical ensemble and can have a winding number larger than zero. However, they retain a lot of intrinsic degrees of freedom which can be used to optimize the algorithm. We let us guide by the rigorous statements on the globally optimal form of Markov chain Monte Carlo simulations in order to devise a locally optimal formulation of the worm algorithm while incorporating ideas from the directed loop algorithm. We provide numerical examples for the soft-core Bose-Hubbard model and various spin- S models.

  18. Geometric allocation approaches in Markov chain Monte Carlo

    International Nuclear Information System (INIS)

    Todo, S; Suwa, H

    2013-01-01

    The Markov chain Monte Carlo method is a versatile tool in statistical physics to evaluate multi-dimensional integrals numerically. For the method to work effectively, we must consider the following key issues: the choice of ensemble, the selection of candidate states, the optimization of transition kernel, algorithm for choosing a configuration according to the transition probabilities. We show that the unconventional approaches based on the geometric allocation of probabilities or weights can improve the dynamics and scaling of the Monte Carlo simulation in several aspects. Particularly, the approach using the irreversible kernel can reduce or sometimes completely eliminate the rejection of trial move in the Markov chain. We also discuss how the space-time interchange technique together with Walker's method of aliases can reduce the computational time especially for the case where the number of candidates is large, such as models with long-range interactions

  19. Exploring Various Monte Carlo Simulations for Geoscience Applications

    Science.gov (United States)

    Blais, R.

    2010-12-01

    Computer simulations are increasingly important in geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN), or chaotic random number (CRN) generators. Equidistributed quasi-random numbers (QRNs) can also be used in Monte Carlo simulations. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as Importance Sampling and Stratified Sampling can be implemented to significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on examples of geodetic applications of gravimetric terrain corrections and gravity inversion, conclusions and recommendations concerning their performance and general applicability are included.

  20. Exploring pseudo- and chaotic random Monte Carlo simulations

    Science.gov (United States)

    Blais, J. A. Rod; Zhang, Zhan

    2011-07-01

    Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer-generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as importance sampling and stratified sampling can be applied in most Monte Carlo simulations and significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on some practical examples of geodetic direct and inverse problems, conclusions and recommendations concerning their performance and general applicability are included.

  1. Quantum Monte Carlo Endstation for Petascale Computing

    Energy Technology Data Exchange (ETDEWEB)

    Lubos Mitas

    2011-01-26

    NCSU research group has been focused on accomplising the key goals of this initiative: establishing new generation of quantum Monte Carlo (QMC) computational tools as a part of Endstation petaflop initiative for use at the DOE ORNL computational facilities and for use by computational electronic structure community at large; carrying out high accuracy quantum Monte Carlo demonstration projects in application of these tools to the forefront electronic structure problems in molecular and solid systems; expanding the impact of QMC methods and approaches; explaining and enhancing the impact of these advanced computational approaches. In particular, we have developed quantum Monte Carlo code (QWalk, www.qwalk.org) which was significantly expanded and optimized using funds from this support and at present became an actively used tool in the petascale regime by ORNL researchers and beyond. These developments have been built upon efforts undertaken by the PI's group and collaborators over the period of the last decade. The code was optimized and tested extensively on a number of parallel architectures including petaflop ORNL Jaguar machine. We have developed and redesigned a number of code modules such as evaluation of wave functions and orbitals, calculations of pfaffians and introduction of backflow coordinates together with overall organization of the code and random walker distribution over multicore architectures. We have addressed several bottlenecks such as load balancing and verified efficiency and accuracy of the calculations with the other groups of the Endstation team. The QWalk package contains about 50,000 lines of high quality object-oriented C++ and includes also interfaces to data files from other conventional electronic structure codes such as Gamess, Gaussian, Crystal and others. This grant supported PI for one month during summers, a full-time postdoc and partially three graduate students over the period of the grant duration, it has resulted in 13

  2. Frequency domain Monte Carlo simulation method for cross power spectral density driven by periodically pulsed spallation neutron source using complex-valued weight Monte Carlo

    International Nuclear Information System (INIS)

    Yamamoto, Toshihiro

    2014-01-01

    Highlights: • The cross power spectral density in ADS has correlated and uncorrelated components. • A frequency domain Monte Carlo method to calculate the uncorrelated one is developed. • The method solves the Fourier transformed transport equation. • The method uses complex-valued weights to solve the equation. • The new method reproduces well the CPSDs calculated with time domain MC method. - Abstract: In an accelerator driven system (ADS), pulsed spallation neutrons are injected at a constant frequency. The cross power spectral density (CPSD), which can be used for monitoring the subcriticality of the ADS, is composed of the correlated and uncorrelated components. The uncorrelated component is described by a series of the Dirac delta functions that occur at the integer multiples of the pulse repetition frequency. In the present paper, a Monte Carlo method to solve the Fourier transformed neutron transport equation with a periodically pulsed neutron source term has been developed to obtain the CPSD in ADSs. Since the Fourier transformed flux is a complex-valued quantity, the Monte Carlo method introduces complex-valued weights to solve the Fourier transformed equation. The Monte Carlo algorithm used in this paper is similar to the one that was developed by the author of this paper to calculate the neutron noise caused by cross section perturbations. The newly-developed Monte Carlo algorithm is benchmarked to the conventional time domain Monte Carlo simulation technique. The CPSDs are obtained both with the newly-developed frequency domain Monte Carlo method and the conventional time domain Monte Carlo method for a one-dimensional infinite slab. The CPSDs obtained with the frequency domain Monte Carlo method agree well with those with the time domain method. The higher order mode effects on the CPSD in an ADS with a periodically pulsed neutron source are discussed

  3. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2007-09-21

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  4. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Vilches, M.; Lallena, A.M.

    2007-01-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool

  5. Simulation of neutron transport equation using parallel Monte Carlo for deep penetration problems

    International Nuclear Information System (INIS)

    Bekar, K. K.; Tombakoglu, M.; Soekmen, C. N.

    2001-01-01

    Neutron transport equation is simulated using parallel Monte Carlo method for deep penetration neutron transport problem. Monte Carlo simulation is parallelized by using three different techniques; direct parallelization, domain decomposition and domain decomposition with load balancing, which are used with PVM (Parallel Virtual Machine) software on LAN (Local Area Network). The results of parallel simulation are given for various model problems. The performances of the parallelization techniques are compared with each other. Moreover, the effects of variance reduction techniques on parallelization are discussed

  6. The Monte Carlo Simulation Method for System Reliability and Risk Analysis

    CERN Document Server

    Zio, Enrico

    2013-01-01

    Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.   Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.   This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...

  7. Application of Monte Carlo techniques to optimization of high-energy beam transport in a stochastic environment

    Science.gov (United States)

    Parrish, R. V.; Dieudonne, J. E.; Filippas, T. A.

    1971-01-01

    An algorithm employing a modified sequential random perturbation, or creeping random search, was applied to the problem of optimizing the parameters of a high-energy beam transport system. The stochastic solution of the mathematical model for first-order magnetic-field expansion allows the inclusion of state-variable constraints, and the inclusion of parameter constraints allowed by the method of algorithm application eliminates the possibility of infeasible solutions. The mathematical model and the algorithm were programmed for a real-time simulation facility; thus, two important features are provided to the beam designer: (1) a strong degree of man-machine communication (even to the extent of bypassing the algorithm and applying analog-matching techniques), and (2) extensive graphics for displaying information concerning both algorithm operation and transport-system behavior. Chromatic aberration was also included in the mathematical model and in the optimization process. Results presented show this method as yielding better solutions (in terms of resolutions) to the particular problem than those of a standard analog program as well as demonstrating flexibility, in terms of elements, constraints, and chromatic aberration, allowed by user interaction with both the algorithm and the stochastic model. Example of slit usage and a limited comparison of predicted results and actual results obtained with a 600 MeV cyclotron are given.

  8. EGS4, Electron Photon Shower Simulation by Monte-Carlo

    International Nuclear Information System (INIS)

    1998-01-01

    1 - Description of program or function: The EGS code system is one of a chain of three codes designed to solve the electromagnetic shower problem by Monte Carlo simulation. This chain makes possible simulation of almost any electron-photon transport problem conceivable. The structure of the system, with its global features, modular form, and structured programming, is readily adaptable to virtually any interfacing scheme that is desired on the part of the user. EGS4 is a package of subroutines plus block data with a flexible user interface. This allows for greater flexibility without requiring the user to be overly familiar with the internal details of the code. Combining this with the macro facility capabilities of the Mortran3 language, this reduces the likelihood that user edits will introduce bugs into the code. EGS4 uses material cross section and branching ratio data created and fit by the companion code, PEGS4. EGS4 allows for the implementation of importance sampling and other variance reduction techniques such as leading particle biasing, splitting, path length biasing, Russian roulette, etc. 2 - Method of solution: EGS employs the Monte Carlo method of solution. It allows all of the fundamental processes to be included and arbitrary geometries can be treated, also. Other minor processes, such as photoneutron production, can be added as a further generalization. Since showers develop randomly according to the quantum laws of probability, each shower is different. We again are led to the Monte Carlo method. 3 - Restrictions on the complexity of the problem: None noted

  9. Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

    Science.gov (United States)

    Restrepo, Carolina; Hurtado, John E.

    2011-01-01

    The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

  10. Observation of Jet Photoproduction and Comparison to Monte Carlo Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Lincoln, Donald W. [Rice Univ., Houston, TX (United States)

    1994-01-01

    The photon is the carrier of the electromagnetic force. However in addition to its well known nature, the theories of QCD and quantum mechanics would indicate that the photon can also for brief periods of time split into a $q\\bar{q}$ pair (an extended photon.) How these constituents share energy and momentum is an interesting question and such a measurement was investigated by scattering photons off protons. The post collision kinematics should reveal pre-collision information. Unfortunately, when these constituents exit the collision point, they undergo subsequent interactions (gluon radiation, fragmentation, etc.) which scramble their kinematics. An algorithm was explored which was shown via Monte Carlo techniques to partially disentangle these post collision interactions and reveal the collision kinematics. The presence or absence of large transverse momenta internal ($k_\\perp$) to the photon has a significant impact on the ability to reconstruct the kinematics of the leading order calculation hard scatter system. Reconstruction of the next to leading order high $E_\\perp$ partons is more straightforward. Since the photon exhibits this unusual behavior only part of the time, many of the collisions recorded will be with a non-extended (or direct) photon. Unless a method for culling only the extended photons out can be invented, this contamination of direct photons must be accounted for. No such culling method is currently known, and so any measurement will necessarily contain both photon types. Theoretical predictions using Monte Carlo methods are compared with the data and are found to reproduce many experimentally measured distributions quite well. Overall the LUND Monte Carlo reproduces the data better than the HERWIG Monte Carlo. As expected at low jet $E_\\perp$, the data set seems to be dominated by extended photons, with the mix becoming nearly equal at jet $E_\\perp > 4$ GeV. The existence of a large photon $k_\\perp$ appears to be favored.

  11. Monte Carlo dose calculations in advanced radiotherapy

    Science.gov (United States)

    Bush, Karl Kenneth

    The remarkable accuracy of Monte Carlo (MC) dose calculation algorithms has led to the widely accepted view that these methods should and will play a central role in the radiotherapy treatment verification and planning of the future. The advantages of using MC clinically are particularly evident for radiation fields passing through inhomogeneities, such as lung and air cavities, and for small fields, including those used in today's advanced intensity modulated radiotherapy techniques. Many investigators have reported significant dosimetric differences between MC and conventional dose calculations in such complex situations, and have demonstrated experimentally the unmatched ability of MC calculations in modeling charged particle disequilibrium. The advantages of using MC dose calculations do come at a cost. The nature of MC dose calculations require a highly detailed, in-depth representation of the physical system (accelerator head geometry/composition, anatomical patient geometry/composition and particle interaction physics) to allow accurate modeling of external beam radiation therapy treatments. To perform such simulations is computationally demanding and has only recently become feasible within mainstream radiotherapy practices. In addition, the output of the accelerator head simulation can be highly sensitive to inaccuracies within a model that may not be known with sufficient detail. The goal of this dissertation is to both improve and advance the implementation of MC dose calculations in modern external beam radiotherapy. To begin, a novel method is proposed to fine-tune the output of an accelerator model to better represent the measured output. In this method an intensity distribution of the electron beam incident on the model is inferred by employing a simulated annealing algorithm. The method allows an investigation of arbitrary electron beam intensity distributions and is not restricted to the commonly assumed Gaussian intensity. In a second component of

  12. Monte Carlo and detector simulation in OOP [Object-Oriented Programming

    International Nuclear Information System (INIS)

    Atwood, W.B.; Blankenbecler, R.; Kunz, P.; Burnett, T.; Storr, K.M.

    1990-10-01

    Object-Oriented Programming techniques are explored with an eye toward applications in High Energy Physics codes. Two prototype examples are given: McOOP (a particle Monte Carlo generator) and GISMO (a detector simulation/analysis package)

  13. Exploring the Birthday Paradox Using a Monte Carlo Simulation and Graphing Calculators.

    Science.gov (United States)

    Whitney, Matthew C.

    2001-01-01

    Describes an activity designed to demonstrate the birthday paradox and introduce students to real-world applications of Monte Carlo-type simulation techniques. Includes a sample TI-83 program and graphical analysis of the birthday problem function. (KHR)

  14. Monte Carlo simulation of the ARGO

    International Nuclear Information System (INIS)

    Depaola, G.O.

    1997-01-01

    We use GEANT Monte Carlo code to design an outline of the geometry and simulate the performance of the Argentine gamma-ray observer (ARGO), a telescope based on silicon strip detector technlogy. The γ-ray direction is determined by geometrical means and the angular resolution is calculated for small variations of the basic design. The results show that the angular resolutions vary from a few degrees at low energies (∝50 MeV) to 0.2 , approximately, at high energies (>500 MeV). We also made simulations using as incoming γ-ray the energy spectrum of PKS0208-512 and PKS0528+134 quasars. Moreover, a method based on multiple scattering theory is also used to determine the incoming energy. We show that this method is applicable to energy spectrum. (orig.)

  15. Methods for Monte Carlo simulations of biomacromolecules.

    Science.gov (United States)

    Vitalis, Andreas; Pappu, Rohit V

    2009-01-01

    The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.

  16. Variational Monte Carlo study of pentaquark states

    Energy Technology Data Exchange (ETDEWEB)

    Mark W. Paris

    2005-07-01

    Accurate numerical solution of the five-body Schrodinger equation is effected via variational Monte Carlo. The spectrum is assumed to exhibit a narrow resonance with strangeness S=+1. A fully antisymmetrized and pair-correlated five-quark wave function is obtained for the assumed non-relativistic Hamiltonian which has spin, isospin, and color dependent pair interactions and many-body confining terms which are fixed by the non-exotic spectra. Gauge field dynamics are modeled via flux tube exchange factors. The energy determined for the ground states with J=1/2 and negative (positive) parity is 2.22 GeV (2.50 GeV). A lower energy negative parity state is consistent with recent lattice results. The short-range structure of the state is analyzed via its diquark content.

  17. Monte Carlo simulation of a CZT detector

    International Nuclear Information System (INIS)

    Chun, Sung Dae; Park, Se Hwan; Ha, Jang Ho; Kim, Han Soo; Cho, Yoon Ho; Kang, Sang Mook; Kim, Yong Kyun; Hong, Duk Geun

    2008-01-01

    CZT detector is one of the most promising radiation detectors for hard X-ray and γ-ray measurement. The energy spectrum of CZT detector has to be simulated to optimize the detector design. A CZT detector was fabricated with dimensions of 5x5x2 mm 3 . A Peltier cooler with a size of 40x40 mm 2 was installed below the fabricated CZT detector to reduce the operation temperature of the detector. Energy spectra of were measured with 59.5 keV γ-ray from 241 Am. A Monte Carlo code was developed to simulate the CZT energy spectrum, which was measured with a planar-type CZT detector, and the result was compared with the measured one. The simulation was extended to the CZT detector with strip electrodes. (author)

  18. Geometric Monte Carlo and black Janus geometries

    Energy Technology Data Exchange (ETDEWEB)

    Bak, Dongsu, E-mail: dsbak@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); B.W. Lee Center for Fields, Gravity & Strings, Institute for Basic Sciences, Daejeon 34047 (Korea, Republic of); Kim, Chanju, E-mail: cjkim@ewha.ac.kr [Department of Physics, Ewha Womans University, Seoul 03760 (Korea, Republic of); Kim, Kyung Kiu, E-mail: kimkyungkiu@gmail.com [Department of Physics, Sejong University, Seoul 05006 (Korea, Republic of); Department of Physics, College of Science, Yonsei University, Seoul 03722 (Korea, Republic of); Min, Hyunsoo, E-mail: hsmin@uos.ac.kr [Physics Department, University of Seoul, Seoul 02504 (Korea, Republic of); Song, Jeong-Pil, E-mail: jeong_pil_song@brown.edu [Department of Chemistry, Brown University, Providence, RI 02912 (United States)

    2017-04-10

    We describe an application of the Monte Carlo method to the Janus deformation of the black brane background. We present numerical results for three and five dimensional black Janus geometries with planar and spherical interfaces. In particular, we argue that the 5D geometry with a spherical interface has an application in understanding the finite temperature bag-like QCD model via the AdS/CFT correspondence. The accuracy and convergence of the algorithm are evaluated with respect to the grid spacing. The systematic errors of the method are determined using an exact solution of 3D black Janus. This numerical approach for solving linear problems is unaffected initial guess of a trial solution and can handle an arbitrary geometry under various boundary conditions in the presence of source fields.

  19. Morse Monte Carlo Radiation Transport Code System

    Energy Technology Data Exchange (ETDEWEB)

    Emmett, M.B.

    1975-02-01

    The report contains sections containing descriptions of the MORSE and PICTURE codes, input descriptions, sample problems, deviations of the physical equations and explanations of the various error messages. The MORSE code is a multipurpose neutron and gamma-ray transport Monte Carlo code. Time dependence for both shielding and criticality problems is provided. General three-dimensional geometry may be used with an albedo option available at any material surface. The PICTURE code provide aid in preparing correct input data for the combinatorial geometry package CG. It provides a printed view of arbitrary two-dimensional slices through the geometry. By inspecting these pictures one may determine if the geometry specified by the input cards is indeed the desired geometry. 23 refs. (WRF)

  20. Monte Carlo modeling and meteor showers

    International Nuclear Information System (INIS)

    Kulikova, N.V.

    1987-01-01

    Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented

  1. Monte Carlo simulations of medical imaging modalities

    Energy Technology Data Exchange (ETDEWEB)

    Estes, G.P. [Los Alamos National Lab., NM (United States)

    1998-09-01

    Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computer power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.

  2. Monte carlo analysis of multicolour LED light engine

    DEFF Research Database (Denmark)

    Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

    2015-01-01

    A new Monte Carlo simulation as a tool for analysing colour feedback systems is presented here to analyse the colour uncertainties and achievable stability in a multicolour dynamic LED system. The Monte Carlo analysis presented here is based on an experimental investigation of a multicolour LED...

  3. Multiple histogram method and static Monte Carlo sampling

    NARCIS (Netherlands)

    Inda, M.A.; Frenkel, D.

    2004-01-01

    We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From

  4. Monte Carlo methods for pricing financial options

    Indian Academy of Sciences (India)

    Monte Carlo methods have increasingly become a popular computational tool to price complex financial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the 'curse of dimensionality'. However, even Monte-Carlo ...

  5. New Approaches and Applications for Monte Carlo Perturbation Theory

    Energy Technology Data Exchange (ETDEWEB)

    Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan; Leppänen, Jaakko; Palmiotti, Giuseppe; Salvatores, Massimo; Sen, Sonat; Shwageraus, Eugene; Fratoni, Massimiliano

    2017-02-01

    This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.

  6. Forecasting with nonlinear time series model: A Monte-Carlo ...

    African Journals Online (AJOL)

    In this paper, we propose a new method of forecasting with nonlinear time series model using Monte-Carlo Bootstrap method. This new method gives better result in terms of forecast root mean squared error (RMSE) when compared with the traditional Bootstrap method and Monte-Carlo method of forecasting using a ...

  7. A Monte Carlo approach to combating delayed completion of ...

    African Journals Online (AJOL)

    The objective of this paper is to unveil the relevance of Monte Carlo critical path analysis in resolving problem of delays in scheduled completion of development projects. Commencing with deterministic network scheduling, Monte Carlo critical path analysis was advanced by assigning probability distributions to task times.

  8. Quantum Monte Carlo method for attractive Coulomb potentials

    NARCIS (Netherlands)

    Kole, J.S.; Raedt, H. De

    2001-01-01

    Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quantum Monte Carlo method that can handle singular attractive potentials. We illustrate the basic ideas of this quantum Monte Carlo algorithm by simulating the ground state of hydrogen and helium.

  9. Forest canopy BRDF simulation using Monte Carlo method

    NARCIS (Netherlands)

    Huang, J.; Wu, B.; Zeng, Y.; Tian, Y.

    2006-01-01

    Monte Carlo method is a random statistic method, which has been widely used to simulate the Bidirectional Reflectance Distribution Function (BRDF) of vegetation canopy in the field of visible remote sensing. The random process between photons and forest canopy was designed using Monte Carlo method.

  10. Crop canopy BRDF simulation and analysis using Monte Carlo method

    NARCIS (Netherlands)

    Huang, J.; Wu, B.; Tian, Y.; Zeng, Y.

    2006-01-01

    This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and

  11. Efficiency and accuracy of Monte Carlo (importance) sampling

    NARCIS (Netherlands)

    Waarts, P.H.

    2003-01-01

    Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed

  12. Nuclear data treatment for SAM-CE Monte Carlo calculations

    International Nuclear Information System (INIS)

    Lichtenstein, H.; Troubetzkoy, E.S.; Beer, M.

    1980-01-01

    The treatment of nuclear data by the SAM-CE Monte Carlo code system is presented. The retrieval of neutron, gamma production, and photon data from the ENDF/B fils is described. Integral cross sections as well as differential data are utilized in the Monte Carlo calculations, and the processing procedures for the requisite data are summarized

  13. Approximating Sievert Integrals to Monte Carlo Methods to calculate ...

    African Journals Online (AJOL)

    Radiation dose rates along the transverse axis of a miniature P192PIr source were calculated using Sievert Integral (considered simple and inaccurate), and by the sophisticated and accurate Monte Carlo method. Using data obt-ained by the Monte Carlo method as benchmark and applying least squares regression curve ...

  14. Monte Carlo modelling of TRIGA research reactor

    International Nuclear Information System (INIS)

    El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.

    2010-01-01

    The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucleaires de la Maamora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S(α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file 'up259'. The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.

  15. Monte Carlo modelling of TRIGA research reactor

    Science.gov (United States)

    El Bakkari, B.; Nacir, B.; El Bardouni, T.; El Younoussi, C.; Merroun, O.; Htet, A.; Boulaich, Y.; Zoubair, M.; Boukhal, H.; Chakir, M.

    2010-10-01

    The Moroccan 2 MW TRIGA MARK II research reactor at Centre des Etudes Nucléaires de la Maâmora (CENM) achieved initial criticality on May 2, 2007. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes for their use in agriculture, industry, and medicine. This study deals with the neutronic analysis of the 2-MW TRIGA MARK II research reactor at CENM and validation of the results by comparisons with the experimental, operational, and available final safety analysis report (FSAR) values. The study was prepared in collaboration between the Laboratory of Radiation and Nuclear Systems (ERSN-LMR) from Faculty of Sciences of Tetuan (Morocco) and CENM. The 3-D continuous energy Monte Carlo code MCNP (version 5) was used to develop a versatile and accurate full model of the TRIGA core. The model represents in detailed all components of the core with literally no physical approximation. Continuous energy cross-section data from the more recent nuclear data evaluations (ENDF/B-VI.8, ENDF/B-VII.0, JEFF-3.1, and JENDL-3.3) as well as S( α, β) thermal neutron scattering functions distributed with the MCNP code were used. The cross-section libraries were generated by using the NJOY99 system updated to its more recent patch file "up259". The consistency and accuracy of both the Monte Carlo simulation and neutron transport physics were established by benchmarking the TRIGA experiments. Core excess reactivity, total and integral control rods worth as well as power peaking factors were used in the validation process. Results of calculations are analysed and discussed.

  16. Exploring the multiscale signaling behavior of phototropin1 from Chlamydomonas reinhardtii using a full-residue space kinetic Monte Carlo molecular dynamics technique.

    Science.gov (United States)

    Peter, Emanuel; Dick, Bernhard; Stambolic, Ivan; Baeurle, Stephan A

    2014-09-01

    Devising analysis tools for elucidating the regulatory mechanism of complex enzymes has been a challenging task for many decades. It generally requires the determination of the structural-dynamical information of protein solvent systems far from equilibrium over multiple length and time scales, which is still difficult both theoretically and experimentally. To cope with the problem, we introduce a full-residue space multiscale simulation method based on a combination of the kinetic Monte Carlo and molecular dynamics techniques, in which the rates of the rate-determining processes are evaluated from a biomolecular forcefield on the fly during the simulation run by taking into account the full space of residues. To demonstrate its reliability and efficiency, we explore the light-induced functional behavior of the full-length phototropin1 from Chlamydomonas reinhardtii (Cr-phot1) and its various subdomains. Our results demonstrate that in the dark state the light oxygen voltage-2-Jα (LOV2-Jα) photoswitch inhibits the enzymatic activity of the kinase, whereas the LOV1-Jα photoswitch controls the dimerization with the LOV2 domain. This leads to the repulsion of the LOV1-LOV2 linker out of the interface region between both LOV domains, which results in a positively charged surface suitable for cell-membrane interaction. By contrast, in the light state, we observe that the distance between both LOV domains is increased and the LOV1-LOV2 linker forms a helix-turn-helix (HTH) motif, which enables gene control through nucleotide binding. Finally, we find that the kinase is activated through the disruption of the Jα-helix from the LOV2 domain, which is followed by a stretching of the activation loop (A-loop) and broadening of the catalytic cleft of the kinase. © 2014 Wiley Periodicals, Inc.

  17. SU-E-I-42: Normalized Embryo/fetus Doses for Fluoroscopically Guided Pacemaker Implantation Procedures Calculated Using a Monte Carlo Technique

    Energy Technology Data Exchange (ETDEWEB)

    Damilakis, J; Stratakis, J; Solomou, G [University of Crete, Heraklion (Greece)

    2014-06-01

    Purpose: It is well known that pacemaker implantation is sometimes needed in pregnant patients with symptomatic bradycardia. To our knowledge, there is no reported experience regarding radiation doses to the unborn child resulting from fluoroscopy during pacemaker implantation. The purpose of the current study was to develop a method for estimating embryo/fetus dose from fluoroscopically guided pacemaker implantation procedures performed on pregnant patients during all trimesters of gestation. Methods: The Monte Carlo N-Particle (MCNP) radiation transport code was employed in this study. Three mathematical anthropomorphic phantoms representing the average pregnant patient at the first, second and third trimesters of gestation were generated using Bodybuilder software (White Rock science, White Rock, NM). The normalized embryo/fetus dose from the posteroanterior (PA), the 30° left-anterior oblique (LAO) and the 30° right-anterior oblique (RAO) projections were calculated for a wide range of kVp (50–120 kVp) and total filtration values (2.5–9.0 mm Al). Results: The results consist of radiation doses normalized to a) entrance skin dose (ESD) and b) dose area product (DAP) so that the dose to the unborn child from any fluoroscopic technique and x-ray device used can be calculated. ESD normalized doses ranged from 0.008 (PA, first trimester) to 2.519 μGy/mGy (RAO, third trimester). DAP normalized doses ranged from 0.051 (PA, first trimester) to 12.852 μGy/Gycm2 (RAO, third trimester). Conclusion: Embryo/fetus doses from fluoroscopically guided pacemaker implantation procedures performed on pregnant patients during all stages of gestation can be estimated using the method developed in this study. This study was supported by the Greek Ministry of Education and Religious Affairs, General Secretariat for Research and Technology, Operational Program ‘Education and Lifelong Learning’, ARISTIA (Research project: CONCERT)

  18. Stochastic simulation and Monte-Carlo methods; Simulation stochastique et methodes de Monte-Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Graham, C. [Centre National de la Recherche Scientifique (CNRS), 91 - Gif-sur-Yvette (France); Ecole Polytechnique, 91 - Palaiseau (France); Talay, D. [Institut National de Recherche en Informatique et en Automatique (INRIA), 78 - Le Chesnay (France); Ecole Polytechnique, 91 - Palaiseau (France)

    2011-07-01

    This book presents some numerical probabilistic methods of simulation with their convergence speed. It combines mathematical precision and numerical developments, each proposed method belonging to a precise theoretical context developed in a rigorous and self-sufficient manner. After some recalls about the big numbers law and the basics of probabilistic simulation, the authors introduce the martingales and their main properties. Then, they develop a chapter on non-asymptotic estimations of Monte-Carlo method errors. This chapter gives a recall of the central limit theorem and precises its convergence speed. It introduces the Log-Sobolev and concentration inequalities, about which the study has greatly developed during the last years. This chapter ends with some variance reduction techniques. In order to demonstrate in a rigorous way the simulation results of stochastic processes, the authors introduce the basic notions of probabilities and of stochastic calculus, in particular the essential basics of Ito calculus, adapted to each numerical method proposed. They successively study the construction and important properties of the Poisson process, of the jump and deterministic Markov processes (linked to transport equations), and of the solutions of stochastic differential equations. Numerical methods are then developed and the convergence speed results of algorithms are rigorously demonstrated. In passing, the authors describe the probabilistic interpretation basics of the parabolic partial derivative equations. Non-trivial applications to real applied problems are also developed. (J.S.)

  19. Resolution and intensity in neutron spectrometry determined by Monte Carlo simulation

    DEFF Research Database (Denmark)

    Dietrich, O.W.

    1968-01-01

    The Monte Carlo simulation technique was applied to the propagation of Bragg-reflected neutrons in mosaic single crystals. The method proved to be very useful for the determination of resolution and intensity in neutron spectrometers.......The Monte Carlo simulation technique was applied to the propagation of Bragg-reflected neutrons in mosaic single crystals. The method proved to be very useful for the determination of resolution and intensity in neutron spectrometers....

  20. Review and comparison of effective delayed neutron fraction calculation methods with Monte Carlo codes

    OpenAIRE

    Bécares, V.; Pérez Martín, S.; Vázquez Antolín, Miriam; Villamarín, D.; Martín Fuertes, Francisco; González Romero, E.M.; Merino Rodríguez, Iván

    2014-01-01

    The calculation of the effective delayed neutron fraction, beff , with Monte Carlo codes is a complex task due to the requirement of properly considering the adjoint weighting of delayed neutrons. Nevertheless, several techniques have been proposed to circumvent this difficulty and obtain accurate Monte Carlo results for beff without the need of explicitly determining the adjoint flux. In this paper, we make a review of some of these techniques; namely we have analyzed two variants of what we...

  1. Research on perturbation based Monte Carlo reactor criticality search

    International Nuclear Information System (INIS)

    Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

    2013-01-01

    Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k eff and differential coefficients of concerned parameter, the polynomial estimator of k eff changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)

  2. Monte Carlo 2000 Conference : Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications

    CERN Document Server

    Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro

    2001-01-01

    This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.

  3. Study of the influence of porosity on the radon emanation coefficient in different building material samples by combining the SSNTD technique with Monte Carlo simulations

    CERN Document Server

    Misdaq, M A; Ktata, A

    1998-01-01

    Radon alpha-activities per unit volume have been measured inside and outside different building material samples by using CR-39 and LR-115 type II solid state nuclear track detectors (SSNTD). Radon emanation coefficients of the studied building materials have been evaluated. The porosities of the building material samples studied have been determined by using a Monte Carlo calculational method adapted to the experimental conditions and compared with data obtained by the Archimedes's method. The influence of the building material porosity on the radon emanation coefficient has been investigated.

  4. A fully coupled Monte Carlo/discrete ordinates solution to the neutron transport equation. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Randal Scott [Univ. of Arizona, Tucson, AZ (United States)

    1990-01-01

    The neutron transport equation is solved by a hybrid method that iteratively couples regions where deterministic (SN) and stochastic (Monte Carlo) methods are applied. Unlike previous hybrid methods, the Monte Carlo and SN regions are fully coupled in the sense that no assumption is made about geometrical separation or decoupling. The hybrid method provides a new means of solving problems involving both optically thick and optically thin regions that neither Monte Carlo nor SN is well suited for by themselves. The fully coupled Monte Carlo/SN technique consists of defining spatial and/or energy regions of a problem in which either a Monte Carlo calculation or an SN calculation is to be performed. The Monte Carlo region may comprise the entire spatial region for selected energy groups, or may consist of a rectangular area that is either completely or partially embedded in an arbitrary SN region. The Monte Carlo and SN regions are then connected through the common angular boundary fluxes, which are determined iteratively using the response matrix technique, and volumetric sources. The hybrid method has been implemented in the SN code TWODANT by adding special-purpose Monte Carlo subroutines to calculate the response matrices and volumetric sources, and linkage subrountines to carry out the interface flux iterations. The common angular boundary fluxes are included in the SN code as interior boundary sources, leaving the logic for the solution of the transport flux unchanged, while, with minor modifications, the diffusion synthetic accelerator remains effective in accelerating SN calculations. The special-purpose Monte Carlo routines used are essentially analog, with few variance reduction techniques employed. However, the routines have been successfully vectorized, with approximately a factor of five increase in speed over the non-vectorized version.

  5. The computation of Greeks with multilevel Monte Carlo

    OpenAIRE

    Sylvestre Burgos; M. B. Giles

    2011-01-01

    In mathematical finance, the sensitivities of option prices to various market parameters, also known as the “Greeks”, reflect the exposure to different sources of risk. Computing these is essential to predict the impact of market moves on portfolios and to hedge them adequately. This is commonly done using Monte Carlo simulations. However, obtaining accurate estimates of the Greeks can be computationally costly. Multilevel Monte Carlo offers complexity improvements over standard Monte Carl...

  6. Hybrid Monte Carlo algorithm with fat link fermion actions

    International Nuclear Information System (INIS)

    Kamleh, Waseem; Leinweber, Derek B.; Williams, Anthony G.

    2004-01-01

    The use of APE smearing or other blocking techniques in lattice fermion actions can provide many advantages. There are many variants of these fat link actions in lattice QCD currently, such as flat link irrelevant clover (FLIC) fermions. The FLIC fermion formalism makes use of the APE blocking technique in combination with a projection of the blocked links back into the special unitary group. This reunitarization is often performed using an iterative maximization of a gauge invariant measure. This technique is not differentiable with respect to the gauge field and thus prevents the use of standard Hybrid Monte Carlo simulation algorithms. The use of an alternative projection technique circumvents this difficulty and allows the simulation of dynamical fat link fermions with standard HMC and its variants. The necessary equations of motion for FLIC fermions are derived, and some initial simulation results are presented. The technique is more general however, and is straightforwardly applicable to other smearing techniques or fat link actions

  7. Using adaptive neuro-fuzzy inference system technique for crosstalk correction in simultaneous {sup 99m}Tc/{sup 201}Tl SPECT imaging: A Monte Carlo simulation study

    Energy Technology Data Exchange (ETDEWEB)

    Heidary, Saeed, E-mail: saeedheidary@aut.ac.ir; Setayeshi, Saeed, E-mail: setayesh@aut.ac.ir

    2015-01-11

    This work presents a simulation based study by Monte Carlo which uses two adaptive neuro-fuzzy inference systems (ANFIS) for cross talk compensation of simultaneous {sup 99m}Tc/{sup 201}Tl dual-radioisotope SPECT imaging. We have compared two neuro-fuzzy systems based on fuzzy c-means (FCM) and subtractive (SUB) clustering. Our approach incorporates eight energy-windows image acquisition from 28 keV to 156 keV and two main photo peaks of {sup 201}Tl (77±10% keV) and {sup 99m}Tc (140±10% keV). The Geant4 application in emission tomography (GATE) is used as a Monte Carlo simulator for three cylindrical and a NURBS Based Cardiac Torso (NCAT) phantom study. Three separate acquisitions including two single-isotopes and one dual isotope were performed in this study. Cross talk and scatter corrected projections are reconstructed by an iterative ordered subsets expectation maximization (OSEM) algorithm which models the non-uniform attenuation in the projection/back-projection. ANFIS-FCM/SUB structures are tuned to create three to sixteen fuzzy rules for modeling the photon cross-talk of the two radioisotopes. Applying seven to nine fuzzy rules leads to a total improvement of the contrast and the bias comparatively. It is found that there is an out performance for the ANFIS-FCM due to its acceleration and accurate results.

  8. MCNP trademark Monte Carlo: A precis of MCNP

    International Nuclear Information System (INIS)

    Adams, K.J.

    1996-01-01

    MCNP trademark is a general purpose three-dimensional time-dependent neutron, photon, and electron transport code. It is highly portable and user-oriented, and backed by stringent software quality assurance practices and extensive experimental benchmarks. The cross section database is based upon the best evaluations available. MCNP incorporates state-of-the-art analog and adaptive Monte Carlo techniques. The code is documented in a 600 page manual which is augmented by numerous Los Alamos technical reports which detail various aspects of the code. MCNP represents over a megahour of development and refinement over the past 50 years and an ongoing commitment to excellence

  9. Entropic sampling in the path integral Monte Carlo method

    International Nuclear Information System (INIS)

    Vorontsov-Velyaminov, P N; Lyubartsev, A P

    2003-01-01

    We have extended the entropic sampling Monte Carlo method to the case of path integral representation of a quantum system. A two-dimensional density of states is introduced into path integral form of the quantum canonical partition function. Entropic sampling technique within the algorithm suggested recently by Wang and Landau (Wang F and Landau D P 2001 Phys. Rev. Lett. 86 2050) is then applied to calculate the corresponding entropy distribution. A three-dimensional quantum oscillator is considered as an example. Canonical distributions for a wide range of temperatures are obtained in a single simulation run, and exact data for the energy are reproduced

  10. Adjoint sensitivity and uncertainty analyses in Monte Carlo forward calculations

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Kim, Chang Hyo

    2011-01-01

    The adjoint-weighted perturbation (AWP) method, in which the required adjoint flux is estimated in the course of Monte Carlo (MC) forward calculations, has recently been proposed as an alternative to the conventional MC perturbation techniques, such as the correlated sampling and differential operator sampling (DOS) methods. The equivalence of the first-order AWP method and first-order DOS method with the fission source perturbation taken into account is proven. An algorithm for the AWP calculations is implemented in the Seoul National University MC code McCARD and applied to the sensitivity and uncertainty analyses of the Godiva and Bigten criticalities. (author)

  11. Monte Carlo simulation of a noisy quantum channel with memory.

    Science.gov (United States)

    Akhalwaya, Ismail; Moodley, Mervlyn; Petruccione, Francesco

    2015-10-01

    The classical capacity of quantum channels is well understood for channels with uncorrelated noise. For the case of correlated noise, however, there are still open questions. We calculate the classical capacity of a forgetful channel constructed by Markov switching between two depolarizing channels. Techniques have previously been applied to approximate the output entropy of this channel and thus its capacity. In this paper, we use a Metropolis-Hastings Monte Carlo approach to numerically calculate the entropy. The algorithm is implemented in parallel and its performance is studied and optimized. The effects of memory on the capacity are explored and previous results are confirmed to higher precision.

  12. Diagrammatic Monte Carlo method as applied to the polaron problem

    International Nuclear Information System (INIS)

    Mishchenko, A.S.

    2005-01-01

    Exact numerical solution methods for the problem of a few particles interacting with one another and with several bosonic excitation modes are presented. The diagrammatic Monte Carlo method allows the exact calculation of the Green function, and the stochastic optimization technique provides an analytic continuation. Results unobtainable by conventional methods are discussed, including the properties of excited states in the self-trapping phenomenon, the optical spectra of polarons in all coupling regimes, the validity analysis of the exciton models, and the photoemission spectra of a phonon-coupled hole [ru

  13. Computational radiology and imaging with the MCNP Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Estes, G.P.; Taylor, W.M.

    1995-05-01

    MCNP, a 3D coupled neutron/photon/electron Monte Carlo radiation transport code, is currently used in medical applications such as cancer radiation treatment planning, interpretation of diagnostic radiation images, and treatment beam optimization. This paper will discuss MCNP`s current uses and capabilities, as well as envisioned improvements that would further enhance MCNP role in computational medicine. It will be demonstrated that the methodology exists to simulate medical images (e.g. SPECT). Techniques will be discussed that would enable the construction of 3D computational geometry models of individual patients for use in patient-specific studies that would improve the quality of care for patients.

  14. Iterative acceleration methods for Monte Carlo and deterministic criticality calculations

    Energy Technology Data Exchange (ETDEWEB)

    Urbatsch, T.J.

    1995-11-01

    If you have ever given up on a nuclear criticality calculation and terminated it because it took so long to converge, you might find this thesis of interest. The author develops three methods for improving the fission source convergence in nuclear criticality calculations for physical systems with high dominance ratios for which convergence is slow. The Fission Matrix Acceleration Method and the Fission Diffusion Synthetic Acceleration (FDSA) Method are acceleration methods that speed fission source convergence for both Monte Carlo and deterministic methods. The third method is a hybrid Monte Carlo method that also converges for difficult problems where the unaccelerated Monte Carlo method fails. The author tested the feasibility of all three methods in a test bed consisting of idealized problems. He has successfully accelerated fission source convergence in both deterministic and Monte Carlo criticality calculations. By filtering statistical noise, he has incorporated deterministic attributes into the Monte Carlo calculations in order to speed their source convergence. He has used both the fission matrix and a diffusion approximation to perform unbiased accelerations. The Fission Matrix Acceleration method has been implemented in the production code MCNP and successfully applied to a real problem. When the unaccelerated calculations are unable to converge to the correct solution, they cannot be accelerated in an unbiased fashion. A Hybrid Monte Carlo method weds Monte Carlo and a modified diffusion calculation to overcome these deficiencies. The Hybrid method additionally possesses reduced statistical errors.

  15. Comparison of Monte Carlo method and deterministic method for neutron transport calculation

    International Nuclear Information System (INIS)

    Mori, Takamasa; Nakagawa, Masayuki

    1987-01-01

    The report outlines major features of the Monte Carlo method by citing various applications of the method and techniques used for Monte Carlo codes. Major areas of its application include analysis of measurements on fast critical assemblies, nuclear fusion reactor neutronics analysis, criticality safety analysis, evaluation by VIM code, and calculation for shielding. Major techniques used for Monte Carlo codes include the random walk method, geometric expression method (combinatorial geometry, 1, 2, 4-th degree surface and lattice geometry), nuclear data expression, evaluation method (track length, collision, analog (absorption), surface crossing, point), and dispersion reduction (Russian roulette, splitting, exponential transform, importance sampling, corrected sampling). Major features of the Monte Carlo method are as follows: 1) neutron source distribution and systems of complex geometry can be simulated accurately, 2) physical quantities such as neutron flux in a place, on a surface or at a point can be evaluated, and 3) calculation requires less time. (Nogami, K.)

  16. 'Odontologic dosimetric card' experiments and simulations using Monte Carlo methods

    International Nuclear Information System (INIS)

    Menezes, C.J.M.; Lima, R. de A.; Peixoto, J.E.; Vieira, J.W.

    2008-01-01

    The techniques for data processing, combined with the development of fast and more powerful computers, makes the Monte Carlo methods one of the most widely used tools in the radiation transport simulation. For applications in diagnostic radiology, this method generally uses anthropomorphic phantoms to evaluate the absorbed dose to patients during exposure. In this paper, some Monte Carlo techniques were used to simulation of a testing device designed for intra-oral X-ray equipment performance evaluation called Odontologic Dosimetric Card (CDO of 'Cartao Dosimetrico Odontologico' in Portuguese) for different thermoluminescent detectors. This paper used two computational models of exposition RXD/EGS4 and CDO/EGS4. In the first model, the simulation results are compared with experimental data obtained in the similar conditions. The second model, it presents the same characteristics of the testing device studied (CDO). For the irradiations, the X-ray spectra were generated by the IPEM report number 78, spectrum processor. The attenuated spectrum was obtained for IEC 61267 qualities and various additional filters for a Pantak 320 X-ray industrial equipment. The results obtained for the study of the copper filters used in the determination of the kVp were compared with experimental data, validating the model proposed for the characterization of the CDO. The results shower of the CDO will be utilized in quality assurance programs in order to guarantee that the equipment fulfill the requirements of the Norm SVS No. 453/98 MS (Brazil) 'Directives of Radiation Protection in Medical and Dental Radiodiagnostic'. We conclude that the EGS4 is a suitable code Monte Carlo to simulate thermoluminescent dosimeters and experimental procedures employed in the routine of the quality control laboratory in diagnostic radiology. (author)

  17. Simulation and the Monte Carlo Method, Student Solutions Manual

    CERN Document Server

    Rubinstein, Reuven Y

    2012-01-01

    This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, suc

  18. Multiple Monte Carlo Testing with Applications in Spatial Point Processes

    DEFF Research Database (Denmark)

    Mrkvička, Tomáš; Myllymäki, Mari; Hahn, Ute

    The rank envelope test (Myllym\\"aki et al., Global envelope tests for spatial processes, arXiv:1307.0239 [stat.ME]) is proposed as a solution to multiple testing problem for Monte Carlo tests. Three different situations are recognized: 1) a few univariate Monte Carlo tests, 2) a Monte Carlo test ...... for one group of point patterns, comparison of several groups of point patterns, test of dependence of components in a multi-type point pattern, and test of Boolean assumption for random closed sets....

  19. Dairy goat kids fed liquid diets in substitution of goat milk and slaughtered at different ages: an economic viability analysis using Monte Carlo techniques.

    Science.gov (United States)

    Knupp, L S; Veloso, C M; Marcondes, M I; Silveira, T S; Silva, A L; Souza, N O; Knupp, S N R; Cannas, A

    2016-03-01

    The aim of this study was to analyze the economic viability of producing dairy goat kids fed liquid diets in alternative of goat milk and slaughtered at two different ages. Forty-eight male newborn Saanen and Alpine kids were selected and allocated to four groups using a completely randomized factorial design: goat milk (GM), cow milk (CM), commercial milk replacer (CMR) and fermented cow colostrum (FC). Each group was then divided into two groups: slaughter at 60 and 90 days of age. The animals received Tifton hay and concentrate ad libitum. The values of total costs of liquid and solid feed plus labor, income and average gross margin were calculated. The data were then analyzed using the Monte Carlo techniques with the @Risk 5.5 software, with 1000 iterations of the variables being studied through the model. The kids fed GM and CMR generated negative profitability values when slaughtered at 60 days (US$ -16.4 and US$ -2.17, respectively) and also at 90 days (US$ -30.8 and US$ -0.18, respectively). The risk analysis showed that there is a 98% probability that profitability would be negative when GM is used. In this regard, CM and FC presented low risk when the kids were slaughtered at 60 days (8.5% and 21.2%, respectively) and an even lower risk when animals were slaughtered at 90 days (5.2% and 3.8%, respectively). The kids fed CM and slaughtered at 90 days presented the highest average gross income (US$ 67.88) and also average gross margin (US$ 18.43/animal). For the 60-day rearing regime to be economically viable, the CMR cost should not exceed 11.47% of the animal-selling price. This implies that the replacer cannot cost more than US$ 0.39 and 0.43/kg for the 60- and 90-day feeding regimes, respectively. The sensitivity analysis showed that the variables with the greatest impact on the final model's results were animal selling price, liquid diet cost, final weight at slaughter and labor. In conclusion, the production of male dairy goat kids can be economically

  20. Quantum Monte Carlo on graphical processing units

    Science.gov (United States)

    Anderson, Amos G.; Goddard, William A.; Schröder, Peter

    2007-08-01

    Quantum Monte Carlo (QMC) is among the most accurate methods for solving the time independent Schrödinger equation. Unfortunately, the method is very expensive and requires a vast array of computing resources in order to obtain results of a reasonable convergence level. On the other hand, the method is not only easily parallelizable across CPU clusters, but as we report here, it also has a high degree of data parallelism. This facilitates the use of recent technological advances in Graphical Processing Units (GPUs), a powerful type of processor well known to computer gamers. In this paper we report on an end-to-end QMC application with core elements of the algorithm running on a GPU. With individual kernels achieving as much as 30× speed up, the overall application performs at up to 6× faster relative to an optimized CPU implementation, yet requires only a modest increase in hardware cost. This demonstrates the speedup improvements possible for QMC in running on advanced hardware, thus exploring a path toward providing QMC level accuracy as a more standard tool. The major current challenge in running codes of this type on the GPU arises from the lack of fully compliant IEEE floating point implementations. To achieve better accuracy we propose the use of the Kahan summation formula in matrix multiplications. While this drops overall performance, we demonstrate that the proposed new algorithm can match CPU single precision.

  1. The GENIE neutrino Monte Carlo generator

    International Nuclear Information System (INIS)

    Andreopoulos, C.; Bell, A.; Bhattacharya, D.; Cavanna, F.; Dobson, J.; Dytman, S.; Gallagher, H.; Guzowski, P.; Hatcher, R.; Kehayias, P.; Meregaglia, A.; Naples, D.; Pearce, G.; Rubbia, A.; Whalley, M.; Yang, T.

    2010-01-01

    GENIE is a new neutrino event generator for the experimental neutrino physics community. The goal of the project is to develop a 'canonical' neutrino interaction physics Monte Carlo whose validity extends to all nuclear targets and neutrino flavors from MeV to PeV energy scales. Currently, emphasis is on the few-GeV energy range, the challenging boundary between the non-perturbative and perturbative regimes, which is relevant for the current and near future long-baseline precision neutrino experiments using accelerator-made beams. The design of the package addresses many challenges unique to neutrino simulations and supports the full life-cycle of simulation and generator-related analysis tasks. GENIE is a large-scale software system, consisting of ∼120000 lines of C++ code, featuring a modern object-oriented design and extensively validated physics content. The first official physics release of GENIE was made available in August 2007, and at the time of the writing of this article, the latest available version was v2.4.4.

  2. Pseudopotentials for quantum-Monte-Carlo-calculations

    International Nuclear Information System (INIS)

    Burkatzki, Mark Thomas

    2008-01-01

    The author presents scalar-relativistic energy-consistent Hartree-Fock pseudopotentials for the main-group and 3d-transition-metal elements. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The author demonstrates their transferability through extensive benchmark calculations of atomic excitation spectra as well as molecular properties. In particular, the author computes the vibrational frequencies and binding energies of 26 first- and second-row diatomic molecules using post Hartree-Fock methods, finding excellent agreement with the corresponding all-electron values. The author shows that the presented pseudopotentials give superior accuracy than other existing pseudopotentials constructed specifically for QMC. The localization error and the efficiency in QMC are discussed. The author also presents QMC calculations for selected atomic and diatomic 3d-transitionmetal systems. Finally, valence basis sets of different sizes (VnZ with n=D,T,Q,5 for 1st and 2nd row; with n=D,T for 3rd to 5th row; with n=D,T,Q for the 3d transition metals) optimized for the pseudopotentials are presented. (orig.)

  3. Rare event simulation using Monte Carlo methods

    CERN Document Server

    Rubino, Gerardo

    2009-01-01

    In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...

  4. Atomistic Monte Carlo Simulation of Lipid Membranes

    Directory of Open Access Journals (Sweden)

    Daniel Wüstner

    2014-01-01

    Full Text Available Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA for the phospholipid dipalmitoylphosphatidylcholine (DPPC. We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.

  5. A continuation multilevel Monte Carlo algorithm

    KAUST Repository

    Collier, Nathan

    2014-09-05

    We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. The actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients. © 2014, Springer Science+Business Media Dordrecht.

  6. Dosimetric study of prostate brachytherapy using techniques of Monte-Carlo simulation, experimental measurements and comparison with a treatment plan; Estudo dosimetrico de braquiterapia da prostata utilizando tecnicas de simulacao de Monte-Carlo, medidas experimentais, e comparacao com um procedimento de plano de tratamento

    Energy Technology Data Exchange (ETDEWEB)

    Teles, Pedro; Barros, Silvia; Vaz, Pedro; Goncalves, Isabel [Instituto Tecnologico e Nuclear, Sacavem (Portugal). Instituto Superior Tecnico; Cardoso, Simone [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil); Facure, Alessandro [Comissao Nacional de Energia Nuclear, Rio de Janeiro, RJ (Brazil); Rosa, Luiz da; Santos, Maira [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Pereira Junior, Pedro Paulo [Dosimetrika (Brazil); Zankl, Maria [German Research Centre for Environmental Health, Munchen (Germany). Helmholtz Zentrum Munchen

    2013-10-01

    Prostate Brachytherapy is a radiotherapy technique, which consists in inserting a number of radioactive seeds (containing, usually, the following radionuclides {sup 125} l, {sup 241}Am or {sup 103}Pd ) surrounding or in the vicinity of, prostate tumor tissue . The main objective of this technique is to maximize the radiation dose to the tumor and minimize it in other tissues and organs healthy, in order to reduce its morbidity. The absorbed dose distribution in the prostate, using this technique is usually non-homogeneous and time dependent. Various parameters such as the type of seed, the attenuation interactions between them, their geometrical arrangement within the prostate, the actual geometry of the seeds,and further swelling of the prostate gland after implantation greatly influence the course of absorbed dose in the prostate and surrounding areas. Quantification of these parameters is therefore extremely important for dose optimization and improvement of their plans conventional treatment, which in many cases not fully take into account. The Monte Carlo techniques allow to study these parameters quickly and effectively. In this work, we use the program MCNPX and generic voxel phantom (GOLEM) where simulated different geometric arrangements of seeds containing {sup 125}I, Amersham Health model of type 6711 in prostates of different sizes, in order to try to quantify some of the parameters. The computational model was validated using a phantom prostate cubic RW3 type , consisting of tissue equivalent, and thermoluminescent dosimeters. Finally, to have a term of comparison with a treatment real plan it was simulate a treatment plan used in a hospital of Rio de Janeiro, with exactly the same parameters, and our computational model. The results obtained in our study seem to indicate that the parameters described above may be a source of uncertainty in the correct evaluation of the dose required for actual treatment plans. The use of Monte Carlo techniques can

  7. pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

    Science.gov (United States)

    White, J.; Brakefield, L. K.

    2015-12-01

    The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.

  8. Tracking ink composition on Herculaneum papyrus scrolls: quantification and speciation of lead by X-ray based techniques and Monte Carlo simulations.

    Science.gov (United States)

    Tack, Pieter; Cotte, Marine; Bauters, Stephen; Brun, Emmanuel; Banerjee, Dipanjan; Bras, Wim; Ferrero, Claudio; Delattre, Daniel; Mocella, Vito; Vincze, Laszlo

    2016-02-08

    The writing in carbonized Herculaneum scrolls, covered and preserved by the pyroclastic events of the Vesuvius in 79 AD, was recently revealed using X-ray phase-contrast tomography, without the need of unrolling the sensitive scrolls. Unfortunately, some of the text is difficult to read due to the interference of the papyrus fibers crossing the written text vertically and horizontally. Recently, lead was found as an elemental constituent in the writing, rendering the text more clearly readable when monitoring the lead X-ray fluorescence signal. Here, several hypotheses are postulated for the origin and state of lead in the papyrus writing. Multi-scale X-ray fluorescence micro-imaging, Monte Carlo quantification and X-ray absorption microspectroscopy experiments are used to provide additional information on the ink composition, in an attempt to determine the origin of the lead in the Herculaneum scrolls and validate the postulated hypotheses.

  9. TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

    International Nuclear Information System (INIS)

    Badal, A; Zbijewski, W; Bolch, W; Sechopoulos, I

    2014-01-01

    Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10 7 xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual

  10. Moisture content prediction in poultry litter using artificial intelligence techniques and Monte Carlo simulation to determine the economic yield from energy use.

    Science.gov (United States)

    Rico-Contreras, José Octavio; Aguilar-Lasserre, Alberto Alfonso; Méndez-Contreras, Juan Manuel; López-Andrés, Jhony Josué; Cid-Chama, Gabriela

    2017-11-01

    The objective of this study is to determine the economic return of poultry litter combustion in boilers to produce bioenergy (thermal and electrical), as this biomass has a high-energy potential due to its component elements, using fuzzy logic to predict moisture and identify the high-impact variables. This is carried out using a proposed 7-stage methodology, which includes a statistical analysis of agricultural systems and practices to identify activities contributing to moisture in poultry litter (for example, broiler chicken management, number of air extractors, and avian population density), and thereby reduce moisture to increase the yield of the combustion process. Estimates of poultry litter production and heating value are made based on 4 different moisture content percentages (scenarios of 25%, 30%, 35%, and 40%), and then a risk analysis is proposed using the Monte Carlo simulation to select the best investment alternative and to estimate the environmental impact for greenhouse gas mitigation. The results show that dry poultry litter (25%) is slightly better for combustion, generating 3.20% more energy. Reducing moisture from 40% to 25% involves considerable economic investment due to the purchase of equipment to reduce moisture; thus, when calculating financial indicators, the 40% scenario is the most attractive, as it is the current scenario. Thus, this methodology proposes a technology approach based on the use of advanced tools to predict moisture and representation of the system (Monte Carlo simulation), where the variability and uncertainty of the system are accurately represented. Therefore, this methodology is considered generic for any bioenergy generation system and not just for the poultry sector, whether it uses combustion or another type of technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

    CERN Document Server

    Chapman, J; The ATLAS collaboration; Duehrssen, M; Elsing, M; Froidevaux, D; Harrington, R; Jansky, R; Langenberg, R; Mandrysch, R; Marshall, Z; Ritsch, E; Salzburger, A

    2013-01-01

    The huge success of Run 1 of the LHC for particle physics would not have been possible without detailed detector simulation of the experiments. However, the outstanding performance of the accelerator with a delivered luminosity of $L = 25 fb^{1}$ has created an unprecedented demand for Monte Carlo statistics. This has stretched the possibilities of the experiments due to the constraint of their computing infrastructure and available resources. Ensuring high quality Monte Carlo simulation samples with sufficient statistics became one the major focus points of experimental high energy physics and first analyses saw the advent of limitations in sensitivity or precision due to the lack of available Monte Carlo samples. Modern, concurrent computing techniques optimized for new processor hardware are being exploit to boost future computing resources, but even most optimistic scenarios predict that additional action needs to be taken to guarantee sufficient Monte Carlo production for high quality physics results dur...

  12. Monte Carlo field-theoretic simulations of a homopolymer blend

    Science.gov (United States)

    Spencer, Russell; Matsen, Mark

    Fluctuation corrections to the macrophase segregation transition (MST) in a symmetric homopolymer blend are examined using Monte Carlo field-theoretic simulations (MC-FTS). This technique involves treating interactions between unlike monomers using standard Monte-Carlo techniques, while enforcing incompressibility as is done in mean-field theory. When using MC-FTS, we need to account for a UV divergence. This is done by renormalizing the Flory-Huggins interaction parameter to incorporate the divergent part of the Hamiltonian. We compare different ways of calculating this effective interaction parameter. Near the MST, the length scale of compositional fluctuations becomes large, however, the high computational requirements of MC-FTS restrict us to small system sizes. We account for these finite size effects using the method of Binder cumulants, allowing us to locate the MST with high precision. We examine fluctuation corrections to the mean field MST, χN = 2 , as they vary with the invariant degree of polymerization, N =ρ2a6 N . These results are compared with particle-based simulations as well as analytical calculations using the renormalized one loop theory. This research was funded by the Center for Sustainable Polymers.

  13. Conditional Monte Carlo randomization tests for regression models.

    Science.gov (United States)

    Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

    2014-08-15

    We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

  14. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2014-01-06

    Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.

  15. Supertrack Monte Carlo variance reduction experience for non-Boltzmann tallies

    Energy Technology Data Exchange (ETDEWEB)

    Estes, G.P.; Booth, T.E.

    1995-02-01

    This paper applies a recently developed variance reduction technique to the first principles calculations of photon detector responses. This technique makes possible the direct comparison of pulse height calculations with measurements without the need for unfolding techniques. Comparisons are made between several experiments and the calculations to demonstrate the utility of the supertrack Monte Carlo technique for reproducing and interpreting experimental count rate spectra.

  16. On the Markov Chain Monte Carlo (MCMC) method

    Indian Academy of Sciences (India)

    Abstract. Markov Chain Monte Carlo (MCMC) is a popular method used to generate samples from arbitrary distributions, which may be specified indirectly. In this article, we give an introduction to this method along with some examples.

  17. Usefulness of the Monte Carlo method in reliability calculations

    International Nuclear Information System (INIS)

    Lanore, J.M.; Kalli, H.

    1977-01-01

    Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels

  18. The Monte Carlo simulation of the Ladon photon beam facility

    International Nuclear Information System (INIS)

    Strangio, C.

    1976-01-01

    The backward compton scattering of laser light against high energy electrons has been simulated with a Monte Carlo method. The main features of the produced photon beam are reported as well as a careful description of the numerical calculation

  19. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung

    2009-11-01

    Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.

  20. Time step length versus efficiency of Monte Carlo burnup calculations

    International Nuclear Information System (INIS)

    Dufek, Jan; Valtavirta, Ville

    2014-01-01

    Highlights: • Time step length largely affects efficiency of MC burnup calculations. • Efficiency of MC burnup calculations improves with decreasing time step length. • Results were obtained from SIE-based Monte Carlo burnup calculations. - Abstract: We demonstrate that efficiency of Monte Carlo burnup calculations can be largely affected by the selected time step length. This study employs the stochastic implicit Euler based coupling scheme for Monte Carlo burnup calculations that performs a number of inner iteration steps within each time step. In a series of calculations, we vary the time step length and the number of inner iteration steps; the results suggest that Monte Carlo burnup calculations get more efficient as the time step length is reduced. More time steps must be simulated as they get shorter; however, this is more than compensated by the decrease in computing cost per time step needed for achieving a certain accuracy

  1. Herwig: The Evolution of a Monte Carlo Simulation

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Monte Carlo event generation has seen significant developments in the last 10 years starting with preparation for the LHC and then during the first LHC run. I will discuss the basic ideas behind Monte Carlo event generators and then go on to discuss these developments, focussing on the developments in Herwig(++) event generator. I will conclude by presenting the current status of event generation together with some results of the forthcoming new version of Herwig, Herwig 7.

  2. NUEN-618 Class Project: Actually Implicit Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Vega, R. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunner, T. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-12-14

    This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.

  3. Studies of Monte Carlo Modelling of Jets at ATLAS

    CERN Document Server

    Kar, Deepak; The ATLAS collaboration

    2017-01-01

    The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets.  Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.

  4. The sine Gordon model perturbation theory and cluster Monte Carlo

    CERN Document Server

    Hasenbusch, M; Pinn, K

    1994-01-01

    We study the expansion of the surface thickness in the 2-dimensional lattice Sine Gordon model in powers of the fugacity z. Using the expansion to order z**2, we derive lines of constant physics in the rough phase. We describe and test a VMR cluster algorithm for the Monte Carlo simulation of the model. The algorithm shows nearly no critical slowing down. We apply the algorithm in a comparison of our perturbative results with Monte Carlo data.

  5. Monte Carlo methods and applications in nuclear physics

    International Nuclear Information System (INIS)

    Carlson, J.

    1990-01-01

    Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs

  6. Monte Carlo methods and applications in nuclear physics

    Energy Technology Data Exchange (ETDEWEB)

    Carlson, J.

    1990-01-01

    Monte Carlo methods for studying few- and many-body quantum systems are introduced, with special emphasis given to their applications in nuclear physics. Variational and Green's function Monte Carlo methods are presented in some detail. The status of calculations of light nuclei is reviewed, including discussions of the three-nucleon-interaction, charge and magnetic form factors, the coulomb sum rule, and studies of low-energy radiative transitions. 58 refs., 12 figs.

  7. Monte Carlos of the new generation: status and progress

    International Nuclear Information System (INIS)

    Frixione, Stefano

    2005-01-01

    Standard parton shower monte carlos are designed to give reliable descriptions of low-pT physics. In the very high-energy regime of modern colliders, this is may lead to largely incorrect predictions of the basic reaction processes. This motivated the recent theoretical efforts aimed at improving monte carlos through the inclusion of matrix elements computed beyond the leading order in QCD. I briefly review the progress made, and discuss bottom production at the Tevatron

  8. Modern analysis of ion channeling data by Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)

    2005-10-15

    Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.

  9. Importance estimation in Monte Carlo modelling of neutron and photon transport

    International Nuclear Information System (INIS)

    Mickael, M.W.

    1992-01-01

    The estimation of neutron and photon importance in a three-dimensional geometry is achieved using a coupled Monte Carlo and diffusion theory calculation. The parameters required for the solution of the multigroup adjoint diffusion equation are estimated from an analog Monte Carlo simulation of the system under investigation. The solution of the adjoint diffusion equation is then used as an estimate of the particle importance in the actual simulation. This approach provides an automated and efficient variance reduction method for Monte Carlo simulations. The technique has been successfully applied to Monte Carlo simulation of neutron and coupled neutron-photon transport in the nuclear well-logging field. The results show that the importance maps obtained in a few minutes of computer time using this technique are in good agreement with Monte Carlo generated importance maps that require prohibitive computing times. The application of this method to Monte Carlo modelling of the response of neutron porosity and pulsed neutron instruments has resulted in major reductions in computation time. (Author)

  10. Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Roberto S. Flowers-Cano

    2018-02-01

    Full Text Available Design of hydraulic works requires the estimation of design hydrological events by statistical inference from a probability distribution. Using Monte Carlo simulations, we compared coverage of confidence intervals constructed with four bootstrap techniques: percentile bootstrap (BP, bias-corrected bootstrap (BC, accelerated bias-corrected bootstrap (BCA and a modified version of the standard bootstrap (MSB. Different simulation scenarios were analyzed. In some cases, the mother distribution function was fit to the random samples that were generated. In other cases, a distribution function different to the mother distribution was fit to the samples. When the fitted distribution had three parameters, and was the same as the mother distribution, the intervals constructed with the four techniques had acceptable coverage. However, the bootstrap techniques failed in several of the cases in which the fitted distribution had two parameters.

  11. Advances in Monte Carlo electron transport

    International Nuclear Information System (INIS)

    Bielajew, Alex F.

    1995-01-01

    Notwithstanding the success of Monte Carlo (MC) calculations for determining ion chamber correction factors for air-kerma standards and radiotherapy applications, a great challenge remains. MC is unable to calculate ion chamber response to better than 1% for low-Z and 3% for high-Z wall materials. Moreover, the two major MC code systems employed in radiation dosimetry, the EGS and ITS codes, differ in opposite directions from ion chamber experiments. The discrepancy with experiment is due to inadequacies in the underlying e - condensed-history algorithms. As modeled by MC calculations, the e - step-lengths in the chamber walls and the ionisation cavity differ in terms of material traversed by about three orders of magnitude. This demands that the underlying e - transport algorithms be very stable over a great dynamic range. Otherwise a spurious e - disequilibrium may be generated. The multiple-scattering (MS) algorithms, Moliere in the case of EGS and Goudsmit-Saunderson (GS) in the case of ITS, are either mathematically or numerically unstable in the plural-scattering environment of the ionisation cavity. Recently, a new MS theory has been developed that is an exact solution of the Wentzel small-angle formalism using a screened Rutherford cross section. This new MS theory is mathematically, physically and numerically stable from the no-scattering to the MS regimes. This theory is the small-angle equivalent of the GS equation for a Rutherford cross section. Large-angle corrections connecting this theory to GS theory have been derived by Bethe. The Moliere theory is the large-pathlength limit of this theory. The strategy for employing this new theory for ion chamber and radiotherapy calculations is described

  12. Monte carlo sampling of fission multiplicity.

    Energy Technology Data Exchange (ETDEWEB)

    Hendricks, J. S. (John S.)

    2004-01-01

    Two new methods have been developed for fission multiplicity modeling in Monte Carlo calculations. The traditional method of sampling neutron multiplicity from fission is to sample the number of neutrons above or below the average. For example, if there are 2.7 neutrons per fission, three would be chosen 70% of the time and two would be chosen 30% of the time. For many applications, particularly {sup 3}He coincidence counting, a better estimate of the true number of neutrons per fission is required. Generally, this number is estimated by sampling a Gaussian distribution about the average. However, because the tail of the Gaussian distribution is negative and negative neutrons cannot be produced, a slight positive bias can be found in the average value. For criticality calculations, the result of rejecting the negative neutrons is an increase in k{sub eff} of 0.1% in some cases. For spontaneous fission, where the average number of neutrons emitted from fission is low, the error also can be unacceptably large. If the Gaussian width approaches the average number of fissions, 10% too many fission neutrons are produced by not treating the negative Gaussian tail adequately. The first method to treat the Gaussian tail is to determine a correction offset, which then is subtracted from all sampled values of the number of neutrons produced. This offset depends on the average value for any given fission at any energy and must be computed efficiently at each fission from the non-integrable error function. The second method is to determine a corrected zero point so that all neutrons sampled between zero and the corrected zero point are killed to compensate for the negative Gaussian tail bias. Again, the zero point must be computed efficiently at each fission. Both methods give excellent results with a negligible computing time penalty. It is now possible to include the full effects of fission multiplicity without the negative Gaussian tail bias.

  13. Monte Carlo Volcano Seismic Moment Tensors

    Science.gov (United States)

    Waite, G. P.; Brill, K. A.; Lanza, F.

    2015-12-01

    Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.

  14. Non-Boltzmann Ensembles and Monte Carlo Simulations

    International Nuclear Information System (INIS)

    Murthy, K. P. N.

    2016-01-01

    Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc . This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g ( E , M ), as a function of both energy E , and order parameter M . This is carried out in two stages. We estimate g ( E ) in the first stage

  15. Mean field theory of the swap Monte Carlo algorithm.

    Science.gov (United States)

    Ikeda, Harukuni; Zamponi, Francesco; Ikeda, Atsushi

    2017-12-21

    The swap Monte Carlo algorithm combines the translational motion with the exchange of particle species and is unprecedentedly efficient for some models of glass former. In order to clarify the physics underlying this acceleration, we study the problem within the mean field replica liquid theory. We extend the Gaussian Ansatz so as to take into account the exchange of particles of different species, and we calculate analytically the dynamical glass transition points corresponding to the swap and standard Monte Carlo algorithms. We show that the system evolved with the standard Monte Carlo algorithm exhibits the dynamical transition before that of the swap Monte Carlo algorithm. We also test the result by performing computer simulations of a binary mixture of the Mari-Kurchan model, both with standard and swap Monte Carlo. This scenario provides a possible explanation for the efficiency of the swap Monte Carlo algorithm. Finally, we discuss how the thermodynamic theory of the glass transition should be modified based on our results.

  16. McSCIA: application of the equivalence theorem in a Monte Carlo radiative transfer model for spherical shell

    NARCIS (Netherlands)

    Spada, F.M.; Krol, M.C.; Stammes, P.

    2006-01-01

    A new multiple-scattering Monte Carlo 3-D radiative transfer model named McSCIA (Monte Carlo for SCIAmachy) is presented. The backward technique is used to efficiently simulate narrow field of view instruments. The McSCIA algorithm has been formulated as a function of the Earth’s radius, and can

  17. McSCIA: application of the equivalence theorem in a Monte Carlo radiative transfer model for spherical shell atmospheres

    NARCIS (Netherlands)

    Spada, F.; Krol, M.C.; Stammes, P.

    2006-01-01

    A new multiple-scatteringMonte Carlo 3-D radiative transfer model named McSCIA (Monte Carlo for SCIA-machy) is presented. The backward technique is used to efficiently simulate narrow field of view instruments. The McSCIA algorithm has been formulated as a function of the Earth's radius, and can

  18. On Monte Carlo Simulation and Analysis of Electricity Markets

    International Nuclear Information System (INIS)

    Amelin, Mikael

    2004-07-01

    This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models

  19. Monte Carlo Simulations Validation Study: Vascular Brachytherapy Beta Sources

    International Nuclear Information System (INIS)

    Orion, I.; Koren, K.

    2004-01-01

    During the last decade many versions of angioplasty irradiation treatments have been proposed. The purpose of this unique brachytherapy is to administer a sufficient radiation dose into the vein walls in order to prevent restonosis, a clinical sequel to balloon angioplasty. The most suitable sources for this vascular brachytherapy are the β - emitters such as Re-188, P-32, and Sr-90/Y-90, with a maximum energy range of up to 2.1 MeV [1,2,3]. The radioactive catheters configurations offered for these treatments can be a simple wire [4], a fluid filled balloon or a coated stent. Each source is differently positioned inside the blood vessel, and the emitted electrons ranges therefore vary. Many types of sources and configurations were studied either experimentally or with the use of the Monte Carlo calculation technique, while most of the Monte Carlo simulations were carried out using EGS4 [5] or MCNP [6]. In this study we compared the beta-source absorbed-dose versus radial-distance of two treatment configurations using MCNP and EGS4 simulations. This comparison was aimed to discover the differences between the MCNP and the EGS4 simulation code systems in intermediate energies electron transport

  20. The ATLAS Fast Monte Carlo Production Chain Project

    Science.gov (United States)

    Jansky, Roland

    2015-12-01

    During the last years ATLAS has successfully deployed a new integrated simulation framework (ISF) which allows a flexible mixture of full and fast detector simulation techniques within the processing of one event. The thereby achieved possible speed-up in detector simulation of up to a factor 100 makes subsequent digitization and reconstruction the dominant contributions to the Monte Carlo (MC) production CPU cost. The slowest components of both digitization and reconstruction are inside the Inner Detector due to the complex signal modeling needed in the emulation of the detector readout and in reconstruction due to the combinatorial nature of the problem to solve, respectively. Alternative fast approaches have been developed for these components: for the silicon based detectors a simpler geometrical clustering approach has been deployed replacing the charge drift emulation in the standard digitization modules, which achieves a very high accuracy in describing the standard output. For the Inner Detector track reconstruction, a Monte Carlo generator information based trajectory building has been deployed with the aim of bypassing the CPU intensive pattern recognition. Together with the ISF all components have been integrated into a new fast MC production chain, aiming to produce fast MC simulated data with sufficient agreement with fully simulated and reconstructed data at a processing time of seconds per event, compared to several minutes for full simulation.

  1. Efficient Monte Carlo Simulations of Gas Molecules Inside Porous Materials.

    Science.gov (United States)

    Kim, Jihan; Smit, Berend

    2012-07-10

    Monte Carlo (MC) simulations are commonly used to obtain adsorption properties of gas molecules inside porous materials. In this work, we discuss various optimization strategies that lead to faster MC simulations with CO2 gas molecules inside host zeolite structures used as a test system. The reciprocal space contribution of the gas-gas Ewald summation and both the direct and the reciprocal gas-host potential energy interactions are stored inside energy grids to reduce the wall time in the MC simulations. Additional speedup can be obtained by selectively calling the routine that computes the gas-gas Ewald summation, which does not impact the accuracy of the zeolite's adsorption characteristics. We utilize two-level density-biased sampling technique in the grand canonical Monte Carlo (GCMC) algorithm to restrict CO2 insertion moves into low-energy regions within the zeolite materials to accelerate convergence. Finally, we make use of the graphics processing units (GPUs) hardware to conduct multiple MC simulations in parallel via judiciously mapping the GPU threads to available workload. As a result, we can obtain a CO2 adsorption isotherm curve with 14 pressure values (up to 10 atm) for a zeolite structure within a minute of total compute wall time.

  2. KAMCCO, a reactor physics Monte Carlo neutron transport code

    International Nuclear Information System (INIS)

    Arnecke, G.; Borgwaldt, H.; Brandl, V.; Lalovic, M.

    1976-06-01

    KAMCCO is a 3-dimensional reactor Monte Carlo code for fast neutron physics problems. Two options are available for the solution of 1) the inhomogeneous time-dependent neutron transport equation (census time scheme), and 2) the homogeneous static neutron transport equation (generation cycle scheme). The user defines the desired output, e.g. estimates of reaction rates or neutron flux integrated over specified volumes in phase space and time intervals. Such primary quantities can be arbitrarily combined, also ratios of these quantities can be estimated with their errors. The Monte Carlo techniques are mostly analogue (exceptions: Importance sampling for collision processes, ELP/MELP, Russian roulette and splitting). Estimates are obtained from the collision and track length estimators. Elastic scattering takes into account first order anisotropy in the center of mass system. Inelastic scattering is processed via the evaporation model or via the excitation of discrete levels. For the calculation of cross sections, the energy is treated as a continuous variable. They are computed by a) linear interpolation, b) from optionally Doppler broadened single level Breit-Wigner resonances or c) from probability tables (in the region of statistically distributed resonances). (orig.) [de

  3. Monte Carlo simulations of quantum systems on massively parallel supercomputers

    International Nuclear Information System (INIS)

    Ding, H.Q.

    1993-01-01

    A large class of quantum physics applications uses operator representations that are discrete integers by nature. This class includes magnetic properties of solids, interacting bosons modeling superfluids and Cooper pairs in superconductors, and Hubbard models for strongly correlated electrons systems. This kind of application typically uses integer data representations and the resulting algorithms are dominated entirely by integer operations. The authors implemented an efficient algorithm for one such application on the Intel Touchstone Delta and iPSC/860. The algorithm uses a multispin coding technique which allows significant data compactification and efficient vectorization of Monte Carlo updates. The algorithm regularly switches between two data decompositions, corresponding naturally to different Monte Carlo updating processes and observable measurements such that only nearest-neighbor communications are needed within a given decomposition. On 128 nodes of Intel Delta, this algorithm updates 183 million spins per second (compared to 21 million on CM-2 and 6.2 million on a Cray Y-MP). A systematic performance analysis shows a better than 90% efficiency in the parallel implementation

  4. Approximate zero-variance Monte Carlo estimation of Markovian unreliability

    International Nuclear Information System (INIS)

    Delcoux, J.L.; Labeau, P.E.; Devooght, J.

    1997-01-01

    Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

  5. Testing random number generators for Monte Carlo applications

    International Nuclear Information System (INIS)

    Sim, L.H.

    1992-01-01

    Central to any system for modelling radiation transport phenomena using Monte Carlo techniques is the method by which pseudo random numbers are generated. This method is commonly referred to as the Random Number Generator (RNG). It is usually a computer implemented mathematical algorithm which produces a series of numbers uniformly distributed on the interval [0,1]. If this series satisfies certain statistical tests for randomness, then for practical purposes the pseudo random numbers in the series can be considered to be random. Tests of this nature are important not only for new RNGs but also to test the implementation of known RNG algorithms in different computer environments. Six RNGs have been tested using six statistical tests and one visual test. The statistical tests are the moments, frequency (digit and number), serial, gap, and poker tests. The visual test is a simple two dimensional ordered pair display. In addition the RNGs have been tested in a specific Monte Carlo application. This type of test is often overlooked, however it is important that in addition to satisfactory performance in statistical tests, the RNG be able to perform effectively in the applications of interest. The RNGs tested here are based on a variety of algorithms, including multiplicative and linear congruential, lagged Fibonacci, and combination arithmetic and lagged Fibonacci. The effect of the Bays-Durham shuffling algorithm on the output of a known bad RNG has also been investigated. 18 refs., 11 tabs., 4 figs. of

  6. Monte Carlo source convergence and the Whitesides problem

    International Nuclear Information System (INIS)

    Blomquist, R. N.

    2000-01-01

    The issue of fission source convergence in Monte Carlo eigenvalue calculations is of interest because of the potential consequences of erroneous criticality safety calculations. In this work, the authors compare two different techniques to improve the source convergence behavior of standard Monte Carlo calculations applied to challenging source convergence problems. The first method, super-history powering, attempts to avoid discarding important fission sites between generations by delaying stochastic sampling of the fission site bank until after several generations of multiplication. The second method, stratified sampling of the fission site bank, explicitly keeps the important sites even if conventional sampling would have eliminated them. The test problems are variants of Whitesides' Criticality of the World problem in which the fission site phase space was intentionally undersampled in order to induce marginally intolerable variability in local fission site populations. Three variants of the problem were studied, each with a different degree of coupling between fissionable pieces. Both the superhistory powering method and the stratified sampling method were shown to improve convergence behavior, although stratified sampling is more robust for the extreme case of no coupling. Neither algorithm completely eliminates the loss of the most important fissionable piece, and if coupling is absent, the lost piece cannot be recovered unless its sites from earlier generations have been retained. Finally, criteria for measuring source convergence reliability are proposed and applied to the test problems

  7. Monte Carlo modeling of human tooth optical coherence tomography imaging

    International Nuclear Information System (INIS)

    Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen

    2013-01-01

    We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth. (paper)

  8. Monte Carlo modeling of human tooth optical coherence tomography imaging

    Science.gov (United States)

    Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen

    2013-07-01

    We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth.

  9. Characteristics of miniature electronic brachytherapy x-ray sources based on TG-43U1 formalism using Monte Carlo simulation techniques

    International Nuclear Information System (INIS)

    Safigholi, Habib; Faghihi, Reza; Jashni, Somaye Karimi; Meigooni, Ali S.

    2012-01-01

    Purpose: The goal of this study is to determine a method for Monte Carlo (MC) characterization of the miniature electronic brachytherapy x-ray sources (MEBXS) and to set dosimetric parameters according to TG-43U1 formalism. TG-43U1 parameters were used to get optimal designs of MEBXS. Parameters that affect the dose distribution such as anode shapes, target thickness, target angles, and electron beam source characteristics were evaluated. Optimized MEBXS designs were obtained and used to determine radial dose functions and 2D anisotropy functions in the electron energy range of 25-80 keV. Methods: Tungsten anode material was considered in two different geometries, hemispherical and conical-hemisphere. These configurations were analyzed by the 4C MC code with several different optimization techniques. The first optimization compared target thickness layers versus electron energy. These optimized thicknesses were compared with published results by Ihsan et al.[Nucl. Instrum. Methods Phys. Res. B 264, 371-377 (2007)]. The second optimization evaluated electron source characteristics by changing the cathode shapes and electron energies. Electron sources studied included; (1) point sources, (2) uniform cylinders, and (3) nonuniform cylindrical shell geometries. The third optimization was used to assess the apex angle of the conical-hemisphere target. The goal of these optimizations was to produce 2D-dose anisotropy functions closer to unity. An overall optimized MEBXS was developed from this analysis. The results obtained from this model were compared to known characteristics of HDR 125 I, LDR 103 Pd, and Xoft Axxent electronic brachytherapy source (XAEBS) [Med. Phys. 33, 4020-4032 (2006)]. Results: The optimized anode thicknesses as a function of electron energy is fitted by the linear equation Y (μm) = 0.0459X (keV)-0.7342. The optimized electron source geometry is obtained for a disk-shaped parallel beam (uniform cylinder) with 0.9 mm radius. The TG-43 distribution

  10. Monte Carlo systems used for treatment planning and dose verification

    Energy Technology Data Exchange (ETDEWEB)

    Brualla, Lorenzo [Universitaetsklinikum Essen, NCTeam, Strahlenklinik, Essen (Germany); Rodriguez, Miguel [Centro Medico Paitilla, Balboa (Panama); Lallena, Antonio M. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain)

    2017-04-15

    General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations. (orig.) [German] Seit mehreren Jahrzehnten werden allgemein anwendbare Monte-Carlo-Codes zur Simulation des Strahlungstransports benutzt, um die Verteilung der absorbierten Dosis in der perkutanen Strahlentherapie mit Photonen und Elektronen zu evaluieren. Die damit erzielten Ergebnisse sind meist akkurater als solche, die mit nichtstochastischen Methoden herkoemmlicher Bestrahlungsplanungssysteme erzielt werden koennen. Wegen des damit verbundenen Arbeitsaufwands und der langen Dauer der Berechnungen wurden Monte-Carlo-Simulationen von Dosisverteilungen in der konventionellen Strahlentherapie in der Vergangenheit im Wesentlichen in der Forschung eingesetzt. Im Bemuehen, Monte-Carlo

  11. First validation of the new continuous energy version of the MORET5 Monte Carlo code

    International Nuclear Information System (INIS)

    Miss, Joachim; Bernard, Franck; Forestier, Benoit; Haeck, Wim; Richet, Yann; Jacquet, Olivier

    2008-01-01

    The 5.A.1 version is the next release of the MORET Monte Carlo code dedicated to criticality and reactor calculations. This new version combines all the capabilities that are already available in the multigroup version with many new and enhanced features. The main capabilities of the previous version are the powerful association of a deterministic and Monte Carlo approach (like for instance APOLLO-MORET), the modular geometry, five source sampling techniques and two simulation strategies. The major advance in MORET5 is the ability to perform calculations either a multigroup or a continuous energy simulation. Thanks to these new developments, we now have better control over the whole process of criticality calculations, from reading the basic nuclear data to the Monte Carlo simulation itself. Moreover, this new capability enables us to better validate the deterministic-Monte Carlo multigroup calculations by performing continuous energy calculations with the same code, using the same geometry and tracking algorithms. The aim of this paper is to describe the main options available in this new release, and to present the first results. Comparisons of the MORET5 continuous-energy results with experimental measurements and against another continuous-energy Monte Carlo code are provided in terms of validation and time performance. Finally, an analysis of the interest of using a unified energy grid for continuous energy Monte Carlo calculations is presented. (authors)

  12. Monte-Carlo simulation of a stochastic differential equation

    Science.gov (United States)

    Arif, ULLAH; Majid, KHAN; M, KAMRAN; R, KHAN; Zhengmao, SHENG

    2017-12-01

    For solving higher dimensional diffusion equations with an inhomogeneous diffusion coefficient, Monte Carlo (MC) techniques are considered to be more effective than other algorithms, such as finite element method or finite difference method. The inhomogeneity of diffusion coefficient strongly limits the use of different numerical techniques. For better convergence, methods with higher orders have been kept forward to allow MC codes with large step size. The main focus of this work is to look for operators that can produce converging results for large step sizes. As a first step, our comparative analysis has been applied to a general stochastic problem. Subsequently, our formulization is applied to the problem of pitch angle scattering resulting from Coulomb collisions of charge particles in the toroidal devices.

  13. Continuous-time quantum Monte Carlo impurity solvers

    Science.gov (United States)

    Gull, Emanuel; Werner, Philipp; Fuchs, Sebastian; Surer, Brigitte; Pruschke, Thomas; Troyer, Matthias

    2011-04-01

    Continuous-time quantum Monte Carlo impurity solvers are algorithms that sample the partition function of an impurity model using diagrammatic Monte Carlo techniques. The present paper describes codes that implement the interaction expansion algorithm originally developed by Rubtsov, Savkin, and Lichtenstein, as well as the hybridization expansion method developed by Werner, Millis, Troyer, et al. These impurity solvers are part of the ALPS-DMFT application package and are accompanied by an implementation of dynamical mean-field self-consistency equations for (single orbital single site) dynamical mean-field problems with arbitrary densities of states. Program summaryProgram title: dmft Catalogue identifier: AEIL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: ALPS LIBRARY LICENSE version 1.1 No. of lines in distributed program, including test data, etc.: 899 806 No. of bytes in distributed program, including test data, etc.: 32 153 916 Distribution format: tar.gz Programming language: C++ Operating system: The ALPS libraries have been tested on the following platforms and compilers: Linux with GNU Compiler Collection (g++ version 3.1 and higher), and Intel C++ Compiler (icc version 7.0 and higher) MacOS X with GNU Compiler (g++ Apple-version 3.1, 3.3 and 4.0) IBM AIX with Visual Age C++ (xlC version 6.0) and GNU (g++ version 3.1 and higher) compilers Compaq Tru64 UNIX with Compq C++ Compiler (cxx) SGI IRIX with MIPSpro C++ Compiler (CC) HP-UX with HP C++ Compiler (aCC) Windows with Cygwin or coLinux platforms and GNU Compiler Collection (g++ version 3.1 and higher) RAM: 10 MB-1 GB Classification: 7.3 External routines: ALPS [1], BLAS/LAPACK, HDF5 Nature of problem: (See [2].) Quantum impurity models describe an atom or molecule embedded in a host material with which it can exchange electrons. They are basic to nanoscience as

  14. Nonlinear Spatial Inversion Without Monte Carlo Sampling

    Science.gov (United States)

    Curtis, A.; Nawaz, A.

    2017-12-01

    High-dimensional, nonlinear inverse or inference problems usually have non-unique solutions. The distribution of solutions are described by probability distributions, and these are usually found using Monte Carlo (MC) sampling methods. These take pseudo-random samples of models in parameter space, calculate the probability of each sample given available data and other information, and thus map out high or low probability values of model parameters. However, such methods would converge to the solution only as the number of samples tends to infinity; in practice, MC is found to be slow to converge, convergence is not guaranteed to be achieved in finite time, and detection of convergence requires the use of subjective criteria. We propose a method for Bayesian inversion of categorical variables such as geological facies or rock types in spatial problems, which requires no sampling at all. The method uses a 2-D Hidden Markov Model over a grid of cells, where observations represent localized data constraining the model in each cell. The data in our example application are seismic properties such as P- and S-wave impedances or rock density; our model parameters are the hidden states and represent the geological rock types in each cell. The observations at each location are assumed to depend on the facies at that location only - an assumption referred to as `localized likelihoods'. However, the facies at a location cannot be determined solely by the observation at that location as it also depends on prior information concerning its correlation with the spatial distribution of facies elsewhere. Such prior information is included in the inversion in the form of a training image which represents a conceptual depiction of the distribution of local geologies that might be expected, but other forms of prior information can be used in the method as desired. The method provides direct (pseudo-analytic) estimates of posterior marginal probability distributions over each variable

  15. Copper precipitation in iron: a comparison between metropolis Monte Carlo and lattice kinetic Monte Carlo methods

    CERN Document Server

    Khrushcheva, O; Malerba, L; Becquart, C S; Domain, C; Hou, M

    2003-01-01

    Several variants are possible in the suite of programs forming multiscale predictive tools to estimate the yield strength increase caused by irradiation in RPV steels. For instance, at the atomic scale, both the Metropolis and the lattice kinetic Monte Carlo methods (MMC and LKMC respectively) allow predicting copper precipitation under irradiation conditions. Since these methods are based on different physical models, the present contribution discusses their consistency on the basis of a realistic case study. A cascade debris in iron containing 0.2% of copper was modelled by molecular dynamics with the DYMOKA code, which is part of the REVE suite. We use this debris as input for both the MMC and the LKMC simulations. Thermal motion and lattice relaxation can be avoided in the MMC, making the model closer to the LKMC (LMMC method). The predictions and the complementarity of the three methods for modelling the same phenomenon are then discussed.

  16. Characterizing the Trade Space Between Capability and Complexity in Next Generation Cloud and Precipitation Observing Systems Using Markov Chain Monte Carlos Techniques

    Science.gov (United States)

    Xu, Z.; Mace, G. G.; Posselt, D. J.

    2017-12-01

    As we begin to contemplate the next generation atmospheric observing systems, it will be critically important that we are able to make informed decisions regarding the trade space between scientific capability and the need to keep complexity and cost within definable limits. To explore this trade space as it pertains to understanding key cloud and precipitation processes, we are developing a Markov Chain Monte Carlo (MCMC) algorithm suite that allows us to arbitrarily define the specifications of candidate observing systems and then explore how the uncertainties in key retrieved geophysical parameters respond to that observing system. MCMC algorithms produce a more complete posterior solution space, and allow for an objective examination of information contained in measurements. In our initial implementation, MCMC experiments are performed to retrieve vertical profiles of cloud and precipitation properties from a spectrum of active and passive measurements collected by aircraft during the ACE Radiation Definition Experiments (RADEX). Focusing on shallow cumulus clouds observed during the Integrated Precipitation and Hydrology EXperiment (IPHEX), observing systems in this study we consider W and Ka-band radar reflectivity, path-integrated attenuation at those frequencies, 31 and 94 GHz brightness temperatures as well as visible and near-infrared reflectance. By varying the sensitivity and uncertainty of these measurements, we quantify the capacity of various combinations of observations to characterize the physical properties of clouds and precipitation.

  17. New Product Development in an Emerging Economy: Analysing the Role of Supplier Involvement Practices by Using Bayesian Markov Chain Monte Carlo Technique

    Directory of Open Access Journals (Sweden)

    Kanagi Kanapathy

    2014-01-01

    Full Text Available The research question is whether the positive relationship found between supplier involvement practices and new product development performances in developed economies also holds in emerging economies. The role of supplier involvement practices in new product development performance is yet to be substantially investigated in the emerging economies (other than China. This premise was examined by distributing a survey instrument (Jayaram’s (2008 published survey instrument that has been utilised in developed economies to Malaysian manufacturing companies. To gauge the relationship between the supplier involvement practices and new product development (NPD project performance of 146 companies, structural equation modelling was adopted. Our findings prove that supplier involvement practices have a significant positive impact on NPD project performance in an emerging economy with respect to quality objectives, design objectives, cost objectives, and “time-to-market” objectives. Further analysis using the Bayesian Markov Chain Monte Carlo algorithm, yielding a more credible and feasible differentiation, confirmed these results (even in the case of an emerging economy and indicated that these practices have a 28% impact on variance of NPD project performance. This considerable effect implies that supplier involvement is a must have, although further research is needed to identify the contingencies for its practices.

  18. Numerical integration of detector response functions via Monte Carlo simulations

    Science.gov (United States)

    Kelly, K. J.; O'Donnell, J. M.; Gomez, J. A.; Taddeucci, T. N.; Devlin, M.; Haight, R. C.; White, M. C.; Mosby, S. M.; Neudecker, D.; Buckner, M. Q.; Wu, C. Y.; Lee, H. Y.

    2017-09-01

    Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated in this way can be used to create Monte Carlo simulation output spectra a factor of ∼ 1000 × faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. This method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.

  19. Monte Carlo studies of high-transverse-energy hadronic interactions

    International Nuclear Information System (INIS)

    Corcoran, M.D.

    1985-01-01

    A four-jet Monte Carlo calculation has been used to simulate hadron-hadron interactions which deposit high transverse energy into a large-solid-angle calorimeter and limited solid-angle regions of the calorimeter. The calculation uses first-order QCD cross sections to generate two scattered jets and also produces beam and target jets. Field-Feynman fragmentation has been used in the hadronization. The sensitivity of the results to a few features of the Monte Carlo program has been studied. The results are found to be very sensitive to the method used to ensure overall energy conservation after the fragmentation of the four jets is complete. Results are also sensitive to the minimum momentum transfer in the QCD subprocesses and to the distribution of p/sub T/ to the jet axis and the multiplicities in the fragmentation. With reasonable choices of these features of the Monte Carlo program, good agreement with data at Fermilab/CERN SPS energies is obtained, comparable to the agreement achieved with more sophisticated parton-shower models. With other choices, however, the calculation gives qualitatively different results which are in strong disagreement with the data. These results have important implications for extracting physics conclusions from Monte Carlo calculations. It is not possible to test the validity of a particular model or distinguish between different models unless the Monte Carlo results are unambiguous and different models exhibit clearly different behavior

  20. Monte Carlo capabilities of the SCALE code system

    International Nuclear Information System (INIS)

    Rearden, B.T.; Petrie, L.M.; Peplow, D.E.; Bekar, K.B.; Wiarda, D.; Celik, C.; Perfetti, C.M.; Ibrahim, A.M.; Hart, S.W.D.; Dunn, M.E.; Marshall, W.J.

    2015-01-01

    Highlights: • Foundational Monte Carlo capabilities of SCALE are described. • Improvements in continuous-energy treatments are detailed. • New methods for problem-dependent temperature corrections are described. • New methods for sensitivity analysis and depletion are described. • Nuclear data, users interfaces, and quality assurance activities are summarized. - Abstract: SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2

  1. Parallel MCNP Monte Carlo transport calculations with MPI

    International Nuclear Information System (INIS)

    Wagner, J.C.; Haghighat, A.

    1996-01-01

    The steady increase in computational performance has made Monte Carlo calculations for large/complex systems possible. However, in order to make these calculations practical, order of magnitude increases in performance are necessary. The Monte Carlo method is inherently parallel (particles are simulated independently) and thus has the potential for near-linear speedup with respect to the number of processors. Further, the ever-increasing accessibility of parallel computers, such as workstation clusters, facilitates the practical use of parallel Monte Carlo. Recognizing the nature of the Monte Carlo method and the trends in available computing, the code developers at Los Alamos National Laboratory implemented the message-passing general-purpose Monte Carlo radiation transport code MCNP (version 4A). The PVM package was chosen by the MCNP code developers because it supports a variety of communication networks, several UNIX platforms, and heterogeneous computer systems. This PVM version of MCNP has been shown to produce speedups that approach the number of processors and thus, is a very useful tool for transport analysis. Due to software incompatibilities on the local IBM SP2, PVM has not been available, and thus it is not possible to take advantage of this useful tool. Hence, it became necessary to implement an alternative message-passing library package into MCNP. Because the message-passing interface (MPI) is supported on the local system, takes advantage of the high-speed communication switches in the SP2, and is considered to be the emerging standard, it was selected

  2. Study on random number generator in Monte Carlo code

    International Nuclear Information System (INIS)

    Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi

    2011-01-01

    The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)

  3. ALEPH 1.1.2: A Monte Carlo burn-up code

    International Nuclear Information System (INIS)

    Haeck, W.; Verboomen, B.

    2006-01-01

    In the last 40 years, Monte Carlo particle transport has been applied to a multitude of problems such as shielding and medical applications, to various types of nuclear reactors, . . . The success of the Monte Carlo method is mainly based on its broad application area, on its ability to handle nuclear data not only in its most basic but also most complex form (namely continuous energy cross sections, complex interaction laws, detailed energy-angle correlations, multi-particle physics, . . . ), on its capability of modeling geometries from simple 1D to complex 3D, . . . There is also a current trend in Monte Carlo applications toward high detail 3D calculations (for instance voxel-based medical applications), something for which deterministic codes are neither suited nor performant as to computational time and precision. Apart from all these fields where Monte Carlo particle transport has been applied successfully, there is at least one area where Monte Carlo has had limited success, namely burn-up and activation calculations where the time parameter is added to the problem. The concept of Monte Carlo burn-up consists of coupling a Monte Carlo code to a burn-up module to improve the accuracy of depletion and activation calculations. For every time step the Monte Carlo code will provide reaction rates to the burn-up module which will return new material compositions to the Monte Carlo code. So if static Monte Carlo particle transport is slow, then Monte Carlo particle transport with burn-up will be even slower as calculations have to be performed for every time step in the problem. The computational issues to perform accurate Monte Carlo calculations are however continuously reduced due to improvements made in the basic Monte Carlo algorithms, due to the development of variance reduction techniques and due to developments in computer architecture (more powerful processors, the so-called brute force approach through parallel processors and networked systems

  4. Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods

    Science.gov (United States)

    Ralph, Jason F.; Maskell, Simon; Jacobs, Kurt

    2017-11-01

    This paper proposes an efficient method for the simultaneous estimation of the state of a quantum system and the classical parameters that govern its evolution. This hybrid approach benefits from efficient numerical methods for the integration of stochastic master equations for the quantum system, and efficient parameter estimation methods from classical signal processing. The classical techniques use sequential Monte Carlo (SMC) methods, which aim to optimize the selection of points within the parameter space, conditioned by the measurement data obtained. We illustrate these methods using a specific example, an SMC sampler applied to a nonlinear system, the Duffing oscillator, where the evolution of the quantum state of the oscillator and three Hamiltonian parameters are estimated simultaneously.

  5. Treatment planning in radiosurgery: parallel Monte Carlo simulation software

    Energy Technology Data Exchange (ETDEWEB)

    Scielzo, G. [Galliera Hospitals, Genova (Italy). Dept. of Hospital Physics; Grillo Ruggieri, F. [Galliera Hospitals, Genova (Italy) Dept. for Radiation Therapy; Modesti, M.; Felici, R. [Electronic Data System, Rome (Italy); Surridge, M. [University of South Hampton (United Kingdom). Parallel Apllication Centre

    1995-12-01

    The main objective of this research was to evaluate the possibility of direct Monte Carlo simulation for accurate dosimetry with short computation time. We made us of: graphics workstation, linear accelerator, water, PMMA and anthropomorphic phantoms, for validation purposes; ionometric, film and thermo-luminescent techniques, for dosimetry; treatment planning system for comparison. Benchmarking results suggest that short computing times can be obtained with use of the parallel version of EGS4 that was developed. Parallelism was obtained assigning simulation incident photons to separate processors, and the development of a parallel random number generator was necessary. Validation consisted in: phantom irradiation, comparison of predicted and measured values good agreement in PDD and dose profiles. Experiments on anthropomorphic phantoms (with inhomogeneities) were carried out, and these values are being compared with results obtained with the conventional treatment planning system.

  6. RMC - A Monte Carlo Code for Reactor Core Analysis

    Science.gov (United States)

    Wang, Kan; Li, Zeguang; She, Ding; Liang, Jin'gang; Xu, Qi; Qiu, Yishu; Yu, Jiankai; Sun, Jialong; Fan, Xiao; Yu, Ganglin

    2014-06-01

    A new Monte Carlo transport code RMC has been being developed by Department of Engineering Physics, Tsinghua University, Beijing as a tool for reactor core analysis on high-performance computing platforms. To meet the requirements of reactor analysis, RMC now has such functions as criticality calculation, fixed-source calculation, burnup calculation and kinetics simulations. Some techniques for geometry treatment, new burnup algorithm, source convergence acceleration, massive tally and parallel calculation, and temperature dependent cross sections processing are researched and implemented in RMC to improve the effciency. Validation results of criticality calculation, burnup calculation, source convergence acceleration, tallies performance and parallel performance shown in this paper prove the capabilities of RMC in dealing with reactor analysis problems with good performances.

  7. Markov Chain Monte Carlo Bayesian Learning for Neural Networks

    Science.gov (United States)

    Goodrich, Michael S.

    2011-01-01

    Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.

  8. Optimization of reconstruction algorithms using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Hanson, K.M.

    1989-01-01

    A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by an iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a non-negativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. (author)

  9. Simulation of thermochromotographic processes by the Monte-Carlo method

    International Nuclear Information System (INIS)

    Zvara, I.

    1983-01-01

    A simplified microscopic model is proposed for the gas adsorption thermochromatography in open columns with laminar flow of the carrier gas. This model describes the downstream migration of a sample molecule as a rather small number of some effective random displacements and sequences of adsorption-desorption events that occur without changing the coordinates. The relevant probability density distributions are thereby derived. Based on this model, a computer program has been developed for simulating thermochromatographic zone profiles by employing the Monte-Carlo technique. The program is versatile in accounting for a wide range of experimental conditions and for treating various properties of the species to be separated. Some results of these simulations are given to demonstrate the influence of several parameters on the zone profile

  10. The ATLAS Fast Monte Carlo Production Chain Project

    CERN Document Server

    Jansky, Roland Wolfgang; The ATLAS collaboration

    2015-01-01

    During the last years ATLAS has successfully deployed a new integrated simulation framework (ISF) which allows a flexible mixture of full and fast detector simulation techniques within the processing of one event. The thereby achieved possible speed-up in detector simulation of up to a factor 100 makes subsequent digitization and reconstruction the dominant contributions to the Monte Carlo (MC) production CPU cost. The slowest components of both digitization and reconstruction are inside the Inner Detector due to the complex signal modeling needed in the emulation of the detector readout and in reconstruction due to the combinatorial nature of the problem to solve, respectively. Alternative fast approaches have been developed for these components: for the silicon based detectors a simpler geometrical clustering approach has been deployed replacing the charge drift emulation in the standard digitization modules, which achieves a very high accuracy in describing the standard output. For the Inner Detector track...

  11. Reactive Monte Carlo sampling with an ab initio potential

    International Nuclear Information System (INIS)

    Leiding, Jeff; Coe, Joshua D.

    2016-01-01

    We present the first application of reactive Monte Carlo in a first-principles context. The algorithm samples in a modified NVT ensemble in which the volume, temperature, and total number of atoms of a given type are held fixed, but molecular composition is allowed to evolve through stochastic variation of chemical connectivity. We discuss general features of the method, as well as techniques needed to enhance the efficiency of Boltzmann sampling. Finally, we compare the results of simulation of NH 3 to those of ab initio molecular dynamics (AIMD). We find that there are regions of state space for which RxMC sampling is much more efficient than AIMD due to the “rare-event” character of chemical reactions.

  12. Monte Carlo Modeling of Crystal Channeling at High Energies

    CERN Document Server

    Schoofs, Philippe; Cerutti, Francesco

    Charged particles entering a crystal close to some preferred direction can be trapped in the electromagnetic potential well existing between consecutive planes or strings of atoms. This channeling effect can be used to extract beam particles if the crystal is bent beforehand. Crystal channeling is becoming a reliable and efficient technique for collimating beams and removing halo particles. At CERN, the installation of silicon crystals in the LHC is under scrutiny by the UA9 collaboration with the goal of investigating if they are a viable option for the collimation system upgrade. This thesis describes a new Monte Carlo model of planar channeling which has been developed from scratch in order to be implemented in the FLUKA code simulating particle transport and interactions. Crystal channels are described through the concept of continuous potential taking into account thermal motion of the lattice atoms and using Moliere screening function. The energy of the particle transverse motion determines whether or n...

  13. Optical monitoring of rheumatoid arthritis: Monte Carlo generated reconstruction kernels

    Science.gov (United States)

    Minet, O.; Beuthan, J.; Hielscher, A. H.; Zabarylo, U.

    2008-06-01

    Optical imaging in biomedicine is governed by the light absorption and scattering interaction on microscopic and macroscopic constituents in the medium. Therefore, light scattering characteristics of human tissue correlate with the stage of some diseases. In the near infrared range the scattering event with the coefficient approximately two orders of magnitude greater than absorption plays a dominant role. When measuring the optical parameters variations were discovered that correlate with the rheumatoid arthritis of a small joint. The potential of an experimental setup for transillumination the finger joint with a laser diode and the pattern of the stray light detection are demonstrated. The scattering caused by skin contains no useful information and it can be removed by a deconvolution technique to enhance the diagnostic value of this non-invasive optical method. Monte Carlo simulations ensure both the construction of the corresponding point spread function and both the theoretical verification of the stray light picture in rather complex geometry.

  14. Monte Carlo simulation of electron swarms in H2

    International Nuclear Information System (INIS)

    Hunter, S.R.

    1977-01-01

    A Monte Carlo simulation of the motion of an electron swarm in molecular hydrogen has been studied in the range E/N 1.4-170 Td. The simulation was performed for 400-600 electrons at several values of E/N for two different sets of inelastic collision cross sections at high E/N. Results were obtained for the longitudinal diffusion coefficient Dsub(L), lateral diffusion coefficient D, swarm drift velocity W, average swarm energy and ionization and excitation production coefficients, and these were compared with experimental data where available. It is found that the results differ significantly from the experimental values and this is attributed to the isotropic scattering model used in this work. However, the results lend support to the experimental technique used recently by Blevin et al. to determine these transport parameters, and in particular confirm their results that Dsub(L) > D at high values of E/N. (Author)

  15. Diagrammatic Monte Carlo method as applied to the polaron problems

    International Nuclear Information System (INIS)

    Mishchenko, Andrei S

    2005-01-01

    Numerical methods whereby exact solutions to the problem of a few particles interacting with one another and with several bosonic excitation branches are presented. The diagrammatic Monte Carlo method allows the exact calculation of the Matsubara Green function, and the stochastic optimization technique provides an approximation-free analytic continuation. In this review, results unobtainable by conventional methods are discussed, including the properties of excited states in the self-trapping phenomenon, the optical spectra of polarons in all coupling regimes, the validity range analysis of the Frenkel and Wannier approximations relevant to the exciton, and the peculiarities of photoemission spectra of a lattice-coupled hole in a Mott insulator. (reviews of topical problems)

  16. Efficient sampling algorithms for Monte Carlo based treatment planning

    International Nuclear Information System (INIS)

    DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.

    1998-01-01

    Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed

  17. Monte Carlo applications at Hanford Engineering Development Laboratory

    International Nuclear Information System (INIS)

    Carter, L.L.; Morford, R.J.; Wilcox, A.D.

    1980-03-01

    Twenty applications of neutron and photon transport with Monte Carlo have been described to give an overview of the current effort at HEDL. A satisfaction factor was defined which quantitatively assigns an overall return for each calculation relative to the investment in machine time and expenditure of manpower. Low satisfaction factors are frequently encountered in the calculations. Usually this is due to limitations in execution rates of present day computers, but sometimes a low satisfaction factor is due to computer code limitations, calendar time constraints, or inadequacy of the nuclear data base. Present day computer codes have taken some of the burden off of the user. Nevertheless, it is highly desirable for the engineer using the computer code to have an understanding of particle transport including some intuition for the problems being solved, to understand the construction of sources for the random walk, to understand the interpretation of tallies made by the code, and to have a basic understanding of elementary biasing techniques

  18. Quantum Monte Carlo method for models of molecular nanodevices

    Science.gov (United States)

    Arrachea, Liliana; Rozenberg, Marcelo J.

    2005-07-01

    We introduce a quantum Monte Carlo technique to calculate exactly at finite temperatures the Green function of a fermionic quantum impurity coupled to a bosonic field. While the algorithm is general, we focus on the single impurity Anderson model coupled to a Holstein phonon as a schematic model for a molecular transistor. We compute the density of states at the impurity in a large range of parameters, to demonstrate the accuracy and efficiency of the method. We also obtain the conductance of the impurity model and analyze different regimes. The results show that even in the case when the effective attractive phonon interaction is larger than the Coulomb repulsion, a Kondo-like conductance behavior might be observed.

  19. Direct Simulation Monte Carlo (DSMC) on the Connection Machine

    International Nuclear Information System (INIS)

    Wong, B.C.; Long, L.N.

    1992-01-01

    The massively parallel computer Connection Machine is utilized to map an improved version of the direct simulation Monte Carlo (DSMC) method for solving flows with the Boltzmann equation. The kinetic theory is required for analyzing hypersonic aerospace applications, and the features and capabilities of the DSMC particle-simulation technique are discussed. The DSMC is shown to be inherently massively parallel and data parallel, and the algorithm is based on molecule movements, cross-referencing their locations, locating collisions within cells, and sampling macroscopic quantities in each cell. The serial DSMC code is compared to the present parallel DSMC code, and timing results show that the speedup of the parallel version is approximately linear. The correct physics can be resolved from the results of the complete DSMC method implemented on the connection machine using the data-parallel approach. 41 refs

  20. Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues

    International Nuclear Information System (INIS)

    Harris, G.; Van Horn, R.

    1996-06-01

    The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL

  1. Use of Monte Carlo methods in environmental risk assessments at the INEL: Applications and issues

    Energy Technology Data Exchange (ETDEWEB)

    Harris, G.; Van Horn, R.

    1996-06-01

    The EPA is increasingly considering the use of probabilistic risk assessment techniques as an alternative or refinement of the current point estimate of risk. This report provides an overview of the probabilistic technique called Monte Carlo Analysis. Advantages and disadvantages of implementing a Monte Carlo analysis over a point estimate analysis for environmental risk assessment are discussed. The general methodology is provided along with an example of its implementation. A phased approach to risk analysis that allows iterative refinement of the risk estimates is recommended for use at the INEL.

  2. Monte Carlo simulated dynamical magnetization of single-chain magnets

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jun; Liu, Bang-Gui, E-mail: bgliu@iphy.ac.cn

    2015-03-15

    Here, a dynamical Monte-Carlo (DMC) method is used to study temperature-dependent dynamical magnetization of famous Mn{sub 2}Ni system as typical example of single-chain magnets with strong magnetic anisotropy. Simulated magnetization curves are in good agreement with experimental results under typical temperatures and sweeping rates, and simulated coercive fields as functions of temperature are also consistent with experimental curves. Further analysis indicates that the magnetization reversal is determined by both thermal-activated effects and quantum spin tunnelings. These can help explore basic properties and applications of such important magnetic systems. - Highlights: • Monte Carlo simulated magnetization curves are in good agreement with experimental results. • Simulated coercive fields as functions of temperature are consistent with experimental results. • The magnetization reversal is understood in terms of the Monte Carlo simulations.

  3. Exploring cluster Monte Carlo updates with Boltzmann machines.

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

  4. A Multivariate Time Series Method for Monte Carlo Reactor Analysis

    International Nuclear Information System (INIS)

    Taro Ueki

    2008-01-01

    A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor

  5. Exploring cluster Monte Carlo updates with Boltzmann machines

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

  6. Minimum variance Monte Carlo importance sampling with parametric dependence

    International Nuclear Information System (INIS)

    Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

    1981-01-01

    An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

  7. Fixed forced detection for fast SPECT Monte-Carlo simulation

    Science.gov (United States)

    Cajgfinger, T.; Rit, S.; Létang, J. M.; Halty, A.; Sarrut, D.

    2018-03-01

    Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

  8. MORET: Version 4.B. A multigroup Monte Carlo criticality code

    International Nuclear Information System (INIS)

    Jacquet, Olivier; Miss, Joachim; Courtois, Gerard

    2003-01-01

    MORET 4 is a three dimensional multigroup Monte Carlo code which calculates the effective multiplication factor (keff) of any configurations more or less complex as well as reaction rates in the different volumes of the geometry and the leakage out of the system. MORET 4 is the Monte Carlo code of the APOLLO2-MORET 4 standard route of CRISTAL, the French criticality package. It is the most commonly used Monte Carlo code for French criticality calculations. During the last four years, the MORET 4 team has developed or improved the following major points: modernization of the geometry, implementation of perturbation algorithms, source distribution convergence, statistical detection of stationarity, unbiased variance estimation and creation of pre-processing and post-processing tools. The purpose of this paper is not only to present the new features of MORET but also to detail clearly the physical models and the mathematical methods used in the code. (author)

  9. Stabilization effect of fission source in coupled Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Borge; Dufek, Jan [Div. of Nuclear Reactor Technology, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm (Sweden)

    2017-08-15

    A fission source can act as a stabilization element in coupled Monte Carlo simulations. We have observed this while studying numerical instabilities in nonlinear steady-state simulations performed by a Monte Carlo criticality solver that is coupled to a xenon feedback solver via fixed-point iteration. While fixed-point iteration is known to be numerically unstable for some problems, resulting in large spatial oscillations of the neutron flux distribution, we show that it is possible to stabilize it by reducing the number of Monte Carlo criticality cycles simulated within each iteration step. While global convergence is ensured, development of any possible numerical instability is prevented by not allowing the fission source to converge fully within a single iteration step, which is achieved by setting a small number of criticality cycles per iteration step. Moreover, under these conditions, the fission source may converge even faster than in criticality calculations with no feedback, as we demonstrate in our numerical test simulations.

  10. Monte Carlo Simulation in Statistical Physics An Introduction

    CERN Document Server

    Binder, Kurt

    2010-01-01

    Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...

  11. Two proposed convergence criteria for Monte Carlo solutions

    International Nuclear Information System (INIS)

    Forster, R.A.; Pederson, S.P.; Booth, T.E.

    1992-01-01

    The central limit theorem (CLT) can be applied to a Monte Carlo solution if two requirements are satisfied: (1) The random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these two conditions are satisfied, a confidence interval (CI) based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the Monte Carlo tally being used. The Monte Carlo practitioner has a limited number of marginal methods to assess the fulfillment of the second requirement, such as statistical error reduction proportional to 1/√N with error magnitude guidelines. Two proposed methods are discussed in this paper to assist in deciding if N is large enough: estimating the relative variance of the variance (VOV) and examining the empirical history score probability density function (pdf)

  12. Applicability of quasi-Monte Carlo for lattice systems

    Energy Technology Data Exchange (ETDEWEB)

    Ammon, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Physics; Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Hartung, Tobias [King' s College London (United Kingdom). Dept. of Mathematics; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leovey, Hernan; Griewank, Andreas [Berlin Humboldt-Univ. (Germany). Dept. of Mathematics; Mueller-Preussker, Michael [Berlin Humboldt-Univ. (Germany). Dept. of Physics

    2013-11-15

    This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like N{sup -1/2}, where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to N{sup -1}, or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.

  13. Applicability of quasi-Monte Carlo for lattice systems

    International Nuclear Information System (INIS)

    Ammon, Andreas; Deutsches Elektronen-Synchrotron; Hartung, Tobias; Jansen, Karl; Leovey, Hernan; Griewank, Andreas; Mueller-Preussker, Michael

    2013-11-01

    This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over random observations generated from ordinary Monte Carlo simulations scales like N -1/2 , where N is the number of observations. By means of quasi-Monte Carlo methods it is possible to improve this scaling for certain problems to N -1 , or even further if the problems are regular enough. We adapted and applied this approach to simple systems like the quantum harmonic and anharmonic oscillator and verified an improved error scaling of all investigated observables in both cases.

  14. Range uncertainties in proton therapy and the role of Monte Carlo simulations

    International Nuclear Information System (INIS)

    Paganetti, Harald

    2012-01-01

    The main advantages of proton therapy are the reduced total energy deposited in the patient as compared to photon techniques and the finite range of the proton beam. The latter adds an additional degree of freedom to treatment planning. The range in tissue is associated with considerable uncertainties caused by imaging, patient setup, beam delivery and dose calculation. Reducing the uncertainties would allow a reduction of the treatment volume and thus allow a better utilization of the advantages of protons. This paper summarizes the role of Monte Carlo simulations when aiming at a reduction of range uncertainties in proton therapy. Differences in dose calculation when comparing Monte Carlo with analytical algorithms are analyzed as well as range uncertainties due to material constants and CT conversion. Range uncertainties due to biological effects and the role of Monte Carlo for in vivo range verification are discussed. Furthermore, the current range uncertainty recipes used at several proton therapy facilities are revisited. We conclude that a significant impact of Monte Carlo dose calculation can be expected in complex geometries where local range uncertainties due to multiple Coulomb scattering will reduce the accuracy of analytical algorithms. In these cases Monte Carlo techniques might reduce the range uncertainty by several mm. (topical review)

  15. Crossed source-detector geometry for a novel spray diagnostic: Monte Carlo simulation and analytical results.

    Science.gov (United States)

    Berrocal, Edouard; Churmakov, Dmitry Y; Romanov, Vadim P; Jermy, Mark C; Meglinski, Igor V

    2005-05-01

    Sprays and other industrially relevant turbid media can be quantitatively characterized by light scattering. However, current optical diagnostic techniques generate errors in the intermediate scattering regime where the average number of light scattering is too great for the single scattering to be assumed, but too few for the diffusion approximation to be applied. Within this transitional single-to-multiple scattering regime, we consider a novel crossed source-detector geometry that allows the intensity of single scattering to be measured separately from the higher scattering orders. We verify Monte Carlo calculations that include the imperfections of the experiment against analytical results. We show quantitatively the influence of the detector numerical aperture and the angle between the source and the detector on the relative intensity of the scattering orders in the intermediate single-to-multiple scattering regime. Monte Carlo and analytical calculations of double light-scattering intensity are made with small particles that exhibit isotropic scattering. The agreement between Monte Carlo and analytical techniques validates use of the Monte Carlo approach in the intermediate scattering regime. Monte Carlo calculations are then performed for typical parameters of sprays and aerosols with anisotropic (Mie) scattering in the intermediate single-to-multiple scattering regime.

  16. The optimal balance between quality and efficiency in proton radiography imaging technique at various proton beam energies: A Monte Carlo study.

    Science.gov (United States)

    Biegun, A K; van Goethem, M-J; van der Graaf, E R; van Beuzekom, M; Koffeman, E N; Nakaji, T; Takatsu, J; Visser, J; Brandenburg, S

    2017-09-01

    Proton radiography is a novel imaging modality that allows direct measurement of the proton energy loss in various tissues. Currently, due to the conversion of so-called Hounsfield units from X-ray Computed Tomography (CT) into relative proton stopping powers (RPSP), the uncertainties of RPSP are 3-5% or higher, which need to be minimized down to 1% to make the proton treatment plans more accurate. In this work, we simulated a proton radiography system, with position-sensitive detectors (PSDs) and a residual energy detector (RED). The simulations were built using Geant4, a Monte Carlo simulation toolkit. A phantom, consisting of several materials was placed between the PSDs of various Water Equivalent Thicknesses (WET), corresponding to an ideal detector, a gaseous detector, silicon and plastic scintillator detectors. The energy loss radiograph and the scattering angle distributions of the protons were studied for proton beam energies of 150MeV, 190MeV and 230MeV. To improve the image quality deteriorated by the multiple Coulomb scattering (MCS), protons with small angles were selected. Two ways of calculating a scattering angle were considered using the proton's direction and position. A scattering angle cut of 8.7mrad was applied giving an optimal balance between quality and efficiency of the radiographic image. For the three proton beam energies, the number of protons used in image reconstruction with the direction method was half the number of protons kept using the position method. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  17. Molecular dynamics algorithms for quantum Monte Carlo methods

    Science.gov (United States)

    Miura, Shinichi

    2009-11-01

    In the present Letter, novel molecular dynamics methods compatible with corresponding quantum Monte Carlo methods are developed. One is a variational molecular dynamics method that is a molecular dynamics analog of quantum variational Monte Carlo method. The other is a variational path integral molecular dynamics method, which is based on the path integral molecular dynamics method for finite temperature systems by Tuckerman et al. [M. Tuckerman, B.J. Berne, G.J. Martyna, M.L. Klein, J. Chem. Phys. 99 (1993) 2796]. These methods are applied to model systems including the liquid helium-4, demonstrated to work satisfactorily for the tested ground state calculations.

  18. Grain-boundary melting: A Monte Carlo study

    DEFF Research Database (Denmark)

    Besold, Gerhard; Mouritsen, Ole G.

    1994-01-01

    Grain-boundary melting in a lattice-gas model of a bicrystal is studied by Monte Carlo simulation using the grand canonical ensemble. Well below the bulk melting temperature T(m), a disordered liquidlike layer gradually emerges at the grain boundary. Complete interfacial wetting can be observed...... when the temperature approaches T(m) from below. Monte Carlo data over an extended temperature range indicate a logarithmic divergence w(T) approximately - ln(T(m)-T) of the width of the disordered layer w, in agreement with mean-field theory....

  19. Monte Carlo Form-Finding Method for Tensegrity Structures

    Science.gov (United States)

    Li, Yue; Feng, Xi-Qiao; Cao, Yan-Ping

    2010-05-01

    In this paper, we propose a Monte Carlo-based approach to solve tensegrity form-finding problems. It uses a stochastic procedure to find the deterministic equilibrium configuration of a tensegrity structure. The suggested Monte Carlo form-finding (MCFF) method is highly efficient because it does not involve complicated matrix operations and symmetry analysis and it works for arbitrary initial configurations. Both regular and non-regular tensegrity problems of large scale can be solved. Some representative examples are presented to demonstrate the efficiency and accuracy of this versatile method.

  20. Aspects of perturbative QCD in Monte Carlo shower models

    International Nuclear Information System (INIS)

    Gottschalk, T.D.

    1986-01-01

    The perturbative QCD content of Monte Carlo models for high energy hadron-hadron scattering is examined. Particular attention is given to the recently developed backwards evolution formalism for initial state parton showers, and the merging of parton shower evolution with hard scattering cross sections. Shower estimates of K-factors are discussed, and a simple scheme is presented for incorporating 2 → QCD cross sections into shower model calculations without double counting. Additional issues in the development of hard scattering Monte Carlo models are summarized. 69 references, 20 figures

  1. ALEPH: An optimal approach to Monte Carlo burn-up

    International Nuclear Information System (INIS)

    Verboomen, B.

    2007-01-01

    The incentive of creating Monte Carlo burn-up codes arises from its ability to provide the most accurate locally dependent spectra and flux values in realistic 3D geometries of any type. These capabilities linked with the ability to handle nuclear data not only in its most basic but also most complex form (namely continuous energy cross sections, detailed energy-angle correlations, multi-particle physics, etc.) could make Monte Carlo burn-up codes very powerful, especially for hybrid and advanced nuclear systems (like for instance Accelerator Driven Systems). Still, such Monte Carlo burn-up codes have had limited success mainly due to the rather long CPU time required to carry out very detailed and accurate calculations, even with modern computer technology. To work around this issue, users often have to reduce the number of nuclides in the evolution chains or to consider either longer irradiation time steps and/or larger spatial burn-up cells, jeopardizing the accuracy of the calculation in all cases. There should always be a balance between accuracy and what is (reasonably) achievable. So when the Monte Carlo simulation time is as low as possible and if calculating the cross sections and flux values required for the depletion calculation takes little or no extra time compared to this simulation time, then we can actually be as accurate as we want. That is the optimum situation for Monte Carlo burn-up calculations.The ultimate goal of this work is to provide the Monte Carlo community with an efficient, flexible and easy to use alternative for Monte Carlo burn-up and activation calculations, which is what we did with ALEPH. ALEPH is a Monte Carlo burn-up code that uses ORIGEN 2.2 as a depletion module and any version of MCNP or MCNPX as the transport module. For now, ALEPH has been limited to updating microscopic cross section data only. By providing an easy to understand user interface, we also take away the burden from the user. For the user, it is as if he is

  2. Monte carlo analysis of multicolour LED light engine

    DEFF Research Database (Denmark)

    Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

    2015-01-01

    A new Monte Carlo simulation as a tool for analysing colour feedback systems is presented here to analyse the colour uncertainties and achievable stability in a multicolour dynamic LED system. The Monte Carlo analysis presented here is based on an experimental investigation of a multicolour LED...... light engine designed for white tuneable studio lighting. The measured sensitivities to the various factors influencing the colour uncertainty for similar system are incorporated. The method aims to provide uncertainties in the achievable chromaticity coordinates as output over the tuneable range, e...

  3. THE APPLICATION OF MONTE CARLO SIMULATION FOR A DECISION PROBLEM

    Directory of Open Access Journals (Sweden)

    Çiğdem ALABAŞ

    2001-01-01

    Full Text Available The ultimate goal of the standard decision tree approach is to calculate the expected value of a selected performance measure. In the real-world situations, the decision problems become very complex as the uncertainty factors increase. In such cases, decision analysis using standard decision tree approach is not useful. One way of overcoming this difficulty is the Monte Carlo simulation. In this study, a Monte Carlo simulation model is developed for a complex problem and statistical analysis is performed to make the best decision.

  4. A study on the shielding element using Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ki Jeong [Dept. of Radiology, Konkuk University Medical Center, Seoul (Korea, Republic of); Shim, Jae Goo [Dept. of Radiologic Technology, Daegu Health College, Daegu (Korea, Republic of)

    2017-06-15

    In this research, we simulated the elementary star shielding ability using Monte Carlo simulation to apply medical radiation shielding sheet which can replace existing lead. In the selection of elements, mainly elements and metal elements having a large atomic number, which are known to have high shielding performance, recently, various composite materials have improved shielding performance, so that weight reduction, processability, In consideration of activity etc., 21 elements were selected. The simulation tools were utilized Monte Carlo method. As a result of simulating the shielding performance by each element, it was estimated that the shielding ratio is the highest at 98.82% and 98.44% for tungsten and gold.

  5. Modifications to the Monte Carlo neutronics code MONK

    International Nuclear Information System (INIS)

    Hutton, J.L.

    1979-09-01

    The Monte Carlo neutronics code MONK has been widely used for criticality calculations, and is one of the standard methods for assessing the safety of transport flasks and fuel storage facilities in the UK. Recently, attempts have been made to extend the range of applications of this calculational technique. In particular studies have been carried out using Monte Carlo to analyse reactor physics experiments. In these applications various shortcomings of the standard version MONK5 became apparent. The basic data library was found to be inadequate and additional estimates of parameters (eg power distribution) not normally included in criticality studies were required. These features which required improvement, primarily in the context of using the code for reactor physics calculations, are enumerated. To facilitate the use of the code as a reactor physics calculational tool a series of modifications have been carried out. The code has been modified so that the user can use group data tabulations of the cross sections instead of the present 'point' data values. The code can now interface with a number of reactor physics group data preparation schemes but in particular it can use WIMS-E interfaces as a source of group data. Details of the changes are outlined and a new version of MONK incorporating these modifications has been created. This version is called MONK5W. This paper provides a guide to the use of this version. The data input is described along with other details required to use this code on the Harwell IBM 3033. To aid the user, examples of calculations using the new facilities incorporated in MONK5W are given. (UK)

  6. Underwater Optical Wireless Channel Modeling Using Monte-Carlo Method

    Science.gov (United States)

    Saini, P. Sri; Prince, Shanthi

    2011-10-01

    At present, there is a lot of interest in the functioning of the marine environment. Unmanned or Autonomous Underwater Vehicles (UUVs or AUVs) are used in the exploration of the underwater resources, pollution monitoring, disaster prevention etc. Underwater, where radio waves do not propagate, acoustic communication is being used. But, underwater communication is moving towards Optical Communication which has higher bandwidth when compared to Acoustic Communication but has shorter range comparatively. Underwater Optical Wireless Communication (OWC) is mainly affected by the absorption and scattering of the optical signal. In coastal waters, both inherent and apparent optical properties (IOPs and AOPs) are influenced by a wide array of physical, biological and chemical processes leading to optical variability. The scattering effect has two effects: the attenuation of the signal and the Inter-Symbol Interference (ISI) of the signal. However, the Inter-Symbol Interference is ignored in the present paper. Therefore, in order to have an efficient underwater OWC link it is necessary to model the channel efficiently. In this paper, the underwater optical channel is modeled using Monte-Carlo method. The Monte Carlo approach provides the most general and most flexible technique for numerically solving the equations of Radiative transfer. The attenuation co-efficient of the light signal is studied as a function of the absorption (a) and scattering (b) coefficients. It has been observed that for pure sea water and for less chlorophyll conditions blue wavelength is less absorbed whereas for chlorophyll rich environment red wavelength signal is absorbed less comparative to blue and green wavelength.

  7. Validation of Monte Carlo Geant4 code for a

    Directory of Open Access Journals (Sweden)

    Jaafar EL Bakkali

    2017-01-01

    Full Text Available This study is aimed at validating the Monte Carlo Geant4.9.4 code for a 6 MV Varian linac configuring a 10 × 10 cm2 radiation field. For this purpose a user-friendly Geant4 code called G4Linac has been developed from scratch allowing an accurate modeling of a 6 MV Varian linac head and performing dose calculation in a homogeneous water phantom. Discarding the other accelerator parts where electrons are created, accelerated and deviated, a virtual source of 6 MeV electrons was considered. The parameters associated with this virtual source are often unknown. Those parameters are mean energy, sigma and its full width at half maximum has been adjusted by following our own methodology that has been developed in such a manner that the optimization phase will be fast and efficient, in fact, a small number of Monte Carlo simulations has been conducted simultaneously on a cluster of computers thanks to the Rocks cluster software. The calculated dosimetric functions in a 40 × 40 × 40 cm3 water phantom were compared to the measured ones thanks to the Gamma Index method, where the gamma criterion was fixed within 2%–1 mm accuracy. After optimization, it was observed that the proper mean energy, sigma and its full width at half maximum are 5.6 MeV, 0.42 MeV and 1.177 mm, respectively. Furthermore, we have made some changes in an existing bremsstrahlung splitting technique, due to which we have succeeded to reduce the CPU time spent by the treatment head simulation about five times.

  8. Online Bayesian phylogenetic inference: theoretical foundations via Sequential Monte Carlo.

    Science.gov (United States)

    Dinh, Vu; Darling, Aaron E; Matsen Iv, Frederick A

    2017-12-13

    Phylogenetics, the inference of evolutionary trees from molecular sequence data such as DNA, is an enterprise that yields valuable evolutionary understanding of many biological systems. Bayesian phylogenetic algorithms, which approximate a posterior distribution on trees, have become a popular if computationally expensive means of doing phylogenetics. Modern data collection technologies are quickly adding new sequences to already substantial databases. With all current techniques for Bayesian phylogenetics, computation must start anew each time a sequence becomes available, making it costly to maintain an up-to-date estimate of a phylogenetic posterior. These considerations highlight the need for an online Bayesian phylogenetic method which can update an existing posterior with new sequences. Here we provide theoretical results on the consistency and stability of methods for online Bayesian phylogenetic inference based on Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC). We first show a consistency result, demonstrating that the method samples from the correct distribution in the limit of a large number of particles. Next we derive the first reported set of bounds on how phylogenetic likelihood surfaces change when new sequences are added. These bounds enable us to characterize the theoretical performance of sampling algorithms by bounding the effective sample size (ESS) with a given number of particles from below. We show that the ESS is guaranteed to grow linearly as the number of particles in an SMC sampler grows. Surprisingly, this result holds even though the dimensions of the phylogenetic model grow with each new added sequence. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

  9. Non-analogue Monte Carlo method, application to neutron simulation; Methode de Monte Carlo non analogue, application a la simulation des neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Morillon, B.

    1996-12-31

    With most of the traditional and contemporary techniques, it is still impossible to solve the transport equation if one takes into account a fully detailed geometry and if one studies precisely the interactions between particles and matters. Only the Monte Carlo method offers such a possibility. However with significant attenuation, the natural simulation remains inefficient: it becomes necessary to use biasing techniques where the solution of the adjoint transport equation is essential. The Monte Carlo code Tripoli has been using such techniques successfully for a long time with different approximate adjoint solutions: these methods require from the user to find out some parameters. If this parameters are not optimal or nearly optimal, the biases simulations may bring about small figures of merit. This paper presents a description of the most important biasing techniques of the Monte Carlo code Tripoli ; then we show how to calculate the importance function for general geometry with multigroup cases. We present a completely automatic biasing technique where the parameters of the biased simulation are deduced from the solution of the adjoint transport equation calculated by collision probabilities. In this study we shall estimate the importance function through collision probabilities method and we shall evaluate its possibilities thanks to a Monte Carlo calculation. We compare different biased simulations with the importance function calculated by collision probabilities for one-group and multigroup problems. We have run simulations with new biasing method for one-group transport problems with isotropic shocks and for multigroup problems with anisotropic shocks. The results show that for the one-group and homogeneous geometry transport problems the method is quite optimal without splitting and russian roulette technique but for the multigroup and heterogeneous X-Y geometry ones the figures of merit are higher if we add splitting and russian roulette technique.

  10. Pseudopotentials for quantum-Monte-Carlo-calculations; Pseudopotentiale fuer Quanten-Monte-Carlo-Rechnungen

    Energy Technology Data Exchange (ETDEWEB)

    Burkatzki, Mark Thomas

    2008-07-01

    The author presents scalar-relativistic energy-consistent Hartree-Fock pseudopotentials for the main-group and 3d-transition-metal elements. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The author demonstrates their transferability through extensive benchmark calculations of atomic excitation spectra as well as molecular properties. In particular, the author computes the vibrational frequencies and binding energies of 26 first- and second-row diatomic molecules using post Hartree-Fock methods, finding excellent agreement with the corresponding all-electron values. The author shows that the presented pseudopotentials give superior accuracy than other existing pseudopotentials constructed specifically for QMC. The localization error and the efficiency in QMC are discussed. The author also presents QMC calculations for selected atomic and diatomic 3d-transitionmetal systems. Finally, valence basis sets of different sizes (VnZ with n=D,T,Q,5 for 1st and 2nd row; with n=D,T for 3rd to 5th row; with n=D,T,Q for the 3d transition metals) optimized for the pseudopotentials are presented. (orig.)

  11. An improved wavelength selection scheme for Monte Carlo solvers applied to hypersonic plasmas

    International Nuclear Information System (INIS)

    Feldick, Andrew; Modest, Michael F.

    2011-01-01

    A new databasing scheme is developed for Monte Carlo Ray Tracing methods applied to hypersonic planetary entry. In this scheme, the complex relationships for the emission wavelength selection of atomic and molecular species in nonequilibrium flows are simplified by developing random number relationships for individual transitions, as opposed to using relationships for the spectral emission coefficient of a given species. These new techniques speed up wavelength selection by about 2 orders of magnitude, and offer flexibility for use in weighted or part-spectrum Monte Carlo solvers.

  12. A hybrid transport-diffusion method for Monte Carlo radiative-transfer simulations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Urbatsch, Todd J.; Evans, Thomas M.; Buksas, Michael W.

    2007-01-01

    Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Monte Carlo particle-transport simulations in diffusive media. If standard Monte Carlo is used in such media, particle histories will consist of many small steps, resulting in a computationally expensive calculation. In DDMC, particles take discrete steps between spatial cells according to a discretized diffusion equation. Each discrete step replaces many small Monte Carlo steps, thus increasing the efficiency of the simulation. In addition, given that DDMC is based on a diffusion equation, it should produce accurate solutions if used judiciously. In practice, DDMC is combined with standard Monte Carlo to form a hybrid transport-diffusion method that can accurately simulate problems with both diffusive and non-diffusive regions. In this paper, we extend previously developed DDMC techniques in several ways that improve the accuracy and utility of DDMC for nonlinear, time-dependent, radiative-transfer calculations. The use of DDMC in these types of problems is advantageous since, due to the underlying linearizations, optically thick regions appear to be diffusive. First, we employ a diffusion equation that is discretized in space but is continuous in time. Not only is this methodology theoretically more accurate than temporally discretized DDMC techniques, but it also has the benefit that a particle's time is always known. Thus, there is no ambiguity regarding what time to assign a particle that leaves an optically thick region (where DDMC is used) and begins transporting by standard Monte Carlo in an optically thin region. Also, we treat the interface between optically thick and optically thin regions with an improved method, based on the asymptotic diffusion-limit boundary condition, that can produce accurate results regardless of the angular distribution of the incident Monte Carlo particles. Finally, we develop a technique for estimating radiation momentum deposition during the

  13. Monte Carlo simulation of radiation streaming from a radioactive material shipping cask

    International Nuclear Information System (INIS)

    Liu, Y.Y.; Schwarz, R.A.; Tang, J.S.

    1996-01-01

    Simulated detection of gamma radiation streaming from a radioactive material shipping cask have been performed with the Monte Carlo codes MCNP4A and MORSE-SGC/S. Despite inherent difficulties in simulating deep penetration of radiation and streaming, the simulations have yielded results that agree within one order of magnitude with the radiation survey data, with reasonable statistics. These simulations have also provided insight into modeling radiation detection, notably on location and orientation of the radiation detector with respect to photon streaming paths, and on techniques used to reduce variance in the Monte Carlo calculations. 13 refs., 4 figs., 2 tabs

  14. Determination of scatter fractions of some materials by experimental studies and Monte Carlo calculations

    CERN Document Server

    Meric, N; Bor, D

    1999-01-01

    Scatter fractions have been determined experimentally for lucite, polyethylene, polypropylene, aluminium and copper of varying thicknesses using a polyenergetic broad X-ray beam of 67 kVp. Simulation of the experiment has been carried out by the Monte Carlo technique under the same input conditions. Comparison of the measured and predicted data with each other and with the previously reported values has been given. The Monte Carlo calculations have also been carried out for water, bakelite and bone to examine the dependence of scatter fraction on the density of the scatterer.

  15. Monte Carlo analysis of field-dependent electron avalanche coefficients in nitrogen at atmospheric pressure

    Science.gov (United States)

    Nguyen, H. K.; Mankowski, J.; Dickens, J. C.; Neuber, A. A.; Joshi, R. P.

    2017-12-01

    Calculations of electron impact ionization of nitrogen gas at atmospheric pressure are presented based on the kinetic Monte Carlo technique. The emphasis is on energy partitioning between primary and secondary electrons, and three different energy sharing schemes have been evaluated. The ionization behavior is based on Wannier's classical treatment. Our Monte Carlo results for the field-dependent drift velocities match the available experimental data. More interestingly, the field-dependent first Townsend coefficient predicted by the Monte Carlo calculations is shown to be in close agreement with reported data for E/N values ranging as high as 4000 Td, only when a random assignment of excess energies between the primary and secondary particles is used.

  16. MCNP: a general Monte Carlo code for neutron and photon transport. Version 3A. Revision 2

    International Nuclear Information System (INIS)

    Briesmeister, J.F.

    1986-09-01

    This manual is a practical guide for the use of our general-purpose Monte Carlo code MCNP. The first chapter is a primer for the novice user. The second chapter describes the mathematics, data, physics, and Monte Carlo simulation found in MCNP. This discussion is not meant to be exhaustive - details of the particular techniques and of the Monte Carlo method itself will have to be found elsewhere. The third chapter shows the user how to prepare input for the code. The fourth chapter contains several examples, and the fifth chapter explains the output. The appendices show how to use MCNP on particular computer systems at the Los Alamos National Laboratory and also give details about some of the code internals that those who wish to modify the code may find useful. 57 refs

  17. Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

    CERN Document Server

    Chapman, J; Duehrssen, M; Elsing, M; Froidevaux, D; Harrington, R; Jansky, R; Langenberg, R; Mandrysch, R; Marshall, Z; Ritsch, E; Salzburger, A

    2014-01-01

    The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during run I relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for run II, and beyond. A number of fast detector simulation, digitization and reconstruction techniques and are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

  18. A Monte Carlo approach for simulating the propagation of partially coherent x-ray beams

    DEFF Research Database (Denmark)

    Prodi, A.; Bergbäck Knudsen, Erik; Willendrup, Peter Kjær

    2011-01-01

    by sampling Huygens-Fresnel waves with Monte Carlo methods and is used to propagate each source realization to the detector plane. The sampling is implemented with a modified Monte Carlo ray tracing scheme where the optical path of each generated ray is stored. Such information is then used in the summation...... coherence function (MCF) are propagated to the exit plane. Here we present an approach based on Monte Carlo sampling of the Green function. A Gauss-Shell Stochastic Source with arbitrary spatial coherence is synthesized by means of the Gaussian copula statistical tool. The Green function is obtained......Advances at SR sources in the generation of nanofocused beams with a high degree of transverse coherence call for effective techniques to simulate the propagation of partially coherent X-ray beams through complex optical systems in order to characterize how coherence properties such as the mutual...

  19. Exploring the use of a deterministic adjoint flux calculation in criticality Monte Carlo simulations

    International Nuclear Information System (INIS)

    Jinaphanh, A.; Miss, J.; Richet, Y.; Martin, N.; Hebert, A.

    2011-01-01

    The paper presents a preliminary study on the use of a deterministic adjoint flux calculation to improve source convergence issues by reducing the number of iterations needed to reach the converged distribution in criticality Monte Carlo calculations. Slow source convergence in Monte Carlo eigenvalue calculations may lead to underestimate the effective multiplication factor or reaction rates. The convergence speed depends on the initial distribution and the dominance ratio. We propose using an adjoint flux estimation to modify the transition kernel according to the Importance Sampling technique. This adjoint flux is also used as the initial guess of the first generation distribution for the Monte Carlo simulation. Calculated Variance of a local estimator of current is being checked. (author)

  20. Non-periodic pseudo-random numbers used in Monte Carlo calculations

    International Nuclear Information System (INIS)

    Barberis, Gaston E.

    2007-01-01

    The generation of pseudo-random numbers is one of the interesting problems in Monte Carlo simulations, mostly because the common computer generators produce periodic numbers. We used simple pseudo-random numbers generated with the simplest chaotic system, the logistic map, with excellent results. The numbers generated in this way are non-periodic, which we demonstrated for 10 13 numbers, and they are obtained in a deterministic way, which allows to repeat systematically any calculation. The Monte Carlo calculations are the ideal field to apply these numbers, and we did it for simple and more elaborated cases. Chemistry and Information Technology use this kind of simulations, and the application of this numbers to quantum Monte Carlo and cryptography is immediate. I present here the techniques to calculate, analyze and use these pseudo-random numbers, show that they lack periodicity up to 10 13 numbers and that they are not correlated

  1. Non-periodic pseudo-random numbers used in Monte Carlo calculations

    Science.gov (United States)

    Barberis, Gaston E.

    2007-09-01

    The generation of pseudo-random numbers is one of the interesting problems in Monte Carlo simulations, mostly because the common computer generators produce periodic numbers. We used simple pseudo-random numbers generated with the simplest chaotic system, the logistic map, with excellent results. The numbers generated in this way are non-periodic, which we demonstrated for 1013 numbers, and they are obtained in a deterministic way, which allows to repeat systematically any calculation. The Monte Carlo calculations are the ideal field to apply these numbers, and we did it for simple and more elaborated cases. Chemistry and Information Technology use this kind of simulations, and the application of this numbers to quantum Monte Carlo and cryptography is immediate. I present here the techniques to calculate, analyze and use these pseudo-random numbers, show that they lack periodicity up to 1013 numbers and that they are not correlated.

  2. New Zero-Variance Methods for Monte Carlo Criticality and Source-Detector Problems

    International Nuclear Information System (INIS)

    Larsen, Edward W.; Densmore, Jeffery D.

    2001-01-01

    A zero-variance (ZV) Monte Carlo transport method is a theoretical construct that, if it could be implemented on a practical computer, would produce the exact result after any number of histories. Unfortunately, ZV methods are impractical; nevertheless, ZV methods are of practical interest because it is possible to approximate them in ways that yield efficient variance-reduction schemes. New ZV methods for Monte Carlo criticality and source-detector problems are described. Although these methods have the same requirements and disadvantages of earlier methods, their implementation is very different; thus, the concept of approximating them to obtain practical variance-reduction schemes opens new possibilities. The relationships between the new ZV schemes, conventional ZV schemes, and recently proposed variational variance-reduction techniques are discussed. The goal is the development of more efficient Monte Carlo variance-reduction methods

  3. Annealing evolutionary stochastic approximation Monte Carlo for global optimization

    KAUST Repository

    Liang, Faming

    2010-04-08

    In this paper, we propose a new algorithm, the so-called annealing evolutionary stochastic approximation Monte Carlo (AESAMC) algorithm as a general optimization technique, and study its convergence. AESAMC possesses a self-adjusting mechanism, whose target distribution can be adapted at each iteration according to the current samples. Thus, AESAMC falls into the class of adaptive Monte Carlo methods. This mechanism also makes AESAMC less trapped by local energy minima than nonadaptive MCMC algorithms. Under mild conditions, we show that AESAMC can converge weakly toward a neighboring set of global minima in the space of energy. AESAMC is tested on multiple optimization problems. The numerical results indicate that AESAMC can potentially outperform simulated annealing, the genetic algorithm, annealing stochastic approximation Monte Carlo, and some other metaheuristics in function optimization. © 2010 Springer Science+Business Media, LLC.

  4. Monte Carlo simulation of virtual compton scattering at MAMI

    International Nuclear Information System (INIS)

    D'Hose, N.; Ducret, J.E.; Gousset, TH.; Guichon, P.A.M.; Kerhoas, S.; Lhuillier, D.; Marchand, C.; Marchand, D.; Martino, J.; Mougey, J.; Roche, J.; Vanderhaeghen, M.; Vernin, P.; Bohm, H.; Distler, M.; Edelhoff, R.; Friedrich, J.M.; Geiges, R.; Jennewein, P.; Kahrau, M.; Korn, M.; Kramer, H.; Krygier, K.W.; Kunde, V.; Liesenfeld, A.; Merkel, H.; Merle, K.; Neuhausen, R.; Pospischil, TH.; Rosner, G.; Sauer, P.; Schmieden, H.; Schardt, S.; Tamas, G.; Wagner, A.; Walcher, TH.; Wolf, S.; Hyde-Wright, CH.; Boeglin, W.U.; Van de Wiele, J.

    1996-01-01

    The Monte Carlo simulation developed specially for the VCS experiments taking place at MAMI in fully described. This simulation can generate events according to the Bethe-Heitler + Born cross section behaviour and takes into account resolution deteriorating effects. It is used to determine solid angles for the various experimental settings. (authors)

  5. A multi-microcomputer system for Monte Carlo calculations

    International Nuclear Information System (INIS)

    Hertzberger, L.O.; Berg, B.; Krasemann, H.

    1981-01-01

    We propose a microcomputer system which allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and presumably many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 68000 microprocessor. One attraction if this processor is that it allows up to 16 M Byte random access memory. (orig.)

  6. Monte Carlo simulation of fluorescence correlation spectroscopy data

    Czech Academy of Sciences Publication Activity Database

    Košovan, P.; Uhlík, F.; Kuldová, J.; Štěpánek, M.; Limpouchová, Z.; Procházka, K.; Benda, Aleš; Humpolíčková, Jana; Hof, Martin

    2011-01-01

    Roč. 76, č. 3 (2011), s. 207-222 ISSN 0010-0765 R&D Projects: GA AV ČR IAA400400621 Institutional research plan: CEZ:AV0Z40400503 Keywords : Monte Carlo Study * fluorescence * spectroscopy Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.283, year: 2011

  7. Monte Carlo Simulation of Partially Confined Flexible Polymers

    NARCIS (Netherlands)

    Hermsen, G.F.; de Geeter, B.A.; van der Vegt, N.F.A.; Wessling, Matthias

    2002-01-01

    We have studied conformational properties of flexible polymers partially confined to narrow pores of different size using configurational biased Monte Carlo simulations under athermal conditions. The asphericity of the chain has been studied as a function of its center of mass position along the

  8. Present Status and Extensions of the Monte Carlo Performance Benchmark

    Science.gov (United States)

    Hoogenboom, J. Eduard; Petrovic, Bojan; Martin, William R.

    2014-06-01

    The NEA Monte Carlo Performance benchmark started in 2011 aiming to monitor over the years the abilities to perform a full-size Monte Carlo reactor core calculation with a detailed power production for each fuel pin with axial distribution. This paper gives an overview of the contributed results thus far. It shows that reaching a statistical accuracy of 1 % for most of the small fuel zones requires about 100 billion neutron histories. The efficiency of parallel execution of Monte Carlo codes on a large number of processor cores shows clear limitations for computer clusters with common type computer nodes. However, using true supercomputers the speedup of parallel calculations is increasing up to large numbers of processor cores. More experience is needed from calculations on true supercomputers using large numbers of processors in order to predict if the requested calculations can be done in a short time. As the specifications of the reactor geometry for this benchmark test are well suited for further investigations of full-core Monte Carlo calculations and a need is felt for testing other issues than its computational performance, proposals are presented for extending the benchmark to a suite of benchmark problems for evaluating fission source convergence for a system with a high dominance ratio, for coupling with thermal-hydraulics calculations to evaluate the use of different temperatures and coolant densities and to study the correctness and effectiveness of burnup calculations. Moreover, other contemporary proposals for a full-core calculation with realistic geometry and material composition will be discussed.

  9. Minimum Thresholds of Monte Carlo Cycles for Nigerian Empirical ...

    African Journals Online (AJOL)

    Monte Carlo simulation has proven to be an eective means of incorporating reliability analysisinto the Mechanistic-Empirical (M-E) design process for exible pavements. Nigerian Empirical-Mechanistic Pavement Analysis and Design System procedure for Nigeria Environments has beenproposed. This work aimed at ...

  10. Direct determination of liquid phase coexistence by Monte Carlo simulations

    NARCIS (Netherlands)

    Zweistra, H.J.A.; Besseling, N.A.M.

    2006-01-01

    A formalism to determine coexistence points by means of Monte Carlo simulations is presented. The general idea of the method is to perform a simulation simultaneously in several unconnected boxes which can exchange particles. At equilibrium, most of the boxes will be occupied by a homogeneous phase.

  11. An Overview of the Monte Carlo Methods, Codes, & Applications Group

    Energy Technology Data Exchange (ETDEWEB)

    Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-08-30

    This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.

  12. A separable shadow Hamiltonian hybrid Monte Carlo method

    Science.gov (United States)

    Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.

    2009-11-01

    Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).

  13. Application of Monte Carlo Method to Steady State Heat Conduction ...

    African Journals Online (AJOL)

    The Monte Carlo method was used in modelling steady state heat conduction problems. The method uses the fixed and the floating random walks to determine temperature in the domain of the definition of the heat conduction equation, at a single point directly. A heat conduction problem with an irregular shaped geometry ...

  14. Monte Carlo capabilities of the SCALE code system

    International Nuclear Information System (INIS)

    Rearden, B.T.; Petrie, L.M.; Peplow, D.E.; Bekar, K.B.; Wiarda, D.; Celik, C.; Perfetti, C.M.; Ibrahim, A.M.; Dunn, M.E.; Hart, S.W.D.

    2013-01-01

    SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a 'plug-and-play' framework that includes three deterministic and three Monte Carlo radiation transport solvers (KENO, MAVRIC, TSUNAMI) that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE's graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2, to be released in 2014, will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2. (authors)

  15. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  16. A combination of Monte Carlo Temperature Basin Paving and Graph ...

    Indian Academy of Sciences (India)

    theory: Water cluster low energy structures and completeness of search. RAJAN SHRIVASTAVA, AVIJIT RAKSHIT, ... Monte Carlo sampling; water cluster; graph theory. 1. Introduction. Exploration of the energy landscape ..... use our algorithm for large water clusters, at present, it turns out that use of this for (H20)20 would ...

  17. Monte Carlo radiation transport: A revolution in science

    International Nuclear Information System (INIS)

    Hendricks, J.

    1993-01-01

    When Enrico Fermi, Stan Ulam, Nicholas Metropolis, John von Neuman, and Robert Richtmyer invented the Monte Carlo method fifty years ago, little could they imagine the far-flung consequences, the international applications, and the revolution in science epitomized by their abstract mathematical method. The Monte Carlo method is used in a wide variety of fields to solve exact computational models approximately by statistical sampling. It is an alternative to traditional physics modeling methods which solve approximate computational models exactly by deterministic methods. Modern computers and improved methods, such as variance reduction, have enhanced the method to the point of enabling a true predictive capability in areas such as radiation or particle transport. This predictive capability has contributed to a radical change in the way science is done: design and understanding come from computations built upon experiments rather than being limited to experiments, and the computer codes doing the computations have become the repository for physics knowledge. The MCNP Monte Carlo computer code effort at Los Alamos is an example of this revolution. Physicians unfamiliar with physics details can design cancer treatments using physics buried in the MCNP computer code. Hazardous environments and hypothetical accidents can be explored. Many other fields, from underground oil well exploration to aerospace, from physics research to energy production, from safety to bulk materials processing, benefit from MCNP, the Monte Carlo method, and the revolution in science

  18. A combination of Monte Carlo Temperature Basin Paving and Graph ...

    Indian Academy of Sciences (India)

    Abstract. The knowledge of degree of completeness of energy landscape search by stochastic algorithms is often lacking. A graph theory based method is used to investigate the completeness of search performed by. Monte Carlo Temperature Basin Paving (MCTBP) algorithm for (H2O)n, (n=6, 7, and 20). In the second part.

  19. Monte Carlo simulation of the seed germination process

    International Nuclear Information System (INIS)

    Gladyszewska, B.; Koper, R.

    2000-01-01

    Paper presented a mathematical model of seed germination process based on the Monte Carlo method and theoretical premises resulted from the physiology of seed germination suggesting three consecutive stages: physical, biochemical and physiological. The model was experimentally verified by determination of germination characteristics for seeds of ground tomatoes, Promyk cultivar, within broad range of temperatures (from 15 to 30 deg C)

  20. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    van der Stoep, A.W.; Grzelak, L.A.; Oosterlee, C.W.

    2017-01-01

    We present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant. Finance,