Dynamic bounds coupled with Monte Carlo simulations
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
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.
Stabilization effect of fission source in coupled Monte Carlo simulations
Directory of Open Access Journals (Sweden)
Börge Olsen
2017-08-01
Full Text Available 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.
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)
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 (S_{N}) and stochastic (Monte Carlo) methods are applied. Unlike previous hybrid methods, the Monte Carlo and S_{N} 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 S_{N} is well suited for by themselves. The fully coupled Monte Carlo/S_{N} technique consists of defining spatial and/or energy regions of a problem in which either a Monte Carlo calculation or an S_{N} 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 S_{N} region. The Monte Carlo and S_{N} 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 S_{N} 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 S_{N} 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 S_{N} 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.
A flexible coupling scheme for Monte Carlo and thermal-hydraulics codes
International Nuclear Information System (INIS)
Hoogenboom, J. Eduard; Ivanov, Aleksandar; Sanchez, Victor; Diop, Cheikh
2011-01-01
A coupling scheme between a Monte Carlo code and a thermal-hydraulics code is being developed within the European NURISP project for comprehensive and validated reactor analysis. The scheme is flexible as it allows different Monte Carlo codes and different thermal-hydraulics codes to be used. At present the MCNP and TRIPOLI4 Monte Carlo codes can be used and the FLICA4 and SubChanFlow thermal-hydraulics codes. For all these codes only an original executable is necessary. A Python script drives the iterations between Monte Carlo and thermal-hydraulics calculations. It also calls a conversion program to merge a master input file for the Monte Carlo code with the appropriate temperature and coolant density data from the thermal-hydraulics calculation. Likewise it calls another conversion program to merge a master input file for the thermal-hydraulics code with the power distribution data from the Monte Carlo calculation. Special attention is given to the neutron cross section data for the various required temperatures in the Monte Carlo calculation. Results are shown for an infinite lattice of PWR fuel pin cells and a 3 x 3 fuel BWR pin cell cluster. Various possibilities for further improvement and optimization of the coupling system are discussed. (author)
International Nuclear Information System (INIS)
Han Jingru; Chen Yixue; Yuan Longjun
2013-01-01
The Monte Carlo (MC) and discrete ordinates (SN) are the commonly used methods in the design of radiation shielding. Monte Carlo method is able to treat the geometry exactly, but time-consuming in dealing with the deep penetration problem. The discrete ordinate method has great computational efficiency, but it is quite costly in computer memory and it suffers from ray effect. Single discrete ordinates method or single Monte Carlo method has limitation in shielding calculation for large complex nuclear facilities. In order to solve the problem, the Monte Carlo and discrete ordinates bidirectional coupling method is developed. The bidirectional coupling method is implemented in the interface program to transfer the particle probability distribution of MC and angular flux of discrete ordinates. The coupling method combines the advantages of MC and SN. The test problems of cartesian and cylindrical coordinate have been calculated by the coupling methods. The calculation results are performed with comparison to MCNP and TORT and satisfactory agreements are obtained. The correctness of the program is proved. (authors)
Deficiency in Monte Carlo simulations of coupled neutron-gamma-ray fields
Maleka, Peane P.; Maucec, Marko; de Meijer, Robert J.
2011-01-01
The deficiency in Monte Carlo simulations of coupled neutron-gamma-ray field was investigated by benchmarking two simulation codes with experimental data. Simulations showed better correspondence with the experimental data for gamma-ray transport only. In simulations, the neutron interactions with
International Nuclear Information System (INIS)
Zazula, J.M.
1983-01-01
The general purpose code BALTORO was written for coupling the three-dimensional Monte-Carlo /MC/ with the one-dimensional Discrete Ordinates /DO/ radiation transport calculations. The quantity of a radiation-induced /neutrons or gamma-rays/ nuclear effect or the score from a radiation-yielding nuclear effect can be analysed in this way. (author)
Reactor physics simulations with coupled Monte Carlo calculation and computational fluid dynamics
International Nuclear Information System (INIS)
Seker, V.; Thomas, J.W.; Downar, T.J.
2007-01-01
A computational code system based on coupling the Monte Carlo code MCNP5 and the Computational Fluid Dynamics (CFD) code STAR-CD was developed as an audit tool for lower order nuclear reactor calculations. This paper presents the methodology of the developed computer program 'McSTAR'. McSTAR is written in FORTRAN90 programming language and couples MCNP5 and the commercial CFD code STAR-CD. MCNP uses a continuous energy cross section library produced by the NJOY code system from the raw ENDF/B data. A major part of the work was to develop and implement methods to update the cross section library with the temperature distribution calculated by STARCD for every region. Three different methods were investigated and implemented in McSTAR. The user subroutines in STAR-CD are modified to read the power density data and assign them to the appropriate variables in the program and to write an output data file containing the temperature, density and indexing information to perform the mapping between MCNP and STAR-CD cells. Preliminary testing of the code was performed using a 3x3 PWR pin-cell problem. The preliminary results are compared with those obtained from a STAR-CD coupled calculation with the deterministic transport code DeCART. Good agreement in the k eff and the power profile was observed. Increased computational capabilities and improvements in computational methods have accelerated interest in high fidelity modeling of nuclear reactor cores during the last several years. High-fidelity has been achieved by utilizing full core neutron transport solutions for the neutronics calculation and computational fluid dynamics solutions for the thermal-hydraulics calculation. Previous researchers have reported the coupling of 3D deterministic neutron transport method to CFD and their application to practical reactor analysis problems. One of the principal motivations of the work here was to utilize Monte Carlo methods to validate the coupled deterministic neutron transport
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.
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 ...
Espel, Federico Puente
The main objective of this PhD research is to develop a high accuracy modeling tool using a Monte Carlo based coupled system. The presented research comprises the development of models to include the thermal-hydraulic feedback to the Monte Carlo method and speed-up mechanisms to accelerate the Monte Carlo criticality calculation. Presently, deterministic codes based on the diffusion approximation of the Boltzmann transport equation, coupled with channel-based (or sub-channel based) thermal-hydraulic codes, carry out the three-dimensional (3-D) reactor core calculations of the Light Water Reactors (LWRs). These deterministic codes utilize nuclear homogenized data (normally over large spatial zones, consisting of fuel assembly or parts of fuel assembly, and in the best case, over small spatial zones, consisting of pin cell), which is functionalized in terms of thermal-hydraulic feedback parameters (in the form of off-line pre-generated cross-section libraries). High accuracy modeling is required for advanced nuclear reactor core designs that present increased geometry complexity and material heterogeneity. Such high-fidelity methods take advantage of the recent progress in computation technology and coupled neutron transport solutions with thermal-hydraulic feedback models on pin or even on sub-pin level (in terms of spatial scale). The continuous energy Monte Carlo method is well suited for solving such core environments with the detailed representation of the complicated 3-D problem. The major advantages of the Monte Carlo method over the deterministic methods are the continuous energy treatment and the exact 3-D geometry modeling. However, the Monte Carlo method involves vast computational time. The interest in Monte Carlo methods has increased thanks to the improvements of the capabilities of high performance computers. Coupled Monte-Carlo calculations can serve as reference solutions for verifying high-fidelity coupled deterministic neutron transport methods
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
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.
Energy Technology Data Exchange (ETDEWEB)
O' Brien, M. J.; Brantley, P. S.
2015-01-20
In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2^{21} = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.
Advanced Multilevel Monte Carlo Methods
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.
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.
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
Jiang, Xue; Na, Jin; Lu, Wenxi; Zhang, Yu
2017-11-01
Simulation-optimization techniques are effective in identifying an optimal remediation strategy. Simulation models with uncertainty, primarily in the form of parameter uncertainty with different degrees of correlation, influence the reliability of the optimal remediation strategy. In this study, a coupled Monte Carlo simulation and Copula theory is proposed for uncertainty analysis of a simulation model when parameters are correlated. Using the self-adaptive weight particle swarm optimization Kriging method, a surrogate model was constructed to replace the simulation model and reduce the computational burden and time consumption resulting from repeated and multiple Monte Carlo simulations. The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were employed to identify whether the t Copula function or the Gaussian Copula is the optimal Copula function to match the relevant structure of the parameters. The results show that both the AIC and BIC values of the t Copula function are less than those of the Gaussian Copula function. This indicates that the t Copula function is the optimal function for matching the relevant structure of the parameters. The outputs of the simulation model when parameter correlation was considered and when it was ignored were compared. The results show that the amplitude of the fluctuation interval when parameter correlation was considered is less than the corresponding amplitude when parameter estimation was ignored. Moreover, it was demonstrated that considering the correlation among parameters is essential for uncertainty analysis of a simulation model, and the results of uncertainty analysis should be incorporated into the remediation strategy optimization process.
Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model
International Nuclear Information System (INIS)
Cubasch, U.; Santer, B.D.; Hegerl, G.; Hoeck, H.; Maier-Reimer, E.; Mikolajwicz, U.; Stoessel, A.; Voss, R.
1992-01-01
The Monte Carlo approach, which has increasingly been used during the last decade in the field of extended range weather forecasting, has been applied for climate change experiments. Four integrations with a global coupled ocean-atmosphere model have been started from different initial conditions, but with the same greenhouse gas forcing according to the IPCC scenario A. All experiments have been run for a period of 50 years. The results indicate that the time evolution of the global mean warming depends strongly on the initial state of the climate system. It can vary between 6 and 31 years. The Monte Carlo approach delivers information about both the mean response and the statistical significance of the response. While the individual members of the ensemble show a considerable variation in the climate change pattern of temperature after 50 years, the ensemble mean climate change pattern closely resembles the pattern obtained in a 100 year integration and is, at least over most of the land areas, statistically significant. The ensemble averaged sea-level change due to thermal expansion is significant in the global mean and locally over wide regions of the Pacific. The hydrological cycle is also significantly enhanced in the global mean, but locally the changes in precipitation and soil moisture are masked by the variability of the experiments. (orig.)
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 ...
International Nuclear Information System (INIS)
Derenzo, S.E.; Riles, J.K.
1981-10-01
The high density and atomic number of bismuth germanate (Bi 4 Ge 3 O 12 or BGO) make it a very useful detector for positron emission tomography. Modern tomograph designs use large numbers of small, closely-packed crystals for high spatial resolution and high sensitivity. However, the low light output, the high refractive index (n=2.15), and the need for accurate timing make it important to optimize the transfer of light to the photomultiplier tube (PMT). We describe the results of a Monte Carlo computer program developed to study the effect of crystal shape, reflector type, and the refractive index of the PMT window on coupling efficiency. The program simulates total internal, external, and Fresnel reflection as well as internal absorption and scattering by bubbles
International Nuclear Information System (INIS)
Wu, Xu; Kozlowski, Tomasz
2015-01-01
Highlights: • Coupling of Monte Carlo code Serpent and thermal–hydraulics code RELAP5. • A convergence criterion is developed based on the statistical uncertainty of power. • Correlation between MC statistical uncertainty and coupled error is quantified. • Both UO 2 and MOX single assembly models are used in the coupled simulation. • Validation of coupling results with a multi-group transport code DeCART. - Abstract: Coupled multi-physics approach plays an important role in improving computational accuracy. Compared with deterministic neutronics codes, Monte Carlo codes have the advantage of a higher resolution level. In the present paper, a three-dimensional continuous-energy Monte Carlo reactor physics burnup calculation code, Serpent, is coupled with a thermal–hydraulics safety analysis code, RELAP5. The coupled Serpent/RELAP5 code capability is demonstrated by the improved axial power distribution of UO 2 and MOX single assembly models, based on the OECD-NEA/NRC PWR MOX/UO 2 Core Transient Benchmark. Comparisons of calculation results using the coupled code with those from the deterministic methods, specifically heterogeneous multi-group transport code DeCART, show that the coupling produces more precise results. A new convergence criterion for the coupled simulation is developed based on the statistical uncertainty in power distribution in the Monte Carlo code, rather than ad-hoc criteria used in previous research. The new convergence criterion is shown to be more rigorous, equally convenient to use but requiring a few more coupling steps to converge. Finally, the influence of Monte Carlo statistical uncertainty on the coupled error of power and thermal–hydraulics parameters is quantified. The results are presented such that they can be used to find the statistical uncertainty to use in Monte Carlo in order to achieve a desired precision in coupled simulation
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)
International Nuclear Information System (INIS)
Zazula, J.M.
1984-01-01
This work concerns calculation of a neutron response, caused by a neutron field perturbed by materials surrounding the source or the detector. Solution of a problem is obtained using coupling of the Monte Carlo radiation transport computation for the perturbed region and the discrete ordinates transport computation for the unperturbed system. (author). 62 refs
Coupled electron-ion Monte Carlo simulation of hydrogen molecular crystals
Rillo, Giovanni; Morales, Miguel A.; Ceperley, David M.; Pierleoni, Carlo
2018-03-01
We performed simulations for solid molecular hydrogen at high pressures (250 GPa ≤ P ≤ 500 GPa) along two isotherms at T = 200 K (phase III) and at T = 414 K (phase IV). At T = 200 K, we considered likely candidates for phase III, the C2c and Cmca12 structures, while at T = 414 K in phase IV, we studied the Pc48 structure. We employed both Coupled Electron-Ion Monte Carlo (CEIMC) and Path Integral Molecular Dynamics (PIMD). The latter is based on Density Functional Theory (DFT) with the van der Waals approximation (vdW-DF). The comparison between the two methods allows us to address the question of the accuracy of the exchange-correlation approximation of DFT for thermal and quantum protons without recurring to perturbation theories. In general, we find that atomic and molecular fluctuations in PIMD are larger than in CEIMC which suggests that the potential energy surface from vdW-DF is less structured than the one from quantum Monte Carlo. We find qualitatively different behaviors for systems prepared in the C2c structure for increasing pressure. Within PIMD, the C2c structure is dynamically partially stable for P ≤ 250 GPa only: it retains the symmetry of the molecular centers but not the molecular orientation; at intermediate pressures, it develops layered structures like Pbcn or Ibam and transforms to the metallic Cmca-4 structure at P ≥ 450 GPa. Instead, within CEIMC, the C2c structure is found to be dynamically stable at least up to 450 GPa; at increasing pressure, the molecular bond length increases and the nuclear correlation decreases. For the other two structures, the two methods are in qualitative agreement although quantitative differences remain. We discuss various structural properties and the electrical conductivity. We find that these structures become conducting around 350 GPa but the metallic Drude-like behavior is reached only at around 500 GPa, consistent with recent experimental claims.
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.
Monte Carlo and discrete-ordinate simulations of irradiances in the coupled atmosphere-ocean system.
Gjerstad, Karl Idar; Stamnes, Jakob J; Hamre, Børge; Lotsberg, Jon K; Yan, Banghua; Stamnes, Knut
2003-05-20
We compare Monte Carlo (MC) and discrete-ordinate radiative-transfer (DISORT) simulations of irradiances in a one-dimensional coupled atmosphere-ocean (CAO) system consisting of horizontal plane-parallel layers. The two models have precisely the same physical basis, including coupling between the atmosphere and the ocean, and we use precisely the same atmospheric and oceanic input parameters for both codes. For a plane atmosphere-ocean interface we find agreement between irradiances obtained with the two codes to within 1%, both in the atmosphere and the ocean. Our tests cover case 1 water, scattering by density fluctuations both in the atmosphere and in the ocean, and scattering by particulate matter represented by a one-parameter Henyey-Greenstein (HG) scattering phase function. The CAO-MC code has an advantage over the CAO-DISORT code in that it can handle surface waves on the atmosphere-ocean interface, but the CAO-DISORT code is computationally much faster. Therefore we use CAO-MC simulations to study the influence of ocean surface waves and propose a way to correct the results of the CAO-DISORT code so as to obtain fast and accurate underwater irradiances in the presence of surface waves.
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.
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.
The development of depletion program coupled with Monte Carlo computer code
International Nuclear Information System (INIS)
Nguyen Kien Cuong; Huynh Ton Nghiem; Vuong Huu Tan
2015-01-01
The paper presents the development of depletion code for light water reactor coupled with MCNP5 code called the MCDL code (Monte Carlo Depletion for Light Water Reactor). The first order differential depletion system equations of 21 actinide isotopes and 50 fission product isotopes are solved by the Radau IIA Implicit Runge Kutta (IRK) method after receiving neutron flux, reaction rates in one group energy and multiplication factors for fuel pin, fuel assembly or whole reactor core from the calculation results of the MCNP5 code. The calculation for beryllium poisoning and cooling time is also integrated in the code. To verify and validate the MCDL code, high enriched uranium (HEU) and low enriched uranium (LEU) fuel assemblies VVR-M2 types and 89 fresh HEU fuel assemblies, 92 LEU fresh fuel assemblies cores of the Dalat Nuclear Research Reactor (DNRR) have been investigated and compared with the results calculated by the SRAC code and the MCNP R EBUS linkage system code. The results show good agreement between calculated data of the MCDL code and reference codes. (author)
Continuous Time Monte Carlo for Lattice QCD in the Strong Coupling Limit
Unger, Wolfgang
2011-01-01
We present results for lattice QCD with staggered fermions in the limit of infinite gauge coupling, obtained from a worm-type Monte Carlo algorithm on a discrete spatial lattice but with continuous Euclidean time. This is achieved by sending both the anisotropy parameter $\\gamma^2\\simeq a/\\at$ and the number of time-slices $N_\\tau$ to infinity, keeping the ratio $\\gamma^2/N_\\tau \\simeq aT$ fixed. In this limit, ambiguities arising from the anisotropy parameter $\\gamma$ are eliminated and discretization errors usually introduced by a finite temporal lattice extent $\\Nt$ are absent. The obvious gain is that no continuum extrapolation $N_\\tau \\rightarrow \\infty$ has to be carried out. Moreover, the algorithm is faster and the sign problem disappears completely. As a first application, we determine the phase diagram as a function of temperature and real and imaginary baryon chemical potential. We compare our computations with those on lattices with discrete Euclidean time. Discretization errors due to finite $\\Nt...
ITS, TIGER System of Coupled Electron Photon Transport by Monte-Carlo
International Nuclear Information System (INIS)
Halbleib, J.A.; Mehlhorn, T.A.; Young, M.F.
1996-01-01
1 - Description of program or function: ITS permits a state-of-the-art Monte Carlo solution of linear time-integrated coupled electron/ photon radiation transport problems with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. 2 - Method of solution: Through a machine-portable utility that emulates the basic features of the CDC UPDATE processor, the user selects one of eight codes for running on a machine of one of four (at least) major vendors. With the ITS-3.0 release the PSR-0245/UPEML package is included to perform these functions. The ease with which this utility is applied combines with an input scheme based on order-independent descriptive keywords that makes maximum use of defaults and internal error checking to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Physical rigor is maximized by employing the best available cross sections and sampling distributions, and the most complete physical model for describing the production and transport of the electron/ photon cascade from 1.0 GeV down to 1.0 keV. Flexibility of construction permits the codes to be tailored to specific applications and the capabilities of the codes to be extended to more complex applications through update procedures. 3 - Restrictions on the complexity of the problem: - Restrictions and/or limitations for ITS depend upon the local operating system
ITS Version 6 : the integrated TIGER series of coupled electron/photon Monte Carlo transport codes.
Energy Technology Data Exchange (ETDEWEB)
Franke, Brian Claude; Kensek, Ronald Patrick; Laub, Thomas William
2008-04-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of lineartime-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. Our goal has been to simultaneously maximize operational simplicity and physical accuracy. Through a set of preprocessor directives, the user selects one of the many ITS codes. The ease with which the makefile system is applied combines with an input scheme based on order-independent descriptive keywords that makes maximum use of defaults and internal error checking to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Physical rigor is provided by employing accurate cross sections, sampling distributions, and physical models for describing the production and transport of the electron/photon cascade from 1.0 GeV down to 1.0 keV. The availability of source code permits the more sophisticated user to tailor the codes to specific applications and to extend the capabilities of the codes to more complex applications. Version 6, the latest version of ITS, contains (1) improvements to the ITS 5.0 codes, and (2) conversion to Fortran 90. The general user friendliness of the software has been enhanced through memory allocation to reduce the need for users to modify and recompile the code.
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
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.
Wormhole Hamiltonian Monte Carlo
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...
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
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.
ITS - The integrated TIGER series of coupled electron/photon Monte Carlo transport codes
International Nuclear Information System (INIS)
Halbleib, J.A.; Mehlhorn, T.A.
1985-01-01
The TIGER series of time-independent coupled electron/photon Monte Carlo transport codes is a group of multimaterial, multidimensional codes designed to provide a state-of-the-art description of the production and transport of the electron/photon cascade. The codes follow both electrons and photons from 1.0 GeV down to 1.0 keV, and the user has the option of combining the collisional transport with transport in macroscopic electric and magnetic fields of arbitrary spatial dependence. Source particles can be either electrons or photons. The most important output data are (a) charge and energy deposition profiles, (b) integral and differential escape coefficients for both electrons and photons, (c) differential electron and photon flux, and (d) pulse-height distributions for selected regions of the problem geometry. The base codes of the series differ from one another primarily in their dimensionality and geometric modeling. They include (a) a one-dimensional multilayer code, (b) a code that describes the transport in two-dimensional axisymmetric cylindrical material geometries with a fully three-dimensional description of particle trajectories, and (c) a general three-dimensional transport code which employs a combinatorial geometry scheme. These base codes were designed primarily for describing radiation transport for those situations in which the detailed atomic structure of the transport medium is not important. For some applications, it is desirable to have a more detailed model of the low energy transport. The system includes three additional codes that contain a more elaborate ionization/relaxation model than the base codes. Finally, the system includes two codes that combine the collisional transport of the multidimensional base codes with transport in macroscopic electric and magnetic fields of arbitrary spatial dependence
Energy Technology Data Exchange (ETDEWEB)
Clouet, J.F.; Samba, G. [CEA Bruyeres-le-Chatel, 91 (France)
2005-07-01
We use asymptotic analysis to study the diffusion limit of the Symbolic Implicit Monte-Carlo (SIMC) method for the transport equation. For standard SIMC with piecewise constant basis functions, we demonstrate mathematically that the solution converges to the solution of a wrong diffusion equation. Nevertheless a simple extension to piecewise linear basis functions enables to obtain the correct solution. This improvement allows the calculation in opaque medium on a mesh resolving the diffusion scale much larger than the transport scale. Anyway, the huge number of particles which is necessary to get a correct answer makes this computation time consuming. Thus, we have derived from this asymptotic study an hybrid method coupling deterministic calculation in the opaque medium and Monte-Carlo calculation in the transparent medium. This method gives exactly the same results as the previous one but at a much lower price. We present numerical examples which illustrate the analysis. (authors)
Cullen, D
2000-01-01
TART2000 is a coupled neutron-photon, 3 Dimensional, combinatorial geometry, time dependent Monte Carlo radiation transport code. This code can run on any modern computer. It is a complete system to assist you with input Preparation, running Monte Carlo calculations, and analysis of output results. TART2000 is also incredibly FAST; if you have used similar codes, you will be amazed at how fast this code is compared to other similar codes. Use of the entire system can save you a great deal of time and energy. TART2000 is distributed on CD. This CD contains on-line documentation for all codes included in the system, the codes configured to run on a variety of computers, and many example problems that you can use to familiarize yourself with the system. TART2000 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART2000 and its data files.
International Nuclear Information System (INIS)
Cullen, D.E
2000-01-01
TART2000 is a coupled neutron-photon, 3 Dimensional, combinatorial geometry, time dependent Monte Carlo radiation transport code. This code can run on any modern computer. It is a complete system to assist you with input Preparation, running Monte Carlo calculations, and analysis of output results. TART2000 is also incredibly FAST; if you have used similar codes, you will be amazed at how fast this code is compared to other similar codes. Use of the entire system can save you a great deal of time and energy. TART2000 is distributed on CD. This CD contains on-line documentation for all codes included in the system, the codes configured to run on a variety of computers, and many example problems that you can use to familiarize yourself with the system. TART2000 completely supersedes all older versions of TART, and it is strongly recommended that users only use the most recent version of TART2000 and its data files
Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2014-05-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape
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
Monte carlo simulation for soot dynamics
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.
Tippayakul, Chanatip
The main objective of this research is to develop a practical fuel management system for the Pennsylvania State University Breazeale research reactor (PSBR) based on several advanced Monte Carlo coupled depletion methodologies. Primarily, this research involved two major activities: model and method developments and analyses and validations of the developed models and methods. The starting point of this research was the utilization of the earlier developed fuel management tool, TRIGSIM, to create the Monte Carlo model of core loading 51 (end of the core loading). It was found when comparing the normalized power results of the Monte Carlo model to those of the current fuel management system (using HELIOS/ADMARC-H) that they agreed reasonably well (within 2%--3% differences on average). Moreover, the reactivity of some fuel elements was calculated by the Monte Carlo model and it was compared with measured data. It was also found that the fuel element reactivity results of the Monte Carlo model were in good agreement with the measured data. However, the subsequent task of analyzing the conversion from the core loading 51 to the core loading 52 using TRIGSIM showed quite significant difference of each control rod worth between the Monte Carlo model and the current methodology model. The differences were mainly caused by inconsistent absorber atomic number densities between the two models. Hence, the model of the first operating core (core loading 2) was revised in light of new information about the absorber atomic densities to validate the Monte Carlo model with the measured data. With the revised Monte Carlo model, the results agreed better to the measured data. Although TRIGSIM showed good modeling and capabilities, the accuracy of TRIGSIM could be further improved by adopting more advanced algorithms. Therefore, TRIGSIM was planned to be upgraded. The first task of upgrading TRIGSIM involved the improvement of the temperature modeling capability. The new TRIGSIM was
ITS Version 3.0: The Integrated TIGER Series of coupled electron/photon Monte Carlo transport codes
International Nuclear Information System (INIS)
Halbleib, J.A.; Kensek, R.P.; Valdez, G.D.; Mehlhorn, T.A.; Seltzer, S.M.; Berger, M.J.
1993-01-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of linear time-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields. It combines operational simplicity and physical accuracy in order to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Flexibility of construction permits tailoring of the codes to specific applications and extension of code capabilities to more complex applications through simple update procedures
Jaillon, Franck; Zheng, Wei; Huang, Zhiwei
2008-06-10
In this study, we propose a beveled fiber-optic probe coupled with a half-ball lens for improving the depth-resolved fluorescence measurements of epithelial tissue. The Monte Carlo (MC) simulation results show that for a given excitation-collection fiber separation, the probe design with a bevel-angled collection fiber is more sensitive to detect fluorescence photons emitted from the shallow layer of tissue, whereas the flat-tip collection fiber is in favor of probing fluorescence photons originating from deeper tissue areas. This compact half-ball lens-beveled fiber probe design has the potential to facilitate the depth-resolved fluorescence detection of epithelial tissue.
Dynamic Monte Carlo rate constants for magnetic Hamiltonians coupled to a phonon bath
Solomon, Lazarus; Novotny, Mark
2007-03-01
For quantitative comparisons between experimental time- dependent measurements and dynamic Monte Carlo simulations, a relation between the time constant in the simulation and real time is necessary. We calculate the transition rate for spin S system using the lattice frame method for a rigid spin cluster in an elastic medium [1]. We compare this with the transition rate for an Ising spin 12 system using the quantum- mechanical density-matrix method [2] with the results of ref [1,3]. These transition probabilities are different from those of either the Glauber or the Metropolis dynamics, and reflect the properties of the bosonic bath. Comparison with recent experiments [4] will be discussed. [1] E. M. Chudnovsky, D. A. Garanin, and R. Schilling (PRB 72, 2006) [2] K. Park, M. A. Novotny, and P. A. Rikvold (PRE 66, 2002) [3] K Saito, S. Takesue, and S. Miyashita, (PRE 61, 2002) [4] T. Meunier et al (Condensed Matter, 2006)
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
Metropolis Methods for Quantum Monte Carlo Simulations
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, ...
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
Lectures on Monte Carlo methods
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
Wormhole Hamiltonian Monte Carlo
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
Wormhole Hamiltonian Monte Carlo.
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.
Hidayat, Iki; Sutopo; Pratama, Heru Berian
2017-12-01
The Kerinci geothermal field is one phase liquid reservoir system in the Kerinci District, western part of Jambi Province. In this field, there are geothermal prospects that identified by the heat source up flow inside a National Park area. Kerinci field was planned to develop 1×55 MWe by Pertamina Geothermal Energy. To define reservoir characterization, the numerical simulation of Kerinci field is developed by using TOUGH2 software with information from conceptual model. The pressure and temperature profile well data of KRC-B1 are validated with simulation data to reach natural state condition. The result of the validation is suitable matching. Based on natural state simulation, the resource assessment of Kerinci geothermal field is estimated by using Monte Carlo simulation with the result P10-P50-P90 are 49.4 MW, 64.3 MW and 82.4 MW respectively. This paper is the first study of resource assessment that has been estimated successfully in Kerinci Geothermal Field using numerical simulation coupling with Monte carlo simulation.
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"--
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
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
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.
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 ...
Croce, Pierpaolo; Zappasodi, Filippo; Merla, Arcangelo; Chiarelli, Antonio Maria
2017-08-01
Objective. Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown. Approach. Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF). Main results. We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements. Significance. The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.
Buividovich, P. V.; Davody, A.
2017-12-01
We develop numerical tools for diagrammatic Monte Carlo simulations of non-Abelian lattice field theories in the t'Hooft large-N limit based on the weak-coupling expansion. First, we note that the path integral measure of such theories contributes a bare mass term in the effective action which is proportional to the bare coupling constant. This mass term renders the perturbative expansion infrared-finite and allows us to study it directly in the large-N and infinite-volume limits using the diagrammatic Monte Carlo approach. On the exactly solvable example of a large-N O (N ) sigma model in D =2 dimensions we show that this infrared-finite weak-coupling expansion contains, in addition to powers of bare coupling, also powers of its logarithm, reminiscent of resummed perturbation theory in thermal field theory and resurgent trans-series without exponential terms. We numerically demonstrate the convergence of these double series to the manifestly nonperturbative dynamical mass gap. We then develop a diagrammatic Monte Carlo algorithm for sampling planar diagrams in the large-N matrix field theory, and apply it to study this infrared-finite weak-coupling expansion for large-N U (N ) ×U (N ) nonlinear sigma model (principal chiral model) in D =2 . We sample up to 12 leading orders of the weak-coupling expansion, which is the practical limit set by the increasingly strong sign problem at high orders. Comparing diagrammatic Monte Carlo with conventional Monte Carlo simulations extrapolated to infinite N , we find a good agreement for the energy density as well as for the critical temperature of the "deconfinement" transition. Finally, we comment on the applicability of our approach to planar QCD at zero and finite density.
Multilevel sequential Monte Carlo samplers
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 . âˆž>h0>h1â‹¯>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. Â© 2016 Elsevier B.V.
International Nuclear Information System (INIS)
Rinkel, J.; Dinten, J.M.; Tabary, J.
2004-01-01
The use of focused anti-scatter grids on digital radiographic systems with two-dimensional detectors produces acquisitions with a decreased scatter to primary ratio and thus improved contrast and resolution. Simulation software is of great interest in optimizing grid configuration according to a specific application. Classical simulators are based on complete detailed geometric descriptions of the grid. They are accurate but very time consuming since they use Monte Carlo code to simulate scatter within the high-frequency grids. We propose a new practical method which couples an analytical simulation of the grid interaction with a radiographic system simulation program. First, a two dimensional matrix of probability depending on the grid is created offline, in which the first dimension represents the angle of impact with respect to the normal to the grid lines and the other the energy of the photon. This matrix of probability is then used by the Monte Carlo simulation software in order to provide the final scattered flux image. To evaluate the gain of CPU time, we define the increasing factor as the increase of CPU time of the simulation with as opposed to without the grid. Increasing factors were calculated with the new model and with classical methods representing the grid with its CAD model as part of the object. With the new method, increasing factors are shorter by one to two orders of magnitude compared with the second one. These results were obtained with a difference in calculated scatter of less than five percent between the new and the classical method. (authors)
Multi-Scale Coupling Between Monte Carlo Molecular Simulation and Darcy-Scale Flow in Porous Media
Saad, Ahmed Mohamed
2016-06-01
In this work, an efficient coupling between Monte Carlo (MC) molecular simulation and Darcy-scale flow in porous media is presented. The cell centered finite difference method with non-uniform rectangular mesh were used to discretize the simulation domain and solve the governing equations. To speed up the MC simulations, we implemented a recently developed scheme that quickly generates MC Markov chains out of pre-computed ones, based on the reweighting and reconstruction algorithm. This method astonishingly reduces the required computational times by MC simulations from hours to seconds. To demonstrate the strength of the proposed coupling in terms of computational time efficiency and numerical accuracy in fluid properties, various numerical experiments covering different compressible single-phase flow scenarios were conducted. The novelty in the introduced scheme is in allowing an efficient coupling of the molecular scale and the Darcy\\'s one in reservoir simulators. This leads to an accurate description of thermodynamic behavior of the simulated reservoir fluids; consequently enhancing the confidence in the flow predictions in porous media.
Directory of Open Access Journals (Sweden)
O. El rhazouani
2017-09-01
Full Text Available In the last few years there has been a growing interest in mixed magnetic oxides containing the transition-metal Cr, as they show interesting physical properties and a great ability to use in spintronic, photovoltaic and magnetocaloric applications. Therefore, several publications have appeared documenting Cr-based double perovskites, but very few have explored the promising compounds Ca2CrNO6 (N = Mo, Re. Exchange couplings in Ca2CrNO6 (N = Mo, Re Double perovskites (DPs have been fitted by Monte Carlo Simulation (MCS calculations in the framework of Ising model by using a method based on a relation between internal energy per site and magnetization per site. The exchange couplings JCr−Mo=−1.977meV, JCr−Cr=4.614meV and JMo−Mo=1.481meV have been obtained for Ca2CrMoO6, while JCr−Re=−12.221meV, J'Cr−Cr=11.244meV and JRe-Re=11.492meV have been obtained for Ca2CrReO6. The role of exchange couplings strengths in the magnetism of this class of materials has been discussed. Internal energy per site has been calculated.
Cohen, D; Stamnes, S; Tanikawa, T; Sommersten, E R; Stamnes, J J; Lotsberg, J K; Stamnes, K
2013-04-22
A comparison is presented of two different methods for polarized radiative transfer in coupled media consisting of two adjacent slabs with different refractive indices, each slab being a stratified medium with no change in optical properties except in the direction of stratification. One of the methods is based on solving the integro-differential radiative transfer equation for the two coupled slabs using the discrete ordinate approximation. The other method is based on probabilistic and statistical concepts and simulates the propagation of polarized light using the Monte Carlo approach. The emphasis is on non-Rayleigh scattering for particles in the Mie regime. Comparisons with benchmark results available for a slab with constant refractive index show that both methods reproduce these benchmark results when the refractive index is set to be the same in the two slabs. Computed results for test cases with coupling (different refractive indices in the two slabs) show that the two methods produce essentially identical results for identical input in terms of absorption and scattering coefficients and scattering phase matrices.
Petit, Odile; Jouanne, Cédric; Litaize, Olivier; Serot, Olivier; Chebboubi, Abdelhazize; Pénéliau, Yannick
2017-09-01
TRIPOLI-4® Monte Carlo transport code and FIFRELIN fission model have been coupled by means of external files so that neutron transport can take into account fission distributions (multiplicities and spectra) that are not averaged, as is the case when using evaluated nuclear data libraries. Spectral effects on responses in shielding configurations with fission sampling are then expected. In the present paper, the principle of this coupling is detailed and a comparison between TRIPOLI-4® fission distributions at the emission of fission neutrons is presented when using JEFF-3.1.1 evaluated data or FIFRELIN data generated either through a n/g-uncoupled mode or through a n/g-coupled mode. Finally, an application to a modified version of the ASPIS benchmark is performed and the impact of using FIFRELIN data on neutron transport is analyzed. Differences noticed on average reaction rates on the surfaces closest to the fission source are mainly due to the average prompt fission spectrum. Moreover, when working with the same average spectrum, a complementary analysis based on non-average reaction rates still shows significant differences that point out the real impact of using a fission model in neutron transport simulations.
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
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.
International Nuclear Information System (INIS)
Caribe, Paulo Rauli Rafeson Vasconcelos; Cassola, Vagner Ferreira; Kramer, Richard; Khoury, Helen Jamil
2013-01-01
The use of three-dimensional models described by polygonal meshes in numerical dosimetry enables more accurate modeling of complex objects than the use of simple solid. The objectives of this work were validate the coupling of mesh models to the Monte Carlo code GEANT4 and evaluate the influence of the number of vertices in the simulations to obtain absorbed fractions of energy (AFEs). Validation of the coupling was performed to internal sources of photons with energies between 10 keV and 1 MeV for spherical geometries described by the GEANT4 and three-dimensional models with different number of vertices and triangular or quadrilateral faces modeled using Blender program. As a result it was found that there were no significant differences between AFEs for objects described by mesh models and objects described using solid volumes of GEANT4. Since that maintained the shape and the volume the decrease in the number of vertices to describe an object does not influence so meant dosimetric data, but significantly decreases the time required to achieve the dosimetric calculations, especially for energies less than 100 keV
Monte Carlo and discrete-ordinate simulations of spectral radiances in a coupled air-tissue system.
Hestenes, Kjersti; Nielsen, Kristian P; Zhao, Lu; Stamnes, Jakob J; Stamnes, Knut
2007-04-20
We perform a detailed comparison study of Monte Carlo (MC) simulations and discrete-ordinate radiative-transfer (DISORT) calculations of spectral radiances in a 1D coupled air-tissue (CAT) system consisting of horizontal plane-parallel layers. The MC and DISORT models have the same physical basis, including coupling between the air and the tissue, and we use the same air and tissue input parameters for both codes. We find excellent agreement between radiances obtained with the two codes, both above and in the tissue. Our tests cover typical optical properties of skin tissue at the 280, 540, and 650 nm wavelengths. The normalized volume scattering function for internal structures in the skin is represented by the one-parameter Henyey-Greenstein function for large particles and the Rayleigh scattering function for small particles. The CAT-DISORT code is found to be approximately 1000 times faster than the CAT-MC code. We also show that the spectral radiance field is strongly dependent on the inherent optical properties of the skin tissue.
Energy Technology Data Exchange (ETDEWEB)
Schunert, Sebastian; Schwen, Daniel; Ghassemi, Pedram; Baker, Benjamin; Zabriskie, Adam; Ortensi, Javier; Wang, Yaqi; Gleicher, Frederick; DeHart, Mark; Martineau, Richard
2017-04-01
This work presents a multi-physics, multi-scale approach to modeling the Transient Test Reactor (TREAT) currently prepared for restart at the Idaho National Laboratory. TREAT fuel is made up of microscopic fuel grains (r ˜ 20µm) dispersed in a graphite matrix. The novelty of this work is in coupling a binary collision Monte-Carlo (BCMC) model to the Finite Element based code Moose for solving a microsopic heat-conduction problem whose driving source is provided by the BCMC model tracking fission fragment energy deposition. This microscopic model is driven by a transient, engineering scale neutronics model coupled to an adiabatic heating model. The macroscopic model provides local power densities and neutron energy spectra to the microscpic model. Currently, no feedback from the microscopic to the macroscopic model is considered. TREAT transient 15 is used to exemplify the capabilities of the multi-physics, multi-scale model, and it is found that the average fuel grain temperature differs from the average graphite temperature by 80 K despite the low-power transient. The large temperature difference has strong implications on the Doppler feedback a potential LEU TREAT core would see, and it underpins the need for multi-physics, multi-scale modeling of a TREAT LEU core.
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.
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 ...
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.
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.
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)
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
Mairani, A; Kraemer, M; Sommerer, F; Parodi, K; Scholz, M; Cerutti, F; Ferrari, A; Fasso, A
2010-01-01
Clinical Monte Carlo (MC) calculations for carbon ion therapy have to provide absorbed and RBE-weighted dose. The latter is defined as the product of the dose and the relative biological effectiveness (RBE). At the GSI Helmholtzzentrum fur Schwerionenforschung as well as at the Heidelberg Ion Therapy Center (HIT), the RBE values are calculated according to the local effect model (LEM). In this paper, we describe the approach followed for coupling the FLUKA MC code with the LEM and its application to dose and RBE-weighted dose calculations for a superimposition of two opposed C-12 ion fields as applied in therapeutic irradiations. The obtained results are compared with the available experimental data of CHO (Chinese hamster ovary) cell survival and the outcomes of the GSI analytical treatment planning code TRiP98. Some discrepancies have been observed between the analytical and MC calculations of absorbed physical dose profiles, which can be explained by the differences between the laterally integrated depth-d...
Magro, G.; Dahle, T. J.; Molinelli, S.; Ciocca, M.; Fossati, P.; Ferrari, A.; Inaniwa, T.; Matsufuji, N.; Ytre-Hauge, K. S.; Mairani, A.
2017-05-01
Particle therapy facilities often require Monte Carlo (MC) simulations to overcome intrinsic limitations of analytical treatment planning systems (TPS) related to the description of the mixed radiation field and beam interaction with tissue inhomogeneities. Some of these uncertainties may affect the computation of effective dose distributions; therefore, particle therapy dedicated MC codes should provide both absorbed and biological doses. Two biophysical models are currently applied clinically in particle therapy: the local effect model (LEM) and the microdosimetric kinetic model (MKM). In this paper, we describe the coupling of the NIRS (National Institute for Radiological Sciences, Japan) clinical dose to the FLUKA MC code. We moved from the implementation of the model itself to its application in clinical cases, according to the NIRS approach, where a scaling factor is introduced to rescale the (carbon-equivalent) biological dose to a clinical dose level. A high level of agreement was found with published data by exploring a range of values for the MKM input parameters, while some differences were registered in forward recalculations of NIRS patient plans, mainly attributable to differences with the analytical TPS dose engine (taken as reference) in describing the mixed radiation field (lateral spread and fragmentation). We presented a tool which is being used at the Italian National Center for Oncological Hadrontherapy to support the comparison study between the NIRS clinical dose level and the LEM dose specification.
Mattei, S.; Nishida, K.; Onai, M.; Lettry, J.; Tran, M. Q.; Hatayama, A.
2017-12-01
We present a fully-implicit electromagnetic Particle-In-Cell Monte Carlo collision code, called NINJA, written for the simulation of inductively coupled plasmas. NINJA employs a kinetic enslaved Jacobian-Free Newton Krylov method to solve self-consistently the interaction between the electromagnetic field generated by the radio-frequency coil and the plasma response. The simulated plasma includes a kinetic description of charged and neutral species as well as the collision processes between them. The algorithm allows simulations with cell sizes much larger than the Debye length and time steps in excess of the Courant-Friedrichs-Lewy condition whilst preserving the conservation of the total energy. The code is applied to the simulation of the plasma discharge of the Linac4 H- ion source at CERN. Simulation results of plasma density, temperature and EEDF are discussed and compared with optical emission spectroscopy measurements. A systematic study of the energy conservation as a function of the numerical parameters is presented.
Fathi, K.; Galer, S.; Kirkby, K. J.; Palmans, H.; Nisbet, A.
2017-11-01
The high uncertainty in the Relative Biological Effectiveness (RBE) values of particle therapy beam, which are used in combination with the quantity absorbed dose in radiotherapy, together with the increase in the number of particle therapy centres worldwide necessitate a better understating of the biological effect of such modalities. The present novel study is part of performance testing and development of a micro-calorimeter based on Superconducting QUantum Interference Devices (SQUIDs). Unlike other microdosimetric detectors that are used for investigating the energy distribution, this detector provides a direct measurement of energy deposition at the micrometre scale, that can be used to improve our understanding of biological effects in particle therapy application, radiation protection and environmental dosimetry. Temperature rises of less than 1μK are detectable and when combined with the low specific heat capacity of the absorber at cryogenic temperature, extremely high energy deposition sensitivity of approximately 0.4 eV can be achieved. The detector consists of 3 layers: tissue equivalent (TE) absorber, superconducting (SC) absorber and silicon substrate. Ideally all energy would be absorbed in the TE absorber and heat rise in the superconducting layer would arise due to heat conduction from the TE layer. However, in practice direct particle absorption occurs in all 3 layers and must be corrected for. To investigate the thermal behaviour within the detector, and quantify any possible correction, particle tracks were simulated employing Geant4 (v9.6) Monte Carlo simulations. The track information was then passed to the COMSOL Multiphysics (Finite Element Method) software. The 3D heat transfer within each layer was then evaluated in a time-dependent model. For a statistically reliable outcome, the simulations had to be repeated for a large number of particles. An automated system has been developed that couples Geant4 Monte Carlo output to COMSOL for
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.
(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.
Multilevel sequential Monte-Carlo samplers
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.
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
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
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.
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
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
Adaptive Multilevel Monte Carlo Simulation
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).
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
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
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)
International Nuclear Information System (INIS)
Mairani, A; Brons, S; Parodi, K; Cerutti, F; Ferrari, A; Sommerer, F; Fasso, A; Kraemer, M; Scholz, M
2010-01-01
Clinical Monte Carlo (MC) calculations for carbon ion therapy have to provide absorbed and RBE-weighted dose. The latter is defined as the product of the dose and the relative biological effectiveness (RBE). At the GSI Helmholtzzentrum fuer Schwerionenforschung as well as at the Heidelberg Ion Therapy Center (HIT), the RBE values are calculated according to the local effect model (LEM). In this paper, we describe the approach followed for coupling the FLUKA MC code with the LEM and its application to dose and RBE-weighted dose calculations for a superimposition of two opposed 12 C ion fields as applied in therapeutic irradiations. The obtained results are compared with the available experimental data of CHO (Chinese hamster ovary) cell survival and the outcomes of the GSI analytical treatment planning code TRiP98. Some discrepancies have been observed between the analytical and MC calculations of absorbed physical dose profiles, which can be explained by the differences between the laterally integrated depth-dose distributions in water used as input basic data in TRiP98 and the FLUKA recalculated ones. On the other hand, taking into account the differences in the physical beam modeling, the FLUKA-based biological calculations of the CHO cell survival profiles are found in good agreement with the experimental data as well with the TRiP98 predictions. The developed approach that combines the MC transport/interaction capability with the same biological model as in the treatment planning system (TPS) will be used at HIT to support validation/improvement of both dose and RBE-weighted dose calculations performed by the analytical TPS.
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
Antitwilight II: Monte Carlo simulations.
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°.
Monte Carlo techniques in radiation therapy
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...
Mean field simulation for Monte Carlo integration
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
Energy Technology Data Exchange (ETDEWEB)
Biondo, Elliott D [ORNL; Ibrahim, Ahmad M [ORNL; Mosher, Scott W [ORNL; Grove, Robert E [ORNL
2015-01-01
Detailed radiation transport calculations are necessary for many aspects of the design of fusion energy systems (FES) such as ensuring occupational safety, assessing the activation of system components for waste disposal, and maintaining cryogenic temperatures within superconducting magnets. Hybrid Monte Carlo (MC)/deterministic techniques are necessary for this analysis because FES are large, heavily shielded, and contain streaming paths that can only be resolved with MC. The tremendous complexity of FES necessitates the use of CAD geometry for design and analysis. Previous ITER analysis has required the translation of CAD geometry to MCNP5 form in order to use the AutomateD VAriaNce reducTion Generator (ADVANTG) for hybrid MC/deterministic transport. In this work, ADVANTG was modified to support CAD geometry, allowing hybrid (MC)/deterministic transport to be done automatically and eliminating the need for this translation step. This was done by adding a new ray tracing routine to ADVANTG for CAD geometries using the Direct Accelerated Geometry Monte Carlo (DAGMC) software library. This new capability is demonstrated with a prompt dose rate calculation for an ITER computational benchmark problem using both the Consistent Adjoint Driven Importance Sampling (CADIS) method an the Forward Weighted (FW)-CADIS method. The variance reduction parameters produced by ADVANTG are shown to be the same using CAD geometry and standard MCNP5 geometry. Significant speedups were observed for both neutrons (as high as a factor of 7.1) and photons (as high as a factor of 59.6).
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.)
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
Kovtanyuk, Andrey E.
2012-01-01
Radiative-conductive heat transfer in a medium bounded by two reflecting and radiating plane surfaces is considered. This process is described by a nonlinear system of two differential equations: an equation of the radiative heat transfer and an equation of the conductive heat exchange. The problem is characterized by anisotropic scattering of the medium and by specularly and diffusely reflecting boundaries. For the computation of solutions of this problem, two approaches based on iterative techniques are considered. First, a recursive algorithm based on some modification of the Monte Carlo method is proposed. Second, the diffusion approximation of the radiative transfer equation is utilized. Numerical comparisons of the approaches proposed are given in the case of isotropic scattering. © 2011 Elsevier Ltd. All rights reserved.
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
Monte Carlo Simulation of Phase Transitions
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
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.
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
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)
Nuttin, A.; Capellan, N.; David, S.; Doligez, X.; El Mhari, C.; Méplan, O.
2014-06-01
Safety analysis of innovative reactor designs requires three dimensional modeling to ensure a sufficiently realistic description, starting from steady state. Actual Monte Carlo (MC) neutron transport codes are suitable candidates to simulate large complex geometries, with eventual innovative fuel. But if local values such as power densities over small regions are needed, reliable results get more difficult to obtain within an acceptable computation time. In this scope, NEA has proposed a performance test of full PWR core calculations based on Monte Carlo neutron transport, which we have used to define an optimal detail level for convergence of steady state coupled neutronics. Coupling between MCNP for neutronics and the subchannel code COBRA for thermal-hydraulics has been performed using the C++ tool MURE, developed for about ten years at LPSC and IPNO. In parallel with this study and within the same MURE framework, a simplified code of nodal kinetics based on two-group and few-point diffusion equations has been developed and validated on a typical CANDU LOCA. Methods for the computation of necessary diffusion data have been defined and applied to NU (Nat. U) and Th fuel CANDU after assembly evolutions by MURE. Simplicity of CANDU LOCA model has made possible a comparison of these two fuel behaviours during such a transient.
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
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
International Nuclear Information System (INIS)
Jaillon, Franck; Zheng Wei; Huang Zhiwei
2008-01-01
In this study, we evaluate the feasibility of designing a beveled fiber-optic probe coupled with a ball lens for improving depth-resolved fluorescence measurements of epithelial tissue using Monte Carlo (MC) simulations. The results show that by using the probe configuration with a beveled tip collection fiber and a flat tip excitation fiber associated with a ball lens, discrimination of fluorescence signals generated in different tissue depths is achievable. In comparison with a flat-tip collection fiber, the use of a large bevel angled collection fiber enables a better differentiation between the shallow and deep tissue layers by changing the excitation-collection fiber separations. This work suggests that the beveled fiber-optic probe coupled with a ball lens has the potential to facilitate depth-resolved fluorescence measurements of epithelial tissues
Jaillon, Franck; Zheng, Wei; Huang, Zhiwei
2008-02-21
In this study, we evaluate the feasibility of designing a beveled fiber-optic probe coupled with a ball lens for improving depth-resolved fluorescence measurements of epithelial tissue using Monte Carlo (MC) simulations. The results show that by using the probe configuration with a beveled tip collection fiber and a flat tip excitation fiber associated with a ball lens, discrimination of fluorescence signals generated in different tissue depths is achievable. In comparison with a flat-tip collection fiber, the use of a large bevel angled collection fiber enables a better differentiation between the shallow and deep tissue layers by changing the excitation-collection fiber separations. This work suggests that the beveled fiber-optic probe coupled with a ball lens has the potential to facilitate depth-resolved fluorescence measurements of epithelial tissues.
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
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.
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.)
Adaptive Markov Chain Monte Carlo
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.
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
11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing
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.
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)
Hybrid Monte Carlo methods in computational finance
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
Simulation and the Monte Carlo method
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...
Monte Carlo methods for particle transport
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 ...
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.)
Quantum Monte Carlo approaches for correlated systems
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 ...
Monte Carlo Algorithms for Linear Problems
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...
Multilevel Monte Carlo in Approximate Bayesian Computation
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.
Energy Technology Data Exchange (ETDEWEB)
Li, Wenfang; Du, Jinjin; Wen, Ruijuan; Yang, Pengfei; Li, Gang; Zhang, Tiancai, E-mail: tczhang@sxu.edu.cn [State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Opto-Electronics, Shanxi University, Taiyuan 030006 (China); Liang, Junjun [Department of Physics, Shanxi University, Taiyuan 030006 (China)
2014-03-17
We investigate the transmission of single-atom transits based on a strongly coupled cavity quantum electrodynamics system. By superposing the transit transmissions of a considerable number of atoms, we obtain the absorption spectra of the cavity induced by single atoms and obtain the temperature of the cold atom. The number of atoms passing through the microcavity for each release is also counted, and this number changes exponentially along with the atom temperature. Monte Carlo simulations agree closely with the experimental results, and the initial temperature of the cold atom is determined. Compared with the conventional time-of-flight (TOF) method, this approach avoids some uncertainties in the standard TOF and sheds new light on determining temperature of cold atoms by counting atoms individually in a confined space.
Bayesian statistics and Monte Carlo methods
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.
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
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.)
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.)
Adiabatic optimization versus diffusion Monte Carlo methods
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 .
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
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.
Off-diagonal expansion quantum Monte Carlo.
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.
Off-diagonal expansion quantum Monte Carlo
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.
Random Numbers and Monte Carlo Methods
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.
Monte Carlo strategies in scientific computing
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...
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
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.)
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)
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...
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.)
Monte Carlo applications to radiation shielding problems
International Nuclear Information System (INIS)
Subbaiah, K.V.
2009-01-01
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling of physical and mathematical systems to compute their results. However, basic concepts of MC are both simple and straightforward and can be learned by using a personal computer. Uses of Monte Carlo methods require large amounts of random numbers, and it was their use that spurred the development of pseudorandom number generators, which were far quicker to use than the tables of random numbers which had been previously used for statistical sampling. In Monte Carlo simulation of radiation transport, the history (track) of a particle is viewed as a random sequence of free flights that end with an interaction event where the particle changes its direction of movement, loses energy and, occasionally, produces secondary particles. The Monte Carlo simulation of a given experimental arrangement (e.g., an electron beam, coming from an accelerator and impinging on a water phantom) consists of the numerical generation of random histories. To simulate these histories we need an interaction model, i.e., a set of differential cross sections (DCS) for the relevant interaction mechanisms. The DCSs determine the probability distribution functions (pdf) of the random variables that characterize a track; 1) free path between successive interaction events, 2) type of interaction taking place and 3) energy loss and angular deflection in a particular event (and initial state of emitted secondary particles, if any). Once these pdfs are known, random histories can be generated by using appropriate sampling methods. If the number of generated histories is large enough, quantitative information on the transport process may be obtained by simply averaging over the simulated histories. The Monte Carlo method yields the same information as the solution of the Boltzmann transport equation, with the same interaction model, but is easier to implement. In particular, the simulation of radiation
Automated Monte Carlo biasing for photon-generated electrons near surfaces.
Energy Technology Data Exchange (ETDEWEB)
Franke, Brian Claude; Crawford, Martin James; Kensek, Ronald Patrick
2009-09-01
This report describes efforts to automate the biasing of coupled electron-photon Monte Carlo particle transport calculations. The approach was based on weight-windows biasing. Weight-window settings were determined using adjoint-flux Monte Carlo calculations. A variety of algorithms were investigated for adaptivity of the Monte Carlo tallies. Tree data structures were used to investigate spatial partitioning. Functional-expansion tallies were used to investigate higher-order spatial representations.
Fast sequential Monte Carlo methods for counting and optimization
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
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)
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)
On the use of stochastic approximation Monte Carlo for Monte Carlo integration
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.
Monte Carlo methods in AB initio quantum chemistry quantum Monte Carlo for molecules
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
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
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.
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.
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.)
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
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
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
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...
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....
Design and analysis of Monte Carlo experiments
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
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.
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...
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
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
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.
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.
International Nuclear Information System (INIS)
White, Morgan C.
2000-01-01
The fundamental motivation for the research presented in this dissertation was the need to development a more accurate prediction method for characterization of mixed radiation fields around medical electron accelerators (MEAs). Specifically, a model is developed for simulation of neutron and other particle production from photonuclear reactions and incorporated in the Monte Carlo N-Particle (MCNP) radiation transport code. This extension of the capability within the MCNP code provides for the more accurate assessment of the mixed radiation fields. The Nuclear Theory and Applications group of the Los Alamos National Laboratory has recently provided first-of-a-kind evaluated photonuclear data for a select group of isotopes. These data provide the reaction probabilities as functions of incident photon energy with angular and energy distribution information for all reaction products. The availability of these data is the cornerstone of the new methodology for state-of-the-art mutually coupled photon-neutron transport simulations. The dissertation includes details of the model development and implementation necessary to use the new photonuclear data within MCNP simulations. A new data format has been developed to include tabular photonuclear data. Data are processed from the Evaluated Nuclear Data Format (ENDF) to the new class ''u'' A Compact ENDF (ACE) format using a standalone processing code. MCNP modifications have been completed to enable Monte Carlo sampling of photonuclear reactions. Note that both neutron and gamma production are included in the present model. The new capability has been subjected to extensive verification and validation (V and V) testing. Verification testing has established the expected basic functionality. Two validation projects were undertaken. First, comparisons were made to benchmark data from literature. These calculations demonstrate the accuracy of the new data and transport routines to better than 25 percent. Second, the ability to
Energy Technology Data Exchange (ETDEWEB)
White, Morgan C. [Univ. of Florida, Gainesville, FL (United States)
2000-07-01
The fundamental motivation for the research presented in this dissertation was the need to development a more accurate prediction method for characterization of mixed radiation fields around medical electron accelerators (MEAs). Specifically, a model is developed for simulation of neutron and other particle production from photonuclear reactions and incorporated in the Monte Carlo N-Particle (MCNP) radiation transport code. This extension of the capability within the MCNP code provides for the more accurate assessment of the mixed radiation fields. The Nuclear Theory and Applications group of the Los Alamos National Laboratory has recently provided first-of-a-kind evaluated photonuclear data for a select group of isotopes. These data provide the reaction probabilities as functions of incident photon energy with angular and energy distribution information for all reaction products. The availability of these data is the cornerstone of the new methodology for state-of-the-art mutually coupled photon-neutron transport simulations. The dissertation includes details of the model development and implementation necessary to use the new photonuclear data within MCNP simulations. A new data format has been developed to include tabular photonuclear data. Data are processed from the Evaluated Nuclear Data Format (ENDF) to the new class ''u'' A Compact ENDF (ACE) format using a standalone processing code. MCNP modifications have been completed to enable Monte Carlo sampling of photonuclear reactions. Note that both neutron and gamma production are included in the present model. The new capability has been subjected to extensive verification and validation (V&V) testing. Verification testing has established the expected basic functionality. Two validation projects were undertaken. First, comparisons were made to benchmark data from literature. These calculations demonstrate the accuracy of the new data and transport routines to better than 25 percent. Second
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.
Present Status and Extensions of the Monte Carlo Performance Benchmark
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.
Genetic algorithms and Monte Carlo simulation for optimal plant design
International Nuclear Information System (INIS)
Cantoni, M.; Marseguerra, M.; Zio, E.
2000-01-01
We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown-Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance
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
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)
Multilevel Monte Carlo Approaches for Numerical Homogenization
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.
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
Implementation of Monte Carlo Production in LCG-2
García-Abia, J
2005-01-01
In this note we present the implementation of the CMS Monte Carlo production system on LCG-2. We have introduced novel concepts which have made running the full production chain possible on LCG, from the generation of events to the publication of data for analysis, through all the intermediate steps. We have also coupled production and the CMS data transfer system and made the tools more robust, significantly improving the performance of production in LCG.
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
Monte Carlo modeling of eye iris color
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.
Handbook of Markov chain Monte Carlo
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.
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.)
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
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.
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....
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
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)
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.)
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.)
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.
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)
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
Monte carlo methods and models in finance and insurance
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...
Monte Carlo methods and models in finance and insurance
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...
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
Fensin, Michael Lorne
Monte Carlo-linked depletion methods have gained recent interest due to the ability to more accurately model complex 3-dimesional geometries and better track the evolution of temporal nuclide inventory by simulating the actual physical process utilizing continuous energy coefficients. The integration of CINDER90 into the MCNPX Monte Carlo radiation transport code provides a high-fidelity completely self-contained Monte-Carlo-linked depletion capability in a well established, widely accepted Monte Carlo radiation transport code that is compatible with most nuclear criticality (KCODE) particle tracking features in MCNPX. MCNPX depletion tracks all necessary reaction rates and follows as many isotopes as cross section data permits in order to achieve a highly accurate temporal nuclide inventory solution. This work chronicles relevant nuclear history, surveys current methodologies of depletion theory, details the methodology in applied MCNPX and provides benchmark results for three independent OECD/NEA benchmarks. Relevant nuclear history, from the Oklo reactor two billion years ago to the current major United States nuclear fuel cycle development programs, is addressed in order to supply the motivation for the development of this technology. A survey of current reaction rate and temporal nuclide inventory techniques is then provided to offer justification for the depletion strategy applied within MCNPX. The MCNPX depletion strategy is then dissected and each code feature is detailed chronicling the methodology development from the original linking of MONTEBURNS and MCNP to the most recent public release of the integrated capability (MCNPX 2.6.F). Calculation results of the OECD/NEA Phase IB benchmark, H. B. Robinson benchmark and OECD/NEA Phase IVB are then provided. The acceptable results of these calculations offer sufficient confidence in the predictive capability of the MCNPX depletion method. This capability sets up a significant foundation, in a well established
Energy Technology Data Exchange (ETDEWEB)
Franke, Brian Claude; Kensek, Ronald Patrick; Laub, Thomas William
2005-09-01
ITS is a powerful and user-friendly software package permitting state-of-the-art Monte Carlo solution of linear time-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. Our goal has been to simultaneously maximize operational simplicity and physical accuracy. Through a set of preprocessor directives, the user selects one of the many ITS codes. The ease with which the makefile system is applied combines with an input scheme based on order-independent descriptive keywords that makes maximum use of defaults and internal error checking to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Physical rigor is provided by employing accurate cross sections, sampling distributions, and physical models for describing the production and transport of the electron/photon cascade from 1.0 GeV down to 1.0 keV. The availability of source code permits the more sophisticated user to tailor the codes to specific applications and to extend the capabilities of the codes to more complex applications. Version 5.0, the latest version of ITS, contains (1) improvements to the ITS 3.0 continuous-energy codes, (2) multigroup codes with adjoint transport capabilities, (3) parallel implementations of all ITS codes, (4) a general purpose geometry engine for linking with CAD or other geometry formats, and (5) the Cholla facet geometry library. Moreover, the general user friendliness of the software has been enhanced through increased internal error checking and improved code portability.
Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models
Sato, Toshihiro; Assaad, Fakher F.; Grover, Tarun
2018-03-01
The absence of the negative sign problem in quantum Monte Carlo simulations of spin and fermion systems has different origins. World-line based algorithms for spins require positivity of matrix elements whereas auxiliary field approaches for fermions depend on symmetries such as particle-hole symmetry. For negative-sign-free spin and fermionic systems, we show that one can formulate a negative-sign-free auxiliary field quantum Monte Carlo algorithm that allows Kondo coupling of fermions with the spins. Using this general approach, we study a half-filled Kondo lattice model on the honeycomb lattice with geometric frustration. In addition to the conventional Kondo insulator and antiferromagnetically ordered phases, we find a partial Kondo screened state where spins are selectively screened so as to alleviate frustration, and the lattice rotation symmetry is broken nematically.
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
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)
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
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.)
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...
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
MBR Monte Carlo Simulation in PYTHIA8
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.
Markov chains analytic and Monte Carlo computations
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
Score Bounded Monte-Carlo Tree Search
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.
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
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.
Pseudo-extended Markov chain Monte Carlo
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...
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
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.
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)
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...
Mumford, K. G.; Mustafa, N. A.; Gerhard, J.
2012-12-01
probability of exceedance at community risk receptors was explored. This was accomplished by conducting Monte Carlo suites of simulations of a three-dimensional 1000 m × 500 m × 14 m domain to calculate the probability of exceeding regulatory criteria at different locations. The results allowed comparison of the potential importance of heterogeneity in permeability, sorption, and degradation parameters in risk-based decision making. More than 650 simulations were conducted to investigate different values of mean and variance of permeability, sorption coefficients, degradation rate constants, and correlations between heterogeneous fields. This work showed that greater reductions in source concentration were required to meet regulations for inhalation of indoor air compared to ingestion of groundwater, and that mean concentrations and probabilities of exceedance were more sensitive when evaluated at receptors that were laterally offset from the plume center line.
Liu, Yue; Booth, Jean-Paul; Chabert, Pascal
2018-02-01
A Cartesian-coordinate two-dimensional electrostatic particle-in-cell/Monte Carlo collision (PIC/MCC) plasma simulation code is presented, including a new treatment of charge balance at dielectric boundaries. It is used to simulate an Ar plasma in a symmetric radiofrequency capacitively-coupled parallel-plate reactor with a thick (3.5 cm) dielectric side-wall. The reactor size (12 cm electrode width, 2.5 cm electrode spacing) and frequency (15 MHz) are such that electromagnetic effects can be ignored. The dielectric side-wall effectively shields the plasma from the enhanced electric field at the powered-grounded electrode junction, which has previously been shown to produce locally enhanced plasma density (Dalvie et al 1993 Appl. Phys. Lett. 62 3207–9 Overzet and Hopkins 1993 Appl. Phys. Lett. 63 2484–6 Boeuf and Pitchford 1995 Phys. Rev. E 51 1376–90). Nevertheless, enhanced electron heating is observed in a region adjacent to the dielectric boundary, leading to maxima in ionization rate, plasma density and ion flux to the electrodes in this region, and not at the reactor centre as would otherwise be expected. The axially-integrated electron power deposition peaks closer to the dielectric edge than the electron density. The electron heating components are derived from the PIC/MCC simulations and show that this enhanced electron heating results from increased Ohmic heating in the axial direction as the electron density decreases towards the side-wall. We investigated the validity of different analytical formulas to estimate the Ohmic heating by comparing them to the PIC results. The widespread assumption that a time-averaged momentum transfer frequency, v m , can be used to estimate the momentum change can cause large errors, since it neglects both phase and amplitude information. Furthermore, the classical relationship between the total electron current and the electric field must be used with caution, particularly close to the dielectric edge where the
Chemical accuracy from quantum Monte Carlo for the benzene dimer
Energy Technology Data Exchange (ETDEWEB)
Azadi, Sam, E-mail: s.azadi@ucl.ac.uk [Department of Earth Science and Thomas Young Centre, University College London, London WC1E 6BT (United Kingdom); Cohen, R. E. [London Centre for Nanotechnology, University College London, London WC1E 6BT, United Kingdom and Extreme Materials Initiative, Geophysical Laboratory, Carnegie Institution of Washington, Washington, D.C. 20015 (United States)
2015-09-14
We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of −2.3(4) and −2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is −2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.
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)
Odd-flavor Simulations by the Hybrid Monte Carlo
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.
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
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
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.
Parallel Monte Carlo Search for Hough Transform
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.
Multi-Index Monte Carlo (MIMC)
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).
Multi-Index Monte Carlo (MIMC)
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.
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)
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.)
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
International Nuclear Information System (INIS)
Pham, Quang Trung
2014-01-01
The Monte Carlo simulation methods are successfully being used in various areas of medical physics but also at different scales, for example, from the radiation therapy treatment planning systems to the prediction of the effects of radiation in cancer cells. The Monte Carlo simulation platform GATE based on the Geant4 tool-kit offers features dedicated to simulations in medical physics (nuclear medicine and radiotherapy). For radiobiology applications, the Geant4-DNA physical models are implemented to track particles till very low energy (eV) and are adapted for estimation of micro-dosimetric quantities. In order to implement a multi-scale Monte Carlo platform, we first validated the physical models of Geant4-DNA, and integrated them into GATE. Finally, we validated this implementation in the context of radiation therapy and proton therapy. In order to validate the Geant4-DNA physical models, dose point kernels for monoenergetic electrons (10 keV to 100 keV) were simulated using the physical models of Geant4-DNA and were compared to those simulated with Geant4 Standard physical models and another Monte Carlo code EGSnrc. The range and the stopping powers of electrons (7.4 eV to 1 MeV) and protons (1 keV to 100 MeV) calculated with GATE/Geant4-DNA were then compared with literature. We proposed to simulate with the GATE platform the impact of clinical and preclinical beams on cellular DNA. We modeled a clinical proton beam of 193.1 MeV, 6 MeV clinical electron beam and a X-ray irradiator beam. The beams models were validated by comparing absorbed dose computed and measured in liquid water. Then, the beams were used to calculate the frequency of energy deposits in DNA represented by different geometries. First, the DNA molecule was represented by small cylinders: 2 nm x 2 nm (∼10 bp), 5 nm x 10 nm (nucleosome) and 25 nm x 25 nm (chromatin fiber). All these cylinders were placed randomly in a sphere of liquid water (500 nm radius). Then we reconstructed the DNA
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
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
Monte Carlo advances for the Eolus Asci Project
International Nuclear Information System (INIS)
Hendrick, J. S.; McKinney, G. W.; Cox, L. J.
2000-01-01
The Eolus ASCI project includes parallel, 3-D transport simulation for various nuclear applications. The codes developed within this project provide neutral and charged particle transport, detailed interaction physics, numerous source and tally capabilities, and general geometry packages. One such code is MCNPW which is a general purpose, 3-dimensional, time-dependent, continuous-energy Monte Carlo fully-coupled N-Particle transport code. Significant advances are also being made in the areas of modern software engineering and parallel computing. These advances are described in detail
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.
A Monte Carlo reflectance model for soil surfaces with three-dimensional structure
Cooper, K. D.; Smith, J. A.
1985-01-01
A Monte Carlo soil reflectance model has been developed to study the effect of macroscopic surface irregularities larger than the wavelength of incident flux. The model treats incoherent multiple scattering from Lambertian facets distributed on a periodic surface. Resulting bidirectional reflectance distribution functions are non-Lambertian and compare well with experimental trends reported in the literature. Examples showing the coupling of the Monte Carlo soil model to an adding bidirectional canopy of reflectance model are also given.
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.)
Methods for Monte Carlo simulations of biomacromolecules.
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.
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.
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)
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
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.
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)
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
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.
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
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
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...
Projector Quantum Monte Carlo without minus-sign problem
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
Multiple histogram method and static Monte Carlo sampling
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
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 ...
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 ...
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
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.
Quantum Monte Carlo method for attractive Coulomb potentials
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.
Forest canopy BRDF simulation using Monte Carlo method
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.
Crop canopy BRDF simulation and analysis using Monte Carlo method
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
Efficiency and accuracy of Monte Carlo (importance) sampling
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
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
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 ...
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 ...
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)
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.
Accelerated GPU based SPECT Monte Carlo simulations.
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
Accelerated GPU based SPECT Monte Carlo simulations
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
Monte Carlo modelling of TRIGA research reactor
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.
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)
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.
The computation of Greeks with multilevel Monte Carlo
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...
MCOR - Monte Carlo depletion code for reference LWR calculations
Energy Technology Data Exchange (ETDEWEB)
Puente Espel, Federico, E-mail: fup104@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Tippayakul, Chanatip, E-mail: cut110@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Ivanov, Kostadin, E-mail: kni1@psu.edu [Department of Mechanical and Nuclear Engineering, Pennsylvania State University (United States); Misu, Stefan, E-mail: Stefan.Misu@areva.com [AREVA, AREVA NP GmbH, Erlangen (Germany)
2011-04-15
Research highlights: > Introduction of a reference Monte Carlo based depletion code with extended capabilities. > Verification and validation results for MCOR. > Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations. Additionally
MCOR - Monte Carlo depletion code for reference LWR calculations
International Nuclear Information System (INIS)
Puente Espel, Federico; Tippayakul, Chanatip; Ivanov, Kostadin; Misu, Stefan
2011-01-01
Research highlights: → Introduction of a reference Monte Carlo based depletion code with extended capabilities. → Verification and validation results for MCOR. → Utilization of MCOR for benchmarking deterministic lattice physics (spectral) codes. - Abstract: The MCOR (MCnp-kORigen) code system is a Monte Carlo based depletion system for reference fuel assembly and core calculations. The MCOR code is designed as an interfacing code that provides depletion capability to the LANL Monte Carlo code by coupling two codes: MCNP5 with the AREVA NP depletion code, KORIGEN. The physical quality of both codes is unchanged. The MCOR code system has been maintained and continuously enhanced since it was initially developed and validated. The verification of the coupling was made by evaluating the MCOR code against similar sophisticated code systems like MONTEBURNS, OCTOPUS and TRIPOLI-PEPIN. After its validation, the MCOR code has been further improved with important features. The MCOR code presents several valuable capabilities such as: (a) a predictor-corrector depletion algorithm, (b) utilization of KORIGEN as the depletion module, (c) individual depletion calculation of each burnup zone (no burnup zone grouping is required, which is particularly important for the modeling of gadolinium rings), and (d) on-line burnup cross-section generation by the Monte Carlo calculation for 88 isotopes and usage of the KORIGEN libraries for PWR and BWR typical spectra for the remaining isotopes. Besides the just mentioned capabilities, the MCOR code newest enhancements focus on the possibility of executing the MCNP5 calculation in sequential or parallel mode, a user-friendly automatic re-start capability, a modification of the burnup step size evaluation, and a post-processor and test-matrix, just to name the most important. The article describes the capabilities of the MCOR code system; from its design and development to its latest improvements and further ameliorations
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)
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.
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)
Energy Technology Data Exchange (ETDEWEB)
Rinkel, J.; Dinten, J.M.; Tabary, J
2004-07-01
The use of focused anti-scatter grids on digital radiographic systems with two-dimensional detectors produces acquisitions with a decreased scatter to primary ratio and thus improved contrast and resolution. Simulation software is of great interest in optimizing grid configuration according to a specific application. Classical simulators are based on complete detailed geometric descriptions of the grid. They are accurate but very time consuming since they use Monte Carlo code to simulate scatter within the high-frequency grids. We propose a new practical method which couples an analytical simulation of the grid interaction with a radiographic system simulation program. First, a two dimensional matrix of probability depending on the grid is created offline, in which the first dimension represents the angle of impact with respect to the normal to the grid lines and the other the energy of the photon. This matrix of probability is then used by the Monte Carlo simulation software in order to provide the final scattered flux image. To evaluate the gain of CPU time, we define the increasing factor as the increase of CPU time of the simulation with as opposed to without the grid. Increasing factors were calculated with the new model and with classical methods representing the grid with its CAD model as part of the object. With the new method, increasing factors are shorter by one to two orders of magnitude compared with the second one. These results were obtained with a difference in calculated scatter of less than five percent between the new and the classical method. (authors)
Simulation and the Monte Carlo Method, Student Solutions Manual
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
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....
The Monte Carlo method the method of statistical trials
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
Quantum Monte Carlo study of the Rabi-Hubbard model
Flottat, Thibaut; Hébert, Frédéric; Rousseau, Valéry G.; Batrouni, George Ghassan
2016-10-01
We study, using quantum Monte Carlo (QMC) simulations, the ground state properties of a one dimensional Rabi-Hubbard model. The model consists of a lattice of Rabi systems coupled by a photon hopping term between near neighbor sites. For large enough coupling between photons and atoms, the phase diagram generally consists of only two phases: a coherent phase and a compressible incoherent one separated by a quantum phase transition (QPT). We show that, as one goes deeper in the coherent phase, the system becomes unstable exhibiting a divergence of the number of photons. The Mott phases which are present in the Jaynes-Cummings-Hubbard model are not observed in these cases due to the presence of non-negligible counter-rotating terms. We show that these two models become equivalent only when the detuning is negative and large enough, or if the counter-rotating terms are small enough
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)
Quantum Monte Carlo method for models of molecular nanodevices
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.
Directory of Open Access Journals (Sweden)
S. Palit
2013-09-01
Full Text Available X-ray photons emitted during solar flares cause ionization in the lower ionosphere (~60 to 100 km in excess of what is expected to occur due to a quiet sun. Very low frequency (VLF radio wave signals reflected from the D-region of the ionosphere are affected by this excess ionization. In this paper, we reproduce the deviation in VLF signal strength during solar flares by numerical modeling. We use GEANT4 Monte Carlo simulation code to compute the rate of ionization due to a M-class flare and a X-class flare. The output of the simulation is then used in a simplified ionospheric chemistry model to calculate the time variation of electron density at different altitudes in the D-region of the ionosphere. The resulting electron density variation profile is then self-consistently used in the LWPC code to obtain the time variation of the change in VLF signal. We did the modeling of the VLF signal along the NWC (Australia to IERC/ICSP (India propagation path and compared the results with observations. The agreement is found to be very satisfactory.
Energy Technology Data Exchange (ETDEWEB)
Winnischofer, Herbert; Araujo, Marcio Peres de; Dias Junior, Lauro Camargo; Novo, Joao Batista Marques [Universidade Federal do Parana (UFPR), Curitiba, PR (Brazil)
2010-07-01
A software based in the Monte Carlo method have been developed aiming the teaching of important cases of mechanisms found in luminescence and in excited states decay kinetics, including: multiple decays, consecutive decays and coupled systems decays. The Monte Carlo Method allows the student to easily simulate and visualize the luminescence mechanisms, focusing on the probabilities of the related steps. The software CINESTEX was written for FreeBASIC compiler; it assumes first-order kinetics and any number of excited states, where the pathways are allowed with probabilities assigned by the user. (author)
Quantum Monte Carlo on graphical processing units
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.
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.)
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.
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.)
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.)
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.
Rare event simulation using Monte Carlo methods
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. ...
Parallel Monte Carlo simulation of aerosol dynamics
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.
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.
A continuation multilevel Monte Carlo algorithm
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.
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.
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
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
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)
Bayesian phylogeny analysis via stochastic approximation Monte Carlo
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.
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
Herwig: The Evolution of a Monte Carlo Simulation
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.
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.
Studies of Monte Carlo Modelling of Jets at ATLAS
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.
Multiscale Monte Carlo equilibration: Pure Yang-Mills theory
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.
The sine Gordon model perturbation theory and cluster Monte Carlo
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.
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
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.
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.
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
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.
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
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.
Monte Carlo Volcano Seismic Moment Tensors
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.
Energy Technology Data Exchange (ETDEWEB)
Liang, Jingang; Wang, Kan; Qiu, Yishu [Dept. of Engineering Physics, LiuQing Building, Tsinghua University, Beijing (China); Chai, Xiao Ming; Qiang, Sheng Long [Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu (China)
2016-06-15
Because of prohibitive data storage requirements in large-scale simulations, the memory problem is an obstacle for Monte Carlo (MC) codes in accomplishing pin-wise three-dimensional (3D) full-core calculations, particularly for whole-core depletion analyses. Various kinds of data are evaluated and quantificational total memory requirements are analyzed based on the Reactor Monte Carlo (RMC) code, showing that tally data, material data, and isotope densities in depletion are three major parts of memory storage. The domain decomposition method is investigated as a means of saving memory, by dividing spatial geometry into domains that are simulated separately by parallel processors. For the validity of particle tracking during transport simulations, particles need to be communicated between domains. In consideration of efficiency, an asynchronous particle communication algorithm is designed and implemented. Furthermore, we couple the domain decomposition method with MC burnup process, under a strategy of utilizing consistent domain partition in both transport and depletion modules. A numerical test of 3D full-core burnup calculations is carried out, indicating that the RMC code, with the domain decomposition method, is capable of pin-wise full-core burnup calculations with millions of depletion regions.
Mean field theory of the swap Monte Carlo algorithm.
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.
Bayesian Optimal Experimental Design Using Multilevel Monte Carlo
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.
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
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)
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.
Hybrid Monte-Carlo method for ICF calculations
Energy Technology Data Exchange (ETDEWEB)
Clouet, J.F.; Samba, G. [CEA Bruyeres-le-Chatel, 91 (France)
2003-07-01
) conduction and ray-tracing for laser description. Radiation transport is usually solved by a Monte-Carlo method. In coupling diffusion approximation and transport description, the difficult part comes from the need for an implicit discretization of the emission-absorption terms: this problem was solved by using the symbolic Monte-Carlo method. This means that at each step of the simulation a matrix is computed by a Monte-Carlo method which accounts for the radiation energy exchange between the cells. Because of time step limitation by hydrodynamic motion, energy exchange is limited to a small number of cells and the matrix remains sparse. This matrix is added to usual diffusion matrix for thermal and radiative conductions: finally we arrive at a non-symmetric linear system to invert. A generalized Marshak condition describe the coupling between transport and diffusion. In this paper we will present the principles of the method and numerical simulation of an ICF hohlraum. We shall illustrate the benefits of the method by comparing the results with full implicit Monte-Carlo calculations. In particular we shall show how the spectral cut-off evolves during the propagation of the radiative front in the gold wall. Several issues are still to be addressed (robust algorithm for spectral cut- off calculation, coupling with ALE capabilities): we shall briefly discuss these problems. (authors)
Hybrid Monte-Carlo method for ICF calculations
International Nuclear Information System (INIS)
Clouet, J.F.; Samba, G.
2003-01-01
) conduction and ray-tracing for laser description. Radiation transport is usually solved by a Monte-Carlo method. In coupling diffusion approximation and transport description, the difficult part comes from the need for an implicit discretization of the emission-absorption terms: this problem was solved by using the symbolic Monte-Carlo method. This means that at each step of the simulation a matrix is computed by a Monte-Carlo method which accounts for the radiation energy exchange between the cells. Because of time step limitation by hydrodynamic motion, energy exchange is limited to a small number of cells and the matrix remains sparse. This matrix is added to usual diffusion matrix for thermal and radiative conductions: finally we arrive at a non-symmetric linear system to invert. A generalized Marshak condition describe the coupling between transport and diffusion. In this paper we will present the principles of the method and numerical simulation of an ICF hohlraum. We shall illustrate the benefits of the method by comparing the results with full implicit Monte-Carlo calculations. In particular we shall show how the spectral cut-off evolves during the propagation of the radiative front in the gold wall. Several issues are still to be addressed (robust algorithm for spectral cut- off calculation, coupling with ALE capabilities): we shall briefly discuss these problems. (authors)
Monte Carlo Simulations of Background Spectra in Integral Imager Detectors
Armstrong, T. W.; Colborn, B. L.; Dietz, K. L.; Ramsey, B. D.; Weisskopf, M. C.
1998-01-01
Predictions of the expected gamma-ray backgrounds in the ISGRI (CdTe) and PiCsIT (Csl) detectors on INTEGRAL due to cosmic-ray interactions and the diffuse gamma-ray background have been made using a coupled set of Monte Carlo radiation transport codes (HETC, FLUKA, EGS4, and MORSE) and a detailed, 3-D mass model of the spacecraft and detector assemblies. The simulations include both the prompt background component from induced hadronic and electromagnetic cascades and the delayed component due to emissions from induced radioactivity. Background spectra have been obtained with and without the use of active (BGO) shielding and charged particle rejection to evaluate the effectiveness of anticoincidence counting on background rejection.
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
Applications guide to the MORSE Monte Carlo code
Energy Technology Data Exchange (ETDEWEB)
Cramer, S.N.
1985-08-01
A practical guide for the implementation of the MORESE-CG Monte Carlo radiation transport computer code system is presented. The various versions of the MORSE code are compared and contrasted, and the many references dealing explicitly with the MORSE-CG code are reviewed. The treatment of angular scattering is discussed, and procedures for obtaining increased differentiality of results in terms of reaction types and nuclides from a multigroup Monte Carlo code are explained in terms of cross-section and geometry data manipulation. Examples of standard cross-section data input and output are shown. Many other features of the code system are also reviewed, including (1) the concept of primary and secondary particles, (2) fission neutron generation, (3) albedo data capability, (4) DOMINO coupling, (5) history file use for post-processing of results, (6) adjoint mode operation, (7) variance reduction, and (8) input/output. In addition, examples of the combinatorial geometry are given, and the new array of arrays geometry feature (MARS) and its three-dimensional plotting code (JUNEBUG) are presented. Realistic examples of user routines for source, estimation, path-length stretching, and cross-section data manipulation are given. A deatiled explanation of the coupling between the random walk and estimation procedure is given in terms of both code parameters and physical analogies. The operation of the code in the adjoint mode is covered extensively. The basic concepts of adjoint theory and dimensionality are discussed and examples of adjoint source and estimator user routines are given for all common situations. Adjoint source normalization is explained, a few sample problems are given, and the concept of obtaining forward differential results from adjoint calculations is covered. Finally, the documentation of the standard MORSE-CG sample problem package is reviewed and on-going and future work is discussed.
Su, Lin; Yang, Youming; Bednarz, Bryan; Sterpin, Edmond; Du, Xining; Liu, Tianyu; Ji, Wei; Xu, X. George
2014-01-01
Purpose: Using the graphical processing units (GPU) hardware technology, an extremely fast Monte Carlo (MC) code ARCHERRT is developed for radiation dose calculations in radiation therapy. This paper describes the detailed software development and testing for three clinical TomoTherapy® cases: the prostate, lung, and head & neck. Methods: To obtain clinically relevant dose distributions, phase space files (PSFs) created from optimized radiation therapy treatment plan fluence maps were used as the input to ARCHERRT. Patient-specific phantoms were constructed from patient CT images. Batch simulations were employed to facilitate the time-consuming task of loading large PSFs, and to improve the estimation of statistical uncertainty. Furthermore, two different Woodcock tracking algorithms were implemented and their relative performance was compared. The dose curves of an Elekta accelerator PSF incident on a homogeneous water phantom were benchmarked against DOSXYZnrc. For each of the treatment cases, dose volume histograms and isodose maps were produced from ARCHERRT and the general-purpose code, GEANT4. The gamma index analysis was performed to evaluate the similarity of voxel doses obtained from these two codes. The hardware accelerators used in this study are one NVIDIA K20 GPU, one NVIDIA K40 GPU, and six NVIDIA M2090 GPUs. In addition, to make a fairer comparison of the CPU and GPU performance, a multithreaded CPU code was developed using OpenMP and tested on an Intel E5-2620 CPU. Results: For the water phantom, the depth dose curve and dose profiles from ARCHERRT agree well with DOSXYZnrc. For clinical cases, results from ARCHERRT are compared with those from GEANT4 and good agreement is observed. Gamma index test is performed for voxels whose dose is greater than 10% of maximum dose. For 2%/2mm criteria, the passing rates for the prostate, lung case, and head & neck cases are 99.7%, 98.5%, and 97.2%, respectively. Due to specific architecture of GPU, modified
Su, Lin; Yang, Youming; Bednarz, Bryan; Sterpin, Edmond; Du, Xining; Liu, Tianyu; Ji, Wei; Xu, X George
2014-07-01
Using the graphical processing units (GPU) hardware technology, an extremely fast Monte Carlo (MC) code ARCHERRT is developed for radiation dose calculations in radiation therapy. This paper describes the detailed software development and testing for three clinical TomoTherapy® cases: the prostate, lung, and head & neck. To obtain clinically relevant dose distributions, phase space files (PSFs) created from optimized radiation therapy treatment plan fluence maps were used as the input to ARCHERRT. Patient-specific phantoms were constructed from patient CT images. Batch simulations were employed to facilitate the time-consuming task of loading large PSFs, and to improve the estimation of statistical uncertainty. Furthermore, two different Woodcock tracking algorithms were implemented and their relative performance was compared. The dose curves of an Elekta accelerator PSF incident on a homogeneous water phantom were benchmarked against DOSXYZnrc. For each of the treatment cases, dose volume histograms and isodose maps were produced from ARCHERRT and the general-purpose code, GEANT4. The gamma index analysis was performed to evaluate the similarity of voxel doses obtained from these two codes. The hardware accelerators used in this study are one NVIDIA K20 GPU, one NVIDIA K40 GPU, and six NVIDIA M2090 GPUs. In addition, to make a fairer comparison of the CPU and GPU performance, a multithreaded CPU code was developed using OpenMP and tested on an Intel E5-2620 CPU. For the water phantom, the depth dose curve and dose profiles from ARCHERRT agree well with DOSXYZnrc. For clinical cases, results from ARCHERRT are compared with those from GEANT4 and good agreement is observed. Gamma index test is performed for voxels whose dose is greater than 10% of maximum dose. For 2%/2mm criteria, the passing rates for the prostate, lung case, and head & neck cases are 99.7%, 98.5%, and 97.2%, respectively. Due to specific architecture of GPU, modified Woodcock tracking algorithm
Advanced Mesh-Enabled Monte carlo capability for Multi-Physics Reactor Analysis
Energy Technology Data Exchange (ETDEWEB)
Wilson, Paul; Evans, Thomas; Tautges, Tim
2012-12-24
This project will accumulate high-precision fluxes throughout reactor geometry on a non- orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well
Nonlinear Spatial Inversion Without Monte Carlo Sampling
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
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
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.
REVIEW: Fifty years of Monte Carlo simulations for medical physics
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.
Numerical integration of detector response functions via Monte Carlo simulations
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.
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
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
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
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
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)
Monte Carlo dose calculations in advanced radiotherapy
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
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
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.
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
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.
Exploring cluster Monte Carlo updates with Boltzmann machines.
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.
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
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.
Exploring cluster Monte Carlo updates with Boltzmann machines
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.
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
Fixed forced detection for fast SPECT Monte-Carlo simulation
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.
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)
Monte Carlo Simulation in Statistical Physics An Introduction
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 ...
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)
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.
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.
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)
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
Molecular dynamics algorithms for quantum Monte Carlo methods
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.
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....
Monte Carlo Form-Finding Method for Tensegrity Structures
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.
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.
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
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
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...
Novel Quantum Monte Carlo Approaches for Quantum Liquids
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
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.
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.
Monte Carlo simulation of the OCP freezing transition
International Nuclear Information System (INIS)
DeWitt, H.E.; Slattery, W.L.; Yang, Juxing
1992-09-01
The One Component Plasma (OCP) in three dimensions is a system of classical point charges moving in a fixed uniform neutralizing background. In nature the OCP is a rough approximation of the conditions in a white dwarf star in which one has fully ionized nuclei such as carbon, oxygen, and smaller amounts of heavier elements up to iron all moving in a nearly uniform background provided by relativistically degenerate electrons. The OCP is also a mathematical limiting model for a non-neutral plasma of ions in a Penning trap and cooled to strongly coupled conditions. Similarly, a collection of charge colloidal suspensions in water can exhibit the Coulomb freezing behavior of the OCP. A single dimensionless parameter, Γ is sufficient to describe the system. For very weak coupling, Γ much-lt 1, the thermodynamic properties of the OCP are given rigorously by the Debye-Huckel theory. This paper reports on Monte Carlo simulation of the freezing of the OCP from a random start for particle numbers ranging from 500 to 2000. In one case the authors obtained a perfect bcc lattice, but in most cases the final state would be an imperfect crystal or two different microcrystals, fcc and bcc, growing into each other. With a cluster analysis program the authors looked at the formation of nucleating clusters, and followed the actual freezing process. Roughly 80 particles are needed in a cluster before it starts to grow rapidly and freeze
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
Directory of Open Access Journals (Sweden)
Liang Li
2016-06-01
Full Text Available Monte Carlo simulations were performed for three-dimensional Ising model to study the relationships between magnetic Barkhausen noise and elastic stress of steel. The magnetization process was simulated and the dimensionless magnetic Barkhausen noise was calculated by the differentiation of magnetization. Coupling constant of energy exchange in Ising model is considered to be inversely proportional to applied tensile stress. The simulation results show that as coupling constant decreases, the magnetic Barkhausen noise increases, as proved by the experimental results.
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.)
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.)
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)
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.)
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
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)
Monte Carlo Simulation of Partially Confined Flexible Polymers
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
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 ...
Direct determination of liquid phase coexistence by Monte Carlo simulations
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.
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.
A separable shadow Hamiltonian hybrid Monte Carlo method
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).
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 ...
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)
A novel Monte Carlo approach to hybrid local volatility models
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.
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 ...
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...
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
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.
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)
A novel Monte Carlo approach to hybrid local volatility models
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,
Tackling the premature convergence problem in Monte-Carlo localization
Kootstra, Gert; de Boer, Bart
2009-01-01
Monte-Carlo localization uses particle filtering to estimate the position of the robot. The method is known to suffer from the loss of potential positions when there is ambiguity present in the environment. Since many indoor environments are highly symmetric, this problem of premature convergence is
Monte Carlo simulation models of breeding-population advancement.
J.N. King; G.R. Johnson
1993-01-01
Five generations of population improvement were modeled using Monte Carlo simulations. The model was designed to address questions that are important to the development of an advanced generation breeding population. Specifically we addressed the effects on both gain and effective population size of different mating schemes when creating a recombinant population for...
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)
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 ...
A Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
Mean and standard deviation values, as well as probability density function of ground surface responses due to the dislocation are computed. Based on analytical and numerical calculation of dislocation, two approaches of Monte Carlo simulations are proposed. Various comparisons are examined to illustrate the capability ...
Faster comparison of stopping times by nested conditional Monte Carlo
Dickmann, Fabian; Schweizer, Nikolaus
2016-01-01
We show that deliberately introducing a nested simulation stage can lead to significant variance reductions when comparing two stopping times by Monte Carlo. We derive the optimal number of nested simulations and prove that the algorithm is remarkably robust to misspecifications of this number. The
Monte Carlo simulation of quantum statistical lattice models
Raedt, Hans De; Lagendijk, Ad
1985-01-01
In this article we review recent developments in computational methods for quantum statistical lattice problems. We begin by giving the necessary mathematical basis, the generalized Trotter formula, and discuss the computational tools, exact summations and Monte Carlo simulation, that will be used
Monte Carlo simulations of the stability of delta-Pu
DEFF Research Database (Denmark)
Landa, A.; Soderlind, P.; Ruban, Andrei
2003-01-01
The transition temperature (T-c) for delta-Pu has been calculated for the first time. A Monte Carlo method is employed for this purpose and the effective cluster interactions are obtained from first-principles calculations incorporated with the Connolly-Williams and generalized perturbation methods...
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 ...
Monte Carlo studies of nuclei and quantum liquid drops
Energy Technology Data Exchange (ETDEWEB)
Pandharipande, V.R.; Pieper, S.C.
1989-01-01
The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs.
Variational Monte Carlo calculations of few-body nuclei
International Nuclear Information System (INIS)
Wiringa, R.B.
1986-01-01
The variational Monte Carlo method is described. Results for the binding energies, density distributions, momentum distributions, and static longitudinal structure functions of the 3 H, 3 He, and 4 He ground states, and for the energies of the low-lying scattering states in 4 He are presented. 25 refs., 3 figs
Monte Carlo studies of nuclei and quantum liquid drops
International Nuclear Information System (INIS)
Pandharipande, V.R.; Pieper, S.C.
1989-01-01
The progress in application of variational and Green's function Monte Carlo methods to nuclei is reviewed. The nature of single-particle orbitals in correlated quantum liquid drops is discussed, and it is suggested that the difference between quasi-particle and mean-field orbitals may be of importance in nuclear structure physics. 27 refs., 7 figs., 2 tabs
Variational Monte Carlo calculations of few-body nuclei
Energy Technology Data Exchange (ETDEWEB)
Wiringa, R.B.
1986-01-01
The variational Monte Carlo method is described. Results for the binding energies, density distributions, momentum distributions, and static longitudinal structure functions of the /sup 3/H, /sup 3/He, and /sup 4/He ground states, and for the energies of the low-lying scattering states in /sup 4/He are presented. 25 refs., 3 figs.
A Monte Carlo adapted finite element method for dislocation ...
Indian Academy of Sciences (India)
Dislocation modelling of an earthquake fault is of great importance due to the fact that ground surface response may be predicted by the model. However, geological features of a fault cannot be measured exactly, and therefore these features and data involve uncertainties. This paper presents a Monte Carlo based random ...
SPANDY: a Monte Carlo program for gas target scattering geometry
International Nuclear Information System (INIS)
Jarmie, N.; Jett, J.H.; Niethammer, A.C.
1977-02-01
A Monte Carlo computer program is presented that simulates a two-slit gas target scattering geometry. The program is useful in estimating effects due to finite geometry and multiple scattering in the target foil. Details of the program are presented and experience with a specific example is discussed
Strain in the mesoscale kinetic Monte Carlo model for sintering
DEFF Research Database (Denmark)
Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.
2014-01-01
Shrinkage strains measured from microstructural simulations using the mesoscale kinetic Monte Carlo (kMC) model for solid state sintering are discussed. This model represents the microstructure using digitized discrete sites that are either grain or pore sites. The algorithm used to simulate dens...
The Use of Monte Carlo Techniques to Teach Probability.
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…
Monte Carlo event generators for hadron-hadron collisions
Energy Technology Data Exchange (ETDEWEB)
Knowles, I.G. [Argonne National Lab., IL (United States). High Energy Physics Div.; Protopopescu, S.D. [Brookhaven National Lab., Upton, NY (United States)
1993-06-01
A brief review of Monte Carlo event generators for simulating hadron-hadron collisions is presented. Particular emphasis is placed on comparisons of the approaches used to describe physics elements and identifying their relative merits and weaknesses. This review summarizes a more detailed report.
Fitting experimental data by using weighted Monte Carlo events
International Nuclear Information System (INIS)
Stojnev, S.
2003-01-01
A method for fitting experimental data using modified Monte Carlo (MC) sample is developed. It is intended to help when a single finite MC source has to fit experimental data looking for parameters in a certain underlying theory. The extraction of the searched parameters, the errors estimation and the goodness-of-fit testing is based on the binned maximum likelihood method
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
Multi-microcomputer system for Monte-Carlo calculations
Berg, B; Krasemann, H
1981-01-01
The authors propose a microcomputer system that allows parallel processing for Monte Carlo calculations in lattice gauge theories, simulations of high energy physics experiments and many other fields of current interest. The master-n-slave multiprocessor system is based on the Motorola MC 6800 microprocessor. One attraction of this processor is that it allows up to 16 M Byte random access memory.
forecasting with nonlinear time series model: a monte-carlo ...
African Journals Online (AJOL)
PUBLICATIONS1
with nonlinear time series model by comparing the RMSE with the traditional bootstrap and. Monte-Carlo method of forecasting. We use the logistic smooth transition autoregressive. (LSTAR) model as a case study. We first consider a linear model called the AR. (p) model of order p which satisfies the follow- ing linear ...
Control Variates for Monte Carlo Valuation of American Options
DEFF Research Database (Denmark)
Rasmussen, Nicki S.
2005-01-01
This paper considers two applications of control variates to the Monte Carlo valuation of American options. The main contribution of the paper lies in the particular choice of a control variate for American or Bermudan options. It is shown that for any martingale process used as a control variate...
Monte Carlo Generation of the 2BN Bremsstrahlung Distribution
Peralta, L; Trindade, A
2003-01-01
The 2BN bremsstrahlung cross-section is a well-adapted distribution to describe the radiative processes at low electron kinetic energy (Ek<500 keV). In this work a method to implement this distribution in a Monte Carlo generator is developed.
Monte Carlo simulation with the Gate software using grid computing
International Nuclear Information System (INIS)
Reuillon, R.; Hill, D.R.C.; Gouinaud, C.; El Bitar, Z.; Breton, V.; Buvat, I.
2009-03-01
Monte Carlo simulations are widely used in emission tomography, for protocol optimization, design of processing or data analysis methods, tomographic reconstruction, or tomograph design optimization. Monte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the 'Multiple Replications In Parallel' approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-science), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses. (authors)
Monte Carlo methods of PageRank computation
Litvak, Nelli
2004-01-01
We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink
Osmotic pressure of ring polymer solutions : A Monte Carlo study
Flikkema, Edwin; Brinke, Gerrit ten
2000-01-01
Using the wall theorem, the osmotic pressure of ring polymers in solution has been determined using an off-lattice topology conserving Monte Carlo algorithm. The ring polymers are modeled as freely-jointed chains with point-like beads, i.e., under conditions corresponding to θ-conditions for the
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 ...
Direct Monte Carlo simulation of nanoscale mixed gas bearings
Directory of Open Access Journals (Sweden)
Kyaw Sett Myo
2015-06-01
Full Text Available The conception of sealed hard drives with helium gas mixture has been recently suggested over the current hard drives for achieving higher reliability and less position error. Therefore, it is important to understand the effects of different helium gas mixtures on the slider bearing characteristics in the head–disk interface. In this article, the helium/air and helium/argon gas mixtures are applied as the working fluids and their effects on the bearing characteristics are studied using the direct simulation Monte Carlo method. Based on direct simulation Monte Carlo simulations, the physical properties of these gas mixtures such as mean free path and dynamic viscosity are achieved and compared with those obtained from theoretical models. It is observed that both results are comparable. Using these gas mixture properties, the bearing pressure distributions are calculated under different fractions of helium with conventional molecular gas lubrication models. The outcomes reveal that the molecular gas lubrication results could have relatively good agreement with those of direct simulation Monte Carlo simulations, especially for pure air, helium, or argon gas cases. For gas mixtures, the bearing pressures predicted by molecular gas lubrication model are slightly larger than those from direct simulation Monte Carlo simulation.
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 ...
Monte Carlo simulations of ionization potential depression in dense plasmas
Czech Academy of Sciences Publication Activity Database
Stránský, Michal
2016-01-01
Roč. 23, č. 1 (2016), 1-5, č. článku 012708. ISSN 1070-664X R&D Projects: GA MŠk LG15013 Institutional support: RVO:68378271 Keywords : Monte Carlo methods * aluminium * plasma temperature * computer modeling * ionization Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 2.115, year: 2016
Adaptive sample map for Monte Carlo ray tracing
Teng, Jun; Luo, Lixin; Chen, Zhibo
2010-07-01
Monte Carlo ray tracing algorithm is widely used by production quality renderers to generate synthesized images in films and TV programs. Noise artifact exists in synthetic images generated by Monte Carlo ray tracing methods. In this paper, a novel noise artifact detection and noise level representation method is proposed. We first apply discrete wavelet transform (DWT) on a synthetic image; the high frequency sub-bands of the DWT result encode the noise information. The sub-bands coefficients are then combined to generate a noise level description of the synthetic image, which is called noise map in the paper. This noise map is then subdivided into blocks for robust noise level metric calculation. Increasing the samples per pixel in Monte Carlo ray tracer can reduce the noise of a synthetic image to visually unnoticeable level. A noise-to-sample number mapping algorithm is thus performed on each block of the noise map, higher noise value is mapped to larger sample number, and lower noise value is mapped to smaller sample number, the result of mapping is called sample map. Each pixel in a sample map can be used by Monte Carlo ray tracer to reduce the noise level in the corresponding block of pixels in a synthetic image. However, this block based scheme produces blocky artifact as appeared in video and image compression algorithms. We use Gaussian filter to smooth the sample map, the result is adaptive sample map (ASP). ASP serves two purposes in rendering process; its statistics information can be used as noise level metric in synthetic image, and it can also be used by a Monte Carlo ray tracer to refine the synthetic image adaptively in order to reduce the noise to unnoticeable level but with less rendering time than the brute force method.
Reconstruction of Human Monte Carlo Geometry from Segmented Images
Zhao, Kai; Cheng, Mengyun; Fan, Yanchang; Wang, Wen; Long, Pengcheng; Wu, Yican
2014-06-01
Human computational phantoms have been used extensively for scientific experimental analysis and experimental simulation. This article presented a method for human geometry reconstruction from a series of segmented images of a Chinese visible human dataset. The phantom geometry could actually describe detailed structure of an organ and could be converted into the input file of the Monte Carlo codes for dose calculation. A whole-body computational phantom of Chinese adult female has been established by FDS Team which is named Rad-HUMAN with about 28.8 billion voxel number. For being processed conveniently, different organs on images were segmented with different RGB colors and the voxels were assigned with positions of the dataset. For refinement, the positions were first sampled. Secondly, the large sums of voxels inside the organ were three-dimensional adjacent, however, there were not thoroughly mergence methods to reduce the cell amounts for the description of the organ. In this study, the voxels on the organ surface were taken into consideration of the mergence which could produce fewer cells for the organs. At the same time, an indexed based sorting algorithm was put forward for enhancing the mergence speed. Finally, the Rad-HUMAN which included a total of 46 organs and tissues was described by the cuboids into the Monte Carlo Monte Carlo Geometry for the simulation. The Monte Carlo geometry was constructed directly from the segmented images and the voxels was merged exhaustively. Each organ geometry model was constructed without ambiguity and self-crossing, its geometry information could represent the accuracy appearance and precise interior structure of the organs. The constructed geometry largely retaining the original shape of organs could easily be described into different Monte Carlo codes input file such as MCNP. Its universal property was testified and high-performance was experimentally verified
Mukumoto, Nobutaka; Tsujii, Katsutomo; Saito, Susumu; Yasunaga, Masayoshi; Takegawa, Hideki; Yamamoto, Tokihiro; Numasaki, Hodaka; Teshima, Teruki
2009-10-01
To develop an infrastructure for the integrated Monte Carlo verification system (MCVS) to verify the accuracy of conventional dose calculations, which often fail to accurately predict dose distributions, mainly due to inhomogeneities in the patient's anatomy, for example, in lung and bone. The MCVS consists of the graphical user interface (GUI) based on a computational environment for radiotherapy research (CERR) with MATLAB language. The MCVS GUI acts as an interface between the MCVS and a commercial treatment planning system to import the treatment plan, create MC input files, and analyze MC output dose files. The MCVS consists of the EGSnrc MC codes, which include EGSnrc/BEAMnrc to simulate the treatment head and EGSnrc/DOSXYZnrc to calculate the dose distributions in the patient/phantom. In order to improve computation time without approximations, an in-house cluster system was constructed. The phase-space data of a 6-MV photon beam from a Varian Clinac unit was developed and used to establish several benchmarks under homogeneous conditions. The MC results agreed with the ionization chamber measurements to within 1%. The MCVS GUI could import and display the radiotherapy treatment plan created by the MC method and various treatment planning systems, such as RTOG and DICOM-RT formats. Dose distributions could be analyzed by using dose profiles and dose volume histograms and compared on the same platform. With the cluster system, calculation time was improved in line with the increase in the number of central processing units (CPUs) at a computation efficiency of more than 98%. Development of the MCVS was successful for performing MC simulations and analyzing dose distributions.
Clear-PEM system counting rates: a Monte Carlo study
Rodrigues, P.; Trindade, A.; Varela, J.
2007-01-01
Positron Emission Mammography (PEM) with 18F-Fluorodeoxyglucose (18F-FDG) is a functional imaging technique for breast cancer detection. The development of dedicated imaging systems with high sensitivity and spatial resolution are crucial for early breast cancer diagnosis and an efficient therapy. Clear-PEM is a dual planar scanner designed for high-resolution breast cancer imaging under development by the Portuguese PET Mammography consortium within the Crystal Clear Collaboration. It brings together a favorable combination of high-density scintillator crystals coupled to compact photodetectors, arranged in a double readout scheme capable of providing depth-of-interaction information. A Monte Carlo study of the Clear-PEM system counting rates is presented in this paper. Hypothetical breast exam scenarios were simulated to estimate the single event rates, true and random coincidence rates. A realistic description of the patient and detector geometry, radiation environment, physics and instrumentation factors was adopted in this work. Special attention was given to the 18F-FDG accumulation in the patient torso organs which, for the Clear-PEM scanner, represent significant activity outside the field-of-view (FOV) contributing to an increase of singles, randoms and scattered coincidences affecting the overall system performance. The potential benefits of patient shielding to minimize the influence of the out-of-field background was explored. The influence of LYSO:Ce crystal intrinsic natural activity due to the presence of the 176Lu isotope on the counting rate performance of the proposed scanner, was also investigated.
Quantum Monte Carlo studies of superfluid Fermi gases
International Nuclear Information System (INIS)
Chang, S.Y.; Pandharipande, V.R.; Carlson, J.; Schmidt, K.E.
2004-01-01
We report results of quantum Monte Carlo calculations of the ground state of dilute Fermi gases with attractive short-range two-body interactions. The strength of the interaction is varied to study different pairing regimes which are characterized by the product of the s-wave scattering length and the Fermi wave vector, ak F . We report results for the ground-state energy, the pairing gap Δ, and the quasiparticle spectrum. In the weak-coupling regime, 1/ak F FG . When a>0, the interaction is strong enough to form bound molecules with energy E mol . For 1/ak F > or approx. 0.5, we find that weakly interacting composite bosons are formed in the superfluid gas with Δ and gas energy per particle approaching E mol /2. In this region, we seem to have Bose-Einstein condensation (BEC) of molecules. The behavior of the energy and the gap in the BCS-to-BEC transition region, -0.5 F <0.5, is discussed
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
DDMC simulation, a quantity that is required to calculate correct fluid motion in coupled radiation-hydrodynamics problems. With a set of numerical examples, we demonstrate that our improved DDMC method is accurate and can provide efficiency gains of several orders of magnitude over standard Monte Carlo
Uniform distribution and quasi-Monte Carlo methods discrepancy, integration and applications
Kritzer, Peter; Pillichshammer, Friedrich; Winterhof, Arne
2014-01-01
The survey articles in this book focus on number theoretic point constructions, uniform distribution theory, and quasi-Monte Carlo methods. As deterministic versions of the Monte Carlo method, quasi-Monte Carlo rules enjoy increasing popularity, with many fruitful applications in mathematical practice, as for example in finance, computer graphics, and biology.
The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature
Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V
2010-01-01
A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.
Lattice gauge theory and Monte Carlo methods
International Nuclear Information System (INIS)
Creutz, M.
1988-11-01
Lattice gauge theory is now the primary non-perturbative technique for quantum field theory. The lattice represents an ultraviolet cutoff, and renormalization group arguments show how the bare coupling must be varied to obtain the continuum limit. Expansions in the inverse of the coupling constant demonstrate quark confinement in the strong coupling limit. Numerical simulation has become the approach to calculating hadronic properties. The basic algorithms for obtaining appropriately weighted gauge field configurations are discussed. Algorithms for treating fermionic fields, which still require considerably more computer time than needed for purely bosonic simulations, are also discussed. Some particularly promising recent approaches are based on global accept-reject steps and should display a rather favorable dependence of computer time on the system volume. 39 refs
Path integral Monte Carlo and the electron gas
Brown, Ethan W.
Path integral Monte Carlo is a proven method for accurately simulating quantum mechanical systems at finite-temperature. By stochastically sampling Feynman's path integral representation of the quantum many-body density matrix, path integral Monte Carlo includes non-perturbative effects like thermal fluctuations and particle correlations in a natural way. Over the past 30 years, path integral Monte Carlo has been successfully employed to study the low density electron gas, high-pressure hydrogen, and superfluid helium. For systems where the role of Fermi statistics is important, however, traditional path integral Monte Carlo simulations have an exponentially decreasing efficiency with decreased temperature and increased system size. In this thesis, we work towards improving this efficiency, both through approximate and exact methods, as specifically applied to the homogeneous electron gas. We begin with a brief overview of the current state of atomic simulations at finite-temperature before we delve into a pedagogical review of the path integral Monte Carlo method. We then spend some time discussing the one major issue preventing exact simulation of Fermi systems, the sign problem. Afterwards, we introduce a way to circumvent the sign problem in PIMC simulations through a fixed-node constraint. We then apply this method to the homogeneous electron gas at a large swatch of densities and temperatures in order to map out the warm-dense matter regime. The electron gas can be a representative model for a host of real systems, from simple medals to stellar interiors. However, its most common use is as input into density functional theory. To this end, we aim to build an accurate representation of the electron gas from the ground state to the classical limit and examine its use in finite-temperature density functional formulations. The latter half of this thesis focuses on possible routes beyond the fixed-node approximation. As a first step, we utilize the variational
Research on reactor physics analysis method based on Monte Carlo homogenization
International Nuclear Information System (INIS)
Ye Zhimin; Zhang Peng
2014-01-01
In order to meet the demand of nuclear energy market in the future, many new concepts of nuclear energy systems has been put forward. The traditional deterministic neutronics analysis method has been challenged in two aspects: one is the ability of generic geometry processing; the other is the multi-spectrum applicability of the multigroup cross section libraries. Due to its strong geometry modeling capability and the application of continuous energy cross section libraries, the Monte Carlo method has been widely used in reactor physics calculations, and more and more researches on Monte Carlo method has been carried out. Neutronics-thermal hydraulics coupling analysis based on Monte Carlo method has been realized. However, it still faces the problems of long computation time and slow convergence which make it not applicable to the reactor core fuel management simulations. Drawn from the deterministic core analysis method, a new two-step core analysis scheme is proposed in this work. Firstly, Monte Carlo simulations are performed for assembly, and the assembly homogenized multi-group cross sections are tallied at the same time. Secondly, the core diffusion calculations can be done with these multigroup cross sections. The new scheme can achieve high efficiency while maintain acceptable precision, so it can be used as an effective tool for the design and analysis of innovative nuclear energy systems. Numeric tests have been done in this work to verify the new scheme. (authors)
Lattice gauge theories and Monte Carlo algorithms
International Nuclear Information System (INIS)
Creutz, M.
1988-10-01
Lattice gauge theory has become the primary tool for non-perturbative calculations in quantum field theory. These lectures review some of the foundations of this subject. The first lecture reviews the basic definition of the theory in terms of invariant integrals over group elements on lattice bonds. The lattice represents an ultraviolet cutoff, and renormalization group arguments show how the bare coupling must be varied to obtain the continuum limit. Expansions in the inverse of the coupling constant demonstrate quark confinement in the strong coupling limit. The second lecture turns to numerical simulation, which has become an important approach to calculating hadronic properties. Here I discuss the basic algorithms for obtaining appropriately weighted gauge field configurations. The third lecture turns to algorithms for treating fermionic fields, which still require considerably more computer time than needed for purely bosonic simulations. Some particularly promising recent approaches are based on global accept-reject steps and should display a rather favorable dependence of computer time on the system volume. 34 refs
Energy Technology Data Exchange (ETDEWEB)
Martin, E.; Gschwind, R.; Henriet, J.; Sauget, M.; Makovicka, L. [IRMA/Enisys/FEMTO-ST, Pole universitaire des Portes du Jura, place Tharradin, BP 71427, 2521 1 - Montbeliard cedex (France)
2010-07-01
In order to reduce the computing time needed by Monte Carlo codes in the field of irradiation physics, notably in dosimetry, the authors report the use of artificial neural networks in combination with preliminary Monte Carlo calculations. During the learning phase, Monte Carlo calculations are performed in homogeneous media to allow the building up of the neural network. Then, dosimetric calculations (in heterogeneous media, unknown by the network) can be performed by the so-learned network. Results with an equivalent precision can be obtained within less than one minute on a simple PC whereas several days are needed with a Monte Carlo calculation
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
Improved local lattice Monte Carlo simulation for charged systems
Jiang, Jian; Wang, Zhen-Gang
2018-03-01
Maggs and Rossetto [Phys. Rev. Lett. 88, 196402 (2002)] proposed a local lattice Monte Carlo algorithm for simulating charged systems based on Gauss's law, which scales with the particle number N as O(N). This method includes two degrees of freedom: the configuration of the mobile charged particles and the electric field. In this work, we consider two important issues in the implementation of the method, the acceptance rate of configurational change (particle move) and the ergodicity in the phase space sampled by the electric field. We propose a simple method to improve the acceptance rate of particle moves based on the superposition principle for electric field. Furthermore, we introduce an additional updating step for the field, named "open-circuit update," to ensure that the system is fully ergodic under periodic boundary conditions. We apply this improved local Monte Carlo simulation to an electrolyte solution confined between two low dielectric plates. The results show excellent agreement with previous theoretical work.
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.)
A Monte Carlo code for ion beam therapy
Anaïs Schaeffer
2012-01-01
Initially developed for applications in detector and accelerator physics, the modern Fluka Monte Carlo code is now used in many different areas of nuclear science. Over the last 25 years, the code has evolved to include new features, such as ion beam simulations. Given the growing use of these beams in cancer treatment, Fluka simulations are being used to design treatment plans in several hadron-therapy centres in Europe. Fluka calculates the dose distribution for a patient treated at CNAO with proton beams. The colour-bar displays the normalized dose values. Fluka is a Monte Carlo code that very accurately simulates electromagnetic and nuclear interactions in matter. In the 1990s, in collaboration with NASA, the code was developed to predict potential radiation hazards received by space crews during possible future trips to Mars. Over the years, it has become the standard tool to investigate beam-machine interactions, radiation damage and radioprotection issues in the CERN accelerator com...
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.
Research on Monte Carlo application based on Hadoop
Directory of Open Access Journals (Sweden)
Wu Minglei
2018-01-01
Full Text Available Monte Carlo method is also known as random simulation method. The more the number of experiments, the more accurate the results obtained. Therefore, a large number of random simulation is required in order to obtain a higher degree of accuracy, but the traditional stand-alone algorithm has been difficult to meet the needs of a large number of simulation. Hadoop platform is a distributed computing platform built on a large data background and an open source software under Apache. It is easier to write and run applications for processing massive amounts of data as an open source software platform. Therefore, this paper takes π value calculation as an example to realize the Monte Carlo algorithm based on Hadoop platform, and get the exact π value with the advantage of Hadoop platform in distributed processing.
Engineering local optimality in quantum Monte Carlo algorithms
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.
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
Monte Carlo Euler approximations of HJM term structure financial models
Björk, Tomas
2012-11-22
We present Monte Carlo-Euler methods for a weak approximation problem related to the Heath-Jarrow-Morton (HJM) term structure model, based on Itô stochastic differential equations in infinite dimensional spaces, and prove strong and weak error convergence estimates. The weak error estimates are based on stochastic flows and discrete dual backward problems, and they can be used to identify different error contributions arising from time and maturity discretization as well as the classical statistical error due to finite sampling. Explicit formulas for efficient computation of sharp error approximation are included. Due to the structure of the HJM models considered here, the computational effort devoted to the error estimates is low compared to the work to compute Monte Carlo solutions to the HJM model. Numerical examples with known exact solution are included in order to show the behavior of the estimates. © 2012 Springer Science+Business Media Dordrecht.
Monte Carlo Methods in ICF (LIRPP Vol. 13)
Zimmerman, George B.
2016-10-01
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 SOX 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.
DEVELOPMENT OF A MULTIMODAL MONTE CARLO BASED TREATMENT PLANNING SYSTEM.
Kumada, Hiroaki; Takada, Kenta; Sakurai, Yoshinori; Suzuki, Minoru; Takata, Takushi; Sakurai, Hideyuki; Matsumura, Akira; Sakae, Takeji
2017-10-26
To establish boron neutron capture therapy (BNCT), the University of Tsukuba is developing a treatment device and peripheral devices required in BNCT, such as a treatment planning system. We are developing a new multimodal Monte Carlo based treatment planning system (developing code: Tsukuba Plan). Tsukuba Plan allows for dose estimation in proton therapy, X-ray therapy and heavy ion therapy in addition to BNCT because the system employs PHITS as the Monte Carlo dose calculation engine. Regarding BNCT, several verifications of the system are being carried out for its practical usage. The verification results demonstrate that Tsukuba Plan allows for accurate estimation of thermal neutron flux and gamma-ray dose as fundamental radiations of dosimetry in BNCT. In addition to the practical use of Tsukuba Plan in BNCT, we are investigating its application to other radiation therapies. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Monte Carlo simulations of neutron oil well logging tools
International Nuclear Information System (INIS)
Azcurra, Mario O.; Zamonsky, Oscar M.
2003-01-01
Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented. The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively. The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation. The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B. Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation. In particular, the ratio C/O was analyzed as an indicator of oil saturation. Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition. (author)
Failure Probability Estimation of Wind Turbines by Enhanced Monte Carlo
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Naess, Arvid
2012-01-01
is controlled by the pitch controller. This provides a fair framework for comparison of the behavior and failure event of the wind turbine with emphasis on the effect of the pitch controller. The Enhanced Monte Carlo method is then applied to the model and the failure probabilities of the model are estimated......, estimation of very low failure probabilities with SMC simulations leads to unacceptably high computational costs. In this study, an Enhanced Monte Carlo (EMC) method is proposed that overcomes this obstacle. The method has advantages over both POT and SMC in terms of its low computational cost and accuracy....... The method is applied to a low-order numerical model of a 5 MW wind turbine with a pitch controller exposed to a turbulent inflow. Two cases of the wind turbine model are investigated. In the first case, the rotor is running with a constant rotational speed. In the second case, the variable rotational speed...
Monte Carlo program for the cold neutron beam guide
International Nuclear Information System (INIS)
Yoshiki, H.
1985-02-01
A Monte Carlo program for the transport of cold neutrons through beam guides has been developed assuming that the neutrons follow the specular reflections. Cold neutron beam guides are normally used to transport cold neutrons (4 ∼ 10 Angstrom) to experimental equipments such as small angle scattering apparatus, TOF measuring devices, polarized neutron spectrometers, and ultra cold neutron generators, etc. The beam guide is about tens of meters in length and is composed from a meter long guide elements made up from four pieces of Ni coated rectangular optical glass. This report describes mathematics and algorithm employed in the Monte Carlo program together with the display of the results. The source program and input data listings are also attached. (Aoki, K.)
Subtle Monte Carlo Updates in Dense Molecular Systems
DEFF Research Database (Denmark)
Bottaro, Sandro; Boomsma, Wouter; Johansson, Kristoffer E.
2012-01-01
as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results......Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce...... a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule...
Simplest Validation of the HIJING Monte Carlo Model
Uzhinsky, V.V.
2003-01-01
Fulfillment of the energy-momentum conservation law, as well as the charge, baryon and lepton number conservation is checked for the HIJING Monte Carlo program in $pp$-interactions at $\\sqrt{s}=$ 200, 5500, and 14000 GeV. It is shown that the energy is conserved quite well. The transverse momentum is not conserved, the deviation from zero is at the level of 1--2 GeV/c, and it is connected with the hard jet production. The deviation is absent for soft interactions. Charge, baryon and lepton numbers are conserved. Azimuthal symmetry of the Monte Carlo events is studied, too. It is shown that there is a small signature of a "flow". The situation with the symmetry gets worse for nucleus-nucleus interactions.
Monte Carlo Transverse Emittance Study on Cs2Te
Banfi, F; Galimberti, P G; Giannetti, C; Pagliara, S; Parmigiani, F; Pedersoli, E
2005-01-01
A Monte Carlo study of electron transport in Cs2Te films is performed to investigate the transverse emittance epsilon at the cathode surface. We find the photoemitted electron angular distribution and explain the physical mechanism involved in the process, a mechanism hindered by the statistical nature of the Monte Carlo method. The effects of electron-phonon scattering are discussed. The transverse emittance is calculated for different radiation wavelengths and a laser spot size of 1.5*10(-3) m. For a laser radiation at 265 nm we find epsilon = 0.56 mm-mrad. The dependence of epsilon and the quantum yield on the electron affinity Ea is also investigated. The data shows the importance of aging/contamination on the material.
The MCLIB library: Monte Carlo simulation of neutron scattering instruments
International Nuclear Information System (INIS)
Seeger, P.A.
1995-01-01
Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC RUN) which use the library are shown as an example
The MCLIB library: Monte Carlo simulation of neutron scattering instruments
Energy Technology Data Exchange (ETDEWEB)
Seeger, P.A.
1995-09-01
Monte Carlo is a method to integrate over a large number of variables. Random numbers are used to select a value for each variable, and the integrand is evaluated. The process is repeated a large number of times and the resulting values are averaged. For a neutron transport problem, first select a neutron from the source distribution, and project it through the instrument using either deterministic or probabilistic algorithms to describe its interaction whenever it hits something, and then (if it hits the detector) tally it in a histogram representing where and when it was detected. This is intended to simulate the process of running an actual experiment (but it is much slower). This report describes the philosophy and structure of MCLIB, a Fortran library of Monte Carlo subroutines which has been developed for design of neutron scattering instruments. A pair of programs (LQDGEOM and MC{_}RUN) which use the library are shown as an example.
Parallelism in continuous energy Monte Carlo method for neutron transport
Energy Technology Data Exchange (ETDEWEB)
Uenohara, Yuji (Nuclear Engineering Lab., Toshiba Corp. (Japan))
1993-04-01
The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)
Parallelism in continuous energy Monte Carlo method for neutron transport
International Nuclear Information System (INIS)
Uenohara, Yuji
1993-01-01
The continuous energy Monte Carlo code VIM was implemented on a prototype highly parallel computer called PRODIGY developed by TOSHIBA Corporation. The author tried to distribute nuclear data to the processing elements (PEs) for the purpose of studying domain decompositon for the velocity space. Eigenvalue problems for a 1-D plate-cell infinite lattice mockup of ZPR-6-7 wa examined. For the geometrical space, the PEs were assigned to domains corresponding to nuclear fuel bundles in a typical boiling water reactor. The author estimated the parallelization efficiencies for both highly parallel and a massively parallel computer. Negligible communication overhead derived from neutron transports resulted from the heavy computing loads of Monte Carlo simulations. In the case of highly parallel computers, the communication overheads scarcely contributed to the parallelization efficiency. In the case of massively parallel computers, the control of PEs resulted in considerable communication overheads. (orig.)
Exploring Various Monte Carlo Simulations for Geoscience Applications
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.
Exploring pseudo- and chaotic random Monte Carlo simulations
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.
Reservoir Modeling Combining Geostatistics with Markov Chain Monte Carlo Inversion
DEFF Research Database (Denmark)
Zunino, Andrea; Lange, Katrine; Melnikova, Yulia
2014-01-01
We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear,...... constitute samples of the posterior distribution.......We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear......, multi-step forward model (rock physics and seismology) and to provide realistic estimates of uncertainties. To generate realistic models which represent samples of the prior distribution, and to overcome the high computational demand, we reduce the search space utilizing an algorithm drawn from...
Estimation of beryllium ground state energy by Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)
2015-05-15
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
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)
Monte Carlo Simulations of Neutron Oil well Logging Tools
International Nuclear Information System (INIS)
Azcurra, Mario
2002-01-01
Monte Carlo simulations of simple neutron oil well logging tools into typical geological formations are presented.The simulated tools consist of both 14 MeV pulsed and continuous Am-Be neutron sources with time gated and continuous gamma ray detectors respectively.The geological formation consists of pure limestone with 15% absolute porosity in a wide range of oil saturation.The particle transport was performed with the Monte Carlo N-Particle Transport Code System, MCNP-4B.Several gamma ray spectra were obtained at the detector position that allow to perform composition analysis of the formation.In particular, the ratio C/O was analyzed as an indicator of oil saturation.Further calculations are proposed to simulate actual detector responses in order to contribute to understand the relation between the detector response with the formation composition
Simulation based sequential Monte Carlo methods for discretely observed Markov processes
Neal, Peter
2014-01-01
Parameter estimation for discretely observed Markov processes is a challenging problem. However, simulation of Markov processes is straightforward using the Gillespie algorithm. We exploit this ease of simulation to develop an effective sequential Monte Carlo (SMC) algorithm for obtaining samples from the posterior distribution of the parameters. In particular, we introduce two key innovations, coupled simulations, which allow us to study multiple parameter values on the basis of a single sim...
Difficult Sudoku Puzzles Created by Replica Exchange Monte Carlo Method
Watanabe, Hiroshi
2013-01-01
An algorithm to create difficult Sudoku puzzles is proposed. An Ising spin-glass like Hamiltonian describing difficulty of puzzles is defined, and difficult puzzles are created by minimizing the energy of the Hamiltonian. We adopt the replica exchange Monte Carlo method with simultaneous temperature adjustments to search lower energy states efficiently, and we succeed in creating a puzzle which is the world hardest ever created in our definition, to our best knowledge. (Added on Mar. 11, the ...
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.)
Programming a Hearthstone agent using Monte Carlo Tree Search
Andersson, Markus Heikki; Hesselberg, Håkon Helgesen
2016-01-01
This thesis describes the effort of adapting Monte Carlo Tree Search (MCTS) to the game of Hearthstone, a card game with hidden information and stochastic elements. The focus is on discovering the suitability of MCTS for this environment, as well as which domain-specific adaptations are needed. An MCTS agent is developed for a Hearthstone simulator, which is used to conduct experiments to measure the agent's performance both against human and computer players. The implementation includes ...
Monte Carlo simulation of PET images for injection doseoptimization
Czech Academy of Sciences Publication Activity Database
Boldyš, Jiří; Dvořák, Jiří; Skopalová, M.; Bělohlávek, O.
2013-01-01
Roč. 29, č. 9 (2013), s. 988-999 ISSN 2040-7939 R&D Projects: GA MŠk 1M0572 Institutional support: RVO:67985556 Keywords : positron emission tomography * Monte Carlo simulation * biological system modeling * image quality Subject RIV: FD - Oncology ; Hematology Impact factor: 1.542, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/boldys-0397175.pdf
Scaling Monte Carlo Tree Search on Intel Xeon Phi
Mirsoleimani, S. Ali; Plaat, Aske; Herik, Jaap van den; Vermaseren, Jos
2015-01-01
Many algorithms have been parallelized successfully on the Intel Xeon Phi coprocessor, especially those with regular, balanced, and predictable data access patterns and instruction flows. Irregular and unbalanced algorithms are harder to parallelize efficiently. They are, for instance, present in artificial intelligence search algorithms such as Monte Carlo Tree Search (MCTS). In this paper we study the scaling behavior of MCTS, on a highly optimized real-world application, on real hardware. ...
Analysis of neutron-reflectometry data by Monte Carlo technique
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.)
Quantum Monte Carlo simulations for high-Tc superconductors
International Nuclear Information System (INIS)
Muramatsu, A.; Dopf, G.; Wagner, J.; Dieterich, P.; Hanke, W.
1992-01-01
Quantum Monte Carlo simulations for a multi-band model of high-Tc superconductors are reviewed with special emphasis on the comparison of different observabels with experiments. It is shown that a give parameter set of the three-band Hubbard model leads to a consistent description of normal-state propteries as well as pairing correlation function for the copper-oxide superconductors as a function of doping and temperature. (orig.)
Monte Carlo Simulation of Random-Anisotropy Amorphous Magnets
Bondarev, A. V.; Bataronov, I. L.
2018-01-01
Using the Monte Carlo method, within the frame of the Heisenberg model, we studies the magnetic properties of amorphous Tb. The relaxation of magnetization of the model of amorphous Tb was studied. We stablished that the relaxation goes in two stages. On the first stage the magnetization sharply decreases by some amount ΔMz , on the second stage the magnetization decreases with time according to the logarithmic law. The possible mechanisms of relaxation is discussed.
Monte carlo dose calculation in dental amalgam phantom
Mohd Zahri Abdul Aziz; A L Yusoff; N D Osman; R Abdullah; N A Rabaie; M S Salikin
2015-01-01
It has become a great challenge in the modern radiation treatment to ensure the accuracy of treatment delivery in electron beam therapy. Tissue inhomogeneity has become one of the factors for accurate dose calculation, and this requires complex algorithm calculation like Monte Carlo (MC). On the other hand, computed tomography (CT) images used in treatment planning system need to be trustful as they are the input in radiotherapy treatment. However, with the presence of metal amalgam in treatm...
Simulating Polymorphic Phase Behavior Using Reaction Ensemble Monte Carlo
Czech Academy of Sciences Publication Activity Database
Brennan, J.K.; Rice, B.M.; Lísal, Martin
2007-01-01
Roč. 111, č. 1 (2007), s. 365-373 ISSN 1932-7447 R&D Projects: GA ČR(CZ) GA203/05/0725; GA AV ČR(CZ) 1ET400720507; GA AV ČR(CZ) 1ET400720409 Institutional research plan: CEZ:AV0Z40720504 Keywords : simulation * monte carlo * phase transition Subject RIV: CF - Physical ; Theoretical Chemistry
Towards a Revised Monte Carlo Neutral Particle Surface Interaction Model
International Nuclear Information System (INIS)
Stotler, D.P.
2005-01-01
The components of the neutral- and plasma-surface interaction model used in the Monte Carlo neutral transport code DEGAS 2 are reviewed. The idealized surfaces and processes handled by that model are inadequate for accurately simulating neutral transport behavior in present day and future fusion devices. We identify some of the physical processes missing from the model, such as mixed materials and implanted hydrogen, and make some suggestions for improving the model
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.
Image reconstruction using Monte Carlo simulation and artificial neural networks
International Nuclear Information System (INIS)
Emert, F.; Missimner, J.; Blass, W.; Rodriguez, A.
1997-01-01
PET data sets are subject to two types of distortions during acquisition: the imperfect response of the scanner and attenuation and scattering in the active distribution. In addition, the reconstruction of voxel images from the line projections composing a data set can introduce artifacts. Monte Carlo simulation provides a means for modeling the distortions and artificial neural networks a method for correcting for them as well as minimizing artifacts. (author) figs., tab., refs
Monte Carlo physical dosimetry for small photon beams
International Nuclear Information System (INIS)
Perucha, M.; Rincon, M.; Leal, A.; Carrasco, E.; Sanchez-Doblado, F.; Hospital Univ. Virgen Macarena, Sevilla; Nunez, L.; Arrans, R.; Sanchez-Calzado, J.A.; Errazquin, L.
2001-01-01
Small field dosimetry is complicated due to the lack of electronic equilibrium and to the high steep dose gradients. This works compares PDD curves, profiles and output factors measured with conventional detectors (film, diode, TLD and ionisation chamber) and calculated with Monte Carlo. The 6 MV nominal energy from a Philips SL-18 linac has been simulated by using the OMEGA code. MC calculation reveals itself as a convenient method to validate OF and profiles in special conditions, such as small fields. (orig.)
Monte Carlo Study of the 3D Thirring Model
Hands, Simon
1997-01-01
I review three different non-perturbative approaches to the three dimensional Thirring model: the 1/N_f expansion, Schwinger-Dyson equations, and Monte Carlo simulation. Simulation results are presented to support the existence of a non-perturbative fixed point at a chiral symmetry breaking phase transition for N_f=2 and 4, but not for N_f=6. Spectrum calculations for $N_f=2$ reveal conventional level ordering near the transition.
Monte-Carlo support for the fluxon confinement mechanism
International Nuclear Information System (INIS)
Greensite, J.; Lautrup, B.
1981-03-01
The authors present Monte-Carlo evidence of a first-order phase transition in 4-dimensional lattice SO(3) gauge theory. This result stands in sharp contrast to the known single-phase structure of the corresponding SU(2) theory. Since SU(2) and SO(3) differ only by a Z 2 center, it is concluded that the Z 2 degrees of freedom are essential in disordering the SU(2) system, probably via the fluxon condensation scheme suggested by 't Hooft. (Auth.)
Monte Carlo calculation with unquenched Wilson-Fermions
International Nuclear Information System (INIS)
Montvay, I.
1984-01-01
A Monte Carlo updating procedure taking into account the virtual quark loops is described. It is based on high order hopping parameter expansion of the quark determinant for Wilson-fermions. In a first test run Wilson-loop expectation values are measured on 6 4 lattice at β=5.70 using 16sup(th) order hopping parameter expansion for the quark determinant. (orig.)
An efficient parallel computing scheme for Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Dufek, Jan; Gudowski, Waclaw
2009-01-01
The existing parallel computing schemes for Monte Carlo criticality calculations suffer from a low efficiency when applied on many processors. We suggest a new fission matrix based scheme for efficient parallel computing. The results are derived from the fission matrix that is combined from all parallel simulations. The scheme allows for a practically ideal parallel scaling as no communication among the parallel simulations is required, and inactive cycles are not needed.
Monte Carlo parameter studies and uncertainty analyses with MCNP5
International Nuclear Information System (INIS)
Brown, F. B.; Sweezy, J. E.; Hayes, R.
2004-01-01
A software tool called mcnp p study has been developed to automate the setup, execution, and collection of results from a series of MCNP5 Monte Carlo calculations. This tool provides a convenient means of performing parameter studies, total uncertainty analyses, parallel job execution on clusters, stochastic geometry modeling, and other types of calculations where a series of MCNP5 jobs must be performed with varying problem input specifications. (authors)
Comparison of Bootstrap Confidence Intervals Using Monte Carlo Simulations
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...
A general purpose code for Monte Carlo simulations
International Nuclear Information System (INIS)
Wilcke, W.W.; Rochester Univ., NY
1984-01-01
A general-purpose computer code 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. (orig.)
A simple introduction to Markov Chain Monte-Carlo sampling.
van Ravenzwaaij, Don; Cassey, Pete; Brown, Scott D
2016-03-11
Markov Chain Monte-Carlo (MCMC) is an increasingly popular method for obtaining information about distributions, especially for estimating posterior distributions in Bayesian inference. This article provides a very basic introduction to MCMC sampling. It describes what MCMC is, and what it can be used for, with simple illustrative examples. Highlighted are some of the benefits and limitations of MCMC sampling, as well as different approaches to circumventing the limitations most likely to trouble cognitive scientists.
Monte Carlo simulation of hybrid systems: An example
International Nuclear Information System (INIS)
Bacha, F.; D'Alencon, H.; Grivelet, J.; Jullien, E.; Jejcic, A.; Maillard, J.; Silva, J.; Zukanovich, R.; Vergnes, J.
1997-01-01
Simulation of hybrid systems needs tracking of particles from the GeV (incident proton beam) range down to a fraction of eV (thermic neutrons). We show how a GEANT based Monte-Carlo program can achieve this, with a realistic computer time and accompanying tools. An example of a dedicated original actinide burner is simulated with this chain. 8 refs., 5 figs
Molecular-level Monte Carlo Simulation at Fixed Entropy
Czech Academy of Sciences Publication Activity Database
Smith, W.R.; Lísal, Martin; Nezbeda, Ivo
2006-01-01
Roč. 426, 4-6 (2006), s. 436-440 ISSN 0009-2614 R&D Projects: GA AV ČR(CZ) 1ET400720507; GA AV ČR 1ET400720409 Grant - others:NRCC(CA) OGP1041 Institutional research plan: CEZ:AV0Z40720504 Keywords : simulation * entropy * Monte Carlo Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.462, year: 2006
Monte Carlo Modelling of Mammograms : Development and Validation
International Nuclear Information System (INIS)
Spyrou, G.; Panayiotakis, G.; Bakas, A.; Tzanakos, G.
1998-01-01
A software package using Monte Carlo methods has been developed for the simulation of x-ray mammography. A simplified geometry of the mammographic apparatus has been considered along with the software phantom of compressed breast. This phantom may contain inhomogeneities of various compositions and sizes at any point. Using this model one can produce simulated mammograms. Results that demonstrate the validity of this simulation are presented. (authors)
Applications of Monte Carlo simulations of gamma-ray spectra
International Nuclear Information System (INIS)
Clark, D.D.
1995-01-01
A short, convenient computer program based on the Monte Carlo method that was developed to generate simulated gamma-ray spectra has been found to have useful applications in research and teaching. In research, we use it to predict spectra in neutron activation analysis (NAA), particularly in prompt gamma-ray NAA (PGNAA). In teaching, it is used to illustrate the dependence of detector response functions on the nature of gamma-ray interactions, the incident gamma-ray energy, and detector geometry
Monte Carlo simulation of NSE at reactor and spallation sources
Energy Technology Data Exchange (ETDEWEB)
Zsigmond, G.; Wechsler, D.; Mezei, F. [Hahn-Meitner-Institut Berlin, Berlin (Germany)
2001-03-01
A MC (Monte Carlo) computation study of NSE (Neutron Spin Echo) has been performed by means of VITESS investigating the classic and TOF-NSE options at spallation sources. The use of white beams in TOF-NSE makes the flipper efficiency in function of the neutron wavelength an important issue. The emphasis was put on exact evaluation of flipper efficiencies for wide wavelength-band instruments. (author)
Strings, Projected Entangled Pair States, and variational Monte Carlo methods
Schuch, Norbert; Wolf, Michael M.; Verstraete, Frank; Cirac, J. Ignacio
2007-01-01
We introduce string-bond states, a class of states obtained by placing strings of operators on a lattice, which encompasses the relevant states in Quantum Information. For string-bond states, expectation values of local observables can be computed efficiently using Monte Carlo sampling, making them suitable for a variational abgorithm which extends DMRG to higher dimensional and irregular systems. Numerical results demonstrate the applicability of these states to the simulation of many-body s...
Present status of vectorization for particle transport Monte Carlo
International Nuclear Information System (INIS)
Martin, W.R.
1987-01-01
The conventional particle transport Monte Carlo algorithm is ill-suited for modern vector supercomputers. This history-based algorithm is not amenable to vectorization due to the random nature of the particle transport process, which inhibits the construction of vectors that are necessary for efficient utilization of a vector (pipelined) processor. An alternative algorithm, the event-based algorithm, is suitable for vectorization and has been used by several researchers in recent years to achieve impressive gains (5-20) in performance on modern vector supercomputers. This paper describes the event-based algorithm in some detail and discusses several implementations of this algorithm for specific applications in particle transport, including photon transport in a nuclear fusion plasma and neutron transport in a nuclear reactor. A discussion of the relative merits of these alternative approaches is included. A short discussion of the implementation of Monte Carlo methods on parallel processors, in particular multiple vector processors such as the Cray X-MP/48 and the IBM 3090/400, is included. The paper concludes with some thoughts regarding the potential of massively parallel processors (vector and scalar) for Monte Carlo simulation
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
Pattern Recognition for a Flight Dynamics Monte Carlo Simulation
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.
Monte Carlo calculations of electron transport on microcomputers
International Nuclear Information System (INIS)
Chung, Manho; Jester, W.A.; Levine, S.H.; Foderaro, A.H.
1990-01-01
In the work described in this paper, the Monte Carlo program ZEBRA, developed by Berber and Buxton, was converted to run on the Macintosh computer using Microsoft BASIC to reduce the cost of Monte Carlo calculations using microcomputers. Then the Eltran2 program was transferred to an IBM-compatible computer. Turbo BASIC and Microsoft Quick BASIC have been used on the IBM-compatible Tandy 4000SX computer. The paper shows the running speed of the Monte Carlo programs on the different computers, normalized to one for Eltran2 on the Macintosh-SE or Macintosh-Plus computer. Higher values refer to faster running times proportionally. Since Eltran2 is a one-dimensional program, it calculates energy deposited in a semi-infinite multilayer slab. Eltran2 has been modified to a two-dimensional program called Eltran3 to computer more accurately the case with a point source, a small detector, and a short source-to-detector distance. The running time of Eltran3 is about twice as long as that of Eltran2 for a similar case
New Monte Carlo approach to the adjoint Boltzmann equation
International Nuclear Information System (INIS)
De Matteis, A.; Simonini, R.
1978-01-01
A class of stochastic models for the Monte Carlo integration of the adjoint neutron transport equation is described. Some current general methods are brought within this class, thus preparing the ground for subsequent comparisons. Monte Carlo integration of the adjoint Boltzmann equation can be seen as a simulation of the transport of mathematical particles with reaction kernels not normalized to unity. This last feature is a source of difficulty: It can influence the variance of the result negatively and also often leads to preparation of special ''libraries'' consisting of tables of normalization factors as functions of energy, presently used by several methods. These are the two main points that are discussed and that are taken into account to devise a nonmultigroup method of solution for a certain class of problems. Reactions considered in detail are radiative capture, elastic scattering, discrete levels and continuum inelastic scattering, for which the need for tables has been almost completely eliminated. The basic policy pursued to avoid a source of statistical fluctuations is to try to make the statistical weight of the traveling particle dependent only on its starting and current energies, at least in simple cases. The effectiveness of the sampling schemes proposed is supported by numerical comparison with other more general adjoint Monte Carlo methods. Computation of neutron flux at a point by means of an adjoint formulation is the problem taken as a test for numerical experiments. Very good results have been obtained in the difficult case of resonant cross sections
Automatic fission source convergence criteria for Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Shim, Hyung Jin; Kim, Chang Hyo
2005-01-01
The Monte Carlo criticality calculations for the multiplication factor and the power distribution in a nuclear system require knowledge of stationary or fundamental-mode fission source distribution (FSD) in the system. Because it is a priori unknown, so-called inactive cycle Monte Carlo (MC) runs are performed to determine it. The inactive cycle MC runs should be continued until the FSD converges to the stationary FSD. Obviously, if one stops them prematurely, the MC calculation results may have biases because the followup active cycles may be run with the non-stationary FSD. Conversely, if one performs the inactive cycle MC runs more than necessary, one is apt to waste computing time because inactive cycle MC runs are used to elicit the fundamental-mode FSD only. In the absence of suitable criteria for terminating the inactive cycle MC runs, one cannot but rely on empiricism in deciding how many inactive cycles one should conduct for a given problem. Depending on the problem, this may introduce biases into Monte Carlo estimates of the parameters one tries to calculate. The purpose of this paper is to present new fission source convergence criteria designed for the automatic termination of inactive cycle MC runs
Understanding quantum tunneling using diffusion Monte Carlo simulations
Inack, E. M.; Giudici, G.; Parolini, T.; Santoro, G.; Pilati, S.
2018-03-01
In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1 /Δ2 , where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1 /Δ , i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.
Comparison of deterministic and Monte Carlo methods in shielding design.
Oliveira, A D; Oliveira, C
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions.
Comparison of deterministic and Monte Carlo methods in shielding design
International Nuclear Information System (INIS)
Oliveira, A. D.; Oliveira, C.
2005-01-01
In shielding calculation, deterministic methods have some advantages and also some disadvantages relative to other kind of codes, such as Monte Carlo. The main advantage is the short computer time needed to find solutions while the disadvantages are related to the often-used build-up factor that is extrapolated from high to low energies or with unknown geometrical conditions, which can lead to significant errors in shielding results. The aim of this work is to investigate how good are some deterministic methods to calculating low-energy shielding, using attenuation coefficients and build-up factor corrections. Commercial software MicroShield 5.05 has been used as the deterministic code while MCNP has been used as the Monte Carlo code. Point and cylindrical sources with slab shield have been defined allowing comparison between the capability of both Monte Carlo and deterministic methods in a day-by-day shielding calculation using sensitivity analysis of significant parameters, such as energy and geometrical conditions. (authors)
Stock Price Simulation Using Bootstrap and Monte Carlo
Directory of Open Access Journals (Sweden)
Pažický Martin
2017-06-01
Full Text Available In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.
The application of weight windows to 'Global' Monte Carlo problems
International Nuclear Information System (INIS)
Becker, T. L.; Larsen, E. W.
2009-01-01
This paper describes two basic types of global deep-penetration (shielding) problems-the global flux problem and the global response problem. For each of these, two methods for generating weight windows are presented. The first approach, developed by the authors of this paper and referred to generally as the Global Weight Window, constructs a weight window that distributes Monte Carlo particles according to a user-specified distribution. The second approach, developed at Oak Ridge National Laboratory and referred to as FW-CADIS, constructs a weight window based on intuitively extending the concept of the source-detector problem to global problems. The numerical results confirm that the theory used to describe the Monte Carlo particle distribution for a given weight window is valid and that the figure of merit is strongly correlated to the Monte Carlo particle distribution. Furthermore, they illustrate that, while both methods are capable of obtaining the correct solution, the Global Weight Window distributes particles much more uniformly than FW-CADIS. As a result, the figure of merit is higher for the Global Weight Window. (authors)
Entanglement negativity and conformal field theory: a Monte Carlo study
International Nuclear Information System (INIS)
Alba, Vincenzo
2013-01-01
We investigate the behavior of the moments of the partially transposed reduced density matrix ρ A T 2 in critical quantum spin chains. Given subsystem A as the union of two blocks, this is the (matrix) transpose of ρ A with respect to the degrees of freedom of one of the two blocks. This is also the main ingredient for constructing the logarithmic negativity. We provide a new numerical scheme for efficiently calculating all the moments of ρ A T 2 using classical Monte Carlo simulations. In particular we study several combinations of the moments which are scale invariant at a critical point. Their behavior is fully characterized in both the critical Ising and the anisotropic Heisenberg XXZ chains. For two adjacent blocks we find, in both models, full agreement with recent conformal field theory (CFT) calculations. For disjoint blocks, in the Ising chain finite size corrections are nonnegligible. We demonstrate that their exponent is the same as that governing the unusual scaling corrections of the mutual information between the two blocks. Monte Carlo data fully match the theoretical CFT prediction only in the asymptotic limit of infinite intervals. Oppositely, in the Heisenberg chain scaling corrections are smaller and, already at finite (moderately large) block sizes, Monte Carlo data are in excellent agreement with the asymptotic CFT result. (paper)