WorldWideScience

Sample records for monte carlo samples

  1. Monte Carlo and Quasi-Monte Carlo Sampling

    CERN Document Server

    Lemieux, Christiane

    2009-01-01

    Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.

  2. Nested Sampling with Constrained Hamiltonian Monte Carlo

    OpenAIRE

    Betancourt, M. J.

    2010-01-01

    Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.

  3. Monte Carlo stratified source-sampling

    International Nuclear Information System (INIS)

    Blomquist, R.N.; Gelbard, E.M.

    1997-01-01

    In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo open-quotes eigenvalue of the worldclose quotes problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. The original test-problem was treated by a special code designed specifically for that purpose. Recently ANL started work on a method for dealing with more realistic eigenvalue of the world configurations, and has been incorporating this method into VIM. The original method has been modified to take into account real-world statistical noise sources not included in the model problem. This paper constitutes a status report on work still in progress

  4. 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.

  5. Nonlinear Spatial Inversion Without Monte Carlo Sampling

    Science.gov (United States)

    Curtis, A.; Nawaz, A.

    2017-12-01

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

  6. Sampling from a polytope and hard-disk Monte Carlo

    International Nuclear Information System (INIS)

    Kapfer, Sebastian C; Krauth, Werner

    2013-01-01

    The hard-disk problem, the statics and the dynamics of equal two-dimensional hard spheres in a periodic box, has had a profound influence on statistical and computational physics. Markov-chain Monte Carlo and molecular dynamics were first discussed for this model. Here we reformulate hard-disk Monte Carlo algorithms in terms of another classic problem, namely the sampling from a polytope. Local Markov-chain Monte Carlo, as proposed by Metropolis et al. in 1953, appears as a sequence of random walks in high-dimensional polytopes, while the moves of the more powerful event-chain algorithm correspond to molecular dynamics evolution. We determine the convergence properties of Monte Carlo methods in a special invariant polytope associated with hard-disk configurations, and the implications for convergence of hard-disk sampling. Finally, we discuss parallelization strategies for event-chain Monte Carlo and present results for a multicore implementation

  7. 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

  8. Monte Carlo simulation of a gas-sampled hadron calorimeter

    Energy Technology Data Exchange (ETDEWEB)

    Chang, C Y; Kunori, S; Rapp, P; Talaga, R; Steinberg, P; Tylka, A J; Wang, Z M

    1988-02-15

    A prototype of the OPAL barrel hadron calorimeter, which is a gas-sampled calorimeter using plastic streamer tubes, was exposed to pions at energies between 1 and 7 GeV. The response of the detector was simulated using the CERN GEANT3 Monte Carlo program. By using the observed high energy muon signals to deduce details of the streamer formation, the Monte Carlo program was able to reproduce the observed calorimeter response. The behavior of the hadron calorimeter when placed behind a lead glass electromagnetic calorimeter was also investigated.

  9. Monte Carlo burnup codes acceleration using the correlated sampling method

    International Nuclear Information System (INIS)

    Dieudonne, C.

    2013-01-01

    For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this document we present an original methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time we develop a theoretical model to study the features of the correlated sampling method to understand its effects on depletion calculations. In a third time the implementation of this method in the TRIPOLI-4 code will be discussed, as well as the precise calculation scheme used to bring important speed-up of the depletion calculation. We will begin to validate and optimize the perturbed depletion scheme with the calculation of a REP-like fuel cell depletion. Then this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes. (author) [fr

  10. A Monte Carlo Sampling Technique for Multi-phonon Processes

    Energy Technology Data Exchange (ETDEWEB)

    Hoegberg, Thure

    1961-12-15

    A sampling technique for selecting scattering angle and energy gain in Monte Carlo calculations of neutron thermalization is described. It is supposed that the scattering is separated into processes involving different numbers of phonons. The number of phonons involved is first determined. Scattering angle and energy gain are then chosen by using special properties of the multi-phonon term.

  11. Testing results of Monte Carlo sampling processes in MCSAD

    International Nuclear Information System (INIS)

    Pinnera, I.; Cruz, C.; Abreu, Y.; Leyva, A.; Correa, C.; Demydenko, C.

    2009-01-01

    The Monte Carlo Simulation of Atom Displacements (MCSAD) is a code implemented by the authors to simulate the complete process of atom displacement (AD) formation. This code makes use of the Monte Carlo (MC) method to sample all the processes involved in the gamma and electronic radiation transport through matter. The kernel of the calculations applied to this code relies on a model based on an algorithm developed by the authors, which firstly splits out multiple electron elastic scattering events from those single ones at higher scattering angles and then, from the last one, sampling those leading to AD at high transferred atomic recoil energies. Some tests have been developed to check the sampling algorithms with the help of the corresponding theoretical distribution functions. Satisfactory results have been obtained, which indicate the strength of the methods and subroutines used in the code. (Author)

  12. Extending the alias Monte Carlo sampling method to general distributions

    International Nuclear Information System (INIS)

    Edwards, A.L.; Rathkopf, J.A.; Smidt, R.K.

    1991-01-01

    The alias method is a Monte Carlo sampling technique that offers significant advantages over more traditional methods. It equals the accuracy of table lookup and the speed of equal probable bins. The original formulation of this method sampled from discrete distributions and was easily extended to histogram distributions. We have extended the method further to applications more germane to Monte Carlo particle transport codes: continuous distributions. This paper presents the alias method as originally derived and our extensions to simple continuous distributions represented by piecewise linear functions. We also present a method to interpolate accurately between distributions tabulated at points other than the point of interest. We present timing studies that demonstrate the method's increased efficiency over table lookup and show further speedup achieved through vectorization. 6 refs., 12 figs., 2 tabs

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

    NARCIS (Netherlands)

    Waarts, P.H.

    2003-01-01

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

  14. Multiple histogram method and static Monte Carlo sampling

    NARCIS (Netherlands)

    Inda, M.A.; Frenkel, D.

    2004-01-01

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

  15. Advanced Markov chain Monte Carlo methods learning from past samples

    CERN Document Server

    Liang, Faming; Carrol, Raymond J

    2010-01-01

    This book provides comprehensive coverage of simulation of complex systems using Monte Carlo methods. Developing algorithms that are immune to the local trap problem has long been considered as the most important topic in MCMC research. Various advanced MCMC algorithms which address this problem have been developed include, the modified Gibbs sampler, the methods based on auxiliary variables and the methods making use of past samples. The focus of this book is on the algorithms that make use of past samples. This book includes the multicanonical algorithm, dynamic weighting, dynamically weight

  16. Entropic sampling in the path integral Monte Carlo method

    International Nuclear Information System (INIS)

    Vorontsov-Velyaminov, P N; Lyubartsev, A P

    2003-01-01

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

  17. Efficient sampling algorithms for Monte Carlo based treatment planning

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  18. Stratified source-sampling techniques for Monte Carlo eigenvalue analysis

    International Nuclear Information System (INIS)

    Mohamed, A.

    1998-01-01

    In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo ''Eigenvalue of the World'' problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. In this paper, stratified source-sampling techniques are generalized and applied to three different Eigenvalue of the World configurations which take into account real-world statistical noise sources not included in the model problem, but which differ in the amount of neutronic coupling among the constituents of each configuration. It is concluded that, in Monte Carlo eigenvalue analysis of loosely-coupled arrays, the use of stratified source-sampling reduces the probability of encountering an anomalous result over that if conventional source-sampling methods are used. However, this gain in reliability is substantially less than that observed in the model-problem results

  19. Respondent-driven sampling as Markov chain Monte Carlo.

    Science.gov (United States)

    Goel, Sharad; Salganik, Matthew J

    2009-07-30

    Respondent-driven sampling (RDS) is a recently introduced, and now widely used, technique for estimating disease prevalence in hidden populations. RDS data are collected through a snowball mechanism, in which current sample members recruit future sample members. In this paper we present RDS as Markov chain Monte Carlo importance sampling, and we examine the effects of community structure and the recruitment procedure on the variance of RDS estimates. Past work has assumed that the variance of RDS estimates is primarily affected by segregation between healthy and infected individuals. We examine an illustrative model to show that this is not necessarily the case, and that bottlenecks anywhere in the networks can substantially affect estimates. We also show that variance is inflated by a common design feature in which the sample members are encouraged to recruit multiple future sample members. The paper concludes with suggestions for implementing and evaluating RDS studies.

  20. Monte Carlo parametric importance sampling with particle tracks scaling

    International Nuclear Information System (INIS)

    Ragheb, M.M.H.

    1981-01-01

    A method for Monte Carlo importance sampling with parametric dependence is proposed. It depends upon obtaining 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 adopted and others rejected. The proposed method is applied to the finite slab penetration problem. When the exponential transformation is used, our method involves scaling of the generated particle tracks, and is a new application of Morton's method of similar trajectories. The method constitutes a generalization of Spanier's multistage importance sampling method, obtained by proper weighting over a single stage the curves he obtains over several stages, and preserves the statistical correlations between histories. It represents an extension of a theory by Frolov and Chentsov on Monte Carlo calculations of smooth curves to surfaces and to importance sampling calculations. By the proposed method, it seems possible to systematically arrive at minimum variance results and to avoid the infinite variances and effective biases sometimes observed in this type of calculation. (orig.) [de

  1. Monte Carlo: Basics

    OpenAIRE

    Murthy, K. P. N.

    2001-01-01

    An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...

  2. Spatial distribution sampling and Monte Carlo simulation of radioactive isotopes

    CERN Document Server

    Krainer, Alexander Michael

    2015-01-01

    This work focuses on the implementation of a program for random sampling of uniformly spatially distributed isotopes for Monte Carlo particle simulations and in specific FLUKA. With FLUKA it is possible to calculate the radio nuclide production in high energy fields. The decay of these nuclide, and therefore the resulting radiation field, however can only be simulated in the same geometry. This works gives the tool to simulate the decay of the produced nuclide in other geometries. With that the radiation field from an irradiated object can be simulated in arbitrary environments. The sampling of isotope mixtures was tested by simulating a 50/50 mixture of $Cs^{137}$ and $Co^{60}$. These isotopes are both well known and provide therefore a first reliable benchmark in that respect. The sampling of uniformly distributed coordinates was tested using the histogram test for various spatial distributions. The advantages and disadvantages of the program compared to standard methods are demonstrated in the real life ca...

  3. Monte Carlo methods

    Directory of Open Access Journals (Sweden)

    Bardenet Rémi

    2013-07-01

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

  4. Analytic continuation of quantum Monte Carlo data. Stochastic sampling method

    Energy Technology Data Exchange (ETDEWEB)

    Ghanem, Khaldoon; Koch, Erik [Institute for Advanced Simulation, Forschungszentrum Juelich, 52425 Juelich (Germany)

    2016-07-01

    We apply Bayesian inference to the analytic continuation of quantum Monte Carlo (QMC) data from the imaginary axis to the real axis. Demanding a proper functional Bayesian formulation of any analytic continuation method leads naturally to the stochastic sampling method (StochS) as the Bayesian method with the simplest prior, while it excludes the maximum entropy method and Tikhonov regularization. We present a new efficient algorithm for performing StochS that reduces computational times by orders of magnitude in comparison to earlier StochS methods. We apply the new algorithm to a wide variety of typical test cases: spectral functions and susceptibilities from DMFT and lattice QMC calculations. Results show that StochS performs well and is able to resolve sharp features in the spectrum.

  5. Monte Carlo importance sampling for the MCNP trademark general source

    International Nuclear Information System (INIS)

    Lichtenstein, H.

    1996-01-01

    Research was performed to develop an importance sampling procedure for a radiation source. The procedure was developed for the MCNP radiation transport code, but the approach itself is general and can be adapted to other Monte Carlo codes. The procedure, as adapted to MCNP, relies entirely on existing MCNP capabilities. It has been tested for very complex descriptions of a general source, in the context of the design of spent-reactor-fuel storage casks. Dramatic improvements in calculation efficiency have been observed in some test cases. In addition, the procedure has been found to provide an acceleration to acceptable convergence, as well as the benefit of quickly identifying user specified variance-reduction in the transport that effects unstable convergence

  6. Multi-index Monte Carlo: when sparsity meets sampling

    KAUST Repository

    Haji Ali, Abdul Lateef

    2015-06-27

    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, we use in MIMC high-order mixed differences instead of using first-order differences as in MLMC to reduce the variance of the hierarchical differences dramatically. This in turn yields new and improved complexity results, which are natural generalizations of Giles’s MLMC analysis and which increase the domain of the problem parameters for which we achieve the optimal convergence, O(TOL−2). Moreover, in MIMC, the rate of increase of required memory with respect to TOL is independent of the number of directions up to a logarithmic term which allows far more accurate solutions to be calculated for higher dimensions than what is possible when using MLMC. We motivate the setting of MIMC by first focusing on a simple full tensor index set. We then propose a systematic construction of optimal sets of indices for MIMC based on properly defined profits that in turn depend on the average cost per sample and the corresponding weak error and variance. Under standard assumptions on the convergence rates of the weak error, variance and work per sample, the optimal index set turns out to be the total degree type. In some cases, using optimal index sets, MIMC achieves a better rate for the computational complexity than the corresponding rate when using full tensor index sets. We also show the asymptotic normality of the statistical error in the resulting MIMC estimator and justify in this way our error estimate, which allows both the required accuracy and the confidence level in our computational

  7. Improvement of correlated sampling Monte Carlo methods for reactivity calculations

    International Nuclear Information System (INIS)

    Nakagawa, Masayuki; Asaoka, Takumi

    1978-01-01

    Two correlated Monte Carlo methods, the similar flight path and the identical flight path methods, have been improved to evaluate up to the second order change of the reactivity perturbation. Secondary fission neutrons produced by neutrons having passed through perturbed regions in both unperturbed and perturbed systems are followed in a way to have a strong correlation between secondary neutrons in both the systems. These techniques are incorporated into the general purpose Monte Carlo code MORSE, so as to be able to estimate also the statistical error of the calculated reactivity change. The control rod worths measured in the FCA V-3 assembly are analyzed with the present techniques, which are shown to predict the measured values within the standard deviations. The identical flight path method has revealed itself more useful than the similar flight path method for the analysis of the control rod worth. (auth.)

  8. Monte Carlo Sampling of Negative-temperature Plasma States

    International Nuclear Information System (INIS)

    John A. Krommes; Sharadini Rath

    2002-01-01

    A Monte Carlo procedure is used to generate N-particle configurations compatible with two-temperature canonical equilibria in two dimensions, with particular attention to nonlinear plasma gyrokinetics. An unusual feature of the problem is the importance of a nontrivial probability density function R0(PHI), the probability of realizing a set Φ of Fourier amplitudes associated with an ensemble of uniformly distributed, independent particles. This quantity arises because the equilibrium distribution is specified in terms of Φ, whereas the sampling procedure naturally produces particles states gamma; Φ and gamma are related via a gyrokinetic Poisson equation, highly nonlinear in its dependence on gamma. Expansion and asymptotic methods are used to calculate R0(PHI) analytically; excellent agreement is found between the large-N asymptotic result and a direct numerical calculation. The algorithm is tested by successfully generating a variety of states of both positive and negative temperature, including ones in which either the longest- or shortest-wavelength modes are excited to relatively very large amplitudes

  9. Monte Carlo sampling strategies for lattice gauge calculations

    International Nuclear Information System (INIS)

    Guralnik, G.; Zemach, C.; Warnock, T.

    1985-01-01

    We have sought to optimize the elements of the Monte Carlo processes for thermalizing and decorrelating sequences of lattice gauge configurations and for this purpose, to develop computational and theoretical diagnostics to compare alternative techniques. These have been applied to speed up generations of random matrices, compare heat bath and Metropolis stepping methods, and to study autocorrelations of sequences in terms of the classical moment problem. The efficient use of statistically correlated lattice data is an optimization problem depending on the relation between computer times to generate lattice sequences of sufficiently small correlation and times to analyze them. We can solve this problem with the aid of a representation of auto-correlation data for various step lags as moments of positive definite distributions, using methods known for the moment problem to put bounds on statistical variances, in place of estimating the variances by too-lengthy computer runs

  10. Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

    KAUST Repository

    Cheon, Sooyoung

    2013-02-16

    Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

  11. Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

    KAUST Repository

    Cheon, Sooyoung; Liang, Faming; Chen, Yuguo; Yu, Kai

    2013-01-01

    Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

  12. Ensemble bayesian model averaging using markov chain Monte Carlo sampling

    Energy Technology Data Exchange (ETDEWEB)

    Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL

    2008-01-01

    Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.

  13. Multi-Index Monte Carlo (MIMC) When sparsity meets sampling

    KAUST Repository

    Tempone, Raul

    2015-01-01

    This talk focuses into our newest method: Multi Index Monte Carlo (MIMC). The MIMC method uses a stochastic combination technique to solve the given approximation problem, generalizing the notion of standard MLMC levels into a set of multi indices that should be properly chosen to exploit the available regularity. Indeed, instead of using first-order differences as in standard MLMC, MIMC uses high-order differences to reduce the variance of the hierarchical differences dramatically. This in turn gives a new improved complexity result that increases the domain of the problem parameters for which the method achieves the optimal convergence rate, O(TOL-2). Using optimal index sets that we determined, MIMC achieves a better rate for the computational complexity does not depend on the dimensionality of the underlying problem, up to logarithmic factors. We present numerical results related to a three dimensional PDE with random coefficients to substantiate some of the derived computational complexity rates. Finally, using the Lindeberg-Feller theorem, we also show the asymptotic normality of the statistical error in the MIMC estimator and justify in this way our error estimate that allows prescribing both the required accuracy and confidence in the final result

  14. Multi-Index Monte Carlo (MIMC) When sparsity meets sampling

    KAUST Repository

    Tempone, Raul

    2015-01-07

    This talk focuses into our newest method: Multi Index Monte Carlo (MIMC). The MIMC method uses a stochastic combination technique to solve the given approximation problem, generalizing the notion of standard MLMC levels into a set of multi indices that should be properly chosen to exploit the available regularity. Indeed, instead of using first-order differences as in standard MLMC, MIMC uses high-order differences to reduce the variance of the hierarchical differences dramatically. This in turn gives a new improved complexity result that increases the domain of the problem parameters for which the method achieves the optimal convergence rate, O(TOL-2). Using optimal index sets that we determined, MIMC achieves a better rate for the computational complexity does not depend on the dimensionality of the underlying problem, up to logarithmic factors. We present numerical results related to a three dimensional PDE with random coefficients to substantiate some of the derived computational complexity rates. Finally, using the Lindeberg-Feller theorem, we also show the asymptotic normality of the statistical error in the MIMC estimator and justify in this way our error estimate that allows prescribing both the required accuracy and confidence in the final result

  15. Monte Carlo principles and applications

    Energy Technology Data Exchange (ETDEWEB)

    Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center

    1976-03-01

    The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.

  16. Vectorized Monte Carlo

    International Nuclear Information System (INIS)

    Brown, F.B.

    1981-01-01

    Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes

  17. Fundamentals of Monte Carlo

    International Nuclear Information System (INIS)

    Wollaber, Allan Benton

    2016-01-01

    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 @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

  18. Fundamentals of Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-16

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

  19. Power distribution system reliability evaluation using dagger-sampling Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Y.; Zhao, S.; Ma, Y. [North China Electric Power Univ., Hebei (China). Dept. of Electrical Engineering

    2009-03-11

    A dagger-sampling Monte Carlo simulation method was used to evaluate power distribution system reliability. The dagger-sampling technique was used to record the failure of a component as an incident and to determine its occurrence probability by generating incident samples using random numbers. The dagger sampling technique was combined with the direct sequential Monte Carlo method to calculate average values of load point indices and system indices. Results of the 2 methods with simulation times of up to 100,000 years were then compared. The comparative evaluation showed that less computing time was required using the dagger-sampling technique due to its higher convergence speed. When simulation times were 1000 years, the dagger-sampling method required 0.05 seconds to accomplish an evaluation, while the direct method required 0.27 seconds. 12 refs., 3 tabs., 4 figs.

  20. A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants

    KAUST Repository

    Liang, Faming; Jin, Ick-Hoon

    2013-01-01

    Simulating from distributions with intractable normalizing constants has been a long-standing problem inmachine learning. In this letter, we propose a new algorithm, the Monte Carlo Metropolis-Hastings (MCMH) algorithm, for tackling this problem. The MCMH algorithm is a Monte Carlo version of the Metropolis-Hastings algorithm. It replaces the unknown normalizing constant ratio by a Monte Carlo estimate in simulations, while still converges, as shown in the letter, to the desired target distribution under mild conditions. The MCMH algorithm is illustrated with spatial autologistic models and exponential random graph models. Unlike other auxiliary variable Markov chain Monte Carlo (MCMC) algorithms, such as the Møller and exchange algorithms, the MCMH algorithm avoids the requirement for perfect sampling, and thus can be applied to many statistical models for which perfect sampling is not available or very expensive. TheMCMHalgorithm can also be applied to Bayesian inference for random effect models and missing data problems that involve simulations from a distribution with intractable integrals. © 2013 Massachusetts Institute of Technology.

  1. Monte Carlo simulation of VHTR particle fuel with chord length sampling

    International Nuclear Information System (INIS)

    Ji, W.; Martin, W. R.

    2007-01-01

    The Very High Temperature Gas-Cooled Reactor (VHTR) poses a problem for neutronic analysis due to the double heterogeneity posed by the particle fuel and either the fuel compacts in the case of the prismatic block reactor or the fuel pebbles in the case of the pebble bed reactor. Direct Monte Carlo simulation has been used in recent years to analyze these VHTR configurations but is computationally challenged when space dependent phenomena are considered such as depletion or temperature feedback. As an alternative approach, we have considered chord length sampling to reduce the computational burden of the Monte Carlo simulation. We have improved on an existing method called 'limited chord length sampling' and have used it to analyze stochastic media representative of either pebble bed or prismatic VHTR fuel geometries. Based on the assumption that the PDF had an exponential form, a theoretical chord length distribution is derived and shown to be an excellent model for a wide range of packing fractions. This chord length PDF was then used to analyze a stochastic medium that was constructed using the RSA (Random Sequential Addition) algorithm and the results were compared to a benchmark Monte Carlo simulation of the actual stochastic geometry. The results are promising and suggest that the theoretical chord length PDF can be used instead of a full Monte Carlo random walk simulation in the stochastic medium, saving orders of magnitude in computational time (and memory demand) to perform the simulation. (authors)

  2. A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants

    KAUST Repository

    Liang, Faming

    2013-08-01

    Simulating from distributions with intractable normalizing constants has been a long-standing problem inmachine learning. In this letter, we propose a new algorithm, the Monte Carlo Metropolis-Hastings (MCMH) algorithm, for tackling this problem. The MCMH algorithm is a Monte Carlo version of the Metropolis-Hastings algorithm. It replaces the unknown normalizing constant ratio by a Monte Carlo estimate in simulations, while still converges, as shown in the letter, to the desired target distribution under mild conditions. The MCMH algorithm is illustrated with spatial autologistic models and exponential random graph models. Unlike other auxiliary variable Markov chain Monte Carlo (MCMC) algorithms, such as the Møller and exchange algorithms, the MCMH algorithm avoids the requirement for perfect sampling, and thus can be applied to many statistical models for which perfect sampling is not available or very expensive. TheMCMHalgorithm can also be applied to Bayesian inference for random effect models and missing data problems that involve simulations from a distribution with intractable integrals. © 2013 Massachusetts Institute of Technology.

  3. Monte Carlo importance sampling optimization for system reliability applications

    International Nuclear Information System (INIS)

    Campioni, Luca; Vestrucci, Paolo

    2004-01-01

    This paper focuses on the reliability analysis of multicomponent systems by the importance sampling technique, and, in particular, it tackles the optimization aspect. A methodology based on the minimization of the variance at the component level is proposed for the class of systems consisting of independent components. The claim is that, by means of such a methodology, the optimal biasing could be achieved without resorting to the typical approach by trials

  4. Exploring Monte Carlo methods

    CERN Document Server

    Dunn, William L

    2012-01-01

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

  5. A Monte Carlo algorithm for sampling rare events: application to a search for the Griffiths singularity

    International Nuclear Information System (INIS)

    Hukushima, K; Iba, Y

    2008-01-01

    We develop a recently proposed importance-sampling Monte Carlo algorithm for sampling rare events and quenched variables in random disordered systems. We apply it to a two dimensional bond-diluted Ising model and study the Griffiths singularity which is considered to be due to the existence of rare large clusters. It is found that the distribution of the inverse susceptibility has an exponential tail down to the origin which is considered the consequence of the Griffiths singularity

  6. The study of importance sampling in Monte-carlo calculation of blocking dips

    International Nuclear Information System (INIS)

    Pan Zhengying; Zhou Peng

    1988-01-01

    Angular blocking dips around the axis in Al single crystal of α-particles of about 2 Mev produced at a depth of 0.2 μm are calculated by a Monte-carlo simulation. The influence of the small solid angle emission of particles and the importance sampling in the solid angle emission have been investigated. By means of importance sampling, a more reasonable results with high accuracy are obtained

  7. Design of sampling tools for Monte Carlo particle transport code JMCT

    International Nuclear Information System (INIS)

    Shangguan Danhua; Li Gang; Zhang Baoyin; Deng Li

    2012-01-01

    A class of sampling tools for general Monte Carlo particle transport code JMCT is designed. Two ways are provided to sample from distributions. One is the utilization of special sampling methods for special distribution; the other is the utilization of general sampling methods for arbitrary discrete distribution and one-dimensional continuous distribution on a finite interval. Some open source codes are included in the general sampling method for the maximum convenience of users. The sampling results show sampling correctly from distribution which are popular in particle transport can be achieved with these tools, and the user's convenience can be assured. (authors)

  8. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures

    Directory of Open Access Journals (Sweden)

    Mahdi Shadab Far

    2016-01-01

    Full Text Available Structural load types, on the one hand, and structural capacity to withstand these loads, on the other hand, are of a probabilistic nature as they cannot be calculated and presented in a fully deterministic way. As such, the past few decades have witnessed the development of numerous probabilistic approaches towards the analysis and design of structures. Among the conventional methods used to assess structural reliability, the Monte Carlo sampling method has proved to be very convenient and efficient. However, it does suffer from certain disadvantages, the biggest one being the requirement of a very large number of samples to handle small probabilities, leading to a high computational cost. In this paper, a simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method. This revised approach was then presented in a step-by-step flowchart, for the purpose of easy programming and implementation.

  9. Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations

    Science.gov (United States)

    Hatch, Harold W.; Jiao, Sally; Mahynski, Nathan A.; Blanco, Marco A.; Shen, Vincent K.

    2017-12-01

    Virial coefficients are predicted over a large range of both temperatures and model parameter values (i.e., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayer-sampling Monte Carlo simulation of the SPC/E (extended simple point charge) water model quantitatively predicted the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicted the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% down to zero charge. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid.

  10. Monte Carlo simulation of air sampling methods for the measurement of radon decay products.

    Science.gov (United States)

    Sima, Octavian; Luca, Aurelian; Sahagia, Maria

    2017-08-01

    A stochastic model of the processes involved in the measurement of the activity of the 222 Rn decay products was developed. The distributions of the relevant factors, including air sampling and radionuclide collection, are propagated using Monte Carlo simulation to the final distribution of the measurement results. The uncertainties of the 222 Rn decay products concentrations in the air are realistically evaluated. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

    International Nuclear Information System (INIS)

    Beer, M.

    1980-01-01

    The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that the use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates

  12. New sampling method in continuous energy Monte Carlo calculation for pebble bed reactors

    International Nuclear Information System (INIS)

    Murata, Isao; Takahashi, Akito; Mori, Takamasa; Nakagawa, Masayuki.

    1997-01-01

    A pebble bed reactor generally has double heterogeneity consisting of two kinds of spherical fuel element. In the core, there exist many fuel balls piled up randomly in a high packing fraction. And each fuel ball contains a lot of small fuel particles which are also distributed randomly. In this study, to realize precise neutron transport calculation of such reactors with the continuous energy Monte Carlo method, a new sampling method has been developed. The new method has been implemented in the general purpose Monte Carlo code MCNP to develop a modified version MCNP-BALL. This method was validated by calculating inventory of spherical fuel elements arranged successively by sampling during transport calculation and also by performing criticality calculations in ordered packing models. From the results, it was confirmed that the inventory of spherical fuel elements could be reproduced using MCNP-BALL within a sufficient accuracy of 0.2%. And the comparison of criticality calculations in ordered packing models between MCNP-BALL and the reference method shows excellent agreement in neutron spectrum as well as multiplication factor. MCNP-BALL enables us to analyze pebble bed type cores such as PROTEUS precisely with the continuous energy Monte Carlo method. (author)

  13. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay; Law, Kody; Suciu, Carina

    2017-01-01

    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.

  14. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay

    2017-04-24

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

  15. MORSE Monte Carlo code

    International Nuclear Information System (INIS)

    Cramer, S.N.

    1984-01-01

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

  16. Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields

    Energy Technology Data Exchange (ETDEWEB)

    Armas-Pérez, Julio C.; Londono-Hurtado, Alejandro [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637 (United States); Guzmán, Orlando [Departamento de Física, Universidad Autónoma Metropolitana, Iztapalapa, DF 09340, México (Mexico); Hernández-Ortiz, Juan P. [Departamento de Materiales y Minerales, Universidad Nacional de Colombia, Sede Medellín, Medellín (Colombia); Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637 (United States); Pablo, Juan J. de, E-mail: depablo@uchicago.edu [Institute for Molecular Engineering, University of Chicago, Chicago, Illinois 60637 (United States); Materials Science Division, Argonne National Laboratory, Argonne, Illinois 60439 (United States)

    2015-07-28

    A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystal droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.

  17. Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields.

    Energy Technology Data Exchange (ETDEWEB)

    Armas-Perez, Julio C.; Londono-Hurtado, Alejandro; Guzman, Orlando; Hernandez-Ortiz, Juan P.; de Pablo, Juan J.

    2015-07-27

    A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystal droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.

  18. Fitted temperature-corrected Compton cross sections for Monte Carlo applications and a sampling distribution

    International Nuclear Information System (INIS)

    Wienke, B.R.; Devaney, J.J.; Lathrop, B.L.

    1984-01-01

    Simple temperature-corrected cross sections, which replace the static Klein-Nishina set in a one-to-one manner, are developed for Monte Carlo applications. The reduced set is obtained from a nonlinear least-squares fit to the exact photon-Maxwellian electron cross sections by using a Klein-Nishina-like formula as the fitting equation. Two parameters are sufficient, and accurate to two decimal places, to explicitly fit the exact cross sections over a range of 0 to 100 keV in electron temperature and 0 to 1 MeV in incident photon energy. Since the fit equations are Klein-Nishina-like, existing Monte Carlo code algorithms using the Klein-Nishina formula can be trivially modified to accommodate corrections for a moving Maxwellian electron background. The simple two parameter scheme and other fits are presented and discussed and comparisons with exact predictions are exhibited. The fits are made to the total photon-Maxwellian electron cross section and the fitting parameters can be consistently used in both the energy conservation equation for photon-electron scattering and the differential cross section, as they are presently sampled in Monte Carlo photonics applications. The fit equations are motivated in a very natural manner by the asymptotic expansion of the exact photon-Maxwellian effective cross-section kernel. A probability distribution is also obtained for the corrected set of equations

  19. 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 ...

  20. Virtual sampling in variational processing of Monte Carlo simulation in a deep neutron penetration problem

    International Nuclear Information System (INIS)

    Allagi, Mabruk O.; Lewins, Jeffery D.

    1999-01-01

    In a further study of virtually processed Monte Carlo estimates in neutron transport, a shielding problem has been studied. The use of virtual sampling to estimate the importance function at a certain point in the phase space depends on the presence of neutrons from the real source at that point. But in deep penetration problems, not many neutrons will reach regions far away from the source. In order to overcome this problem, two suggestions are considered: (1) virtual sampling is used as far as the real neutrons can reach, then fictitious sampling is introduced for the remaining regions, distributed in all the regions, or (2) only one fictitious source is placed where the real neutrons almost terminate and then virtual sampling is used in the same way as for the real source. Variational processing is again found to improve the Monte Carlo estimates, being best when using one fictitious source in the far regions with virtual sampling (option 2). When fictitious sources are used to estimate the importances in regions far away from the source, some optimization has to be performed for the proportion of fictitious to real sources, weighted against accuracy and computational costs. It has been found in this study that the optimum number of cells to be treated by fictitious sampling is problem dependent, but as a rule of thumb, fictitious sampling should be employed in regions where the number of neutrons from the real source fall below a specified limit for good statistics

  1. How the Monte Carlo production of a wide variety of different samples is centrally handled in the LHCb experiment

    CERN Document Server

    Corti, G; Clemencic, M; Closier, J; Couturier, B; Kreps, M; Mathe, Z; O'Hanlon, D; Robbe, P; Romanovsky, V; Stagni, F; Zhelezov, A

    2015-01-01

    In the LHCb experiment a wide variety of Monte Carlo simulated samples needs to be produced for the experiment's physics program. Monte Carlo productions are handled centrally similarly to all massive processing of data in the experiment. In order to cope with the large set of different types of simulation samples, necessary procedures based on common infrastructures have been set up with a numerical event type identification code used throughout. The various elements in the procedure, from writing a configuration for an event type to deploying them on the production environment, from submitting and processing a request to retrieving the sample produced as well as the conventions established to allow their interplay will be described. The choices made have allowed a high level of automation of Monte Carlo productions that are handled centrally in a transparent way with experts concentrating on their specific tasks. As a result the massive Monte Carlo production of the experiment is efficiently processed on a ...

  2. On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Mattelaer, Olivier [Durham University, Institute for Particle Physics Phenomenology (IPPP), Durham (United Kingdom)

    2016-12-15

    Accurate Monte Carlo simulations for high-energy events at CERN's Large Hadron Collider, are very expensive, both from the computing and storage points of view. We describe a method that allows to consistently re-use parton-level samples accurate up to NLO in QCD under different theoretical hypotheses. We implement it in MadGraph5{sub a}MC rate at NLO and show its validation by applying it to several cases of practical interest for the search of new physics at the LHC. (orig.)

  3. On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample

    DEFF Research Database (Denmark)

    Oukbir, J.; Arnaud, M.

    2001-01-01

    We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...

  4. A Hybrid Monte Carlo importance sampling of rare events in Turbulence and in Turbulent Models

    Science.gov (United States)

    Margazoglou, Georgios; Biferale, Luca; Grauer, Rainer; Jansen, Karl; Mesterhazy, David; Rosenow, Tillmann; Tripiccione, Raffaele

    2017-11-01

    Extreme and rare events is a challenging topic in the field of turbulence. Trying to investigate those instances through the use of traditional numerical tools turns to be a notorious task, as they fail to systematically sample the fluctuations around them. On the other hand, we propose that an importance sampling Monte Carlo method can selectively highlight extreme events in remote areas of the phase space and induce their occurrence. We present a brand new computational approach, based on the path integral formulation of stochastic dynamics, and employ an accelerated Hybrid Monte Carlo (HMC) algorithm for this purpose. Through the paradigm of stochastic one-dimensional Burgers' equation, subjected to a random noise that is white-in-time and power-law correlated in Fourier space, we will prove our concept and benchmark our results with standard CFD methods. Furthermore, we will present our first results of constrained sampling around saddle-point instanton configurations (optimal fluctuations). The research leading to these results has received funding from the EU Horizon 2020 research and innovation programme under Grant Agreement No. 642069, and from the EU Seventh Framework Programme (FP7/2007-2013) under ERC Grant Agreement No. 339032.

  5. Potential-Decomposition Strategy in Markov Chain Monte Carlo Sampling Algorithms

    International Nuclear Information System (INIS)

    Shangguan Danhua; Bao Jingdong

    2010-01-01

    We introduce the potential-decomposition strategy (PDS), which can he used in Markov chain Monte Carlo sampling algorithms. PDS can be designed to make particles move in a modified potential that favors diffusion in phase space, then, by rejecting some trial samples, the target distributions can be sampled in an unbiased manner. Furthermore, if the accepted trial samples are insufficient, they can be recycled as initial states to form more unbiased samples. This strategy can greatly improve efficiency when the original potential has multiple metastable states separated by large barriers. We apply PDS to the 2d Ising model and a double-well potential model with a large barrier, demonstrating in these two representative examples that convergence is accelerated by orders of magnitude.

  6. An adaptive Monte Carlo method under emission point as sampling station for deep penetration calculation

    International Nuclear Information System (INIS)

    Wang, Ruihong; Yang, Shulin; Pei, Lucheng

    2011-01-01

    Deep penetration problem has been one of the difficult problems in shielding calculation with Monte Carlo method for several decades. In this paper, an adaptive technique under the emission point as a sampling station is presented. The main advantage is to choose the most suitable sampling number from the emission point station to get the minimum value of the total cost in the process of the random walk. Further, the related importance sampling method is also derived. The main principle is to define the importance function of the response due to the particle state and ensure the sampling number of the emission particle is proportional to the importance function. The numerical results show that the adaptive method under the emission point as a station could overcome the difficulty of underestimation to the result in some degree, and the related importance sampling method gets satisfied results as well. (author)

  7. 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)

  8. New Hybrid Monte Carlo methods for efficient sampling. From physics to biology and statistics

    International Nuclear Information System (INIS)

    Akhmatskaya, Elena; Reich, Sebastian

    2011-01-01

    We introduce a class of novel hybrid methods for detailed simulations of large complex systems in physics, biology, materials science and statistics. These generalized shadow Hybrid Monte Carlo (GSHMC) methods combine the advantages of stochastic and deterministic simulation techniques. They utilize a partial momentum update to retain some of the dynamical information, employ modified Hamiltonians to overcome exponential performance degradation with the system’s size and make use of multi-scale nature of complex systems. Variants of GSHMCs were developed for atomistic simulation, particle simulation and statistics: GSHMC (thermodynamically consistent implementation of constant-temperature molecular dynamics), MTS-GSHMC (multiple-time-stepping GSHMC), meso-GSHMC (Metropolis corrected dissipative particle dynamics (DPD) method), and a generalized shadow Hamiltonian Monte Carlo, GSHmMC (a GSHMC for statistical simulations). All of these are compatible with other enhanced sampling techniques and suitable for massively parallel computing allowing for a range of multi-level parallel strategies. A brief description of the GSHMC approach, examples of its application on high performance computers and comparison with other existing techniques are given. Our approach is shown to resolve such problems as resonance instabilities of the MTS methods and non-preservation of thermodynamic equilibrium properties in DPD, and to outperform known methods in sampling efficiency by an order of magnitude. (author)

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

    KAUST Repository

    Liang, Faming

    2009-01-01

    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

  10. Study on Quantification for Multi-unit Seismic PSA Model using Monte Carlo Sampling

    International Nuclear Information System (INIS)

    Oh, Kyemin; Han, Sang Hoon; Jang, Seung-cheol; Park, Jin Hee; Lim, Ho-Gon; Yang, Joon Eon; Heo, Gyunyoung

    2015-01-01

    In existing PSA, frequency for accident sequences occurred in single-unit has been estimated. While multi-unit PSA has to consider various combinations because accident sequence in each units can be different. However, it is difficult to quantify all of combination between inter-units using traditional method such as Minimal Cut Upper Bound (MCUB). For this reason, we used Monte Carlo sampling as a method to quantify multi-unit PSA model. In this paper, Monte Carlo method was used to quantify multi-unit PSA model. The advantage of this method is to consider all of combinations by the increase of number of unit and to calculate nearly exact value compared to other method. However, it is difficult to get detailed information such as minimal cut sets and accident sequence. To solve partially this problem, FTeMC was modified. In multi-unit PSA, quantification for both internal and external multi-unit accidents is the significant issue. Although our result above mentioned was one of the case studies to check application of method suggested in this paper, it is expected that this method can be used in practical assessment for multi-unit risk

  11. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

    2016-01-01

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

  12. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

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

  13. Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data

    International Nuclear Information System (INIS)

    Silva, A. N. C. da; Amaral, R. S.; Araujo Santos Jr, J.; Wilson Vieira, J.; Lima, F. R. de A.

    2015-01-01

    There are operational difficulties in obtaining samples for radioecological studies. Population data may no longer be available during the study and obtaining new samples may not be possible. These problems do the researcher sometimes work with a small number of data. Therefore, it is difficult to know whether the number of samples will be sufficient to estimate the desired parameter. Hence, it is critical do the analysis of sample sufficiency. It is not interesting uses the classical methods of statistic to analyze sample sufficiency in Radioecology, because naturally occurring radionuclides have a random distribution in soil, usually arise outliers and gaps with missing values. The present work was developed aiming to apply the Monte Carlo Bootstrap method in the analysis of sample sufficiency with quantitative estimation of a single variable such as specific activity of a natural radioisotope present in plants. The pseudo population was a small sample with 14 values of specific activity of 226 Ra in forage palm (Opuntia spp.). Using the R software was performed a computational procedure to calculate the number of the sample values. The re sampling process with replacement took the 14 values of original sample and produced 10,000 bootstrap samples for each round. Then was calculated the estimated average θ for samples with 2, 5, 8, 11 and 14 values randomly selected. The results showed that if the researcher work with only 11 sample values, the average parameter will be within a confidence interval with 90% probability . (Author)

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Androsenko, P.A.; Belousov, V.I. [Obninsk State Technical Univ. of Nuclear Power Engineering, Kaluga region (Russian Federation)

    2005-07-01

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

  16. Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

    Energy Technology Data Exchange (ETDEWEB)

    Vrbik, Jan [Department of Mathematics, Brock University, St. Catharines, Ontario L2S 3A1 (Canada); Ospadov, Egor; Rothstein, Stuart M., E-mail: srothstein@brocku.ca [Department of Physics, Brock University, St. Catharines, Ontario L2S 3A1 (Canada)

    2016-07-14

    Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x′; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

  17. Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

    International Nuclear Information System (INIS)

    Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M.

    2016-01-01

    Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x′; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

  18. Markov Chain Monte Carlo

    Indian Academy of Sciences (India)

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

  19. Self-absorption corrections of various sample-detector geometries in gamma-ray spectrometry using sample Monte Carlo Simulations

    International Nuclear Information System (INIS)

    Ahmad Saat; Appleby, P.G.; Nolan, P.J.

    1997-01-01

    Corrections for self-absorption in gamma-ray spectrometry have been developed using a simple Monte Carlo simulation technique. The simulation enables the calculation of gamma-ray path lengths in the sample which, using available data, can be used to calculate self-absorption correction factors. The simulation was carried out on three sample geometries: disk, Marinelli beaker, and cylinder (for well-type detectors). Mathematical models and experimental measurements are used to evaluate the simulations. A good agreement of within a few percents was observed. The simulation results are also in good agreement with those reported in the literature. The simulation code was carried out in FORTRAN 90,

  20. Bayesian Modelling, Monte Carlo Sampling and Capital Allocation of Insurance Risks

    Directory of Open Access Journals (Sweden)

    Gareth W. Peters

    2017-09-01

    Full Text Available The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method to calculate capital allocations for a general insurance company is developed, with a focus on coherent capital allocation that is compliant with the Swiss Solvency Test. The data used is based on the balance sheet of a representative stylized company. For each line of business in that company, allocations are calculated for the one-year risk with dependencies based on correlations given by the Swiss Solvency Test. Two different approaches for dealing with parameter uncertainty are discussed and simulation algorithms based on (pseudo-marginal Sequential Monte Carlo algorithms are described and their efficiency is analysed.

  1. Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling

    DEFF Research Database (Denmark)

    Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan

    2008-01-01

    uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...

  2. Bayesian Monte Carlo method

    International Nuclear Information System (INIS)

    Rajabalinejad, M.

    2010-01-01

    To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.

  3. Loaded dice in Monte Carlo : importance sampling in phase space integration and probability distributions for discrepancies

    NARCIS (Netherlands)

    Hameren, Andreas Ferdinand Willem van

    2001-01-01

    Discrepancies play an important role in the study of uniformity properties of point sets. Their probability distributions are a help in the analysis of the efficiency of the Quasi Monte Carlo method of numerical integration, which uses point sets that are distributed more uniformly than sets of

  4. Contributon Monte Carlo

    International Nuclear Information System (INIS)

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

    1979-05-01

    The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables

  5. Microcanonical Monte Carlo

    International Nuclear Information System (INIS)

    Creutz, M.

    1986-01-01

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

  6. Monte Carlo alpha calculation

    Energy Technology Data Exchange (ETDEWEB)

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

    1985-01-01

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

  7. Monte Carlo sampling on technical parameters in criticality and burn-up-calculations

    International Nuclear Information System (INIS)

    Kirsch, M.; Hannstein, V.; Kilger, R.

    2011-01-01

    The increase in computing power over the recent years allows for the introduction of Monte Carlo sampling techniques for sensitivity and uncertainty analyses in criticality safety and burn-up calculations. With these techniques it is possible to assess the influence of a variation of the input parameters within their measured or estimated uncertainties on the final value of a calculation. The probabilistic result of a statistical analysis can thus complement the traditional method of figuring out both the nominal (best estimate) and the bounding case of the neutron multiplication factor (k eff ) in criticality safety analyses, e.g. by calculating the uncertainty of k eff or tolerance limits. Furthermore, the sampling method provides a possibility to derive sensitivity information, i.e. it allows figuring out which of the uncertain input parameters contribute the most to the uncertainty of the system. The application of Monte Carlo sampling methods has become a common practice in both industry and research institutes. Within this approach, two main paths are currently under investigation: the variation of nuclear data used in a calculation and the variation of technical parameters such as manufacturing tolerances. This contribution concentrates on the latter case. The newly developed SUnCISTT (Sensitivities and Uncertainties in Criticality Inventory and Source Term Tool) is introduced. It defines an interface to the well established GRS tool for sensitivity and uncertainty analyses SUSA, that provides the necessary statistical methods for sampling based analyses. The interfaced codes are programs that are used to simulate aspects of the nuclear fuel cycle, such as the criticality safety analysis sequence CSAS5 of the SCALE code system, developed by Oak Ridge National Laboratories, or the GRS burn-up system OREST. In the following, first the implementation of the SUnCISTT will be presented, then, results of its application in an exemplary evaluation of the neutron

  8. Analysis of inconsistent source sampling in monte carlo weight-window variance reduction methods

    Directory of Open Access Journals (Sweden)

    David P. Griesheimer

    2017-09-01

    Full Text Available The application of Monte Carlo (MC to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

  9. Monte Carlo Simulation Of The Portfolio-Balance Model Of Exchange Rates: Finite Sample Properties Of The GMM Estimator

    OpenAIRE

    Hong-Ghi Min

    2011-01-01

    Using Monte Carlo simulation of the Portfolio-balance model of the exchange rates, we report finite sample properties of the GMM estimator for testing over-identifying restrictions in the simultaneous equations model. F-form of Sargans statistic performs better than its chi-squared form while Hansens GMM statistic has the smallest bias.

  10. Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator

    Science.gov (United States)

    Suh, Donghyuk; Radak, Brian K.; Chipot, Christophe; Roux, Benoît

    2018-01-01

    Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield

  11. Computer simulation of stochastic processes through model-sampling (Monte Carlo) techniques.

    Science.gov (United States)

    Sheppard, C W.

    1969-03-01

    A simple Monte Carlo simulation program is outlined which can be used for the investigation of random-walk problems, for example in diffusion, or the movement of tracers in the blood circulation. The results given by the simulation are compared with those predicted by well-established theory, and it is shown how the model can be expanded to deal with drift, and with reflexion from or adsorption at a boundary.

  12. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling

    Energy Technology Data Exchange (ETDEWEB)

    Vrugt, Jasper A [Los Alamos National Laboratory; Hyman, James M [Los Alamos National Laboratory; Robinson, Bruce A [Los Alamos National Laboratory; Higdon, Dave [Los Alamos National Laboratory; Ter Braak, Cajo J F [NETHERLANDS; Diks, Cees G H [UNIV OF AMSTERDAM

    2008-01-01

    Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.

  13. Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations.

    Directory of Open Access Journals (Sweden)

    Kecheng Yang

    Full Text Available Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE, is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD-Monte Carlo (MC approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.

  14. A contribution Monte Carlo method

    International Nuclear Information System (INIS)

    Aboughantous, C.H.

    1994-01-01

    A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time

  15. 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)

  16. Monte Carlo Calculation of Thermal Neutron Inelastic Scattering Cross Section Uncertainties by Sampling Perturbed Phonon Spectra

    Science.gov (United States)

    Holmes, Jesse Curtis

    established that depends on uncertainties in the physics models and methodology employed to produce the DOS. Through Monte Carlo sampling of perturbations from the reference phonon spectrum, an S(alpha, beta) covariance matrix may be generated. In this work, density functional theory and lattice dynamics in the harmonic approximation are used to calculate the phonon DOS for hexagonal crystalline graphite. This form of graphite is used as an example material for the purpose of demonstrating procedures for analyzing, calculating and processing thermal neutron inelastic scattering uncertainty information. Several sources of uncertainty in thermal neutron inelastic scattering calculations are examined, including sources which cannot be directly characterized through a description of the phonon DOS uncertainty, and their impacts are evaluated. Covariances for hexagonal crystalline graphite S(alpha, beta) data are quantified by coupling the standard methodology of LEAPR with a Monte Carlo sampling process. The mechanics of efficiently representing and processing this covariance information is also examined. Finally, with appropriate sensitivity information, it is shown that an S(alpha, beta) covariance matrix can be propagated to generate covariance data for integrated cross sections, secondary energy distributions, and coupled energy-angle distributions. This approach enables a complete description of thermal neutron inelastic scattering cross section uncertainties which may be employed to improve the simulation of nuclear systems.

  17. Monte Carlo simulations of channeling spectra recorded for samples containing complex defects

    Energy Technology Data Exchange (ETDEWEB)

    Jagielski, Jacek [Institute for Electronic Materials Technology; Turos, Prof. Andrzej [Institute for Electronic Materials Technology; Nowicki, Lech [Soltan Institute for Nuclear Studies, Swierk, Poland; Jozwik, P. [Institute for Electronic Materials Technology; Shutthanandan, Vaithiyalingam [Pacific Northwest National Laboratory (PNNL); Zhang, Yanwen [ORNL; Sathish, N. [Institute for Electronic Materials Technology; Thome, Lionel [Universite Paris Sud, Orsay, France; Stonert, A. [Soltan Institute for Nuclear Studies, Swierk, Poland; Jozwik-Biala, Iwona [Institute for Electronic Materials Technology

    2012-01-01

    The aim of the present paper is to describe the current status of the development of McChasy, a Monte Carlo simulation code, to make it suitable for the analysis of dislocations and dislocation loops in crystals. Such factors like the shape of the bent channel and geometrical distortions of the crystalline structure in the vicinity of dislocation has been discussed. The results obtained demonstrate that the new procedure applied to the spectra recorded on crystals containing dislocation yields damage profiles which are independent of the energy of the analyzing beam.

  18. 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

  19. Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

    Science.gov (United States)

    Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

    2011-12-01

    Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently

  20. Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

    International Nuclear Information System (INIS)

    Zhu, T.

    2015-01-01

    Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ_e_f_f sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

  1. Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, T.

    2015-07-01

    Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ{sub eff} sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

  2. Prospect on general software of Monte Carlo method

    International Nuclear Information System (INIS)

    Pei Lucheng

    1992-01-01

    This is a short paper on the prospect of Monte Carlo general software. The content consists of cluster sampling method, zero variance technique, self-improved method, and vectorized Monte Carlo method

  3. Statistical estimation Monte Carlo for unreliability evaluation of highly reliable system

    International Nuclear Information System (INIS)

    Xiao Gang; Su Guanghui; Jia Dounan; Li Tianduo

    2000-01-01

    Based on analog Monte Carlo simulation, statistical Monte Carlo methods for unreliable evaluation of highly reliable system are constructed, including direct statistical estimation Monte Carlo method and weighted statistical estimation Monte Carlo method. The basal element is given, and the statistical estimation Monte Carlo estimators are derived. Direct Monte Carlo simulation method, bounding-sampling method, forced transitions Monte Carlo method, direct statistical estimation Monte Carlo and weighted statistical estimation Monte Carlo are used to evaluate unreliability of a same system. By comparing, weighted statistical estimation Monte Carlo estimator has smallest variance, and has highest calculating efficiency

  4. Lectures on Monte Carlo methods

    CERN Document Server

    Madras, Neal

    2001-01-01

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

  5. Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution

    Czech Academy of Sciences Publication Activity Database

    Mukhopadhyay, N. D.; Sampson, A. J.; Deniz, D.; Carlsson, G. A.; Williamson, J.; Malušek, Alexandr

    2012-01-01

    Roč. 70, č. 1 (2012), s. 315-323 ISSN 0969-8043 Institutional research plan: CEZ:AV0Z10480505 Keywords : Monte Carlo * correlated sampling * efficiency * uncertainty * bootstrap Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 1.179, year: 2012 http://www.sciencedirect.com/science/article/pii/S0969804311004775

  6. MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling

    Directory of Open Access Journals (Sweden)

    Kitchen James L

    2012-11-01

    Full Text Available Abstract Background Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR algorithm. Results After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. Conclusions MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.

  7. MCMC-ODPR: primer design optimization using Markov Chain Monte Carlo sampling.

    Science.gov (United States)

    Kitchen, James L; Moore, Jonathan D; Palmer, Sarah A; Allaby, Robin G

    2012-11-05

    Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm. After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.

  8. LCG Monte-Carlo Data Base

    CERN Document Server

    Bartalini, P.; Kryukov, A.; Selyuzhenkov, Ilya V.; Sherstnev, A.; Vologdin, A.

    2004-01-01

    We present the Monte-Carlo events Data Base (MCDB) project and its development plans. MCDB facilitates communication between authors of Monte-Carlo generators and experimental users. It also provides a convenient book-keeping and an easy access to generator level samples. The first release of MCDB is now operational for the CMS collaboration. In this paper we review the main ideas behind MCDB and discuss future plans to develop this Data Base further within the CERN LCG framework.

  9. Multilevel Monte Carlo in Approximate Bayesian Computation

    KAUST Repository

    Jasra, Ajay

    2017-02-13

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

  10. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-02-15

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

  12. Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

    Science.gov (United States)

    Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

    2012-01-01

    Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. 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

  14. Monte Carlo theory and practice

    International Nuclear Information System (INIS)

    James, F.

    1987-01-01

    Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem

  15. Quantum Monte Carlo approaches for correlated systems

    CERN Document Server

    Becca, Federico

    2017-01-01

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

  16. Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

    Science.gov (United States)

    Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang

    2017-07-10

    In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

  17. Study on quantification method based on Monte Carlo sampling for multiunit probabilistic safety assessment models

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Kye Min [KHNP Central Research Institute, Daejeon (Korea, Republic of); Han, Sang Hoon; Park, Jin Hee; Lim, Ho Gon; Yang, Joon Yang [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of)

    2017-06-15

    In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.

  18. Importance sampling and histogrammic representations of reactivity functions and product distributions in Monte Carlo quasiclassical trajectory calculations

    International Nuclear Information System (INIS)

    Faist, M.B.; Muckerman, J.T.; Schubert, F.E.

    1978-01-01

    The application of importance sampling as a variance reduction technique in Monte Carlo quasiclassical trajectory calculations is discussed. Two measures are proposed which quantify the quality of the importance sampling used, and indicate whether further improvements may be obtained by some other choice of importance sampling function. A general procedure for constructing standardized histogrammic representations of differential functions which integrate to the appropriate integral value obtained from a trajectory calculation is presented. Two criteria for ''optimum'' binning of these histogrammic representations of differential functions are suggested. These are (1) that each bin makes an equal contribution to the integral value, and (2) each bin has the same relative error. Numerical examples illustrating these sampling and binning concepts are provided

  19. General Monte Carlo code MONK

    International Nuclear Information System (INIS)

    Moore, J.G.

    1974-01-01

    The Monte Carlo code MONK is a general program written to provide a high degree of flexibility to the user. MONK is distinguished by its detailed representation of nuclear data in point form i.e., the cross-section is tabulated at specific energies instead of the more usual group representation. The nuclear data are unadjusted in the point form but recently the code has been modified to accept adjusted group data as used in fast and thermal reactor applications. The various geometrical handling capabilities and importance sampling techniques are described. In addition to the nuclear data aspects, the following features are also described; geometrical handling routines, tracking cycles, neutron source and output facilities. 12 references. (U.S.)

  20. Symmetry relationships for multiple scattering of polarized light in turbid spherical samples: theory and a Monte Carlo simulation.

    Science.gov (United States)

    Otsuki, Soichi

    2016-02-01

    This paper presents a theory describing totally incoherent multiple scattering of turbid spherical samples. It is proved that if reciprocity and mirror symmetry hold for single scattering by a particle, they also hold for multiple scattering in spherical samples. Monte Carlo simulations generate a reduced effective scattering Mueller matrix, which virtually satisfies reciprocity and mirror symmetry. The scattering matrix was factorized by using the symmetric decomposition in a predefined form, as well as the Lu-Chipman polar decomposition, approximately into a product of a pure depolarizer and vertically oriented linear retarding diattenuators. The parameters of these components were calculated as a function of the polar angle. While the turbid spherical sample is a pure depolarizer at low polar angles, it obtains more functions of the retarding diattenuator with increasing polar angle.

  1. Reflections on early Monte Carlo calculations

    International Nuclear Information System (INIS)

    Spanier, J.

    1992-01-01

    Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances

  2. Strategije drevesnega preiskovanja Monte Carlo

    OpenAIRE

    VODOPIVEC, TOM

    2018-01-01

    Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...

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

    KAUST Repository

    Liang, Faming

    2009-03-01

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

  4. Variational Monte Carlo Technique

    Indian Academy of Sciences (India)

    ias

    on the development of nuclear weapons in Los Alamos ..... cantly improved the paper. ... Carlo simulations of solids, Reviews of Modern Physics, Vol.73, pp.33– ... The computer algorithms are usually based on a random seed that starts the ...

  5. Random Numbers and Monte Carlo Methods

    Science.gov (United States)

    Scherer, Philipp O. J.

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

  6. Transmission of 14 MeV neutrons through concrete, soil, sugar, wood and coal samples - a Monte Carlo Study

    International Nuclear Information System (INIS)

    Abdelmonem, M.S.; Naqvi, A.A.

    2006-01-01

    Full text: Fast neutrons transmission measurements are ideal for the elemental analysis of bulk samples. In particular, they can be used to determine the hydrogen concentration in bulk samples. In the present study, Monte Carlo simulations have been carried to calculate the intensity of 14 MeV neutrons transmitted through concrete, soil, sugar, wood and coal samples. The simulated set-up consists of a cylindrical sample, placed at a distance of 9 cm from the neutron source. Fast neutrons transmitted through the sample are collimated through a double truncated neutron collimator to a fast neutron detector. The collimator contains a mixture of paraffin and lithium carbonate. In this study, transmitted intensity of fast neutron through each sample was calculated as a function of moisture contents of the sample for 14 MeV neutrons. The moisture contents of the samples were varied over 0-7 wt. %. The calculated intensity of 14 MeV neutrons transmitted through the samples, shows effects related to fast neutron thermalization in hydrogen of moisture and energy dependence of neutron transmission through the sample materials. This is clearly shown by different gradients of neutron yield vs moisture content curves of these samples. The gradient of the neutron yield curves for the 14 MeV neutrons has a lower value than those reported for a 241 Am-Be neutron source

  7. Is Monte Carlo embarrassingly parallel?

    Energy Technology Data Exchange (ETDEWEB)

    Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

    2012-07-01

    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)

  8. 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)

  9. Exact Monte Carlo for molecules

    International Nuclear Information System (INIS)

    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 + H 2 , and the singlet-triplet splitting in methylene are presented and discussed. 17 refs

  10. 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

  11. Propagating Mixed Uncertainties in Cyber Attacker Payoffs: Exploration of Two-Phase Monte Carlo Sampling and Probability Bounds Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chatterjee, Samrat; Tipireddy, Ramakrishna; Oster, Matthew R.; Halappanavar, Mahantesh

    2016-09-16

    Securing cyber-systems on a continual basis against a multitude of adverse events is a challenging undertaking. Game-theoretic approaches, that model actions of strategic decision-makers, are increasingly being applied to address cybersecurity resource allocation challenges. Such game-based models account for multiple player actions and represent cyber attacker payoffs mostly as point utility estimates. Since a cyber-attacker’s payoff generation mechanism is largely unknown, appropriate representation and propagation of uncertainty is a critical task. In this paper we expand on prior work and focus on operationalizing the probabilistic uncertainty quantification framework, for a notional cyber system, through: 1) representation of uncertain attacker and system-related modeling variables as probability distributions and mathematical intervals, and 2) exploration of uncertainty propagation techniques including two-phase Monte Carlo sampling and probability bounds analysis.

  12. 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

  13. 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.

  14. SPQR: a Monte Carlo reactor kinetics code

    International Nuclear Information System (INIS)

    Cramer, S.N.; Dodds, H.L.

    1980-02-01

    The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations

  15. 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.)

  16. 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

  17. (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.

  18. 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.)

  19. 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

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

    Directory of Open Access Journals (Sweden)

    TEMITOPE RAPHAEL AYODELE

    2016-04-01

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

  1. Current and future applications of Monte Carlo

    International Nuclear Information System (INIS)

    Zaidi, H.

    2003-01-01

    Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as 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 (pdfs). 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. The use of the Monte Carlo method to simulate radiation transport has become 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 as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. 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 nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic

  2. Monte Carlo method for array criticality calculations

    International Nuclear Information System (INIS)

    Dickinson, D.; Whitesides, G.E.

    1976-01-01

    The Monte Carlo method for solving neutron transport problems consists of mathematically tracing paths of individual neutrons collision by collision until they are lost by absorption or leakage. The fate of the neutron after each collision is determined by the probability distribution functions that are formed from the neutron cross-section data. These distributions are sampled statistically to establish the successive steps in the neutron's path. The resulting data, accumulated from following a large number of batches, are analyzed to give estimates of k/sub eff/ and other collision-related quantities. The use of electronic computers to produce the simulated neutron histories, initiated at Los Alamos Scientific Laboratory, made the use of the Monte Carlo method practical for many applications. In analog Monte Carlo simulation, the calculation follows the physical events of neutron scattering, absorption, and leakage. To increase calculational efficiency, modifications such as the use of statistical weights are introduced. The Monte Carlo method permits the use of a three-dimensional geometry description and a detailed cross-section representation. Some of the problems in using the method are the selection of the spatial distribution for the initial batch, the preparation of the geometry description for complex units, and the calculation of error estimates for region-dependent quantities such as fluxes. The Monte Carlo method is especially appropriate for criticality safety calculations since it permits an accurate representation of interacting units of fissile material. Dissimilar units, units of complex shape, moderators between units, and reflected arrays may be calculated. Monte Carlo results must be correlated with relevant experimental data, and caution must be used to ensure that a representative set of neutron histories is produced

  3. Conditional Monte Carlo sampling to find branching architectures of polymers from radical polymerizations with transfer to polymer and recombination termination

    NARCIS (Netherlands)

    Iedema, P.D.; Wulkow, M.; Hoefsloot, H.C.J.

    2007-01-01

    A model is developed that predicts branching architectures of polymers from radical polymerization with transfer to polymer and termination by disproportionation and recombination, in a continuously stirred tank reactor (CSTR). It is a so-called conditional Monte Carlo (MC) method generating

  4. Isotopic depletion with Monte Carlo

    International Nuclear Information System (INIS)

    Martin, W.R.; Rathkopf, J.A.

    1996-06-01

    This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation

  5. Monte Carlo Methods in ICF

    Science.gov (United States)

    Zimmerman, George B.

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

  6. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, G.B.

    1997-01-01

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

  7. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, George B.

    1997-01-01

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

  8. Shell model Monte Carlo methods

    International Nuclear Information System (INIS)

    Koonin, S.E.; Dean, D.J.; Langanke, K.

    1997-01-01

    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; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) 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, the thermal and rotational behavior of rare-earth and γ-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. (orig.)

  9. 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

  10. 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

  11. Elements of Monte Carlo techniques

    International Nuclear Information System (INIS)

    Nagarajan, P.S.

    2000-01-01

    The Monte Carlo method is essentially mimicking the real world physical processes at the microscopic level. With the incredible increase in computing speeds and ever decreasing computing costs, there is widespread use of the method for practical problems. The method is used in calculating algorithm-generated sequences known as pseudo random sequence (prs)., probability density function (pdf), test for randomness, extension to multidimensional integration etc

  12. Adaptive Multilevel Monte Carlo Simulation

    KAUST Repository

    Hoel, H

    2011-08-23

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

  13. Geometrical splitting in Monte Carlo

    International Nuclear Information System (INIS)

    Dubi, A.; Elperin, T.; Dudziak, D.J.

    1982-01-01

    A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs

  14. 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

  15. Markov Chain Monte Carlo

    Indian Academy of Sciences (India)

    be obtained as a limiting value of a sample path of a suitable ... makes a mathematical model of chance and deals with the problem by .... Is the Markov chain aperiodic? It is! Here is how you can see it. Suppose that after you do the cut, you hold the top half in your right hand, and the bottom half in your left. Then there.

  16. A proposal on alternative sampling-based modeling method of spherical particles in stochastic media for Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Lee, Jae Yong; KIm, Do Hyun; Kim, Jong Kyung [Dept. of Nuclear Engineering, Hanyang University, Seoul (Korea, Republic of); Noh, Jae Man [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-08-15

    Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

  17. A proposal on alternative sampling-based modeling method of spherical particles in stochastic media for Monte Carlo simulation

    International Nuclear Information System (INIS)

    Kim, Song Hyun; Lee, Jae Yong; KIm, Do Hyun; Kim, Jong Kyung; Noh, Jae Man

    2015-01-01

    Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media

  18. Non statistical Monte-Carlo

    International Nuclear Information System (INIS)

    Mercier, B.

    1985-04-01

    We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems

  19. BREM5 electroweak Monte Carlo

    International Nuclear Information System (INIS)

    Kennedy, D.C. II.

    1987-01-01

    This is an update on the progress of the BREMMUS Monte Carlo simulator, particularly in its current incarnation, BREM5. The present report is intended only as a follow-up to the Mark II/Granlibakken proceedings, and those proceedings should be consulted for a complete description of the capabilities and goals of the BREMMUS program. The new BREM5 program improves on the previous version of BREMMUS, BREM2, in a number of important ways. In BREM2, the internal loop (oblique) corrections were not treated in consistent fashion, a deficiency that led to renormalization scheme-dependence; i.e., physical results, such as cross sections, were dependent on the method used to eliminate infinities from the theory. Of course, this problem cannot be tolerated in a Monte Carlo designed for experimental use. BREM5 incorporates a new way of treating the oblique corrections, as explained in the Granlibakken proceedings, that guarantees renormalization scheme-independence and dramatically simplifies the organization and calculation of radiative corrections. This technique is to be presented in full detail in a forthcoming paper. BREM5 is, at this point, the only Monte Carlo to contain the entire set of one-loop corrections to electroweak four-fermion processes and renormalization scheme-independence. 3 figures

  20. Statistical implications in Monte Carlo depletions - 051

    International Nuclear Information System (INIS)

    Zhiwen, Xu; Rhodes, J.; Smith, K.

    2010-01-01

    As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)

  1. 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)

  2. Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

    Science.gov (United States)

    Hansen, T. M.; Cordua, K. S.

    2017-12-01

    Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

  3. Applications of the Monte Carlo method in radiation protection

    International Nuclear Information System (INIS)

    Kulkarni, R.N.; Prasad, M.A.

    1999-01-01

    This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)

  4. Coevolution Based Adaptive Monte Carlo Localization (CEAMCL

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2008-11-01

    Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.

  5. 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.

  6. Distribution of the Determinant of the Sample Correlation Matrix: Monte Carlo Type One Error Rates.

    Science.gov (United States)

    Reddon, John R.; And Others

    1985-01-01

    Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)

  7. Effect of Different Sampling Schedules on Results of Bioavailability and Bioequivalence Studies: Evaluation by Means of Monte Carlo Simulations.

    Science.gov (United States)

    Kano, Eunice Kazue; Chiann, Chang; Fukuda, Kazuo; Porta, Valentina

    2017-08-01

    Bioavailability and bioequivalence study is one of the most frequently performed investigations in clinical trials. Bioequivalence testing is based on the assumption that 2 drug products will be therapeutically equivalent when they are equivalent in the rate and extent to which the active drug ingredient or therapeutic moiety is absorbed and becomes available at the site of drug action. In recent years there has been a significant growth in published papers that use in silico studies based on mathematical simulations to analyze pharmacokinetic and pharmacodynamic properties of drugs, including bioavailability and bioequivalence aspects. The goal of this study is to evaluate the usefulness of in silico studies as a tool in the planning of bioequivalence, bioavailability and other pharmacokinetic assays, e.g., to determine an appropriate sampling schedule. Monte Carlo simulations were used to define adequate blood sampling schedules for a bioequivalence assay comparing 2 different formulations of cefadroxil oral suspensions. In silico bioequivalence studies comparing different formulation of cefadroxil oral suspensions using various sampling schedules were performed using models. An in vivo study was conducted to confirm in silico results. The results of in silico and in vivo bioequivalence studies demonstrated that schedules with fewer sampling times are as efficient as schedules with larger numbers of sampling times in the assessment of bioequivalence, but only if T max is included as a sampling time. It was also concluded that in silico studies are useful tools in the planning of bioequivalence, bioavailability and other pharmacokinetic in vivo assays. © Georg Thieme Verlag KG Stuttgart · New York.

  8. Monte Carlo-based tail exponent estimator

    Science.gov (United States)

    Barunik, Jozef; Vacha, Lukas

    2010-11-01

    In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.

  9. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-01

    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.

  10. Multilevel sequential Monte-Carlo samplers

    KAUST Repository

    Jasra, Ajay

    2016-01-05

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

  11. Calculation of the secondary gamma radiation by the Monte Carlo method at displaced sampling from distributed sources

    International Nuclear Information System (INIS)

    Petrov, Eh.E.; Fadeev, I.A.

    1979-01-01

    A possibility to use displaced sampling from a bulk gamma source in calculating the secondary gamma fields by the Monte Carlo method is discussed. The algorithm proposed is based on the concept of conjugate functions alongside the dispersion minimization technique. For the sake of simplicity a plane source is considered. The algorithm has been put into practice on the M-220 computer. The differential gamma current and flux spectra in 21cm-thick lead have been calculated. The source of secondary gamma-quanta was assumed to be a distributed, constant and isotropic one emitting 4 MeV gamma quanta with the rate of 10 9 quanta/cm 3 xs. The calculations have demonstrated that the last 7 cm of lead are responsible for the whole gamma spectral pattern. The spectra practically coincide with the ones calculated by the ROZ computer code. Thus the algorithm proposed can be offectively used in the calculations of secondary gamma radiation transport and reduces the computation time by 2-4 times

  12. Monte Carlo Methods Development and Applications in Conformational Sampling of Proteins

    DEFF Research Database (Denmark)

    Tian, Pengfei

    quantitative insights into their thermodynamic and mechanistic properties that are difficult to probe in laboratory experiments. However, despite the rapid progress in the development of molecular simulation, there are still two limiting factors, (1), the current molecular mechanics force fields alone...... sampling methods to address these two problems. First of all, a novel technique has been developed for reliably estimating diffusion coefficients for use in the enhanced sampling of molecular simulations. A broad applicability of this method is illustrated by studying various simulation problems...

  13. Efficient Sequential Monte Carlo Sampling for Continuous Monitoring of a Radiation Situation

    Czech Academy of Sciences Publication Activity Database

    Šmídl, Václav; Hofman, Radek

    2014-01-01

    Roč. 56, č. 4 (2014), s. 514-527 ISSN 0040-1706 R&D Projects: GA MV VG20102013018 Institutional support: RVO:67985556 Keywords : radiation protection * atmospheric dispersion model * importance sampling Subject RIV: BD - Theory of Information Impact factor: 1.814, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/smidl-0433631.pdf

  14. Monte Carlo Particle Lists: MCPL

    DEFF Research Database (Denmark)

    Kittelmann, Thomas; Klinkby, Esben Bryndt; Bergbäck Knudsen, Erik

    2017-01-01

    A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular...... simulation packages. Program summary: Program Title: MCPL. Program Files doi: http://dx.doi.org/10.17632/cby92vsv5g.1 Licensing provisions: CC0 for core MCPL, see LICENSE file for details. Programming language: C and C++ External routines/libraries: Geant4, MCNP, McStas, McXtrace Nature of problem: Saving...

  15. Monte Carlo techniques in radiation therapy

    CERN Document Server

    Verhaegen, Frank

    2013-01-01

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

  16. Efficient Monte Carlo Estimation of the Expected Value of Sample Information Using Moment Matching.

    Science.gov (United States)

    Heath, Anna; Manolopoulou, Ioanna; Baio, Gianluca

    2018-02-01

    The Expected Value of Sample Information (EVSI) is used to calculate the economic value of a new research strategy. Although this value would be important to both researchers and funders, there are very few practical applications of the EVSI. This is due to computational difficulties associated with calculating the EVSI in practical health economic models using nested simulations. We present an approximation method for the EVSI that is framed in a Bayesian setting and is based on estimating the distribution of the posterior mean of the incremental net benefit across all possible future samples, known as the distribution of the preposterior mean. Specifically, this distribution is estimated using moment matching coupled with simulations that are available for probabilistic sensitivity analysis, which is typically mandatory in health economic evaluations. This novel approximation method is applied to a health economic model that has previously been used to assess the performance of other EVSI estimators and accurately estimates the EVSI. The computational time for this method is competitive with other methods. We have developed a new calculation method for the EVSI which is computationally efficient and accurate. This novel method relies on some additional simulation so can be expensive in models with a large computational cost.

  17. Monte Carlo method for neutron transport problems

    International Nuclear Information System (INIS)

    Asaoka, Takumi

    1977-01-01

    Some methods for decreasing variances in Monte Carlo neutron transport calculations are presented together with the results of sample calculations. A general purpose neutron transport Monte Carlo code ''MORSE'' was used for the purpose. The first method discussed in this report is the method of statistical estimation. As an example of this method, the application of the coarse-mesh rebalance acceleration method to the criticality calculation of a cylindrical fast reactor is presented. Effective multiplication factor and its standard deviation are presented as a function of the number of histories and comparisons are made between the coarse-mesh rebalance method and the standard method. Five-group neutron fluxes at core center are also compared with the result of S4 calculation. The second method is the method of correlated sampling. This method was applied to the perturbation calculation of control rod worths in a fast critical assembly (FCA-V-3) Two methods of sampling (similar flight paths and identical flight paths) are tested and compared with experimental results. For every cases the experimental value lies within the standard deviation of the Monte Carlo calculations. The third method is the importance sampling. In this report a biased selection of particle flight directions discussed. This method was applied to the flux calculation in a spherical fast neutron system surrounded by a 10.16 cm iron reflector. Result-direction biasing, path-length stretching, and no biasing are compared with S8 calculation. (Aoki, K.)

  18. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov chain Monte Carlo sampling

    DEFF Research Database (Denmark)

    Blasone, Roberta-Serena; Vrugt, Jasper A.; Madsen, Henrik

    2008-01-01

    propose an alternative strategy to determine the value of the cutoff threshold based on the appropriate coverage of the resulting uncertainty bounds. We demonstrate the superiority of this revised GLUE method with three different conceptual watershed models of increasing complexity, using both synthetic......In the last few decades hydrologists have made tremendous progress in using dynamic simulation models for the analysis and understanding of hydrologic systems. However, predictions with these models are often deterministic and as such they focus on the most probable forecast, without an explicit...... of applications. However, the MC based sampling strategy of the prior parameter space typically utilized in GLUE is not particularly efficient in finding behavioral simulations. This becomes especially problematic for high-dimensional parameter estimation problems, and in the case of complex simulation models...

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

    International Nuclear Information System (INIS)

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

    1995-01-01

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

  20. Mean field simulation for Monte Carlo integration

    CERN Document Server

    Del Moral, Pierre

    2013-01-01

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

  1. Sequential Monte Carlo with Highly Informative Observations

    OpenAIRE

    Del Moral, Pierre; Murray, Lawrence M.

    2014-01-01

    We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...

  2. Monte Carlo surface flux tallies

    International Nuclear Information System (INIS)

    Favorite, Jeffrey A.

    2010-01-01

    Particle fluxes on surfaces are difficult to calculate with Monte Carlo codes because the score requires a division by the surface-crossing angle cosine, and grazing angles lead to inaccuracies. We revisit the standard practice of dividing by half of a cosine 'cutoff' for particles whose surface-crossing cosines are below the cutoff. The theory behind this approximation is sound, but the application of the theory to all possible situations does not account for two implicit assumptions: (1) the grazing band must be symmetric about 0, and (2) a single linear expansion for the angular flux must be applied in the entire grazing band. These assumptions are violated in common circumstances; for example, for separate in-going and out-going flux tallies on internal surfaces, and for out-going flux tallies on external surfaces. In some situations, dividing by two-thirds of the cosine cutoff is more appropriate. If users were able to control both the cosine cutoff and the substitute value, they could use these parameters to make accurate surface flux tallies. The procedure is demonstrated in a test problem in which Monte Carlo surface fluxes in cosine bins are converted to angular fluxes and compared with the results of a discrete ordinates calculation.

  3. Statistics of Monte Carlo methods used in radiation transport calculation

    International Nuclear Information System (INIS)

    Datta, D.

    2009-01-01

    Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

  4. Reconstruction of Monte Carlo replicas from Hessian parton distributions

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)

    2017-03-20

    We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

  5. Monte Carlo Solutions for Blind Phase Noise Estimation

    Directory of Open Access Journals (Sweden)

    Çırpan Hakan

    2009-01-01

    Full Text Available This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN channels. The main contributions of the paper are (i the development of a Monte Carlo framework for phase noise estimation, with special attention to sequential importance sampling and Rao-Blackwellization, (ii the interpretation of existing Monte Carlo solutions within this generic framework, and (iii the derivation of a novel phase noise estimator. Contrary to the ad hoc phase noise estimators that have been proposed in the past, the estimators considered in this paper are derived from solid probabilistic and performance-determining arguments. Computer simulations demonstrate that, on one hand, the Monte Carlo phase noise estimators outperform the existing estimators and, on the other hand, our newly proposed solution exhibits a lower complexity than the existing Monte Carlo solutions.

  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.)

  7. Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling

    Science.gov (United States)

    Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad; Janssen, Hans

    2015-02-01

    The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of midpoints in the hypercube intervals (midpoint LHS). Both approaches have been extensively used, but no attempt has been previously made to compare the efficiency and robustness of their resulting sample designs. In this study we compare the two approaches and show that the space-filling characteristics of OLHS designs are sensitive to the initial design that is fed into the optimization algorithm. It is also illustrated that the space-filling characteristics of OLHS designs based on midpoint LHS are significantly better those based on random LHS. The two approaches are compared by incorporating their resulting sample designs in Monte Carlo simulation (MCS) for uncertainty propagation analysis, and then, by employing the sample designs in the selection of the training set for constructing non-intrusive polynomial chaos expansion (NIPCE) meta-models which subsequently replace the original full model in MCSs. The analysis is based on two case studies involving numerical simulation of density dependent flow and solute transport in porous media within the context of seawater intrusion in coastal aquifers. We show that the use of midpoint LHS as the initial design increases the efficiency and robustness of the resulting MCSs and NIPCE meta-models. The study also illustrates that this

  8. 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

  9. 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.

  10. 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...... and validation of a Monte Carlo model of a medical linear accelerator (i), converting a CT scan of a patient to a Monte Carlo compliant phantom (ii) and translating the treatment plan parameters (including beam energy, angles of incidence, collimator settings etc) to a Monte Carlo input file (iii). A protocol...

  11. 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

  12. Importance iteration in MORSE Monte Carlo calculations

    International Nuclear Information System (INIS)

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

    1994-01-01

    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 that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation

  13. 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

  14. 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.

  15. 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.)

  16. Monte carlo simulation for soot dynamics

    KAUST Repository

    Zhou, Kun

    2012-01-01

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

  17. Monte Carlo Codes Invited Session

    International Nuclear Information System (INIS)

    Trama, J.C.; Malvagi, F.; Brown, F.

    2013-01-01

    This document lists 22 Monte Carlo codes used in radiation transport applications throughout the world. For each code the names of the organization and country and/or place are given. We have the following computer codes. 1) ARCHER, USA, RPI; 2) COG11, USA, LLNL; 3) DIANE, France, CEA/DAM Bruyeres; 4) FLUKA, Italy and CERN, INFN and CERN; 5) GEANT4, International GEANT4 collaboration; 6) KENO and MONACO (SCALE), USA, ORNL; 7) MC21, USA, KAPL and Bettis; 8) MCATK, USA, LANL; 9) MCCARD, South Korea, Seoul National University; 10) MCNP6, USA, LANL; 11) MCU, Russia, Kurchatov Institute; 12) MONK and MCBEND, United Kingdom, AMEC; 13) MORET5, France, IRSN Fontenay-aux-Roses; 14) MVP2, Japan, JAEA; 15) OPENMC, USA, MIT; 16) PENELOPE, Spain, Barcelona University; 17) PHITS, Japan, JAEA; 18) PRIZMA, Russia, VNIITF; 19) RMC, China, Tsinghua University; 20) SERPENT, Finland, VTT; 21) SUPERMONTECARLO, China, CAS INEST FDS Team Hefei; and 22) TRIPOLI-4, France, CEA Saclay

  18. 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

  19. Adaptive Markov Chain Monte Carlo

    KAUST Repository

    Jadoon, Khan

    2016-08-08

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

  20. 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...

  1. Monte Carlo method in radiation transport problems

    International Nuclear Information System (INIS)

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

    1986-11-01

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

  2. Evaluation of the self-absorption of 14C beta-rays in gel-suspension samples by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Wakabayashi, G.; Nagao, K.; Okai, T.; Matoba, M.

    2003-01-01

    In order to investigate the self-absorption of the β-rays from 14 C in a gel-suspension sample, the Monte Carlo code, simulating the sequence of stages occurring in the sample, has been developed. The trajectory of the electron was calculated by the continuous slowing down approximation and the multiple Coulomb scattering theory. The effects of the self-absorption, strong quenching and particle size distribution of calcium carbonate on the output counting efficiency and the shape of the energy spectrum were evaluated. (author)

  3. Application of the Monte Carlo method for the efficiency calibration of CsI and NaI detectors for gamma-ray measurements from terrestrial samples

    International Nuclear Information System (INIS)

    Baccouche, S.; Al-Azmi, D.; Karunakara, N.; Trabelsi, A.

    2012-01-01

    Gamma-ray measurements in terrestrial/environmental samples require the use of high efficient detectors because of the low level of the radionuclide activity concentrations in the samples; thus scintillators are suitable for this purpose. Two scintillation detectors were studied in this work; CsI(Tl) and NaI(Tl) with identical size for measurement of terrestrial samples for performance study. This work describes a Monte Carlo method for making the full-energy efficiency calibration curves for both detectors using gamma-ray energies associated with the decay of naturally occurring radionuclides 137 Cs (661 keV), 40 K (1460 keV), 238 U ( 214 Bi, 1764 keV) and 232 Th ( 208 Tl, 2614 keV), which are found in terrestrial samples. The magnitude of the coincidence summing effect occurring for the 2614 keV emission of 208 Tl is assessed by simulation. The method provides an efficient tool to make the full-energy efficiency calibration curve for scintillation detectors for any samples geometry and volume in order to determine accurate activity concentrations in terrestrial samples. - Highlights: ► CsI (Tl) and NaI (Tl) detectors were studied for the measurement of terrestrial samples. ► Monte Carlo method was used for efficiency calibration using natural gamma emitting terrestrial radionuclides. ► The coincidence summing effect occurring for the 2614 keV emission of 208 Tl is assessed by simulation.

  4. 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.

  5. 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.

  6. 11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

    CERN Document Server

    Nuyens, Dirk

    2016-01-01

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

  7. 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)

  8. Frontiers of quantum Monte Carlo workshop: preface

    International Nuclear Information System (INIS)

    Gubernatis, J.E.

    1985-01-01

    The introductory remarks, table of contents, and list of attendees are presented from the proceedings of the conference, Frontiers of Quantum Monte Carlo, which appeared in the Journal of Statistical Physics

  9. 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.)

  10. Experience with the Monte Carlo Method

    Energy Technology Data Exchange (ETDEWEB)

    Hussein, E M.A. [Department of Mechanical Engineering University of New Brunswick, Fredericton, N.B., (Canada)

    2007-06-15

    Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed.

  11. Experience with the Monte Carlo Method

    International Nuclear Information System (INIS)

    Hussein, E.M.A.

    2007-01-01

    Monte Carlo simulation of radiation transport provides a powerful research and design tool that resembles in many aspects laboratory experiments. Moreover, Monte Carlo simulations can provide an insight not attainable in the laboratory. However, the Monte Carlo method has its limitations, which if not taken into account can result in misleading conclusions. This paper will present the experience of this author, over almost three decades, in the use of the Monte Carlo method for a variety of applications. Examples will be shown on how the method was used to explore new ideas, as a parametric study and design optimization tool, and to analyze experimental data. The consequences of not accounting in detail for detector response and the scattering of radiation by surrounding structures are two of the examples that will be presented to demonstrate the pitfall of condensed

  12. Monte Carlo Transport for Electron Thermal Transport

    Science.gov (United States)

    Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

    2015-11-01

    The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

  13. A continuation multilevel Monte Carlo algorithm

    KAUST Repository

    Collier, Nathan; Haji Ali, Abdul Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raul

    2014-01-01

    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

  14. Simulation and the Monte Carlo method

    CERN Document Server

    Rubinstein, Reuven Y

    2016-01-01

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

  15. Hybrid Monte Carlo methods in computational finance

    NARCIS (Netherlands)

    Leitao Rodriguez, A.

    2017-01-01

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

  16. Monte Carlo method applied to medical physics

    International Nuclear Information System (INIS)

    Oliveira, C.; Goncalves, I.F.; Chaves, A.; Lopes, M.C.; Teixeira, N.; Matos, B.; Goncalves, I.C.; Ramalho, A.; Salgado, J.

    2000-01-01

    The main application of the Monte Carlo method to medical physics is dose calculation. This paper shows some results of two dose calculation studies and two other different applications: optimisation of neutron field for Boron Neutron Capture Therapy and optimization of a filter for a beam tube for several purposes. The time necessary for Monte Carlo calculations - the highest boundary for its intensive utilisation - is being over-passed with faster and cheaper computers. (author)

  17. 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

  18. Monte Carlo methods to calculate impact probabilities

    Science.gov (United States)

    Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.

    2014-09-01

    Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward

  19. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

    KAUST Repository

    Ben Issaid, Chaouki; Long, Quan; Scavino, Marco; Tempone, Raul

    2015-01-01

    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.

  20. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

    KAUST Repository

    Ben Issaid, Chaouki

    2015-01-07

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

  1. Prediction of the number of 14 MeV neutron elastically scattered from large sample of aluminium using Monte Carlo simulation method

    International Nuclear Information System (INIS)

    Husin Wagiran; Wan Mohd Nasir Wan Kadir

    1997-01-01

    In neutron scattering processes, the effect of multiple scattering is to cause an effective increase in the measured cross-sections due to increase on the probability of neutron scattering interactions in the sample. Analysis of how the effective cross-section varies with thickness is very complicated due to complicated sample geometries and the variations of scattering cross-section with energy. Monte Carlo method is one of the possible method for treating the multiple scattering processes in the extended sample. In this method a lot of approximations have to be made and the accurate data of microscopic cross-sections are needed at various angles. In the present work, a Monte Carlo simulation programme suitable for a small computer was developed. The programme was capable to predict the number of neutrons scattered from various thickness of aluminium samples at all possible angles between 00 to 36011 with 100 increments. In order to make the the programme not too complicated and capable of being run on microcomputer with reasonable time, the calculations was done in two dimension coordinate system. The number of neutrons predicted from this model show in good agreement with previous experimental results

  2. DS86 neutron dose. Monte Carlo analysis for depth profile of {sup 152}Eu activity in a large stone sample

    Energy Technology Data Exchange (ETDEWEB)

    Endo, Satoru; Hoshi, Masaharu; Takada, Jun [Hiroshima Univ. (Japan). Research Inst. for Radiation Biology and Medicine; Iwatani, Kazuo; Oka, Takamitsu; Shizuma, Kiyoshi; Imanaka, Tetsuji; Fujita, Shoichiro; Hasai, Hiromi

    1999-06-01

    The depth profile of {sup 152}Eu activity induced in a large granite stone pillar by Hiroshima atomic bomb neutrons was calculated by a Monte Carlo N-Particle Transport Code (MCNP). The pillar was on the Motoyasu Bridge, located at a distance of 132 m (WSW) from the hypocenter. It was a square column with a horizontal sectional size of 82.5 cm x 82.5 cm and height of 179 cm. Twenty-one cells from the north to south surface at the central height of the column were specified for the calculation and {sup 152}Eu activities for each cell were calculated. The incident neutron spectrum was assumed to be the angular fluence data of the Dosimetry System 1986 (DS86). The angular dependence of the spectrum was taken into account by dividing the whole solid angle into twenty-six directions. The calculated depth profile of specific activity did not agree with the measured profile. A discrepancy was found in the absolute values at each depth with a mean multiplication factor of 0.58 and also in the shape of the relative profile. The results indicated that a reassessment of the neutron energy spectrum in DS86 is required for correct dose estimation. (author)

  3. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef

    2016-01-06

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

  4. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul

    2016-01-01

    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).

  5. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef; Nobile, Fabio; Tempone, Raul

    2015-01-01

    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.

  6. Multi-Index Monte Carlo (MIMC)

    KAUST Repository

    Haji Ali, Abdul Lateef

    2015-01-07

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

  7. 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

  8. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM

    2016-01-01

    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

  9. 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

  10. 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.)

  11. Application of the Monte Carlo method for the efficiency calibration of CsI and NaI detectors for gamma-ray measurements from terrestrial samples

    Energy Technology Data Exchange (ETDEWEB)

    Baccouche, S., E-mail: souad.baccouche@cnstn.rnrt.tn [UR-MDTN, National Center for Nuclear Sciences and Technology, Technopole Sidi Thabet, 2020 Sidi Thabet (Tunisia); Al-Azmi, D., E-mail: ds.alazmi@paaet.edu.kw [Department of Applied Sciences, College of Technological Studies, Public Authority for Applied Education and Training, Shuwaikh, P.O. Box 42325, Code 70654 (Kuwait); Karunakara, N., E-mail: karunakara_n@yahoo.com [University Science Instrumentation Centre, Mangalore University, Mangalagangotri 574199 (India); Trabelsi, A., E-mail: adel.trabelsi@fst.rnu.tn [UR-MDTN, National Center for Nuclear Sciences and Technology, Technopole Sidi Thabet, 2020 Sidi Thabet (Tunisia); UR-UPNHE, Faculty of Sciences of Tunis, El-Manar University, 2092 Tunis (Tunisia)

    2012-01-15

    Gamma-ray measurements in terrestrial/environmental samples require the use of high efficient detectors because of the low level of the radionuclide activity concentrations in the samples; thus scintillators are suitable for this purpose. Two scintillation detectors were studied in this work; CsI(Tl) and NaI(Tl) with identical size for measurement of terrestrial samples for performance study. This work describes a Monte Carlo method for making the full-energy efficiency calibration curves for both detectors using gamma-ray energies associated with the decay of naturally occurring radionuclides {sup 137}Cs (661 keV), {sup 40}K (1460 keV), {sup 238}U ({sup 214}Bi, 1764 keV) and {sup 232}Th ({sup 208}Tl, 2614 keV), which are found in terrestrial samples. The magnitude of the coincidence summing effect occurring for the 2614 keV emission of {sup 208}Tl is assessed by simulation. The method provides an efficient tool to make the full-energy efficiency calibration curve for scintillation detectors for any samples geometry and volume in order to determine accurate activity concentrations in terrestrial samples. - Highlights: Black-Right-Pointing-Pointer CsI (Tl) and NaI (Tl) detectors were studied for the measurement of terrestrial samples. Black-Right-Pointing-Pointer Monte Carlo method was used for efficiency calibration using natural gamma emitting terrestrial radionuclides. Black-Right-Pointing-Pointer The coincidence summing effect occurring for the 2614 keV emission of {sup 208}Tl is assessed by simulation.

  12. Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

    International Nuclear Information System (INIS)

    Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

    2017-01-01

    In this paper we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

  13. Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

    Science.gov (United States)

    Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

    2017-12-01

    In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated - reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

  14. Monte Carlo strategies in scientific computing

    CERN Document Server

    Liu, Jun S

    2008-01-01

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

  15. Off-diagonal expansion quantum Monte Carlo.

    Science.gov (United States)

    Albash, Tameem; Wagenbreth, Gene; Hen, Itay

    2017-12-01

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

  16. 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.)

  17. Monte Carlo work at Argonne National Laboratory

    International Nuclear Information System (INIS)

    Gelbard, E.M.; Prael, R.E.

    1974-01-01

    A simple model of the Monte Carlo process is described and a (nonlinear) recursion relation between fission sources in successive generations is developed. From the linearized form of these recursion relations, it is possible to derive expressions for the mean square coefficients of error modes in the iterates and for correlation coefficients between fluctuations in successive generations. First-order nonlinear terms in the recursion relation are analyzed. From these nonlinear terms an expression for the bias in the eigenvalue estimator is derived, and prescriptions for measuring the bias are formulated. Plans for the development of the VIM code are reviewed, and the proposed treatment of small sample perturbations in VIM is described. 6 references. (U.S.)

  18. Methods for Monte Carlo simulations of biomacromolecules.

    Science.gov (United States)

    Vitalis, Andreas; Pappu, Rohit V

    2009-01-01

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

  19. Monte Carlo simulation applied to alpha spectrometry

    International Nuclear Information System (INIS)

    Baccouche, S.; Gharbi, F.; Trabelsi, A.

    2007-01-01

    Alpha particle spectrometry is a widely-used analytical method, in particular when we deal with pure alpha emitting radionuclides. Monte Carlo simulation is an adequate tool to investigate the influence of various phenomena on this analytical method. We performed an investigation of those phenomena using the simulation code GEANT of CERN. The results concerning the geometrical detection efficiency in different measurement geometries agree with analytical calculations. This work confirms that Monte Carlo simulation of solid angle of detection is a very useful tool to determine with very good accuracy the detection efficiency.

  20. Simplified monte carlo simulation for Beijing spectrometer

    International Nuclear Information System (INIS)

    Wang Taijie; Wang Shuqin; Yan Wuguang; Huang Yinzhi; Huang Deqiang; Lang Pengfei

    1986-01-01

    The Monte Carlo method based on the functionization of the performance of detectors and the transformation of values of kinematical variables into ''measured'' ones by means of smearing has been used to program the Monte Carlo simulation of the performance of the Beijing Spectrometer (BES) in FORTRAN language named BESMC. It can be used to investigate the multiplicity, the particle type, and the distribution of four-momentum of the final states of electron-positron collision, and also the response of the BES to these final states. Thus, it provides a measure to examine whether the overall design of the BES is reasonable and to decide the physical topics of the BES

  1. Burnup calculations using Monte Carlo method

    International Nuclear Information System (INIS)

    Ghosh, Biplab; Degweker, S.B.

    2009-01-01

    In the recent years, interest in burnup calculations using Monte Carlo methods has gained momentum. Previous burn up codes have used multigroup transport theory based calculations followed by diffusion theory based core calculations for the neutronic portion of codes. The transport theory methods invariably make approximations with regard to treatment of the energy and angle variables involved in scattering, besides approximations related to geometry simplification. Cell homogenisation to produce diffusion, theory parameters adds to these approximations. Moreover, while diffusion theory works for most reactors, it does not produce accurate results in systems that have strong gradients, strong absorbers or large voids. Also, diffusion theory codes are geometry limited (rectangular, hexagonal, cylindrical, and spherical coordinates). Monte Carlo methods are ideal to solve very heterogeneous reactors and/or lattices/assemblies in which considerable burnable poisons are used. The key feature of this approach is that Monte Carlo methods permit essentially 'exact' modeling of all geometrical detail, without resort to ene and spatial homogenization of neutron cross sections. Monte Carlo method would also be better for in Accelerator Driven Systems (ADS) which could have strong gradients due to the external source and a sub-critical assembly. To meet the demand for an accurate burnup code, we have developed a Monte Carlo burnup calculation code system in which Monte Carlo neutron transport code is coupled with a versatile code (McBurn) for calculating the buildup and decay of nuclides in nuclear materials. McBurn is developed from scratch by the authors. In this article we will discuss our effort in developing the continuous energy Monte Carlo burn-up code, McBurn. McBurn is intended for entire reactor core as well as for unit cells and assemblies. Generally, McBurn can do burnup of any geometrical system which can be handled by the underlying Monte Carlo transport code

  2. Improvements for Monte Carlo burnup calculation

    Energy Technology Data Exchange (ETDEWEB)

    Shenglong, Q.; Dong, Y.; Danrong, S.; Wei, L., E-mail: qiangshenglong@tsinghua.org.cn, E-mail: d.yao@npic.ac.cn, E-mail: songdr@npic.ac.cn, E-mail: luwei@npic.ac.cn [Nuclear Power Inst. of China, Cheng Du, Si Chuan (China)

    2015-07-01

    Monte Carlo burnup calculation is development trend of reactor physics, there would be a lot of work to be done for engineering applications. Based on Monte Carlo burnup code MOI, non-fuel burnup calculation methods and critical search suggestions will be mentioned in this paper. For non-fuel burnup, mixed burnup mode will improve the accuracy of burnup calculation and efficiency. For critical search of control rod position, a new method called ABN based on ABA which used by MC21 will be proposed for the first time in this paper. (author)

  3. 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)

  4. 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

  5. Monte Carlo simulation of neutron scattering instruments

    International Nuclear Information System (INIS)

    Seeger, P.A.

    1995-01-01

    A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width

  6. 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

  7. 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.)

  8. Fast sequential Monte Carlo methods for counting and optimization

    CERN Document Server

    Rubinstein, Reuven Y; Vaisman, Radislav

    2013-01-01

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

  9. LCG MCDB - a Knowledgebase of Monte Carlo Simulated Events

    CERN Document Server

    Belov, S; Galkin, E; Gusev, A; Pokorski, Witold; Sherstnev, A V

    2008-01-01

    In this paper we report on LCG Monte Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC collaborations by experts. In many cases, the modern Monte Carlo simulation of physical processes requires expert knowledge in Monte Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project.

  10. Exploring cluster Monte Carlo updates with Boltzmann machines

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

  11. Exploring cluster Monte Carlo updates with Boltzmann machines.

    Science.gov (United States)

    Wang, Lei

    2017-11-01

    Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

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

    International Nuclear Information System (INIS)

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

    2002-01-01

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

  13. 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

  14. 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...

  15. The Monte Carlo applied for calculation dose

    International Nuclear Information System (INIS)

    Peixoto, J.E.

    1988-01-01

    The Monte Carlo method is showed for the calculation of absorbed dose. The trajectory of the photon is traced simulating sucessive interaction between the photon and the substance that consist the human body simulator. The energy deposition in each interaction of the simulator organ or tissue per photon is also calculated. (C.G.C.) [pt

  16. Monte Carlo code for neutron radiography

    International Nuclear Information System (INIS)

    Milczarek, Jacek J.; Trzcinski, Andrzej; El-Ghany El Abd, Abd; Czachor, Andrzej

    2005-01-01

    The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms

  17. Monte Carlo code for neutron radiography

    Energy Technology Data Exchange (ETDEWEB)

    Milczarek, Jacek J. [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)]. E-mail: jjmilcz@cyf.gov.pl; Trzcinski, Andrzej [Institute for Nuclear Studies, Swierk, 05-400 Otwock (Poland); El-Ghany El Abd, Abd [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland); Nuclear Research Center, PC 13759, Cairo (Egypt); Czachor, Andrzej [Institute of Atomic Energy, Swierk, 05-400 Otwock (Poland)

    2005-04-21

    The concise Monte Carlo code, MSX, for simulation of neutron radiography images of non-uniform objects is presented. The possibility of modeling the images of objects with continuous spatial distribution of specific isotopes is included. The code can be used for assessment of the scattered neutron component in neutron radiograms.

  18. 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

  19. 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....

  20. 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

  1. 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.

  2. Monte Carlo methods beyond detailed balance

    NARCIS (Netherlands)

    Schram, Raoul D.; Barkema, Gerard T.|info:eu-repo/dai/nl/101275080

    2015-01-01

    Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying

  3. Monte Carlo studies of ZEPLIN III

    CERN Document Server

    Dawson, J; Davidge, D C R; Gillespie, J R; Howard, A S; Jones, W G; Joshi, M; Lebedenko, V N; Sumner, T J; Quenby, J J

    2002-01-01

    A Monte Carlo simulation of a two-phase xenon dark matter detector, ZEPLIN III, has been achieved. Results from the analysis of a simulated data set are presented, showing primary and secondary signal distributions from low energy gamma ray events.

  4. 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.

  5. 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.

  6. Dynamic bounds coupled with Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)

    2011-02-15

    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 describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.

  7. Dynamic bounds coupled with Monte Carlo simulations

    NARCIS (Netherlands)

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

    2011-01-01

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

  8. Design and analysis of Monte Carlo experiments

    NARCIS (Netherlands)

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

    2012-01-01

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

  9. Some problems on Monte Carlo method development

    International Nuclear Information System (INIS)

    Pei Lucheng

    1992-01-01

    This is a short paper on some problems of Monte Carlo method development. The content consists of deep-penetration problems, unbounded estimate problems, limitation of Mdtropolis' method, dependency problem in Metropolis' method, random error interference problems and random equations, intellectualisation and vectorization problems of general software

  10. Monte Carlo simulations in theoretical physic

    International Nuclear Information System (INIS)

    Billoire, A.

    1991-01-01

    After a presentation of the MONTE CARLO method principle, the method is applied, first to the critical exponents calculations in the three dimensions ISING model, and secondly to the discrete quantum chromodynamic with calculation times in function of computer power. 28 refs., 4 tabs

  11. 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

  12. Variance Reduction Techniques in Monte Carlo Methods

    NARCIS (Netherlands)

    Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

    2010-01-01

    Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

  13. 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.

  14. Biases in Monte Carlo eigenvalue calculations

    International Nuclear Information System (INIS)

    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

  15. Acceleration of monte Carlo solution by conjugate gradient method

    International Nuclear Information System (INIS)

    Toshihisa, Yamamoto

    2005-01-01

    The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)

  16. Fitting by a pearson II function of the spatial deposited energy distribution in superconducting YBaCuO samples calculated by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Cruz Inclan, Carlos M.; Leyva Fabelo, Antonio; Alfonso Vazquez, Onexis

    2001-01-01

    The spatial deposited energy distribution inside YBa 2 Cu 3 O 7 superconducting ceramics irradiated with gamma rays were simulated using the codes system EGS4, based on the Monte Carlo method. The obtained distributions evidence a notable inhomogeneity, which may be one of the possible sources of inconsistent results of irradiation studies. The profiles of these distributions show asymmetrical behaviors, which may be fitted satisfactorily through a Pearson II Gamma type function. These fittings are presented in the paper and the behavior of the fitting parameters with the energy of incident photons, its number, and the experimental geometry were studied. The physical signification of each fitting parameters is discussed in the text. The exponent is related to certain mass absorption coefficient when the thick of the sample is sufficiently large

  17. Sampling procedures using optical-data and partial wave cross sections in a Monte Carlo code for simulating kilovolt electron and positron transport in solids

    International Nuclear Information System (INIS)

    Fernandez-Varea, J.M.; Salvat, F.; Liljequist, D.

    1994-09-01

    The details of a Monte Carlo code for computing the penetration and energy loss of electrons and positrons in solids are described. The code, intended for electrons and positrons with energies from ∼ 100 eV to ∼ 100 keV, is based on the simulation of individual elastic and inelastic collisions. Elastic collisions are simulated using differential cross sections computed by the relativistic partial wave method applied to a muffin-tin Dirac-Hartree-Fock-Slater potential. Inelastic collisions are simulated by means of a model based on optical and photoelectric data, which are extended to the non-zero momentum transfer region by means of somewhat different algorithms for valence electron excitations and inner-shell excitations. This report focuses on the description of detailed formulae and sampling methods. 10 refs, 3 figs, 8 tabs

  18. Effect of sample moisture and bulk density on performance of the 241Am-Be source based prompt gamma rays neutron activation analysis setup. A Monte Carlo study

    International Nuclear Information System (INIS)

    Almisned, Ghada

    2010-01-01

    Monte Carlo simulations were carried out using the dependence of gamma ray yield on the bulk density and moisture content for five different lengths of Portland cement samples in a thermal neutron capture based Prompt Gamma ray Neutron Activation Analysis (PGNAA) setup for source inside moderator geometry using an 241 Am-Be neutron source. In this study, yields of 1.94 and 6.42 MeV prompt gamma rays from calcium in the five Portland cement samples were calculated as a function of sample bulk density and moisture content. The study showed a strong dependence of the 1.94 and 6.42 MeV gamma ray yield upon the sample bulk density but a weaker dependence upon sample moisture content. For an order of magnitude increase in the sample bulk density, an order of magnitude increase in the gamma rays yield was observed, i.e., a one-to-one correspondence. In case of gamma ray yield dependence upon sample moisture content, an order of magnitude increase in the moisture content of the sample resulted in about 16-17% increase in the yield of 1.94 and 6.42 MeV gamma rays from calcium. (author)

  19. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul

    2014-01-01

    . Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost

  20. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung; Liang, Faming

    2009-01-01

    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

  1. Monte Carlo tests of the ELIPGRID-PC algorithm

    International Nuclear Information System (INIS)

    Davidson, J.R.

    1995-04-01

    The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM reg-sign PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within ±0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangular sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error

  2. Monte Carlo simulation in statistical physics an introduction

    CERN Document Server

    Binder, Kurt

    1992-01-01

    The Monte Carlo method is a computer simulation method which uses random numbers to simulate statistical fluctuations The method is used to model complex systems with many degrees of freedom Probability distributions for these systems are generated numerically and the method then yields numerically exact information on the models Such simulations may be used tosee how well a model system approximates a real one or to see how valid the assumptions are in an analyical theory A short and systematic theoretical introduction to the method forms the first part of this book The second part is a practical guide with plenty of examples and exercises for the student Problems treated by simple sampling (random and self-avoiding walks, percolation clusters, etc) are included, along with such topics as finite-size effects and guidelines for the analysis of Monte Carlo simulations The two parts together provide an excellent introduction to the theory and practice of Monte Carlo simulations

  3. Monte Carlo Simulation in Statistical Physics An Introduction

    CERN Document Server

    Binder, Kurt

    2010-01-01

    Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well ...

  4. Scouting the feasibility of Monte Carlo reactor dynamics simulations

    International Nuclear Information System (INIS)

    Legrady, David; Hoogenboom, J. Eduard

    2008-01-01

    In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

  5. Scouting the feasibility of Monte Carlo reactor dynamics simulations

    Energy Technology Data Exchange (ETDEWEB)

    Legrady, David [Forschungszentrum Dresden-Rossendorf, Dresden (Germany); Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)

    2008-07-01

    In this paper we present an overview of the methodological questions related to Monte Carlo simulation of time dependent power transients in nuclear reactors. Investigations using a small fictional 3D reactor with isotropic scattering and a single energy group we have performed direct Monte Carlo transient calculations with simulation of delayed neutrons and with and without thermal feedback. Using biased delayed neutron sampling and population control at time step boundaries calculation times were kept reasonably low. We have identified the initial source determination and the prompt chain simulations as key issues that require most attention. (authors)

  6. A computer code package for electron transport Monte Carlo simulation

    International Nuclear Information System (INIS)

    Popescu, Lucretiu M.

    1999-01-01

    A computer code package was developed for solving various electron transport problems by Monte Carlo simulation. It is based on condensed history Monte Carlo algorithm. In order to get reliable results over wide ranges of electron energies and target atomic numbers, specific techniques of electron transport were implemented such as: Moliere multiscatter angular distributions, Blunck-Leisegang multiscatter energy distribution, sampling of electron-electron and Bremsstrahlung individual interactions. Path-length and lateral displacement corrections algorithms and the module for computing collision, radiative and total restricted stopping powers and ranges of electrons are also included. Comparisons of simulation results with experimental measurements are finally presented. (author)

  7. Applications of Monte Carlo method in Medical Physics

    International Nuclear Information System (INIS)

    Diez Rios, A.; Labajos, M.

    1989-01-01

    The basic ideas of Monte Carlo techniques are presented. Random numbers and their generation by congruential methods, which underlie Monte Carlo calculations are shown. Monte Carlo techniques to solve integrals are discussed. The evaluation of a simple monodimensional integral with a known answer, by means of two different Monte Carlo approaches are discussed. The basic principles to simualate on a computer photon histories reduce variance and the current applications in Medical Physics are commented. (Author)

  8. Monte Carlo calculations and neutron spectrometry in quantitative prompt gamma neutron activation analysis (PGNAA) of bulk samples using an isotopic neutron source

    International Nuclear Information System (INIS)

    Spyrou, N.M.; Awotwi-Pratt, J.B.; Williams, A.M.

    2004-01-01

    An activation analysis facility based on an isotopic neutron source (185 GBq 241 Am/Be) which can perform both prompt and cyclic activation analysis on bulk samples, has been used for more than 20 years in many applications including 'in vivo' activation analysis and the determination of the composition of bio-environmental samples, such as, landfill waste and coal. Although the comparator method is often employed, because of the variety in shape, size and elemental composition of these bulk samples, it is often difficult and time consuming to construct appropriate comparator samples for reference. One of the obvious problems is the distribution and energy of the neutron flux in these bulk and comparator samples. In recent years, it was attempted to adopt the absolute method based on a monostandard and to make calculations using a Monte Carlo code (MCNP4C2) to explore this further. In particular, a model of the irradiation facility has been made using the MCNP4C2 code in order to investigate the factors contributing to the quantitative determination of the elemental concentrations through prompt gamma neutron activation analysis (PGNAA) and most importantly, to estimate how the neutron energy spectrum and neutron dose vary with penetration depth into the sample. This simulation is compared against the scattered and transmitted neutron energy spectra that are experimentally and empirically determined using a portable neutron spectrometry system. (author)

  9. Monte Carlo computation in the applied research of nuclear technology

    International Nuclear Information System (INIS)

    Xu Shuyan; Liu Baojie; Li Qin

    2007-01-01

    This article briefly introduces Monte Carlo Methods and their properties. It narrates the Monte Carlo methods with emphasis in their applications to several domains of nuclear technology. Monte Carlo simulation methods and several commonly used computer software to implement them are also introduced. The proposed methods are demonstrated by a real example. (authors)

  10. Weighted-delta-tracking for Monte Carlo particle transport

    International Nuclear Information System (INIS)

    Morgan, L.W.G.; Kotlyar, D.

    2015-01-01

    Highlights: • This paper presents an alteration to the Monte Carlo Woodcock tracking technique. • The alteration improves computational efficiency within regions of high absorbers. • The rejection technique is replaced by a statistical weighting mechanism. • The modified Woodcock method is shown to be faster than standard Woodcock tracking. • The modified Woodcock method achieves a lower variance, given a specified accuracy. - Abstract: Monte Carlo particle transport (MCPT) codes are incredibly powerful and versatile tools to simulate particle behavior in a multitude of scenarios, such as core/criticality studies, radiation protection, shielding, medicine and fusion research to name just a small subset applications. However, MCPT codes can be very computationally expensive to run when the model geometry contains large attenuation depths and/or contains many components. This paper proposes a simple modification to the Woodcock tracking method used by some Monte Carlo particle transport codes. The Woodcock method utilizes the rejection method for sampling virtual collisions as a method to remove collision distance sampling at material boundaries. However, it suffers from poor computational efficiency when the sample acceptance rate is low. The proposed method removes rejection sampling from the Woodcock method in favor of a statistical weighting scheme, which improves the computational efficiency of a Monte Carlo particle tracking code. It is shown that the modified Woodcock method is less computationally expensive than standard ray-tracing and rejection-based Woodcock tracking methods and achieves a lower variance, given a specified accuracy

  11. 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

  12. Exploring Mass Perception with Markov Chain Monte Carlo

    Science.gov (United States)

    Cohen, Andrew L.; Ross, Michael G.

    2009-01-01

    Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…

  13. Particle-transport simulation with the Monte Carlo method

    International Nuclear Information System (INIS)

    Carter, L.L.; Cashwell, E.D.

    1975-01-01

    Attention is focused on the application of the Monte Carlo method to particle transport problems, with emphasis on neutron and photon transport. Topics covered include sampling methods, mathematical prescriptions for simulating particle transport, mechanics of simulating particle transport, neutron transport, and photon transport. A literature survey of 204 references is included. (GMT)

  14. Gamma-ray yield dependence on bulk density and moisture content of a sample of a PGNAA setup. A Monte Carlo study

    International Nuclear Information System (INIS)

    Nagadi, M.M.; Naqvi, A.A.

    2007-01-01

    Monte Carlo calculations were carried out to study the dependence of γ-ray yield on the bulk density and moisture content of a sample in a thermalneutron capture-based prompt gamma neutron activation analysis (PGNAA) setup. The results of the study showed a strong dependence of the γ-ray yield upon the sample bulk density. An order of magnitude increase in yield of 1.94 and 6.42 MeV prompt γ-rays from calcium in a Portland cement sample was observed for a corresponding order of magnitude increase in the sample bulk density. On the contrary the γ-ray yield has a weak dependence on sample moisture content and an increase of only 20% in yield of 1.94 and 6.42 MeV prompt γ-rays from calcium in the Portland cement sample was observed for an order of magnitude increase in the moisture content of the Portland cement sample. A similar effect of moisture content has been observed on the yield of 1.167 MeV prompt γ-rays from chlorine contaminants in Portland cement samples. For an order of magnitude increase in the moisture content of the sample, a 7 to 12% increase in the yield of the 1.167 MeV chlorine γ-ray was observed for the Portland cement samples containing 1 to 5 wt.% chlorine contaminants. This study has shown that effects of sample moisture content on prompt γ-ray yield from constituents of a Portland cement sample are insignificant in a thermal-neutrons capture-based PGNAA setup. (author)

  15. 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)

  16. Multilevel Monte Carlo Approaches for Numerical Homogenization

    KAUST Repository

    Efendiev, Yalchin R.

    2015-10-01

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

  17. 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

  18. Monte Carlo simulations in skin radiotherapy

    International Nuclear Information System (INIS)

    Sarvari, A.; Jeraj, R.; Kron, T.

    2000-01-01

    The primary goal of this work was to develop a procedure for calculation the appropriate filter shape for a brachytherapy applicator used for skin radiotherapy. In the applicator a radioactive source is positioned close to the skin. Without a filter, the resultant dose distribution would be highly nonuniform.High uniformity is usually required however. This can be achieved using an appropriately shaped filter, which flattens the dose profile. Because of the complexity of the transport and geometry, Monte Carlo simulations had to be used. An 192 Ir high dose rate photon source was used. All necessary transport parameters were simulated with the MCNP4B Monte Carlo code. A highly efficient iterative procedure was developed, which enabled calculation of the optimal filter shape in only few iterations. The initially non-uniform dose distributions became uniform within a percent when applying the filter calculated by this procedure. (author)

  19. 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

  20. Hypothesis testing of scientific Monte Carlo calculations

    Science.gov (United States)

    Wallerberger, Markus; Gull, Emanuel

    2017-11-01

    The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

  1. Monte Carlo Simulation for Particle Detectors

    CERN Document Server

    Pia, Maria Grazia

    2012-01-01

    Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...

  2. 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

  3. Treatment and Combination of Data Quality Monitoring Histograms to Perform Data vs. Monte Carlo Validation

    CERN Document Server

    Colin, Nolan

    2013-01-01

    In CMS's automated data quality validation infrastructure, it is not currently possible to assess how well Monte Carlo simulations describe data from collisions, if at all. In order to guarantee high quality data, a novel work flow was devised to perform `data vs. Monte Carlo' validation. Support for this comparison was added by allowing distributions from several Monte Carlo samples to be combined, matched to the data and then displayed in a histogram stack, overlaid with the experimental data.

  4. 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.)

  5. Handbook of Markov chain Monte Carlo

    CERN Document Server

    Brooks, Steve

    2011-01-01

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

  6. 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)

  7. 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....

  8. 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.)

  9. 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

  10. 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.)

  11. 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

  12. Monte Carlo codes use in neutron therapy

    International Nuclear Information System (INIS)

    Paquis, P.; Mokhtari, F.; Karamanoukian, D.; Pignol, J.P.; Cuendet, P.; Iborra, N.

    1998-01-01

    Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)

  13. Quantum Monte Carlo calculations of light nuclei

    International Nuclear Information System (INIS)

    Pandharipande, V. R.

    1999-01-01

    Quantum Monte Carlo methods provide an essentially exact way to calculate various properties of nuclear bound, and low energy continuum states, from realistic models of nuclear interactions and currents. After a brief description of the methods and modern models of nuclear forces, we review the results obtained for all the bound, and some continuum states of up to eight nucleons. Various other applications of the methods are reviewed along with future prospects

  14. Monte-Carlo simulation of electromagnetic showers

    International Nuclear Information System (INIS)

    Amatuni, Ts.A.

    1984-01-01

    The universal ELSS-1 program for Monte Carlo simulation of high energy electromagnetic showers in homogeneous absorbers of arbitrary geometry is written. The major processes and effects of electron and photon interaction with matter, particularly the Landau-Pomeranchuk-Migdal effect, are taken into account in the simulation procedures. The simulation results are compared with experimental data. Some characteristics of shower detectors and electromagnetic showers for energies up 1 TeV are calculated

  15. Cost of splitting in Monte Carlo transport

    International Nuclear Information System (INIS)

    Everett, C.J.; Cashwell, E.D.

    1978-03-01

    In a simple transport problem designed to estimate transmission through a plane slab of x free paths by Monte Carlo methods, it is shown that m-splitting (m > or = 2) does not pay unless exp(x) > m(m + 3)/(m - 1). In such a case, the minimum total cost in terms of machine time is obtained as a function of m, and the optimal value of m is determined

  16. 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.

  17. 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

  18. Quantum Monte Carlo for vibrating molecules

    International Nuclear Information System (INIS)

    Brown, W.R.; Lawrence Berkeley National Lab., CA

    1996-08-01

    Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H 2 O and C 3 vibrational states, using 7 PES's, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H 2 O and C 3 . In order to construct accurate trial wavefunctions for C 3 , the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C 3 the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C 3 PES's suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies

  19. Lattice gauge theories and Monte Carlo simulations

    International Nuclear Information System (INIS)

    Rebbi, C.

    1981-11-01

    After some preliminary considerations, the discussion of quantum gauge theories on a Euclidean lattice takes up the definition of Euclidean quantum theory and treatment of the continuum limit; analogy is made with statistical mechanics. Perturbative methods can produce useful results for strong or weak coupling. In the attempts to investigate the properties of the systems for intermediate coupling, numerical methods known as Monte Carlo simulations have proved valuable. The bulk of this paper illustrates the basic ideas underlying the Monte Carlo numerical techniques and the major results achieved with them according to the following program: Monte Carlo simulations (general theory, practical considerations), phase structure of Abelian and non-Abelian models, the observables (coefficient of the linear term in the potential between two static sources at large separation, mass of the lowest excited state with the quantum numbers of the vacuum (the so-called glueball), the potential between two static sources at very small distance, the critical temperature at which sources become deconfined), gauge fields coupled to basonic matter (Higgs) fields, and systems with fermions

  20. Uncertainty Propagation in Monte Carlo Depletion Analysis

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Kim, Yeong-il; Park, Ho Jin; Joo, Han Gyu; Kim, Chang Hyo

    2008-01-01

    A new formulation aimed at quantifying uncertainties of Monte Carlo (MC) tallies such as k eff and the microscopic reaction rates of nuclides and nuclide number densities in MC depletion analysis and examining their propagation behaviour as a function of depletion time step (DTS) is presented. It is shown that the variance of a given MC tally used as a measure of its uncertainty in this formulation arises from four sources; the statistical uncertainty of the MC tally, uncertainties of microscopic cross sections and nuclide number densities, and the cross correlations between them and the contribution of the latter three sources can be determined by computing the correlation coefficients between the uncertain variables. It is also shown that the variance of any given nuclide number density at the end of each DTS stems from uncertainties of the nuclide number densities (NND) and microscopic reaction rates (MRR) of nuclides at the beginning of each DTS and they are determined by computing correlation coefficients between these two uncertain variables. To test the viability of the formulation, we conducted MC depletion analysis for two sample depletion problems involving a simplified 7x7 fuel assembly (FA) and a 17x17 PWR FA, determined number densities of uranium and plutonium isotopes and their variances as well as k ∞ and its variance as a function of DTS, and demonstrated the applicability of the new formulation for uncertainty propagation analysis that need be followed in MC depletion computations. (authors)

  1. A continuation multilevel Monte Carlo algorithm

    KAUST Repository

    Collier, Nathan

    2014-09-05

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

  2. Monte Carlo Production Management at CMS

    CERN Document Server

    Boudoul, G.; Pol, A; Srimanobhas, P; Vlimant, J R; Franzoni, Giovanni

    2015-01-01

    The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events.During the runI of LHC (2010-2012), CMS has produced over 12 Billion simulated events,organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up).In order toaggregate the information needed for the configuration and prioritization of the events production,assure the book-keeping and of all the processing requests placed by the physics analysis groups,and to interface with the CMS production infrastructure,the web-based service Monte Carlo Management (McM) has been developed and put in production in 2012.McM is based on recent server infrastructure technology (CherryPy + java) and relies on a CouchDB database back-end.This contribution will coverthe one and half year of operational experience managing samples of simulated events for CMS,the evolution of its functionalitiesand the extension of its capabi...

  3. 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.

  4. Rare event simulation using Monte Carlo methods

    CERN Document Server

    Rubino, Gerardo

    2009-01-01

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

  5. 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)

  6. Monte Carlo methods and models in finance and insurance

    CERN Document Server

    Korn, Ralf; Kroisandt, Gerald

    2010-01-01

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

  7. Multiple-time-stepping generalized hybrid Monte Carlo methods

    Energy Technology Data Exchange (ETDEWEB)

    Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)

    2015-01-01

    Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.

  8. Sequential Monte Carlo Instant Radiosity.

    Science.gov (United States)

    Hedman, Peter; Karras, Tero; Lehtinen, Jaakko

    2017-05-01

    Instant Radiosity and its derivatives are interactive methods for efficiently estimating global (indirect) illumination. They represent the last indirect bounce of illumination before the camera as the composite radiance field emitted by a set of virtual point light sources (VPLs). In complex scenes, current algorithms suffer from a difficult combination of two issues: it remains a challenge to distribute VPLs in a manner that simultaneously gives a high-quality indirect illumination solution for each frame, and to do so in a temporally coherent manner. We address both issues by building, and maintaining over time, an adaptive and temporally coherent distribution of VPLs in locations where they bring indirect light to the image. We introduce a novel heuristic sampling method that strives to only move as few of the VPLs between frames as possible. The result is, to the best of our knowledge, the first interactive global illumination algorithm that works in complex, highly-occluded scenes, suffers little from temporal flickering, supports moving cameras and light sources, and is output-sensitive in the sense that it places VPLs in locations that matter most to the final result.

  9. A Monte Carlo Library Least Square approach in the Neutron Inelastic-scattering and Thermal-capture Analysis (NISTA) process in bulk coal samples

    Science.gov (United States)

    Reyhancan, Iskender Atilla; Ebrahimi, Alborz; Çolak, Üner; Erduran, M. Nizamettin; Angin, Nergis

    2017-01-01

    A new Monte-Carlo Library Least Square (MCLLS) approach for treating non-linear radiation analysis problem in Neutron Inelastic-scattering and Thermal-capture Analysis (NISTA) was developed. 14 MeV neutrons were produced by a neutron generator via the 3H (2H , n) 4He reaction. The prompt gamma ray spectra from bulk samples of seven different materials were measured by a Bismuth Germanate (BGO) gamma detection system. Polyethylene was used as neutron moderator along with iron and lead as neutron and gamma ray shielding, respectively. The gamma detection system was equipped with a list mode data acquisition system which streams spectroscopy data directly to the computer, event-by-event. A GEANT4 simulation toolkit was used for generating the single-element libraries of all the elements of interest. These libraries were then used in a Linear Library Least Square (LLLS) approach with an unknown experimental sample spectrum to fit it with the calculated elemental libraries. GEANT4 simulation results were also used for the selection of the neutron shielding material.

  10. 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

  11. Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors

    International Nuclear Information System (INIS)

    Lucka, Felix

    2012-01-01

    Sparsity has become a key concept for solving of high-dimensional inverse problems using variational regularization techniques. Recently, using similar sparsity-constraints in the Bayesian framework for inverse problems by encoding them in the prior distribution has attracted attention. Important questions about the relation between regularization theory and Bayesian inference still need to be addressed when using sparsity promoting inversion. A practical obstacle for these examinations is the lack of fast posterior sampling algorithms for sparse, high-dimensional Bayesian inversion. Accessing the full range of Bayesian inference methods requires being able to draw samples from the posterior probability distribution in a fast and efficient way. This is usually done using Markov chain Monte Carlo (MCMC) sampling algorithms. In this paper, we develop and examine a new implementation of a single component Gibbs MCMC sampler for sparse priors relying on L1-norms. We demonstrate that the efficiency of our Gibbs sampler increases when the level of sparsity or the dimension of the unknowns is increased. This property is contrary to the properties of the most commonly applied Metropolis–Hastings (MH) sampling schemes. We demonstrate that the efficiency of MH schemes for L1-type priors dramatically decreases when the level of sparsity or the dimension of the unknowns is increased. Practically, Bayesian inversion for L1-type priors using MH samplers is not feasible at all. As this is commonly believed to be an intrinsic feature of MCMC sampling, the performance of our Gibbs sampler also challenges common beliefs about the applicability of sample based Bayesian inference. (paper)

  12. Guideline of Monte Carlo calculation. Neutron/gamma ray transport simulation by Monte Carlo method

    CERN Document Server

    2002-01-01

    This report condenses basic theories and advanced applications of neutron/gamma ray transport calculations in many fields of nuclear energy research. Chapters 1 through 5 treat historical progress of Monte Carlo methods, general issues of variance reduction technique, cross section libraries used in continuous energy Monte Carlo codes. In chapter 6, the following issues are discussed: fusion benchmark experiments, design of ITER, experiment analyses of fast critical assembly, core analyses of JMTR, simulation of pulsed neutron experiment, core analyses of HTTR, duct streaming calculations, bulk shielding calculations, neutron/gamma ray transport calculations of the Hiroshima atomic bomb. Chapters 8 and 9 treat function enhancements of MCNP and MVP codes, and a parallel processing of Monte Carlo calculation, respectively. An important references are attached at the end of this report.

  13. Correlated sampling added to the specific purpose Monte Carlo code McPNL for neutron lifetime log responses

    International Nuclear Information System (INIS)

    Mickael, M.; Verghese, K.; Gardner, R.P.

    1989-01-01

    The specific purpose neutron lifetime oil well logging simulation code, McPNL, has been rewritten for greater user-friendliness and faster execution. Correlated sampling has been added to the code to enable studies of relative changes in the tool response caused by environmental changes. The absolute responses calculated by the code have been benchmarked against laboratory test pit data. The relative responses from correlated sampling are not directly benchmarked, but they are validated using experimental and theoretical results

  14. Study of TXRF experimental system by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Costa, Ana Cristina M.; Leitao, Roberta G.; Lopes, Ricardo T.; Anjos, Marcelino J.; Conti, Claudio C.

    2011-01-01

    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)

  15. A Proposal of New Spherical Particle Modeling Method Based on Stochastic Sampling of Particle Locations in Monte Carlo Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Song Hyun; Kim, Do Hyun; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of); Noh, Jea Man [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    To the high computational efficiency and user convenience, the implicit method had received attention; however, it is noted that the implicit method in the previous studies has low accuracy at high packing fraction. In this study, a new implicit method, which can be used at any packing fraction with high accuracy, is proposed. In this study, the implicit modeling method in the spherical particle distributed medium for using the MC simulation is proposed. A new concept in the spherical particle sampling was developed to solve the problems in the previous implicit methods. The sampling method was verified by simulating the sampling method in the infinite and finite medium. The results show that the particle implicit modeling with the proposed method was accurately performed in all packing fraction boundaries. It is expected that the proposed method can be efficiently utilized for the spherical particle distributed mediums, which are the fusion reactor blanket, VHTR reactors, and shielding analysis.

  16. Bayesian inversion of seismic and electromagnetic data for marine gas reservoir characterization using multi-chain Markov chain Monte Carlo sampling

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Huiying; Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Bao, Jie; Swiler, Laura

    2017-12-01

    In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

  17. 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

  18. DISCLOSING THE RADIO LOUDNESS DISTRIBUTION DICHOTOMY IN QUASARS: AN UNBIASED MONTE CARLO APPROACH APPLIED TO THE SDSS-FIRST QUASAR SAMPLE

    Energy Technology Data Exchange (ETDEWEB)

    Balokovic, M. [Department of Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Smolcic, V. [Argelander-Institut fuer Astronomie, Auf dem Hugel 71, D-53121 Bonn (Germany); Ivezic, Z. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Zamorani, G. [INAF-Osservatorio Astronomico di Bologna, via Ranzani 1, I-40127 Bologna (Italy); Schinnerer, E. [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); Kelly, B. C. [Department of Physics, Broida Hall, University of California, Santa Barbara, CA 93106 (United States)

    2012-11-01

    We investigate the dichotomy in the radio loudness distribution of quasars by modeling their radio emission and various selection effects using a Monte Carlo approach. The existence of two physically distinct quasar populations, the radio-loud and radio-quiet quasars, is controversial and over the last decade a bimodal distribution of radio loudness of quasars has been both affirmed and disputed. We model the quasar radio luminosity distribution with simple unimodal and bimodal distribution functions. The resulting simulated samples are compared to a fiducial sample of 8300 quasars drawn from the SDSS DR7 Quasar Catalog and combined with radio observations from the FIRST survey. Our results indicate that the SDSS-FIRST sample is best described by a radio loudness distribution which consists of two components, with (12 {+-} 1)% of sources in the radio-loud component. On the other hand, the evidence for a local minimum in the loudness distribution (bimodality) is not strong and we find that previous claims for its existence were probably affected by the incompleteness of the FIRST survey close to its faint limit. We also investigate the redshift and luminosity dependence of the radio loudness distribution and find tentative evidence that at high redshift radio-loud quasars were rarer, on average louder, and exhibited a smaller range in radio loudness. In agreement with other recent work, we conclude that the SDSS-FIRST sample strongly suggests that the radio loudness distribution of quasars is not a universal function, and that more complex models than presented here are needed to fully explain available observations.

  19. DISCLOSING THE RADIO LOUDNESS DISTRIBUTION DICHOTOMY IN QUASARS: AN UNBIASED MONTE CARLO APPROACH APPLIED TO THE SDSS-FIRST QUASAR SAMPLE

    International Nuclear Information System (INIS)

    Baloković, M.; Smolčić, V.; Ivezić, Ž.; Zamorani, G.; Schinnerer, E.; Kelly, B. C.

    2012-01-01

    We investigate the dichotomy in the radio loudness distribution of quasars by modeling their radio emission and various selection effects using a Monte Carlo approach. The existence of two physically distinct quasar populations, the radio-loud and radio-quiet quasars, is controversial and over the last decade a bimodal distribution of radio loudness of quasars has been both affirmed and disputed. We model the quasar radio luminosity distribution with simple unimodal and bimodal distribution functions. The resulting simulated samples are compared to a fiducial sample of 8300 quasars drawn from the SDSS DR7 Quasar Catalog and combined with radio observations from the FIRST survey. Our results indicate that the SDSS-FIRST sample is best described by a radio loudness distribution which consists of two components, with (12 ± 1)% of sources in the radio-loud component. On the other hand, the evidence for a local minimum in the loudness distribution (bimodality) is not strong and we find that previous claims for its existence were probably affected by the incompleteness of the FIRST survey close to its faint limit. We also investigate the redshift and luminosity dependence of the radio loudness distribution and find tentative evidence that at high redshift radio-loud quasars were rarer, on average louder, and exhibited a smaller range in radio loudness. In agreement with other recent work, we conclude that the SDSS-FIRST sample strongly suggests that the radio loudness distribution of quasars is not a universal function, and that more complex models than presented here are needed to fully explain available observations.

  20. 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)

  1. Monte Carlo Volcano Seismic Moment Tensors

    Science.gov (United States)

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

    2015-12-01

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

  2. 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

  3. Monte Carlo Simulation of an American Option

    Directory of Open Access Journals (Sweden)

    Gikiri Thuo

    2007-04-01

    Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.

  4. 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

  5. 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.)

  6. ATLAS Monte Carlo tunes for MC09

    CERN Document Server

    The ATLAS collaboration

    2010-01-01

    This note describes the ATLAS tunes of underlying event and minimum bias description for the main Monte Carlo generators used in the MC09 production. For the main shower generators, pythia and herwig (with jimmy), the MRST LO* parton distribution functions (PDFs) were used for the first time in ATLAS. Special studies on the performance of these, conceptually new, PDFs for high pt physics processes at LHC energies are presented. In addition, a tune of jimmy for CTEQ6.6 is presented, for use with MC@NLO.

  7. Markov chains analytic and Monte Carlo computations

    CERN Document Server

    Graham, Carl

    2014-01-01

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

  8. Mosaic crystal algorithm for Monte Carlo simulations

    CERN Document Server

    Seeger, P A

    2002-01-01

    An algorithm is presented for calculating reflectivity, absorption, and scattering of mosaic crystals in Monte Carlo simulations of neutron instruments. The algorithm uses multi-step transport through the crystal with an exact solution of the Darwin equations at each step. It relies on the kinematical model for Bragg reflection (with parameters adjusted to reproduce experimental data). For computation of thermal effects (the Debye-Waller factor and coherent inelastic scattering), an expansion of the Debye integral as a rapidly converging series of exponential terms is also presented. Any crystal geometry and plane orientation may be treated. The algorithm has been incorporated into the neutron instrument simulation package NISP. (orig.)

  9. A note on simultaneous Monte Carlo tests

    DEFF Research Database (Denmark)

    Hahn, Ute

    In this short note, Monte Carlo tests of goodness of fit for data of the form X(t), t ∈ I are considered, that reject the null hypothesis if X(t) leaves an acceptance region bounded by an upper and lower curve for some t in I. A construction of the acceptance region is proposed that complies to a...... to a given target level of rejection, and yields exact p-values. The construction is based on pointwise quantiles, estimated from simulated realizations of X(t) under the null hypothesis....

  10. MBR Monte Carlo Simulation in PYTHIA8

    Science.gov (United States)

    Ciesielski, R.

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

  11. Spectral functions from Quantum Monte Carlo

    International Nuclear Information System (INIS)

    Silver, R.N.

    1989-01-01

    In his review, D. Scalapino identified two serious limitations on the application of Quantum Monte Carlo (QMC) methods to the models of interest in High T c Superconductivity (HTS). One is the ''sign problem''. The other is the ''analytic continuation problem'', which is how to extract electron spectral functions from QMC calculations of the imaginary time Green's functions. Through-out this Symposium on HTS, the spectral functions have been the focus for the discussion of normal state properties including the applicability of band theory, Fermi liquid theory, marginal Fermi liquids, and novel non-perturbative states. 5 refs., 1 fig

  12. An analysis of Monte Carlo tree search

    CSIR Research Space (South Africa)

    James, S

    2017-02-01

    Full Text Available Tree Search Steven James∗, George Konidaris† & Benjamin Rosman∗‡ ∗University of the Witwatersrand, Johannesburg, South Africa †Brown University, Providence RI 02912, USA ‡Council for Scientific and Industrial Research, Pretoria, South Africa steven....james@students.wits.ac.za, gdk@cs.brown.edu, brosman@csir.co.za Abstract Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in re- cent years. Despite the vast amount of research into MCTS, the effect of modifications...

  13. Monte Carlo simulation for the transport beamline

    Energy Technology Data Exchange (ETDEWEB)

    Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania (Italy); Attili, A.; Marchetto, F.; Russo, G. [INFN, Sezione di Torino, Via P.Giuria, 1 10125 Torino (Italy); Cirrone, G. A. P.; Schillaci, F.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Institute of Physics Czech Academy of Science, ELI-Beamlines project, Na Slovance 2, Prague (Czech Republic); Carpinelli, M. [INFN Sezione di Cagliari, c/o Dipartimento di Fisica, Università di Cagliari, Cagliari (Italy); Tramontana, A. [INFN, Laboratori Nazionali del Sud, Via Santa Sofia 62, Catania, Italy and Università di Catania, Dipartimento di Fisica e Astronomia, Via S. Sofia 64, Catania (Italy)

    2013-07-26

    In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.

  14. Monte Carlo simulation for the transport beamline

    International Nuclear Information System (INIS)

    Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.; Tramontana, A.

    2013-01-01

    In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery

  15. 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

  16. Monte Carlo modelling for neutron guide losses

    International Nuclear Information System (INIS)

    Cser, L.; Rosta, L.; Toeroek, Gy.

    1989-09-01

    In modern research reactors, neutron guides are commonly used for beam conducting. The neutron guide is a well polished or equivalently smooth glass tube covered inside by sputtered or evaporated film of natural Ni or 58 Ni isotope where the neutrons are totally reflected. A Monte Carlo calculation was carried out to establish the real efficiency and the spectral as well as spatial distribution of the neutron beam at the end of a glass mirror guide. The losses caused by mechanical inaccuracy and mirror quality were considered and the effects due to the geometrical arrangement were analyzed. (author) 2 refs.; 2 figs

  17. Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

    Science.gov (United States)

    Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

    2018-02-01

    Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

  18. Exploring Various Monte Carlo Simulations for Geoscience Applications

    Science.gov (United States)

    Blais, R.

    2010-12-01

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

  19. Exploring pseudo- and chaotic random Monte Carlo simulations

    Science.gov (United States)

    Blais, J. A. Rod; Zhang, Zhan

    2011-07-01

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

  20. Monte Carlo learning/biasing experiment with intelligent random numbers

    International Nuclear Information System (INIS)

    Booth, T.E.

    1985-01-01

    A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs

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

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Thompson, Kelly G.; Urbatsch, Todd J.

    2011-01-01

    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. (author)

  2. 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)

  3. Temperature variance study in Monte-Carlo photon transport theory

    International Nuclear Information System (INIS)

    Giorla, J.

    1985-10-01

    We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

  4. SELF-ABSORPTION CORRECTIONS BASED ON MONTE CARLO SIMULATIONS

    Directory of Open Access Journals (Sweden)

    Kamila Johnová

    2016-12-01

    Full Text Available The main aim of this article is to demonstrate how Monte Carlo simulations are implemented in our gamma spectrometry laboratory at the Department of Dosimetry and Application of Ionizing Radiation in order to calculate the self-absorption within the samples. A model of real HPGe detector created for MCNP simulations is presented in this paper. All of the possible parameters, which may influence the self-absorption, are at first discussed theoretically and lately described using the calculated results.

  5. POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS

    OpenAIRE

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power...

  6. Self-test Monte Carlo method

    International Nuclear Information System (INIS)

    Ohta, Shigemi

    1996-01-01

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

  7. 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.)

  8. 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

  9. Monte Carlo simulation of grain growth

    Directory of Open Access Journals (Sweden)

    Paulo Blikstein

    1999-07-01

    Full Text Available Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical behavior of the atoms is properly reproduced; microstructural evolution depends only on the real topology of the grains and not on any kind of geometric simplification. Computer simulation has the advantage of allowing the user to visualize graphically the procedures, even dynamically and in three dimensions. Single-phase alloy grain growth simulation was carried out by calculating the free energy of each atom in the lattice (with its present crystallographic orientation and comparing this value to another one calculated with a different random orientation. When the resulting free energy is lower or equal to the initial value, the new orientation replaces the former. The measure of time is the Monte Carlo Step (MCS, which involves a series of trials throughout the lattice. A very close relationship between experimental and theoretical values for the grain growth exponent (n was observed.

  10. Parallel Monte Carlo Search for Hough Transform

    Science.gov (United States)

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

    2017-10-01

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

  11. Monte Carlo simulation for radiographic applications

    International Nuclear Information System (INIS)

    Tillack, G.R.; Bellon, C.

    2003-01-01

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

  12. Reactor perturbation calculations by Monte Carlo methods

    International Nuclear Information System (INIS)

    Gubbins, M.E.

    1965-09-01

    Whilst Monte Carlo methods are useful for reactor calculations involving complicated geometry, it is difficult to apply them to the calculation of perturbation worths because of the large amount of computing time needed to obtain good accuracy. Various ways of overcoming these difficulties are investigated in this report, with the problem of estimating absorbing control rod worths particularly in mind. As a basis for discussion a method of carrying out multigroup reactor calculations by Monte Carlo methods is described. Two methods of estimating a perturbation worth directly, without differencing two quantities of like magnitude, are examined closely but are passed over in favour of a third method based on a correlation technique. This correlation method is described, and demonstrated by a limited range of calculations for absorbing control rods in a fast reactor. In these calculations control rod worths of between 1% and 7% in reactivity are estimated to an accuracy better than 10% (3 standard errors) in about one hour's computing time on the English Electric KDF.9 digital computer. (author)

  13. Odd-flavor Simulations by the Hybrid Monte Carlo

    CERN Document Server

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

    2001-01-01

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

  14. 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)

  15. Monte Carlo shielding analyses using an automated biasing procedure

    International Nuclear Information System (INIS)

    Tang, J.S.; Hoffman, T.J.

    1988-01-01

    A systematic and automated approach for biasing Monte Carlo shielding calculations is described. In particular, adjoint fluxes from a one-dimensional discrete ordinates calculation are used to generate biasing parameters for a Monte Carlo calculation. The entire procedure of adjoint calculation, biasing parameters generation, and Monte Carlo calculation has been automated. The automated biasing procedure has been applied to several realistic deep-penetration shipping cask problems. The results obtained for neutron and gamma-ray transport indicate that with the automated biasing procedure Monte Carlo shielding calculations of spent-fuel casks can be easily performed with minimum effort and that accurate results can be obtained at reasonable computing cost

  16. Monte Carlo techniques for analyzing deep-penetration problems

    International Nuclear Information System (INIS)

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

    1986-01-01

    Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. 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 multigroup 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

  17. Igo - A Monte Carlo Code For Radiotherapy Planning

    International Nuclear Information System (INIS)

    Goldstein, M.; Regev, D.

    1999-01-01

    The goal of radiation therapy is to deliver a lethal dose to the tumor, while minimizing the dose to normal tissues and vital organs. To carry out this task, it is critical to calculate correctly the 3-D dose delivered. Monte Carlo transport methods (especially the Adjoint Monte Carlo have the potential to provide more accurate predictions of the 3-D dose the currently used methods. IG0 is a Monte Carlo code derived from the general Monte Carlo Program - MCNP, tailored specifically for calculating the effects of radiation therapy. This paper describes the IG0 transport code, the PIG0 interface and some preliminary results

  18. Quantum statistical Monte Carlo methods and applications to spin systems

    International Nuclear Information System (INIS)

    Suzuki, M.

    1986-01-01

    A short review is given concerning the quantum statistical Monte Carlo method based on the equivalence theorem that d-dimensional quantum systems are mapped onto (d+1)-dimensional classical systems. The convergence property of this approximate tansformation is discussed in detail. Some applications of this general appoach to quantum spin systems are reviewed. A new Monte Carlo method, ''thermo field Monte Carlo method,'' is presented, which is an extension of the projection Monte Carlo method at zero temperature to that at finite temperatures

  19. Variational Variance Reduction for Monte Carlo Criticality Calculations

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2001-01-01

    A new variational variance reduction (VVR) method for Monte Carlo criticality calculations was developed. This method employs (a) a variational functional that is more accurate than the standard direct functional, (b) a representation of the deterministically obtained adjoint flux that is especially accurate for optically thick problems with high scattering ratios, and (c) estimates of the forward flux obtained by Monte Carlo. The VVR method requires no nonanalog Monte Carlo biasing, but it may be used in conjunction with Monte Carlo biasing schemes. Some results are presented from a class of criticality calculations involving alternating arrays of fuel and moderator regions

  20. Monte Carlo molecular simulations: improving the statistical efficiency of samples with the help of artificial evolution algorithms; Simulations moleculaires de Monte Carlo: amelioration de l'efficacite statistique de l'echantillonnage grace aux algorithmes d'evolution artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Leblanc, B.

    2002-03-01

    Molecular simulation aims at simulating particles in interaction, describing a physico-chemical system. When considering Markov Chain Monte Carlo sampling in this context, we often meet the same problem of statistical efficiency as with Molecular Dynamics for the simulation of complex molecules (polymers for example). The search for a correct sampling of the space of possible configurations with respect to the Boltzmann-Gibbs distribution is directly related to the statistical efficiency of such algorithms (i.e. the ability of rapidly providing uncorrelated states covering all the configuration space). We investigated how to improve this efficiency with the help of Artificial Evolution (AE). AE algorithms form a class of stochastic optimization algorithms inspired by Darwinian evolution. Efficiency measures that can be turned into efficiency criteria have been first searched before identifying parameters that could be optimized. Relative frequencies for each type of Monte Carlo moves, usually empirically chosen in reasonable ranges, were first considered. We combined parallel simulations with a 'genetic server' in order to dynamically improve the quality of the sampling during the simulations progress. Our results shows that in comparison with some reference settings, it is possible to improve the quality of samples with respect to the chosen criterion. The same algorithm has been applied to improve the Parallel Tempering technique, in order to optimize in the same time the relative frequencies of Monte Carlo moves and the relative frequencies of swapping between sub-systems simulated at different temperatures. Finally, hints for further research in order to optimize the choice of additional temperatures are given. (author)

  1. grmonty: A MONTE CARLO CODE FOR RELATIVISTIC RADIATIVE TRANSPORT

    International Nuclear Information System (INIS)

    Dolence, Joshua C.; Gammie, Charles F.; Leung, Po Kin; Moscibrodzka, Monika

    2009-01-01

    We describe a Monte Carlo radiative transport code intended for calculating spectra of hot, optically thin plasmas in full general relativity. The version we describe here is designed to model hot accretion flows in the Kerr metric and therefore incorporates synchrotron emission and absorption, and Compton scattering. The code can be readily generalized, however, to account for other radiative processes and an arbitrary spacetime. We describe a suite of test problems, and demonstrate the expected N -1/2 convergence rate, where N is the number of Monte Carlo samples. Finally, we illustrate the capabilities of the code with a model calculation, a spectrum of the slowly accreting black hole Sgr A* based on data provided by a numerical general relativistic MHD model of the accreting plasma.

  2. Monte Carlo Euler approximations of HJM term structure financial models

    KAUST Repository

    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.

  3. Mesh-based weight window approach for Monte Carlo simulation

    International Nuclear Information System (INIS)

    Liu, L.; Gardner, R.P.

    1997-01-01

    The Monte Carlo method has been increasingly used to solve particle transport problems. Statistical fluctuation from random sampling is the major limiting factor of its application. To obtain the desired precision, variance reduction techniques are indispensable for most practical problems. Among various variance reduction techniques, the weight window method proves to be one of the most general, powerful, and robust. The method is implemented in the current MCNP code. An importance map is estimated during a regular Monte Carlo run, and then the map is used in the subsequent run for splitting and Russian roulette games. The major drawback of this weight window method is lack of user-friendliness. It normally requires that users divide the large geometric cells into smaller ones by introducing additional surfaces to ensure an acceptable spatial resolution of the importance map. In this paper, we present a new weight window approach to overcome this drawback

  4. Improved local lattice Monte Carlo simulation for charged systems

    Science.gov (United States)

    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.

  5. Monte Carlo Euler approximations of HJM term structure financial models

    KAUST Repository

    Bjö rk, Tomas; Szepessy, Anders; Tempone, Raul; Zouraris, Georgios E.

    2012-01-01

    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.

  6. Monte Carlo evaluation of derivative-based global sensitivity measures

    Energy Technology Data Exchange (ETDEWEB)

    Kucherenko, S. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)], E-mail: s.kucherenko@ic.ac.uk; Rodriguez-Fernandez, M. [Process Engineering Group, Instituto de Investigaciones Marinas, Spanish Council for Scientific Research (C.S.I.C.), C/ Eduardo Cabello, 6, 36208 Vigo (Spain); Pantelides, C.; Shah, N. [Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)

    2009-07-15

    A novel approach for evaluation of derivative-based global sensitivity measures (DGSM) is presented. It is compared with the Morris and the Sobol' sensitivity indices methods. It is shown that there is a link between DGSM and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is many orders of magnitude lower than that for estimation of the Sobol' sensitivity indices. It is also lower than that for the Morris method. Efficiencies of Monte Carlo (MC) and quasi-Monte Carlo (QMC) sampling methods for calculation of DGSM are compared. It is shown that the superiority of QMC over MC depends on the problem's effective dimension, which can also be estimated using DGSM.

  7. Monte Carlo evaluation of derivative-based global sensitivity measures

    International Nuclear Information System (INIS)

    Kucherenko, S.; Rodriguez-Fernandez, M.; Pantelides, C.; Shah, N.

    2009-01-01

    A novel approach for evaluation of derivative-based global sensitivity measures (DGSM) is presented. It is compared with the Morris and the Sobol' sensitivity indices methods. It is shown that there is a link between DGSM and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is many orders of magnitude lower than that for estimation of the Sobol' sensitivity indices. It is also lower than that for the Morris method. Efficiencies of Monte Carlo (MC) and quasi-Monte Carlo (QMC) sampling methods for calculation of DGSM are compared. It is shown that the superiority of QMC over MC depends on the problem's effective dimension, which can also be estimated using DGSM.

  8. Dielectric response of periodic systems from quantum Monte Carlo calculations.

    Science.gov (United States)

    Umari, P; Willamson, A J; Galli, Giulia; Marzari, Nicola

    2005-11-11

    We present a novel approach that allows us to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric-enthalpy functional, where the coupling with the field is expressed via the Berry-phase formulation for the macroscopic polarization. A self-consistent local Hamiltonian then determines the ground-state wave function, allowing for accurate diffusion quantum Monte Carlo calculations where the polarization's fixed point is estimated from the average on an iterative sequence, sampled via forward walking. This approach has been validated for the case of an isolated hydrogen atom and then applied to a periodic system, to calculate the dielectric susceptibility of molecular-hydrogen chains. The results found are in excellent agreement with the best estimates obtained from the extrapolation of quantum-chemistry calculations.

  9. Probability Density Estimation Using Neural Networks in Monte Carlo Calculations

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Cho, Jin Young; Song, Jae Seung; Kim, Chang Hyo

    2008-01-01

    The Monte Carlo neutronics analysis requires the capability for a tally distribution estimation like an axial power distribution or a flux gradient in a fuel rod, etc. This problem can be regarded as a probability density function estimation from an observation set. We apply the neural network based density estimation method to an observation and sampling weight set produced by the Monte Carlo calculations. The neural network method is compared with the histogram and the functional expansion tally method for estimating a non-smooth density, a fission source distribution, and an absorption rate's gradient in a burnable absorber rod. The application results shows that the neural network method can approximate a tally distribution quite well. (authors)

  10. Sign problem and Monte Carlo calculations beyond Lefschetz thimbles

    International Nuclear Information System (INIS)

    Alexandru, Andrei; Başar, Gökçe; Bedaque, Paulo F.; Ridgway, Gregory W.; Warrington, Neill C.

    2016-01-01

    We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action (“Lefschetz thimble”). We describe a family of such manifolds that interpolate between the tangent space at one critical point (where the sign problem is milder compared to the real plane but in some cases still severe) and the union of relevant thimbles (where the sign problem is mild but a multimodal distribution function complicates the Monte Carlo sampling). We exemplify this approach using a simple 0+1 dimensional fermion model previously used on sign problem studies and show that it can solve the model for some parameter values where a solution using Lefschetz thimbles was elusive.

  11. Selection of important Monte Carlo histories

    International Nuclear Information System (INIS)

    Egbert, Stephen D.

    1987-01-01

    The 1986 Dosimetry System (DS86) for Japanese A-bomb survivors uses information describing the behavior of individual radiation particles, simulated by Monte Carlo methods, to calculate the transmission of radiation into structures and, thence, into humans. However, there are practical constraints on the number of such particle 'histories' that may be used. First, the number must be sufficiently high to provide adequate statistical precision fir any calculated quantity of interest. For integral quantities, such as dose or kerma, statistical precision of approximately 5% (standard deviation) is required to ensure that statistical uncertainties are not a major contributor to the overall uncertainty of the transmitted value. For differential quantities, such as scalar fluence spectra, 10 to 15% standard deviation on individual energy groups is adequate. Second, the number of histories cannot be so large as to require an unacceptably large amount of computer time to process the entire survivor data base. Given that there are approx. 30,000 survivors, each having 13 or 14 organs of interest, the number of histories per organ must be constrained to less than several ten's of thousands at the very most. Selection and use of the most important Monte Carlo leakage histories from among all those calculated allows the creation of an efficient house and organ radiation transmission system for use at RERF. While attempts have been made during the adjoint Monte Carlo calculation to bias the histories toward an efficient dose estimate, this effort has been far from satisfactory. Many of the adjoint histories on a typical leakage tape are either starting in an energy group in which there is very little kerma or dose or leaking into an energy group with very little free-field couple with. By knowing the typical free-field fluence and the fluence-to-dose factors with which the leaking histories will be used, one can select histories rom a leakage tape that will contribute to dose

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

    CERN Document Server

    Zio, Enrico

    2013-01-01

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

  13. Response decomposition with Monte Carlo correlated coupling

    International Nuclear Information System (INIS)

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

    2001-01-01

    Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)

  14. Response decomposition with Monte Carlo correlated coupling

    Energy Technology Data Exchange (ETDEWEB)

    Ueki, T.; Hoogenboom, J.E.; Kloosterman, J.L. [Delft Univ. of Technology (Netherlands). Interfaculty Reactor Inst.

    2001-07-01

    Particle histories that contribute to a detector response are categorized according to whether they are fully confined inside a source-detector enclosure or cross and recross the same enclosure. The contribution from the confined histories is expressed using a forward problem with the external boundary condition on the source-detector enclosure. The contribution from the crossing and recrossing histories is expressed as the surface integral at the same enclosure of the product of the directional cosine and the fluxes in the foregoing forward problem and the adjoint problem for the whole spatial domain. The former contribution can be calculated by a standard forward Monte Carlo. The latter contribution can be calculated by correlated coupling of forward and adjoint histories independently of the former contribution. We briefly describe the computational method and discuss its application to perturbation analysis for localized material changes. (orig.)

  15. Monte Carlo simulations of low background detectors

    International Nuclear Information System (INIS)

    Miley, H.S.; Brodzinski, R.L.; Hensley, W.K.; Reeves, J.H.

    1995-01-01

    An implementation of the Electron Gamma Shower 4 code (EGS4) has been developed to allow convenient simulation of typical gamma ray measurement systems. Coincidence gamma rays, beta spectra, and angular correlations have been added to adequately simulate a complete nuclear decay and provide corrections to experimentally determined detector efficiencies. This code has been used to strip certain low-background spectra for the purpose of extremely low-level assay. Monte Carlo calculations of this sort can be extremely successful since low background detectors are usually free of significant contributions from poorly localized radiation sources, such as cosmic muons, secondary cosmic neutrons, and radioactive construction or shielding materials. Previously, validation of this code has been obtained from a series of comparisons between measurements and blind calculations. An example of the application of this code to an exceedingly low background spectrum stripping will be presented. (author) 5 refs.; 3 figs.; 1 tab

  16. Homogenized group cross sections by Monte Carlo

    International Nuclear Information System (INIS)

    Van Der Marck, S. C.; Kuijper, J. C.; Oppe, J.

    2006-01-01

    Homogenized group cross sections play a large role in making reactor calculations efficient. Because of this significance, many codes exist that can calculate these cross sections based on certain assumptions. However, the application to the High Flux Reactor (HFR) in Petten, the Netherlands, the limitations of such codes imply that the core calculations would become less accurate when using homogenized group cross sections (HGCS). Therefore we developed a method to calculate HGCS based on a Monte Carlo program, for which we chose MCNP. The implementation involves an addition to MCNP, and a set of small executables to perform suitable averaging after the MCNP run(s) have completed. Here we briefly describe the details of the method, and we report on two tests we performed to show the accuracy of the method and its implementation. By now, this method is routinely used in preparation of the cycle to cycle core calculations for HFR. (authors)

  17. Nuclear reactions in Monte Carlo codes

    CERN Document Server

    Ferrari, Alfredo

    2002-01-01

    The physics foundations of hadronic interactions as implemented in most Monte Carlo codes are presented together with a few practical examples. The description of the relevant physics is presented schematically split into the major steps in order to stress the different approaches required for the full understanding of nuclear reactions at intermediate and high energies. Due to the complexity of the problem, only a few semi-qualitative arguments are developed in this paper. The description will be necessarily schematic and somewhat incomplete, but hopefully it will be useful for a first introduction into this topic. Examples are shown mostly for the high energy regime, where all mechanisms mentioned in the paper are at work and to which perhaps most of the readers are less accustomed. Examples for lower energies can be found in the references. (43 refs) .

  18. 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

  19. An accurate nonlinear Monte Carlo collision operator

    International Nuclear Information System (INIS)

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

    1995-03-01

    A three dimensional nonlinear Monte Carlo collision model is developed based on Coulomb binary collisions with the emphasis both on the accuracy and implementation efficiency. The operator of simple form fulfills particle number, momentum and energy conservation laws, and is equivalent to exact Fokker-Planck operator by correctly reproducing the friction coefficient and diffusion tensor, in addition, can effectively assure small-angle collisions with a binary scattering angle distributed in a limited range near zero. Two highly vectorizable algorithms are designed for its fast implementation. Various test simulations regarding relaxation processes, electrical conductivity, etc. are carried out in velocity space. The test results, which is in good agreement with theory, and timing results on vector computers show that it is practically applicable. The operator may be used for accurately simulating collisional transport problems in magnetized and unmagnetized plasmas. (author)

  20. Computation cluster for Monte Carlo calculations

    International Nuclear Information System (INIS)

    Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S.

    2010-01-01

    Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)

  1. 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)

  2. Vectorization of Monte Carlo particle transport

    International Nuclear Information System (INIS)

    Burns, P.J.; Christon, M.; Schweitzer, R.; Lubeck, O.M.; Wasserman, H.J.; Simmons, M.L.; Pryor, D.V.

    1989-01-01

    This paper reports that fully vectorized versions of the Los Alamos National Laboratory benchmark code Gamteb, a Monte Carlo photon transport algorithm, were developed for the Cyber 205/ETA-10 and Cray X-MP/Y-MP architectures. Single-processor performance measurements of the vector and scalar implementations were modeled in a modified Amdahl's Law that accounts for additional data motion in the vector code. The performance and implementation strategy of the vector codes are related to architectural features of each machine. Speedups between fifteen and eighteen for Cyber 205/ETA-10 architectures, and about nine for CRAY X-MP/Y-MP architectures are observed. The best single processor execution time for the problem was 0.33 seconds on the ETA-10G, and 0.42 seconds on the CRAY Y-MP

  3. Computation cluster for Monte Carlo calculations

    Energy Technology Data Exchange (ETDEWEB)

    Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S. [Dep. Of Nuclear Physics and Technology, Faculty of Electrical Engineering and Information, Technology, Slovak Technical University, Ilkovicova 3, 81219 Bratislava (Slovakia)

    2010-07-01

    Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)

  4. Monte Carlo calculations of channeling radiation

    International Nuclear Information System (INIS)

    Bloom, S.D.; Berman, B.L.; Hamilton, D.C.; Alguard, M.J.; Barrett, J.H.; Datz, S.; Pantell, R.H.; Swent, R.H.

    1981-01-01

    Results of classical Monte Carlo calculations are presented for the radiation produced by ultra-relativistic positrons incident in a direction parallel to the (110) plane of Si in the energy range 30 to 100 MeV. The results all show the characteristic CR(channeling radiation) peak in the energy range 20 keV to 100 keV. Plots of the centroid energies, widths, and total yields of the CR peaks as a function of energy show the power law dependences of γ 1 5 , γ 1 7 , and γ 2 5 respectively. Except for the centroid energies and power-law dependence is only approximate. Agreement with experimental data is good for the centroid energies and only rough for the widths. Adequate experimental data for verifying the yield dependence on γ does not yet exist

  5. Monte Carlo simulation of neutron scattering instruments

    International Nuclear Information System (INIS)

    Seeger, P.A.; Daemen, L.L.; Hjelm, R.P. Jr.

    1998-01-01

    A code package consisting of the Monte Carlo Library MCLIB, the executing code MC RUN, the web application MC Web, and various ancillary codes is proposed as an open standard for simulation of neutron scattering instruments. The architecture of the package includes structures to define surfaces, regions, and optical elements contained in regions. A particle is defined by its vector position and velocity, its time of flight, its mass and charge, and a polarization vector. The MC RUN code handles neutron transport and bookkeeping, while the action on the neutron within any region is computed using algorithms that may be deterministic, probabilistic, or a combination. Complete versatility is possible because the existing library may be supplemented by any procedures a user is able to code. Some examples are shown

  6. 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.)

  7. 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.

  8. 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.

  9. Radiation Modeling with Direct Simulation Monte Carlo

    Science.gov (United States)

    Carlson, Ann B.; Hassan, H. A.

    1991-01-01

    Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.

  10. Markov Chain Monte Carlo from Lagrangian Dynamics.

    Science.gov (United States)

    Lan, Shiwei; Stathopoulos, Vasileios; Shahbaba, Babak; Girolami, Mark

    2015-04-01

    Hamiltonian Monte Carlo (HMC) improves the computational e ciency of the Metropolis-Hastings algorithm by reducing its random walk behavior. Riemannian HMC (RHMC) further improves the performance of HMC by exploiting the geometric properties of the parameter space. However, the geometric integrator used for RHMC involves implicit equations that require fixed-point iterations. In some cases, the computational overhead for solving implicit equations undermines RHMC's benefits. In an attempt to circumvent this problem, we propose an explicit integrator that replaces the momentum variable in RHMC by velocity. We show that the resulting transformation is equivalent to transforming Riemannian Hamiltonian dynamics to Lagrangian dynamics. Experimental results suggests that our method improves RHMC's overall computational e ciency in the cases considered. All computer programs and data sets are available online (http://www.ics.uci.edu/~babaks/Site/Codes.html) in order to allow replication of the results reported in this paper.

  11. Active neutron multiplicity analysis and Monte Carlo calculations

    International Nuclear Information System (INIS)

    Krick, M.S.; Ensslin, N.; Langner, D.G.; Miller, M.C.; Siebelist, R.; Stewart, J.E.; Ceo, R.N.; May, P.K.; Collins, L.L. Jr

    1994-01-01

    Active neutron multiplicity measurements of high-enrichment uranium metal and oxide samples have been made at Los Alamos and Y-12. The data from the measurements of standards at Los Alamos were analyzed to obtain values for neutron multiplication and source-sample coupling. These results are compared to equivalent results obtained from Monte Carlo calculations. An approximate relationship between coupling and multiplication is derived and used to correct doubles rates for multiplication and coupling. The utility of singles counting for uranium samples is also examined

  12. Monte Carlo modelling of TRIGA research reactor

    Science.gov (United States)

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

    2010-10-01

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

  13. PEPSI: a Monte Carlo generator for polarized leptoproduction

    International Nuclear Information System (INIS)

    Mankiewicz, L.

    1992-01-01

    We describe PEPSI (Polarized Electron Proton Scattering Interactions) a Monte Carlo program for the polarized deep inelastic leptoproduction mediated by electromagnetic interaction. The code is a modification of the LEPTO 4.3 Lund Monte Carlo for unpolarized scattering and requires the standard polarization-independent JETSET routines to perform fragmentation into final hadrons. (orig.)

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

    African Journals Online (AJOL)

    Closed-shell variational quantum Monte Carlo simulation for the electric dipole moment calculation of hydrazine molecule using casino-code. ... Nigeria Journal of Pure and Applied Physics ... The variational quantum Monte Carlo (VQMC) technique used in this work employed the restricted Hartree-Fock (RHF) scheme.

  15. 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

  16. 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.

  17. Forest canopy BRDF simulation using Monte Carlo method

    NARCIS (Netherlands)

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

    2006-01-01

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

  18. 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.

  19. A Monte Carlo algorithm for the Vavilov distribution

    International Nuclear Information System (INIS)

    Yi, Chul-Young; Han, Hyon-Soo

    1999-01-01

    Using the convolution property of the inverse Laplace transform, an improved Monte Carlo algorithm for the Vavilov energy-loss straggling distribution of the charged particle is developed, which is relatively simple and gives enough accuracy to be used for most Monte Carlo applications

  20. 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)

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

    NARCIS (Netherlands)

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

    2006-01-01

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

  2. A New Approach to Monte Carlo Simulations in Statistical Physics

    Science.gov (United States)

    Landau, David P.

    2002-08-01

    Monte Carlo simulations [1] have become a powerful tool for the study of diverse problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, most often in the canonical ensemble, and over the past several decades enormous improvements have been made in performance. Nonetheless, difficulties arise near phase transitions-due to critical slowing down near 2nd order transitions and to metastability near 1st order transitions, and these complications limit the applicability of the method. We shall describe a new Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is known, all thermodynamic properties can be calculated. This approach can be extended to multi-dimensional parameter spaces and should be effective for systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc. Generalizations should produce a broadly applicable optimization tool. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

  3. 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

  4. 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

  5. Monte Carlo codes use in neutron therapy; Application de codes Monte Carlo en neutrontherapie

    Energy Technology Data Exchange (ETDEWEB)

    Paquis, P.; Mokhtari, F.; Karamanoukian, D. [Hopital Pasteur, 06 - Nice (France); Pignol, J.P. [Hopital du Hasenrain, 68 - Mulhouse (France); Cuendet, P. [CEA Centre d' Etudes de Saclay, 91 - Gif-sur-Yvette (France). Direction des Reacteurs Nucleaires; Fares, G.; Hachem, A. [Faculte des Sciences, 06 - Nice (France); Iborra, N. [Centre Antoine-Lacassagne, 06 - Nice (France)

    1998-04-01

    Monte Carlo calculation codes allow to study accurately all the parameters relevant to radiation effects, like the dose deposition or the type of microscopic interactions, through one by one particle transport simulation. These features are very useful for neutron irradiations, from device development up to dosimetry. This paper illustrates some applications of these codes in Neutron Capture Therapy and Neutron Capture Enhancement of fast neutrons irradiations. (authors)

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

    CERN Document Server

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

    2001-01-01

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

  7. 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_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f 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)

  8. Linear filtering applied to Monte Carlo criticality calculations

    International Nuclear Information System (INIS)

    Morrison, G.W.; Pike, D.H.; Petrie, L.M.

    1975-01-01

    A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed

  9. Problems in radiation shielding calculations with Monte Carlo methods

    International Nuclear Information System (INIS)

    Ueki, Kohtaro

    1985-01-01

    The Monte Carlo method is a very useful tool for solving a large class of radiation transport problem. In contrast with deterministic method, geometric complexity is a much less significant problem for Monte Carlo calculations. However, the accuracy of Monte Carlo calculations is of course, limited by statistical error of the quantities to be estimated. In this report, we point out some typical problems to solve a large shielding system including radiation streaming. The Monte Carlo coupling technique was developed to settle such a shielding problem accurately. However, the variance of the Monte Carlo results using the coupling technique of which detectors were located outside the radiation streaming, was still not enough. So as to bring on more accurate results for the detectors located outside the streaming and also for a multi-legged-duct streaming problem, a practicable way of ''Prism Scattering technique'' is proposed in the study. (author)

  10. Cluster monte carlo method for nuclear criticality safety calculation

    International Nuclear Information System (INIS)

    Pei Lucheng

    1984-01-01

    One of the most important applications of the Monte Carlo method is the calculation of the nuclear criticality safety. The fair source game problem was presented at almost the same time as the Monte Carlo method was applied to calculating the nuclear criticality safety. The source iteration cost may be reduced as much as possible or no need for any source iteration. This kind of problems all belongs to the fair source game prolems, among which, the optimal source game is without any source iteration. Although the single neutron Monte Carlo method solved the problem without the source iteration, there is still quite an apparent shortcoming in it, that is, it solves the problem without the source iteration only in the asymptotic sense. In this work, a new Monte Carlo method called the cluster Monte Carlo method is given to solve the problem further

  11. Hybrid SN/Monte Carlo research and results

    International Nuclear Information System (INIS)

    Baker, R.S.

    1993-01-01

    The neutral particle transport equation is solved by a hybrid method that iteratively couples regions where deterministic (S N ) and stochastic (Monte Carlo) methods are applied. 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 Monte Carlo/S N 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 hybrid method has been successfully applied to realistic shielding problems. The vectorized Monte Carlo algorithm in the hybrid method has been ported to the massively parallel architecture of the Connection Machine. Comparisons of performance on a vector machine (Cray Y-MP) and the Connection Machine (CM-2) show that significant speedups are obtainable for vectorized Monte Carlo algorithms on massively parallel machines, even when realistic problems requiring variance reduction are considered. However, the architecture of the Connection Machine does place some limitations on the regime in which the Monte Carlo algorithm may be expected to perform well

  12. Monte Carlo simulations of multiple scattering effects in ERD measurements

    International Nuclear Information System (INIS)

    Doyle, Barney Lee; Arstila, Kai.; Nordlumd, K.; Knapp, James Arthur

    2003-01-01

    Multiple scattering effects in ERD measurements are studied by comparing two Monte Carlo simulation codes, representing different approaches to obtain acceptable statistics, to experimental spectra measured from a HfO 2 sample with a time-of-flight-ERD setup. The results show that both codes can reproduce the absolute detection yields and the energy distributions in an adequate way. The effect of the choice of the interatomic potential in multiple scattering effects is also studied. Finally the capabilities of the MC simulations in the design of new measurement setups are demonstrated by simulating the recoil energy spectra from a WC x N y sample with a low energy heavy ion beam.

  13. Reliability analysis of neutron transport simulation using Monte Carlo method

    International Nuclear Information System (INIS)

    Souza, Bismarck A. de; Borges, Jose C.

    1995-01-01

    This work presents a statistical and reliability analysis covering data obtained by computer simulation of neutron transport process, using the Monte Carlo method. A general description of the method and its applications is presented. Several simulations, corresponding to slowing down and shielding problems have been accomplished. The influence of the physical dimensions of the materials and of the sample size on the reliability level of results was investigated. The objective was to optimize the sample size, in order to obtain reliable results, optimizing computation time. (author). 5 refs, 8 figs

  14. A review of Monte Carlo techniques used in various fields of radiation protection

    International Nuclear Information System (INIS)

    Koblinger, L.

    1987-06-01

    Monte Carlo methods and their utilization in radiation protection are overviewed. Basic principles and the most frequently used sampling methods are described. Examples range from the simulation of the random walk of photons and neutrons to neutron spectrum unfolding. (author)

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

    International Nuclear Information System (INIS)

    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

  16. 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.

  17. Monte Carlo based diffusion coefficients for LMFBR analysis

    International Nuclear Information System (INIS)

    Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

    2010-01-01

    A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)

  18. 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)

  19. HEXANN-EVALU - a Monte Carlo program system for pressure vessel neutron irradiation calculation

    International Nuclear Information System (INIS)

    Lux, Ivan

    1983-08-01

    The Monte Carlo program HEXANN and the evaluation program EVALU are intended to calculate Monte Carlo estimates of reaction rates and currents in segments of concentric angular regions around a hexagonal reactor-core region. The report describes the theoretical basis, structure and activity of the programs. Input data preparation guides and a sample problem are also included. Theoretical considerations as well as numerical experimental results suggest the user a nearly optimum way of making use of the Monte Carlo efficiency increasing options included in the program

  20. 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

  1. A radiating shock evaluated using Implicit Monte Carlo Diffusion

    International Nuclear Information System (INIS)

    Cleveland, M.; Gentile, N.

    2013-01-01

    Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)

  2. Recommender engine for continuous-time quantum Monte Carlo methods

    Science.gov (United States)

    Huang, Li; Yang, Yi-feng; Wang, Lei

    2017-03-01

    Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

  3. Discrete Diffusion Monte Carlo for Electron Thermal Transport

    Science.gov (United States)

    Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

    2014-10-01

    The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

  4. The Monte Carlo method the method of statistical trials

    CERN Document Server

    Shreider, YuA

    1966-01-01

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

  5. Neutron flux calculation by means of Monte Carlo methods

    International Nuclear Information System (INIS)

    Barz, H.U.; Eichhorn, M.

    1988-01-01

    In this report a survey of modern neutron flux calculation procedures by means of Monte Carlo methods is given. Due to the progress in the development of variance reduction techniques and the improvements of computational techniques this method is of increasing importance. The basic ideas in application of Monte Carlo methods are briefly outlined. In more detail various possibilities of non-analog games and estimation procedures are presented, problems in the field of optimizing the variance reduction techniques are discussed. In the last part some important international Monte Carlo codes and own codes of the authors are listed and special applications are described. (author)

  6. 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.)

  7. Parallel Monte Carlo simulation of aerosol dynamics

    KAUST Repository

    Zhou, K.

    2014-01-01

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

  8. SERPENT Monte Carlo reactor physics code

    International Nuclear Information System (INIS)

    Leppaenen, J.

    2010-01-01

    SERPENT is a three-dimensional continuous-energy Monte Carlo reactor physics burnup calculation code, developed at VTT Technical Research Centre of Finland since 2004. The code is specialized in lattice physics applications, but the universe-based geometry description allows transport simulation to be carried out in complicated three-dimensional geometries as well. The suggested applications of SERPENT include generation of homogenized multi-group constants for deterministic reactor simulator calculations, fuel cycle studies involving detailed assembly-level burnup calculations, validation of deterministic lattice transport codes, research reactor applications, educational purposes and demonstration of reactor physics phenomena. The Serpent code has been publicly distributed by the OECD/NEA Data Bank since May 2009 and RSICC in the U. S. since March 2010. The code is being used in some 35 organizations in 20 countries around the world. This paper presents an overview of the methods and capabilities of the Serpent code, with examples in the modelling of WWER-440 reactor physics. (Author)

  9. Radon counting statistics - a Monte Carlo investigation

    International Nuclear Information System (INIS)

    Scott, A.G.

    1996-01-01

    Radioactive decay is a Poisson process, and so the Coefficient of Variation (COV) of open-quotes nclose quotes counts of a single nuclide is usually estimated as 1/√n. This is only true if the count duration is much shorter than the half-life of the nuclide. At longer count durations, the COV is smaller than the Poisson estimate. Most radon measurement methods count the alpha decays of 222 Rn, plus the progeny 218 Po and 214 Po, and estimate the 222 Rn activity from the sum of the counts. At long count durations, the chain decay of these nuclides means that every 222 Rn decay must be followed by two other alpha decays. The total number of decays is open-quotes 3Nclose quotes, where N is the number of radon decays, and the true COV of the radon concentration estimate is 1/√(N), √3 larger than the Poisson total count estimate of 1/√3N. Most count periods are comparable to the half lives of the progeny, so the relationship between COV and count time is complex. A Monte-Carlo estimate of the ratio of true COV to Poisson estimate was carried out for a range of count periods from 1 min to 16 h and three common radon measurement methods: liquid scintillation, scintillation cell, and electrostatic precipitation of progeny. The Poisson approximation underestimates COV by less than 20% for count durations of less than 60 min

  10. 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.)

  11. The Monte Carlo calculation of gamma family

    International Nuclear Information System (INIS)

    Shibata, Makio

    1980-01-01

    The method of the Monte Carlo calculation for gamma family was investigated. The effects of the variation of values or terms of parameters on observed quantities were studied. The terms taken for the standard calculation are the scaling law for the model, simple proton spectrum for primary cosmic ray, a constant cross section of interaction, zero probability of neutral pion production, and the bending of the curve of primary energy spectrum. This is called S model. Calculations were made by changing one of above mentioned parameters. The chamber size, the mixing of gamma and hadrons, and the family size were fitted to the practical ECC data. When the model was changed from the scaling law to the CKP model, the energy spectrum of the family was able to be expressed by the CKP model better than the scaling law. The scaling law was better in the symmetry around the family center. It was denied that primary cosmic ray mostly consists of heavy particles. The increase of the interaction cross section was necessary in view of the frequency of the families. (Kato, T.)

  12. Monte Carlo benchmarking: Validation and progress

    International Nuclear Information System (INIS)

    Sala, P.

    2010-01-01

    Document available in abstract form only. Full text of publication follows: Calculational tools for radiation shielding at accelerators are faced with new challenges from the present and next generations of particle accelerators. All the details of particle production and transport play a role when dealing with huge power facilities, therapeutic ion beams, radioactive beams and so on. Besides the traditional calculations required for shielding, activation predictions have become an increasingly critical component. Comparison and benchmarking with experimental data is obviously mandatory in order to build up confidence in the computing tools, and to assess their reliability and limitations. Thin target particle production data are often the best tools for understanding the predictive power of individual interaction models and improving their performances. Complex benchmarks (e.g. thick target data, deep penetration, etc.) are invaluable in assessing the overall performances of calculational tools when all ingredients are put at work together. A review of the validation procedures of Monte Carlo tools will be presented with practical and real life examples. The interconnections among benchmarks, model development and impact on shielding calculations will be highlighted. (authors)

  13. 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.

  14. Monte Carlo technique for local perturbations in multiplying systems

    International Nuclear Information System (INIS)

    Bernnat, W.

    1974-01-01

    The use of the Monte Carlo method for the calculation of reactivity perturbations in multiplying systems due to changes in geometry or composition requires a correlated sampling technique to make such calculations economical or in the case of very small perturbations even feasible. The technique discussed here is suitable for local perturbations. Very small perturbation regions will be treated by an adjoint mode. The perturbation of the source distribution due to the changed system and its reaction on the reactivity worth or other values of interest is taken into account by a fission matrix method. The formulation of the method and its application are discussed. 10 references. (U.S.)

  15. Non-Boltzmann Ensembles and Monte Carlo Simulations

    International Nuclear Information System (INIS)

    Murthy, K. P. N.

    2016-01-01

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

  16. Monte Carlo simulation of lattice bosons in three dimensions

    International Nuclear Information System (INIS)

    Blaer, A.; Han, J.

    1992-01-01

    We present an algorithm for calculating the thermodynamic properties of a system of nonrelativistic bosons on a three-dimensional spatial lattice. The method, which maps the three-dimensional quantum system onto a four-dimensional classical system, uses Monte Carlo sampling of configurations in either the canonical or the grand canonical ensemble. Our procedure is applicable to any system of lattice bosons with arbitrary short-range interactions. We test the algorithm by computing the temperature dependence of the energy, the heat capacity, and the condensate fraction of the free Bose gas

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

    International Nuclear Information System (INIS)

    Mori, Takamasa; Nakagawa, Masayuki

    1987-01-01

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

  18. Monte Carlo studies for irradiation process planning at the Portuguese gamma irradiation facility

    International Nuclear Information System (INIS)

    Oliveira, C.; Salgado, J.; Botelho, M.L.M. Luisa; Ferreira, L.M.

    2000-01-01

    The paper describes a Monte Carlo study for planning the irradiation of test samples for microbiological validation of distinct products in the Portuguese Gamma Irradiation Facility. Three different irradiation geometries have been used. Simulated and experimental results are compared and good agreement is observed. It is shown that Monte Carlo simulation improves process understanding, predicts absorbed dose distributions and calculates dose uniformity in different products. Based on these results, irradiation planning of the product can be performed

  19. Six types Monte Carlo for estimating the current unavailability of Markov system with dependent repair

    International Nuclear Information System (INIS)

    Xiao Gang; Li Zhizhong

    2004-01-01

    Based on integral equaiton describing the life-history of Markov system, six types of estimators of the current unavailability of Markov system with dependent repair are propounded. Combining with the biased sampling of state transition time of system, six types of Monte Carlo for estimating the current unavailability are given. Two numerical examples are given to deal with the variances and efficiencies of the six types of Monte Carlo methods. (authors)

  20. Estimativa da produtividade em soldagem pelo Método de Monte Carlo Productivity estimation in welding by Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    José Luiz Ferreira Martins

    2011-09-01

    Full Text Available O objetivo deste artigo é o de analisar a viabilidade da utilização do método de Monte Carlo para estimar a produtividade na soldagem de tubulações industriais de aço carbono com base em amostras pequenas. O estudo foi realizado através de uma análise de uma amostra de referência contendo dados de produtividade de 160 juntas soldadas pelo processo Eletrodo Revestido na REDUC (refinaria de Duque de Caxias, utilizando o software ControlTub 5.3. A partir desses dados foram retiradas de forma aleatória, amostras com, respectivamente, 10, 15 e 20 elementos e executadas simulações pelo método de Monte Carlo. Comparando-se os resultados da amostra com 160 elementos e os dados gerados por simulação se observa que bons resultados podem ser obtidos usando o método de Monte Carlo para estimativa da produtividade da soldagem. Por outro lado, na indústria da construção brasileira o valor da média de produtividade é normalmente usado como um indicador de produtividade e é baseado em dados históricos de outros projetos coletados e avaliados somente após a conclusão do projeto, o que é uma limitação. Este artigo apresenta uma ferramenta para avaliação da execução em tempo real, permitindo ajustes nas estimativas e monitoramento de produtividade durante o empreendimento. Da mesma forma, em licitações, orçamentos e estimativas de prazo, a utilização desta técnica permite a adoção de outras estimativas diferentes da produtividade média, que é comumente usada e como alternativa, se sugerem três critérios: produtividade otimista, média e pessimista.The aim of this article is to analyze the feasibility of using Monte Carlo method to estimate productivity in industrial pipes welding of carbon steel based on small samples. The study was carried out through an analysis of a reference sample containing productivity data of 160 welded joints by SMAW process in REDUC (Duque de Caxias Refinery, using ControlTub 5.3 software

  1. Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

    KAUST Repository

    Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.

    2010-01-01

    model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order

  2. 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

  3. GE781: a Monte Carlo package for fixed target experiments

    Science.gov (United States)

    Davidenko, G.; Funk, M. A.; Kim, V.; Kuropatkin, N.; Kurshetsov, V.; Molchanov, V.; Rud, S.; Stutte, L.; Verebryusov, V.; Zukanovich Funchal, R.

    The Monte Carlo package for the fixed target experiment B781 at Fermilab, a third generation charmed baryon experiment, is described. This package is based on GEANT 3.21, ADAMO database and DAFT input/output routines.

  4. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung

    2009-11-01

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

  5. Optix: A Monte Carlo scintillation light transport code

    Energy Technology Data Exchange (ETDEWEB)

    Safari, M.J., E-mail: mjsafari@aut.ac.ir [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Afarideh, H. [Department of Energy Engineering and Physics, Amir Kabir University of Technology, PO Box 15875-4413, Tehran (Iran, Islamic Republic of); Ghal-Eh, N. [School of Physics, Damghan University, PO Box 36716-41167, Damghan (Iran, Islamic Republic of); Davani, F. Abbasi [Nuclear Engineering Department, Shahid Beheshti University, PO Box 1983963113, Tehran (Iran, Islamic Republic of)

    2014-02-11

    The paper reports on the capabilities of Monte Carlo scintillation light transport code Optix, which is an extended version of previously introduced code Optics. Optix provides the user a variety of both numerical and graphical outputs with a very simple and user-friendly input structure. A benchmarking strategy has been adopted based on the comparison with experimental results, semi-analytical solutions, and other Monte Carlo simulation codes to verify various aspects of the developed code. Besides, some extensive comparisons have been made against the tracking abilities of general-purpose MCNPX and FLUKA codes. The presented benchmark results for the Optix code exhibit promising agreements. -- Highlights: • Monte Carlo simulation of scintillation light transport in 3D geometry. • Evaluation of angular distribution of detected photons. • Benchmark studies to check the accuracy of Monte Carlo simulations.

  6. Dosimetric measurements and Monte Carlo simulation for achieving ...

    Indian Academy of Sciences (India)

    Research Articles Volume 74 Issue 3 March 2010 pp 457-468 ... Food irradiation; electron accelerator; Monte Carlo; dose uniformity. ... for radiation processing of food and medical products is being commissioned at our centre in Indore, India.

  7. 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

  8. 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

  9. Suppression of the initial transient in Monte Carlo criticality simulations

    International Nuclear Information System (INIS)

    Richet, Y.

    2006-12-01

    Criticality Monte Carlo calculations aim at estimating the effective multiplication factor (k-effective) for a fissile system through iterations simulating neutrons propagation (making a Markov chain). Arbitrary initialization of the neutron population can deeply bias the k-effective estimation, defined as the mean of the k-effective computed at each iteration. A simplified model of this cycle k-effective sequence is built, based on characteristics of industrial criticality Monte Carlo calculations. Statistical tests, inspired by Brownian bridge properties, are designed to discriminate stationarity of the cycle k-effective sequence. The initial detected transient is, then, suppressed in order to improve the estimation of the system k-effective. The different versions of this methodology are detailed and compared, firstly on a plan of numerical tests fitted on criticality Monte Carlo calculations, and, secondly on real criticality calculations. Eventually, the best methodologies observed in these tests are selected and allow to improve industrial Monte Carlo criticality calculations. (author)

  10. Monte Carlo calculations of electron diffusion in materials

    International Nuclear Information System (INIS)

    Schroeder, U.G.

    1976-01-01

    By means of simulated experiments, various transport problems for 10 Mev electrons are investigated. For this purpose, a special Monte-Carlo programme is developed, and with this programme calculations are made for several material arrangements. (orig./LN) [de

  11. A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

    NARCIS (Netherlands)

    MIKOSCH, T; WANG, QA

    We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.

  12. Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)

    2013-07-01

    Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

  13. Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

    International Nuclear Information System (INIS)

    Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.

    2013-01-01

    Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

  14. Calculation of toroidal fusion reactor blankets by Monte Carlo

    International Nuclear Information System (INIS)

    Macdonald, J.L.; Cashwell, E.D.; Everett, C.J.

    1977-01-01

    A brief description of the calculational method is given. The code calculates energy deposition in toroidal geometry, but is a continuous energy Monte Carlo code, treating the reaction cross sections as well as the angular scattering distributions in great detail

  15. 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

  16. Monte Carlo variance reduction approaches for non-Boltzmann tallies

    International Nuclear Information System (INIS)

    Booth, T.E.

    1992-12-01

    Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

  17. 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

  18. Bayesian Optimal Experimental Design Using Multilevel Monte Carlo

    KAUST Repository

    Ben Issaid, Chaouki

    2015-01-01

    informative data about the model parameters. One of the major difficulties in evaluating the expected information gain is that it naturally involves nested integration over a possibly high dimensional domain. We use the Multilevel Monte Carlo (MLMC) method

  19. Studies of Monte Carlo Modelling of Jets at ATLAS

    CERN Document Server

    Kar, Deepak; The ATLAS collaboration

    2017-01-01

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

  20. Herwig: The Evolution of a Monte Carlo Simulation

    CERN Multimedia

    CERN. Geneva

    2015-01-01

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

  1. Clinical considerations of Monte Carlo for electron radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Faddegon, Bruce; Balogh, Judith; Mackenzie, Robert; Scora, Daryl

    1998-01-01

    Technical requirements for Monte Carlo based electron radiotherapy treatment planning are outlined. The targeted overall accuracy for estimate of the delivered dose is the least restrictive of 5% in dose, 5 mm in isodose position. A system based on EGS4 and capable of achieving this accuracy is described. Experience gained in system design and commissioning is summarized. The key obstacle to widespread clinical use of Monte Carlo is lack of clinically acceptable measurement based methodology for accurate commissioning

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-12-14

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

  3. 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

  4. 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.

  5. Study of the Transition Flow Regime using Monte Carlo Methods

    Science.gov (United States)

    Hassan, H. A.

    1999-01-01

    This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.

  6. 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

  7. Dosimetry applications in GATE Monte Carlo toolkit.

    Science.gov (United States)

    Papadimitroulas, Panagiotis

    2017-09-01

    Monte Carlo (MC) simulations are a well-established method for studying physical processes in medical physics. The purpose of this review is to present GATE dosimetry applications on diagnostic and therapeutic simulated protocols. There is a significant need for accurate quantification of the absorbed dose in several specific applications such as preclinical and pediatric studies. GATE is an open-source MC toolkit for simulating imaging, radiotherapy (RT) and dosimetry applications in a user-friendly environment, which is well validated and widely accepted by the scientific community. In RT applications, during treatment planning, it is essential to accurately assess the deposited energy and the absorbed dose per tissue/organ of interest, as well as the local statistical uncertainty. Several types of realistic dosimetric applications are described including: molecular imaging, radio-immunotherapy, radiotherapy and brachytherapy. GATE has been efficiently used in several applications, such as Dose Point Kernels, S-values, Brachytherapy parameters, and has been compared against various MC codes which are considered as standard tools for decades. Furthermore, the presented studies show reliable modeling of particle beams when comparing experimental with simulated data. Examples of different dosimetric protocols are reported for individualized dosimetry and simulations combining imaging and therapy dose monitoring, with the use of modern computational phantoms. Personalization of medical protocols can be achieved by combining GATE MC simulations with anthropomorphic computational models and clinical anatomical data. This is a review study, covering several dosimetric applications of GATE, and the different tools used for modeling realistic clinical acquisitions with accurate dose assessment. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  8. Alternative implementations of the Monte Carlo power method

    International Nuclear Information System (INIS)

    Blomquist, R.N.; Gelbard, E.M.

    2002-01-01

    We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency

  9. Monte Carlo simulations for design of the KFUPM PGNAA facility

    CERN Document Server

    Naqvi, A A; Maslehuddin, M; Kidwai, S

    2003-01-01

    Monte Carlo simulations were carried out to design a 2.8 MeV neutron-based prompt gamma ray neutron activation analysis (PGNAA) setup for elemental analysis of cement samples. The elemental analysis was carried out using prompt gamma rays produced through capture of thermal neutrons in sample nuclei. The basic design of the PGNAA setup consists of a cylindrical cement sample enclosed in a cylindrical high-density polyethylene moderator placed between a neutron source and a gamma ray detector. In these simulations the predominant geometrical parameters of the PGNAA setup were optimized, including moderator size, sample size and shielding of the detector. Using the results of the simulations, an experimental PGNAA setup was then fabricated at the 350 kV Accelerator Laboratory of this University. The design calculations were checked experimentally through thermal neutron flux measurements inside the PGNAA moderator. A test prompt gamma ray spectrum of the PGNAA setup was also acquired from a Portland cement samp...

  10. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2014-01-06

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

  11. 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)

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

    Energy Technology Data Exchange (ETDEWEB)

    Badal, A [U.S. Food and Drug Administration (CDRH/OSEL), Silver Spring, MD (United States); Zbijewski, W [Johns Hopkins University, Baltimore, MD (United States); Bolch, W [University of Florida, Gainesville, FL (United States); Sechopoulos, I [Emory University, Atlanta, GA (United States)

    2014-06-15

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  14. 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

  15. MONTE CARLO SIMULATION OF MULTIFOCAL STOCHASTIC SCANNING SYSTEM

    Directory of Open Access Journals (Sweden)

    LIXIN LIU

    2014-01-01

    Full Text Available Multifocal multiphoton microscopy (MMM has greatly improved the utilization of excitation light and imaging speed due to parallel multiphoton excitation of the samples and simultaneous detection of the signals, which allows it to perform three-dimensional fast fluorescence imaging. Stochastic scanning can provide continuous, uniform and high-speed excitation of the sample, which makes it a suitable scanning scheme for MMM. In this paper, the graphical programming language — LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanners by using white noise signals to control the x and y mirrors independently. Moreover, the stochastic scanning process is simulated by using Monte Carlo method. Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N × N foci array. Therefore, continuous and uniform scanning in the whole field of view is implemented.

  16. Data Analysis Recipes: Using Markov Chain Monte Carlo

    Science.gov (United States)

    Hogg, David W.; Foreman-Mackey, Daniel

    2018-05-01

    Markov Chain Monte Carlo (MCMC) methods for sampling probability density functions (combined with abundant computational resources) have transformed the sciences, especially in performing probabilistic inferences, or fitting models to data. In this primarily pedagogical contribution, we give a brief overview of the most basic MCMC method and some practical advice for the use of MCMC in real inference problems. We give advice on method choice, tuning for performance, methods for initialization, tests of convergence, troubleshooting, and use of the chain output to produce or report parameter estimates with associated uncertainties. We argue that autocorrelation time is the most important test for convergence, as it directly connects to the uncertainty on the sampling estimate of any quantity of interest. We emphasize that sampling is a method for doing integrals; this guides our thinking about how MCMC output is best used. .

  17. Flow in Random Microstructures: a Multilevel Monte Carlo Approach

    KAUST Repository

    Icardi, Matteo

    2016-01-06

    In this work we are interested in the fast estimation of effective parameters of random heterogeneous materials using Multilevel Monte Carlo (MLMC). MLMC is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrisation of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random heterogeneous materials. We make use of the key idea of MLMC, based on different discretization levels, extending it in a more general context, making use of a hierarchy of physical resolution scales, solvers, models and other numerical/geometrical discretisation parameters. Modifications of the classical MLMC estimators are proposed to further reduce variance in cases where analytical convergence rates and asymptotic regimes are not available. Spheres, ellipsoids and general convex-shaped grains are placed randomly in the domain with different placing/packing algorithms and the effective properties of the heterogeneous medium are computed. These are, for example, effective diffusivities, conductivities, and reaction rates. The implementation of the Monte-Carlo estimators, the statistical samples and each single solver is done efficiently in parallel. The method is tested and applied for pore-scale simulations of random sphere packings.

  18. Monte Carlo analysis of Musashi TRIGA mark II reactor core

    International Nuclear Information System (INIS)

    Matsumoto, Tetsuo

    1999-01-01

    The analysis of the TRIGA-II core at the Musashi Institute of Technology Research Reactor (Musashi reactor, 100 kW) was performed by the three-dimensional continuous-energy Monte Carlo code (MCNP4A). Effective multiplication factors (k eff ) for the several fuel-loading patterns including the initial core criticality experiment, the fuel element and control rod reactivity worth as well as the neutron flux measurements were used in the validation process of the physical model and neutron cross section data from the ENDF/B-V evaluation. The calculated k eff overestimated the experimental data by about 1.0%Δk/k for both the initial core and the several fuel-loading arrangements. The calculated reactivity worths of control rod and fuel element agree well the measured ones within the uncertainties. The comparison of neutron flux distribution was consistent with the experimental ones which were measured by activation methods at the sample irradiation tubes. All in all, the agreement between the MCNP predictions and the experimentally determined values is good, which indicated that the Monte Carlo model is enough to simulate the Musashi TRIGA-II reactor core. (author)

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

    International Nuclear Information System (INIS)

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

    1976-06-01

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

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

    Science.gov (United States)

    Kim, Jihan; Smit, Berend

    2012-07-10

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