Monte Carlo Study of the abBA Experiment: Detector Response and Physics Analysis

The abBA collaboration proposes to conduct a comprehensive program of precise measurements of neutron β-decay coefficients a (the correlation between the neutrino momentum and the decay electron momentum), b (the electron energy spectral distortion term), A (the correlation between the neutron spin and the decay electron momentum), and B (the correlation between the neutron spin and the decay neutrino momentum) at a cold neutron beam facility. We have used a GEANT4-based code to simulate the propagation of decay electrons and protons in the electromagnetic spectrometer and study the energy and timing response of a pair of Silicon detectors. We used these results to examine systematic effects and find the uncertainties with which the physics parameters a, b, A, and B can be extracted from an over-determined experimental data set.     

Validation by Monte Carlo sampling of experimental observation functionals

We present and analyze a validation procedure for a given state estimate u ^? of the true field u ^true based on Monte Carlo sampling of experimental observation functionals. Our method provides, given a set of N possibly noisy local experimental observation functionals over the spatial domain Ω, confidence intervals for the L ²(Ω) error in state and the error in L ²(Ω) outputs. For L ²(Ω) outputs, our approach also provides a confidence interval for the output itself, which can be used to improve the initial output estimate based on u ^?. Our approach implicitly takes advantage of variance reduction, through the proximity of u ^? to u ^true, to provide tight confidence intervals even for modest values of N . We present results for a synthetic model problem to illustrate the elements of the methodology and confirm the numerical properties suggested by the theory. Finally, we consider an experimental thermal patch configuration to demonstrate the applicability of our approach to real physical systems.     

基于Monte Carlo法的结构动力学模型确认

提出一种蒙特卡洛模拟(MCS)与多元回归分析相结合的有限元模型确认方法。采用基于动态响应面法生成的代理模型改进直接MCS,用一种逐步迭代的方式改进代理模型保证模型确认的精度。传统欧氏距离/马氏距离从不同方面描述了两点间距离,然而如果在距离准则中能够同时考虑两者则会更全面。在相关性分析过程中,综合欧氏/马氏距离的特点,采用了一种欧氏/马氏距离相结合的不确定量化方法(距离判别方法),并给出了基于此指标的迭代收敛判断准则。算例仿真结果表明:所提出的有限元模型确认方法和此距离判别方法的使用,能比较大地降低MCS的计算量并能得到满意的模型确认结果,迭代收敛的稳定性和精度都有了提高。     

圆柱型空腔电离室修正系数的Monte Carlo模拟与实验验证

采用标称体积为10 cm~3圆柱型空腔电离室对Cs-137空气比释动能进行绝对测量。使用Monte Carlo模拟计算和实验两种方法对电离室壁修正因子k_w和轴向不均匀修正因子k_(an)进行对比研究。结果显示,使用等效壁厚的实验外推法确定的k_w值比MC计算得到的值小0.1%,实验方法确定的k_(an)值比MC计算得到的值小0.63%。两种方法相互印证,给出的修正系数值之间的误差可以接受,由于重复实验不可避免将引入其他误差因素,且MC计算方法简便可重复性高,最终选取MC计算结果为k_w、k_(an)确定值。     

Program FAKE: Monte Carlo Event Generators as Tools of Theory in Early High Energy Physics

The term Monte Carlo method indicates any computer-aided procedure for numerical estimation that combines mathematical calculations with randomly generated numerical input values. Today it is an important tool in high energy physics while physicists and philosophers also often consider it a sort of virtual experiment. The Monte Carlo method was developed in the 1940s, in the context of U.S. American nuclear weapons research, an event often regarded as the origin of both computer simulation and “artificial reality” (Galison 1997). The present paper interrogates this strong claim by focusing on the emergence of Monte Carlo event generators in particle physics in the early 1960s. This historical case study shows how, as Monte Carlo computation became part of the toolbox of particle physicists around 1960, it was neither usually referred to as a “computer simulation” nor was it regarded as a surrogate for experimentation. In revising the history of this method, this paper asks, in what context did particle physicists of the 1960s decide to create FAKE, the first high-energy-physics Monte Carlo event simulator? What was their goal? And what epistemic role did FAKE play? In answering these questions, it is argued that Monte Carlo computations were not introduced into particle physics to simulate experiments, but rather they played the role of theoretical tools. The Monte Carlo method was able to do this thanks to its random component, a property which provided a means of modeling a specific phenomenon, so-called “(particle) resonances”. Indeed, in doing so, event generators even came to mutually assimilate and reshape the notions of particle and resonance, taking up an epistemic function which had previously been confined to physical-mathematical formulae: that of a medium which could express aspects of particle theory.

     

Monte Carlo simulations in zeolites

In this short review, the applications of Monte Carlo simulations to the study of the adsorption and diffusion of hydrocarbons in zeolites are discussed. We focus on those systems for which the conventional molecular simulation techniques, molecular dynamics and Monte Carlo, are not sufficiently efficient. In particular, to simulate the adsorption and diffusion of long-chain hydrocarbons, novel Monte Carlo techniques have been developed. Here we discuss configurational-bias Monte Carlo (CBMC) and kinetic Monte Carlo (KMC). CBMC was developed to compute the thermodynamic properties. KMC is applied to compute transport properties. The use of these methods is illustrated with examples of technological importance.     

Diffusion Monte Carlo in Continuous Time

A detailed outline of a diffusion Monte Carlo algorithm for lattice models is given. The method which relies on evolving wave functions in imaginary time using the operator e^−Hτ is free of time step errors.It is applied to two models: 1) A lattice boson Hubbard model where the bosons carry an internal spin-1 degree of freedom, and 2) The quantum dimer model on the square lattice. In the latter deconfinement of monomers is demonstrated for monomer hopping strengths exceeding a critical value.PACS numbers: 74.20.Mn, 75.10.Jm, 02.70.Ss     

Biasing the transition probabilities in direct Monte Carlo

The mathematical scheme of the biased direct Monte Carlo method is presented in detail and compared with the corresponding biased analogues Monte Carlo method. With reference to the inhomogeneous Poisson processes, an example in the reliability and safety engineering field is given. This refers to sampling from a three-mode Weibull distribution by forcing each of the three modes to be exponential with decay constants 10 times larger than the natural ones. Since the natural distribution under analysis shows a rather uniform behaviour over most of the range of interest, biasing to a uniform distribution has also been investigated. Both examples are shown to lead to a simplification in the sampling procedure and an improvement in the computational efficiency.     

Monte Carlo calculations of quasidiffusion in silicon

Monte Carlo study of high-energy phonon propagation with elastic scattering and frequency down-conversion is reported. Experimentally observed exponential decay of phonon intensity at late arrival times is well reproduced. The phonon focusing is crucial for accounting for the overall shape of the observed phonon spectrum.     

Monte Carlo unfolding of pulse-height spectra

A Monte Carlo unfolding method is developed for the unfolding of pulse-height spectra. The method utilizes linear programming to know the range where solutions are allowed to exist. Then the distribution of a possible solution family is evaluated by Monte Carlo process by starting from a flat distribution. The obtained distribution is used to evaluate a new distribution. The process is repeated till a converging distribution is obtained.The proposed method is tested through unfolding of synthesized spectra. The spectra unfolded by the Monte Carlo method are smooth in shape. In all the test runs, the method well reproduces the real spectra even with errors introduced in a random manner in both the pulse-height data and the response matrix.     

Monte Carlo study of the atmospheric spread function

Monte Carlo radiative transfer simulations are used to study the atmospheric spread function appropriate to satellite-based sensing of the earth's surface. The parameters which are explored include the nadir angle of view, the size distribution of the atmospheric aerosol, and the aerosol vertical profile.     

A Monte Carlo formulation of the Bogolubov theory

Abstract

We propose an efficient stochastic method to implement numerically the Bogolubov approach to study finite-temperature Bose-Einstein condensates. Our method is based on the Wigner representation of the density matrix describing the non-condensed modes and a Brownian motion simulation to sample the Wigner distribution at thermal equilibrium. Allowing it to sample any density operator Gaussian in the field variables, our method is very general and it applies both to the Bogolubov and to the Hartree-Fock Bogolubov approach, in the equilibrium case as well as in the time-dependent case. We think that our method can be useful to study trapped Bose-Einstein condensates in two or three spatial dimensions without rotational symmetry properties, as in the case of condensates with vortices, where the traditional Bogolubov approach is difficult to implement numerically due to the need to diagonalize very big matrices.     

失配误差的蒙特卡洛分析

针对极限相位法评定失配误差引入的测量不确定度普遍偏大的问题,提出了采用蒙特卡洛法对其评定的新方法。以交替比较法校准功率座为实例,研究了蒙特卡洛法评定失配误差引入的测量不确定度的具体实现方法,并将其得到的结果与极限相位法进行比较。结果表明,蒙特卡洛法更适合用于失配误差引入的测量不确定度进行评定。     

Monte Carlo model of nonlinear chromatography

A stochastic approach to the nonlinear chromatography theory, based on the Monte Carlo simulation method, is presented. A computer program, acting as a "virtual chromatograph" and performing a discrete event simulation, is described. Such a program allows one to choose the column type, operating conditions, sample composition, injection method, mobile-phase dispersion model, and stationary-phase sorption-desorption kinetics. Nonlinearity is accounted for by continuously monitoring and updating both the column and the solute status and by moving individual molecules step by step along the column according to specific random modes. The program has been validated through a series of statistical tests and comparing the results with the well-known achievements of the classical stochastic theory. A first application is presented, referred to a real case benzene elution on a gas solid capillary column, where the Langmuir adsorption isotherm is assumed. The effect of both the sorption modes and the site capacity are investigated. Possible applications to investigate open problems in several fields of separation science are emphasized. In addition, several specific points such as the down-scaling of a real case and the correspondence of specific adsorption dynamics with the equilibrium Langmuir isotherm are described.     

Uncertainties beyond statistics in Monte Carlo simulations

The Monte Carlo method has become an essential tool for the simulation of radiation and particle transport problems. The combination of its ease of use and the power of the method can create a temptation to use Monte Carlo as a 'black box' tool. In this paper, we shall mention a number of important issues that any user of a Monte Carlo computer code should keep firmly in mind when attempting a transport simulation, and we shall present a recent practical example to show the potential significance of such issues.