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The standard Kernel Quadrature method for numerical integration with random point sets (also called Bayesian Monte Carlo) is known to converge in root mean square error at a rate determined by the ratio $s/d$, where $s$ and $d$ encode the…

Machine Learning · Statistics 2017-08-01 Francois-Xavier Briol , Chris J. Oates , Jon Cockayne , Wilson Ye Chen , Mark Girolami

In this work we present a theoretical study on the propagation of light in heterogeneous systems with fluctuating optical properties. To understand the consequences of the fluctuations we perform numerical calculations with uniform and non…

Optics · Physics 2015-07-07 Emiliano Terán-Bobadilla , Eugenio Méndez

The Monte Carlo algorithm is increasingly utilized, with its central step involving computer-based random sampling from stochastic models. While both Markov Chain Monte Carlo (MCMC) and Reject Monte Carlo serve as sampling methods, the…

Computation · Statistics 2024-02-28 Fengyu Li , Huijiao Yu , Jun Yan , Xianyong Meng

A lattice gas model of adsorption inside cylindrical pores is evaluated with Monte Carlo simulations. The model incorporates two kinds of site: (a line of) ``axial'' sites and surrounding ``cylindrical shell'' sites, in ratio 1:7. The…

Statistical Mechanics · Physics 2009-11-10 Raluca A. Trasca , M. Mercedes Calbi , Milton W. Cole , Jose L. Riccardo

We present a Monte Carlo rendering framework for the physically-accurate simulation of speckle patterns arising from volumetric scattering of coherent waves. These noise-like patterns are characterized by strong statistical properties, such…

Optics · Physics 2019-01-23 Chen Bar , Marina Alterman , Ioannis Gkioulekas , Anat Levin

In this work, we develop a novel Monte Carlo method for solving the electromagnetic scattering problem. The method is based on a formal solution of the scattering problem as a modified Born series whose coefficients are found by a conformal…

Computational Physics · Physics 2022-05-25 Hector Lopez-Menchon , Juan M. Rius , Alexander Heldring , Eduard Ubeda

We demonstrate that the effects of matter upon neutrino propagation may be recast as the scattering of the initial neutrino wavefunction. Exchanging the differential, Schrodinger equation for an integral equation for the scattering matrix S…

High Energy Physics - Phenomenology · Physics 2009-11-11 James P. Kneller , Gail C. McLaughlin

We investigate the properties of a sequential Monte Carlo method where the particle weight that appears in the algorithm is estimated by a positive, unbiased estimator. We present broadly-applicable convergence results, including a central…

Methodology · Statistics 2022-08-26 Paul B. Rohrbach , Robert L. Jack

Two different Reverse Monte Carlo strategies, 'RMC++' and 'RMCPOW', have been compared for determining the microscopic structure of some liquid and amorphous solid systems on the basis of neutron diffraction measurements. The first, '$g(r)$…

Soft Condensed Matter · Physics 2015-01-27 V. Sánchez-Gil , E. G. Noya , L. Temleitner , L. Pusztai

Recently, a Monte Carlo method has been presented which allows for the form-free retrieval of size distributions from isotropic scattering patterns, complete with uncertainty estimates linked to the data quality. Here, we present an…

Data Analysis, Statistics and Probability · Physics 2013-03-13 Brian R. Pauw , Masato Ohnuma , Kenji Sakurai , Enno A. Klop

Recursive Monte Carlo filters, also called particle filters, are a powerful tool to perform computations in general state space models. We discuss and compare the accept--reject version with the more common sampling importance resampling…

Statistics Theory · Mathematics 2007-06-13 Hans R. Künsch

We discuss multivariate Monte Carlo methods appropriate for X-ray dispersive spectrometers. Dispersive spectrometers have many advantages for high resolution spectroscopy in the X-ray band. Analysis of data from these instruments is…

Astrophysics · Physics 2007-05-23 J. R. Peterson , J. G. Jernigan , S. M. Kahn

We describe Monte Carlo methods for estimating lower envelopes of expectations of real random variables. We prove that the estimation bias is negative and that its absolute value shrinks with increasing sample size. We discuss fairly…

Probability · Mathematics 2019-09-02 Arne Decadt , Gert de Cooman , Jasper De Bock

Magneto-Optical Traps have been used for several decades. Among fundamental mechanisms occuring in such traps, the magnitude of the multiple scattering is still unclear. Indeed, many experimental situations cannot be modeled easily,…

Atomic Physics · Physics 2014-06-11 Rudy Romain , Hélène Louis , Philippe Verkerk , Daniel Hennequin

Opaque scintillators are designed to have a short scattering length such that scintillation photons are probabilistically confined to a small region of space about their origin. The benefit of this feature is that information on the…

Instrumentation and Detectors · Physics 2023-02-10 Andrew Wilhelm , Garrett Wendel , Brandon Collins , Doug Cowen , Igor Jovanovic

A new method, based on the simulated annealing algorithm and aimed at the inverse problem in the analysis of intergalactic (interstellar) complex spectra of hydrogen and metal lines, is presented. We consider the process of line formation…

Astrophysics · Physics 2007-05-23 Sergei A. Levshakov , Irina I. Agafonova , Wilhelm H. Kegel

We modify the reweighting factor of the projector used in diffusion Monte Carlo to reduce the time-step error of the total energy. Further, we present a reweighting scheme that has the desirable feature that it is exactly size-consistent,…

Chemical Physics · Physics 2024-03-18 Tyler A. Anderson , Manolo C. Per , C. J. Umrigar

Monte Carlo methods play important part in modern statistical physics. The application of these methods suffer from two main difficulties.The first is caused by the relatively small number of particles that can participate in any numerical…

Statistical Mechanics · Physics 2007-05-23 A. Brandt , V. Ilyin

The Short-Time approximation is a method introduced to evaluate electroweak nuclear response for systems with $A\geq12$, extending the reach of first-principle many-body Quantum Monte Carlo calculations. Using realistic two- and three-body…

Inverse rendering methods have achieved remarkable performance in reconstructing high-fidelity 3D objects with disentangled geometries, materials, and environmental light. However, they still face huge challenges in reflective surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Tengjie Zhu , Zhuo Chen , Jingnan Gao , Yichao Yan , Xiaokang Yang