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Equality-constrained models naturally arise in problems in which measurements are taken at different levels of resolution. The challenge in this setting is that the models usually induce a joint distribution which is intractable. Resorting…

Computation · Statistics 2025-04-28 Shenggang Hu , Hongsheng Dai , Fanlin Meng , Louis Aslett , Murray Pollock , Gareth O. Roberts

We study random compressible viscous magnetohydrodynamic flows. Combining the Monte Carlo method with a deterministic finite volume method we solve the random system numerically. Quantitative error estimates including statistical and…

Numerical Analysis · Mathematics 2024-10-24 Eduard Feireisl , Maria Lukacova-Medvidova , Bangwei She , Yuhuan Yuan

Distortion risk measures play a critical role in quantifying risks associated with uncertain outcomes. Accurately estimating these risk measures in the context of computationally expensive simulation models that lack analytical tractability…

Risk Management · Quantitative Finance 2025-08-29 Sören Bettels , Stefan Weber

In previous publications, we have presented an alternative approach to determine essential detector properties like the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS) and the Detective Quantum Efficiency (DQE) based on a…

Medical Physics · Physics 2024-08-15 Karl Stierstorfer , Martin Hupfer

We review the method of stochastic error correction which eliminates the truncation error associated with any subspace diagonalization. Monte Carlo sampling is used to compute the contribution of the remaining basis vectors not included in…

High Energy Physics - Lattice · Physics 2009-10-31 Dean Lee

Monte Carlo radiative transfer, which has been demonstrated as a successful algorithm for modeling radiation transport through the astrophysical medium, relies on sampling of scattering phase functions. We review several classic sampling…

Computational Physics · Physics 2019-09-18 Jianing Zhang

We propose a Monte Carlo sampler from the reverse diffusion process. Unlike the practice of diffusion models, where the intermediary updates -- the score functions -- are learned with a neural network, we transform the score matching…

Machine Learning · Statistics 2024-03-14 Xunpeng Huang , Hanze Dong , Yifan Hao , Yi-An Ma , Tong Zhang

A Monte Carlo simulation has been performed to track light rays in cylindrical fibres by ray optics. The trapping efficiencies for skew and meridional rays in active fibres and distributions of characteristic quantities for all trapped…

Optics · Physics 2009-11-07 C. P. Achenbach , J. H. Cobb

In this work we report on the Monte Carlo study performed to understand and reproduce experimental measurements of a new plastic \b{eta}-detector with cylindrical geometry. Since energy deposition simulations differ from the experimental…

Adjoint methods form a class of importance sampling methods that are used to accelerate Monte Carlo (MC) simulations of transport equations. Ideally, adjoint methods allow for zero-variance MC estimators provided that the solution to an…

Mathematical Physics · Physics 2015-03-19 Guillaume Bal , Ian Langmore

In this work we present a novel 3D Monte Carlo photon transport program for simulation of multiple refractive scattering based on the refractive properties of X-rays in highly scattering media, like lung tissue. Multiple scattering reduces…

Medical Physics · Physics 2010-02-03 A. N. Khromova , L. Rigon , F. Arfelli , R. H. Menk , H. J. Besch , H. Plothow-Besch

We consider the scattering of neutrons and photons on solid volume rectangular targets. It is common to treat this problem using the Maxwell Boltzmann Transport Equation and to use underlying symmetries to simplify the calculation. For…

Computational Physics · Physics 2017-12-27 Eric V. Steinfelds , Keith Andrew

A Monte Carlo program based on a three dimensional vector approach was developed to model multiple refractive scattering of X-ray photons in objects with a fine structure. A particular interest was paid to the investigation of lung tissue.…

Medical Physics · Physics 2010-02-02 Anastasiya Khromova

The following electromagnetism (EM) inverse problem is addressed. It consists in estimating local radioelectric properties of materials recovering an object from global EM scattering measurements, at various incidences and wave frequencies.…

Applications · Statistics 2015-06-12 François Giraud , Pierre Minvielle , Pierre Del Moral

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

Using Monte Carlo method we study a two-dimensional model with infinitely many absorbing states. Our estimation of the critical exponent beta=0.273(5) suggests that the model belongs to the (1+1) rather than (2+1) directed-percolation…

Statistical Mechanics · Physics 2009-10-31 Adam Lipowski

We study cluster perturbation theory [Phys. Rev. Lett. \textbf{84}, 522 (2000)] when auxiliary field quantum Monte Carlo method is used for solving the cluster hamiltonian. As a case study, we calculate the spectral functions of the Hubbard…

Strongly Correlated Electrons · Physics 2007-05-23 Fei Lin , Erik S. Sorensen , Catherine Kallin , A. John Berlinsky

The implementation and reliability of a quadratic diffusion Monte Carlo method for the study of ground-state properties of atoms are discussed. We show in the simple yet non-trivial calculation of the binding energy of the Li atom that the…

Condensed Matter · Physics 2009-11-07 A. Sarsa , J. Boronat , J. Casulleras

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

We study time harmonic acoustic scattering on large deviation rough random scatterers. Therein, the roughness of the scatterers is caused by a low Sobolev regularity in the covariance function of their deformation field. The motivation for…

Numerical Analysis · Mathematics 2023-11-22 Jürgen Dölz , Wei Huang , Michael Multerer