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We discuss suitable classes of diffusion processes, for which functionals relevant to finance can be computed via Monte Carlo methods. In particular, we construct exact simulation schemes for processes from this class. However, should the…

Numerical Analysis · Mathematics 2012-04-06 Jan Baldeaux , Eckhard Platen

We introduce a Monte-Carlo algorithm for the simulation of charged particles moving in the continuum. Electrostatic interactions are not instantaneous as in conventional approaches, but are mediated by a constrained, diffusing electric…

Soft Condensed Matter · Physics 2009-11-10 Joerg Rottler , A. C. Maggs

The Monte Carlo method is a powerful tool for performing radiative equilibrium calculations, even in complex geometries. The main drawback of the standard Monte Carlo radiative equilibrium methods is that they require iteration, which makes…

Variational quantum algorithms are poised to have significant impact on high-dimensional optimization, with applications in classical combinatorics, quantum chemistry, and condensed matter. Nevertheless, the optimization landscape of these…

Quantum Physics · Physics 2022-02-02 Taylor L. Patti , Omar Shehab , Khadijeh Najafi , Susanne F. Yelin

Diffusion Monte Carlo is one of the most accurate scalable many-body methods for solid state systems. However, to date, spin-orbit interactions have not been incorporated into these calcualtions at a first-principles level; only having been…

Materials Science · Physics 2020-03-04 Yueqing Chang , Lucas K. Wagner

The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. The focus of the paper is on binary-input channels with constraints on the allowed input configurations. The…

Information Theory · Computer Science 2012-12-27 Mehdi Molkaraie , Hans-Andrea Loeliger

Sampling from complicated probability distributions is a hard computational problem arising in many fields, including statistical physics, optimization, and machine learning. Quantum computers have recently been used to sample from…

Diffuse scattering is a rich source of information about disorder in crystalline materials, which can be modelled using atomistic techniques such as Monte Carlo and molecular dynamics simulations. Modern X-ray and neutron scattering…

Materials Science · Physics 2018-12-21 Joseph A. M. Paddison

We discuss the theoretical approach and practical algorithms for simulation of radiative events in elastic ep-scattering. A new Monte Carlo generator for real photon emission events in the process of elastic electron-proton scattering is…

High Energy Physics - Phenomenology · Physics 2008-11-26 A. V. Afanasev , I. Akushevich , A. Ilyichev , B. Niczyporuk

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

Scattering, especially multiple scattering, is a well known problem in imaging, ranging from astronomy to medicine. In particular it is often desirable to be able to perform non-invasive imaging through turbid and/or opaque media. Many…

Optics · Physics 2024-04-23 Harry Penketh , Jacopo Bertolotti

We propose a Monte Carlo algorithm to sample from high dimensional probability distributions that combines Markov chain Monte Carlo and importance sampling. We provide a careful theoretical analysis, including guarantees on robustness to…

Computation · Statistics 2019-09-18 Giacomo Zanella , Gareth Roberts

How to turn the flip of a coin into a random variable whose expected value equals a scattering amplitude? We answer this question by constructing a numerical algorithm to evaluate curve integrals - a novel formulation of scattering…

High Energy Physics - Theory · Physics 2025-03-12 Giulio Salvatori

It is demonstrated that non-constant kernel solution, that can fit the spatial variations of the kernel can be obtained with minimum computing time. The CPU cost required with this new extension of the image subtraction method is almost the…

Astrophysics · Physics 2007-05-23 C. Alard

We present an optical picture of linear-optics superradiance, based on a single scattering event embedded in a dispersive effective medium composed by the other atoms. This linear-dispersion theory is valid at low density and in the…

Atomic Physics · Physics 2021-02-05 P. Weiss , A. Cipris , R. Kaiser , I. M. Sokolov , W. Guerin

Monte Carlo methods are widely used importance sampling techniques for studying complex physical systems. Integrating these methods with deep learning has significantly improved efficiency and accuracy in high-dimensional problems and…

Disordered Systems and Neural Networks · Physics 2024-12-24 Yixiong Ren , Jianhui Zhou

One of the methods for studying the highest energy cosmic rays is to measure the fluorescence light emitted by the extensive air showers induced by them. To reconstruct a shower cascade curve from measurements of the number of photons…

High Energy Astrophysical Phenomena · Physics 2015-06-03 Maria Giller , Andrzej Smialkowski

We implement a Monte Carlo radiative transfer method, that uses a large number of monochromatic luminosity packets to represent the radiation transported through a system. These packets are injected into the system and interact…

Astrophysics · Physics 2009-11-10 D. Stamatellos , A. P. Whitworth

This paper presents high-order integral equation methods for evaluation of electromagnetic wave scattering by dielectric bumps and dielectric cavities on perfectly conducting or dielectric half-planes. In detail, the algorithms introduced…

Computational Physics · Physics 2015-06-19 Carlos Pérez-Arancibia , Oscar P. Bruno

Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dimensional integrals. However, traditional Monte Carlo methods…

Quantum Physics · Physics 2025-10-14 Heechan Yi , Kayoung Ban , Myeonghun Park , Kyoungchul Kong
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