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Related papers: Quasi-Monte Carlo Radiative Transfer

200 papers

We describe an embarrassingly parallel, anytime Monte Carlo method for likelihood-free models. The algorithm starts with the view that the stochasticity of the pseudo-samples generated by the simulator can be controlled externally by a…

Machine Learning · Computer Science 2015-12-03 Edward Meeds , Max Welling

We propose numerical integration methods for Choquet integrals where the capacities are given by distortion functions of an underlying probability measure. It relies on the explicit representation of the integrals for step functions and can…

Numerical Analysis · Mathematics 2015-02-17 Yumiharu Nakano

We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated non-local…

Computational Physics · Physics 2015-06-15 N. S. Blunt , T. W. Rogers , J. S. Spencer , W. M. C. Foulkes

Quasi-Monte Carlo (qMC) methods are a powerful alternative to classical Monte-Carlo (MC) integration. Under certain conditions, they can approximate the desired integral at a faster rate than the usual Central Limit Theorem, resulting in…

Econometrics · Economics 2019-11-22 Jean-Jacques Forneron

In this project we initiate an investigation of the applicability of Quasi-Monte Carlo methods to lattice field theories in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an…

High Energy Physics - Lattice · Physics 2015-06-12 K. Jansen , H. Leovey , A. Nube , A. Griewank , M. Mueller-Preussker

We derive and study SQMC (Sequential Quasi-Monte Carlo), a class of algorithms obtained by introducing QMC point sets in particle filtering. SQMC is related to, and may be seen as an extension of, the array-RQMC algorithm of L'Ecuyer et al.…

Computation · Statistics 2014-12-01 Mathieu Gerber , Nicolas Chopin

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix

In this paper we analyze and compare the use of Monte Carlo, Quasi-Monte Carlo and hybrid Monte Carlo-methods in the credit risk management system Credit Metrics by J.P.Morgan. We show that hybrid sequences used for simulations, in a…

Numerical Analysis · Mathematics 2014-05-09 Lucia Del Chicca , Gerhard Larcher

We implemented a fast Reciprocal Monte Carlo algorithm, to accurately solve radiative heat transfer in turbulent flows of non-grey participating media that can be coupled to fully resolved turbulent flows, namely to Direct Numerical…

Computational Engineering, Finance, and Science · Computer Science 2019-05-21 Simone Silvestri , Rene Pecnik

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 describe a general radiative equilibrium and temperature correction procedure for use in Monte Carlo radiation transfer codes with sources of temperature-independent opacity, such as astrophysical dust. The technique utilizes the fact…

Astrophysics · Physics 2010-04-08 J. E. Bjorkman , Kenneth Wood

This article provides an overview of some interfaces between the theory of quasi-Monte Carlo (QMC) methods and applications. We summarize three QMC theoretical settings: first order QMC methods in the unit cube $[0,1]^s$ and in…

Numerical Analysis · Mathematics 2017-10-30 Frances Y. Kuo , Dirk Nuyens

An empirical numerical model that includes nuclear absorption, multiple Coulomb scattering, and energy loss is presented in this work to calculate the transmission of the thick objects in high energy proton radiography, and in this…

Instrumentation and Detectors · Physics 2014-10-16 Zheng Na , Xu Hai-bo

Monte Carlo and Quasi-Monte Carlo methods present a convenient approach for approximating the expected value of a random variable. Algorithms exist to adaptively sample the random variable until a user defined absolute error tolerance is…

Numerical Analysis · Mathematics 2023-11-14 Aleksei G. Sorokin , Jagadeeswaran Rathinavel

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…

Sequential Monte Carlo algorithms (also known as particle filters) are popular methods to approximate filtering (and related) distributions of state-space models. However, they converge at the slow $1/\sqrt{N}$ rate, which may be an issue…

Computation · Statistics 2015-03-06 Nicolas Chopin , Mathieu Gerber

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over…

High Energy Physics - Lattice · Physics 2013-11-20 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leovey , Andreas Griewank , Micheal Müller-Preussker

We present a set of new numerical methods that are relevant to calculating radiation pressure terms in hydrodynamics calculations, with a particular focus on massive star formation. The radiation force is determined from a Monte Carlo…

Solar and Stellar Astrophysics · Physics 2015-06-23 Tim J. Harries

A simple Monte Carlo procedure is described for simulating the multiple scattering and absorption of electrons with the incident energy in the range 1-50 keV moving through a slab of uniformly distributed material of given atomic number,…

Materials Science · Physics 2007-05-23 Nima Ghal-eh , Mohammad Farhad Rahimi , Mehrnoush Manouchehri

Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. These methods have found numerous applications in…

Computation · Statistics 2021-06-23 Jeremy Heng , Adrian N. Bishop , George Deligiannidis , Arnaud Doucet
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