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Related papers: Quasi-Monte Carlo Radiative Transfer

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We discuss the efficiency of Monte Carlo methods in solving continuum radiative transfer problems. The sampling of the radiation field and convergence of dust temperature calculations in the case of optically thick clouds are both studied.…

Astrophysics · Physics 2009-11-10 M. Juvela

A Monte Carlo model of radiative transfer in multi-phase dusty media is applied to the situation of stars and clumpy dust in a sphere or a disk. The distribution of escaping and absorbed photons are shown for various filling factors and…

Astrophysics · Physics 2007-05-23 Frank Varosi , Eli Dwek

Quasi-Monte Carlo methods have proven to be effective extensions of traditional Monte Carlo methods in, amongst others, problems of quadrature and the sample path simulation of stochastic differential equations. By replacing the random…

Quantitative Methods · Quantitative Biology 2019-12-12 Casper H. L. Beentjes , Ruth E. Baker

We present the DIRTY radiative transfer model in this paper and a companion paper. This model computes the polarized radiative transfer of photons from arbitrary distributions of stars through arbitrary distributions of dust using Monte…

Astrophysics · Physics 2009-10-31 Karl D. Gordon , K. A. Misselt , Adolf N. Witt , Geoffrey C. Clayton

In a random ray method of neutral particle transport simulation, each iteration begins by sampling a set of rays before proceeding to solve the characteristic transport equation along the linear paths the rays follow. Historically,…

Computational Physics · Physics 2025-01-13 Samuel Pasmann , John Tramm

Quasi-Monte Carlo methods have become the industry standard in computer graphics. For that purpose, efficient algorithms for low discrepancy sequences are discussed. In addition, numerical pitfalls encountered in practice are revealed. We…

Graphics · Computer Science 2023-07-31 Alexander Keller , Carsten Wächter , Nikolaus Binder

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…

Radiative transfer simulation is an important tool that allows us to generate synthetic images of various astrophysical objects. In the case of complex three-dimensional geometries, a Monte Carlo-based method that simulates photon packages…

Instrumentation and Methods for Astrophysics · Physics 2021-01-27 A. Krieger , S. Wolf

Computer simulations of photon transport through an absorbing and/or scattering medium form an important research tool in astrophysics. Nearly all software codes performing such simulations for three-dimensional geometries employ the Monte…

Instrumentation and Methods for Astrophysics · Physics 2018-07-25 Peter Camps , Maarten Baes

We study signal processing tasks in which the signal is mapped via some generalized time-frequency transform to a higher dimensional time-frequency space, processed there, and synthesized to an output signal. We show how to approximate such…

Numerical Analysis · Mathematics 2021-09-07 Ron Levie , Haim Avron , Gitta Kutyniok

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

While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the abscence of a reliable way to estimate that error.…

High Energy Physics - Phenomenology · Physics 2009-11-11 R. H. Kleiss , A. Lazopoulos

A revised and greatly improved version of the 3D continuum radiative transfer code MC3D is presented. It is based on the Monte-Carlo method and solves the radiative transfer problem self-consistently. It is designed for the simulation of…

Astrophysics · Physics 2009-11-07 Sebastian Wolf

We introduce the Quantization Monte Carlo method to solve thermal radiative transport equations with possibly several collision regimes, ranging from few collisions to massive number of collisions per time unit. For each particle in a given…

Computational Physics · Physics 2024-09-13 Laetitia Laguzet , Gabriel Turinici

Thermal dust emission carries information on physical conditions and dust properties in many astronomical sources. Because observations represent a sum of emission along the line of sight, their interpretation often requires radiative…

Instrumentation and Methods for Astrophysics · Physics 2019-02-06 M. Juvela

We present a numerical method and computer code to calculate the radiative transfer and excitation of molecular lines. Formulating the Monte Carlo method from the viewpoint of cells rather than photons allows us to separate local and…

Astrophysics · Physics 2007-05-23 Michiel R. Hogerheijde , Floris F. S. van der Tak

Radiative transfer describes the propagation of electromagnetic radiation through an interacting medium. This process is often simulated by the use of the Monte Carlo method, which involves the probabilistic determination and tracking of…

Instrumentation and Methods for Astrophysics · Physics 2020-03-31 A. Krieger , S. Wolf

Aims. We present an implementation of an algorithm for 3D time-dependent Monte Carlo radiative transfer. It allows one to simulate temperature distributions as well as images and spectral energy distributions of the scattered light and…

Instrumentation and Methods for Astrophysics · Physics 2022-12-14 A. Bensberg , S. Wolf

Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for…

Many machine learning problems involve Monte Carlo gradient estimators. As a prominent example, we focus on Monte Carlo variational inference (MCVI) in this paper. The performance of MCVI crucially depends on the variance of its stochastic…

Machine Learning · Statistics 2018-07-05 Alexander Buchholz , Florian Wenzel , Stephan Mandt
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