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This paper introduces a new Monte Carlo algorithm to invert large matrices. It is based on simultaneous coupled draws from two random vectors whose covariance is the required inverse. It can be considered a generalization of a previously…

Data Structures and Algorithms · Computer Science 2025-10-20 L. A. Garcia-Cortes , C. Cabrillo

Implicit Monte Carlo (IMC) and Discrete Diffusion Monte Carlo (DDMC) are methods used to stochastically solve the radiative transport and diffusion equations, respectively. These methods combine into a hybrid transport-diffusion method we…

High Energy Astrophysical Phenomena · Physics 2015-06-22 Ryan T. Wollaeger , Daniel R. van Rossum

We introduce Monte Carlo methods to compute the solution of elliptic equations with pure Neumann boundary conditions. We first prove that the solution obtained by the stochastic representation has a zero mean value with respect to the…

Probability · Mathematics 2013-08-28 Sylvain Maire , Etienne Tanré

This paper develops a computational framework for Multi-Period Martingale Optimal Transport (MMOT), addressing convergence rates, algorithmic efficiency, and financial calibration. Our contributions include: (1) Theoretical analysis: We…

Computational Finance · Quantitative Finance 2026-04-21 Sri Sairam Gautam B

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

In this paper we present a multilevel projection-based iterative scheme for solving thermal radiative transfer problems that performs iteration cycles on the high-order Boltzmann transport equation (BTE) and low-order moment equations.…

Numerical Analysis · Mathematics 2026-03-18 Joseph M. Coale , Dmitriy Y. Anistratov

We present benchmark problems and solutions for the continuum radiative transfer (RT) in a 2D disk configuration. The reliability of three Monte-Carlo and two grid-based codes is tested by comparing their results for a set of well-defined…

Astrophysics · Physics 2009-11-10 I. Pascucci , S. Wolf , J. Steinacker , C. P. Dullemond , Th. Henning , G. Niccolini , P. Woitke , B. Lopez

We introduce a gradient-based learning method to automatically adapt Markov chain Monte Carlo (MCMC) proposal distributions to intractable targets. We define a maximum entropy regularised objective function, referred to as generalised speed…

Machine Learning · Statistics 2020-01-07 Michalis K. Titsias , Petros Dellaportas

We present an implicit collision method with on-the-fly multiplicity adjustment based on the forward weight window methodology for efficient Dynamic Monte Carlo (MC) simulation of reactivity excursion transport problems. Test problems based…

Computational Physics · Physics 2025-01-14 Ilham Variansyah , Ryan G. McClarren , Todd S. Palmer

The Multilevel Monte Carlo method is an efficient variance reduction technique. It uses a sequence of coarse approximations to reduce the computational cost in uncertainty quantification applications. The method is nowadays often considered…

Numerical Analysis · Mathematics 2018-06-15 Pieterjan Robbe , Dirk Nuyens , Stefan Vandewalle

In this paper, we introduce \texttt{SuperLite}, an open-source Monte Carlo radiation transport code designed to produce synthetic spectra for astrophysical transient phenomena affected by circumstellar interaction. \texttt{SuperLite}…

High Energy Astrophysical Phenomena · Physics 2023-08-11 Gururaj A. Wagle , Emmanouil Chatzopoulos , Ryan Wollaeger , Christopher J. Fontes

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

Owing to their favorable scaling with dimensionality, Monte Carlo (MC) methods have become the tool of choice for numerical integration across the quantitative sciences. Almost invariably, efficient MC integration schemes are strictly…

Statistical Mechanics · Physics 2010-01-29 Artur B. Adib

This analysis proposes an analytical-numerical approach for providing solutions of a class of nonlinear fractional Klein-Gordon equation subjected to appropriate initial conditions in Caputo sense by using the Fractional Reduced…

Numerical Analysis · Mathematics 2017-04-25 Eman Abuteen , Asad Freihat , Mohammed Al-Smadi , Hammad Khalil , Rahmat Ali Khan

We propose in this work a Monte Carlo method for three dimensional scalar radiative transfer equations with non-integrable, space-dependent scattering kernels. Such kernels typically account for long-range statistical features, and arise…

Numerical Analysis · Mathematics 2023-07-19 Christophe Gomez , Olivier Pinaud

Fredholm integral equations of the first kind are the prototypical example of ill-posed linear inverse problems. They model, among other things, reconstruction of distorted noisy observations and indirect density estimation and also appear…

Methodology · Statistics 2021-04-26 Francesca R Crucinio , Arnaud Doucet , Adam M Johansen

We propose a novel application of coded computing to the problem of the nearest neighbor estimation using MatDot Codes [Fahim. et.al. 2017], that are known to be optimal for matrix multiplication in terms of recovery threshold under storage…

Information Theory · Computer Science 2018-11-30 Utsav Sheth , Sanghamitra Dutta , Malhar Chaudhari , Haewon Jeong , Yaoqing Yang , Jukka Kohonen , Teemu Roos , Pulkit Grover

A systematic extension of the Monte Carlo (MC) algorithm, that solves the DGLAP equation, into the so-called the one-loop CCFM evolution is presented. Modifications are related to a z-dependent coupling constant; transverse momentum…

High Energy Physics - Phenomenology · Physics 2014-11-18 K. Golec-Biernat , S. Jadach , W. Placzek , P. Stephens , M. Skrzypek

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-21 Emanuele Vitali , Davide Gadioli , Gianluca Palermo , Martin Golasowski , Joao Bispo , Pedro Pinto , Jan Martinovic , Katerina Slaninova , Joao M. P. Cardoso , Cristina Silvano

Classical algorithms in numerical analysis for numerical integration (quadrature/cubature) follow the principle of approximate and integrate: the integrand is approximated by a simple function (e.g. a polynomial), which is then integrated…

Numerical Analysis · Mathematics 2018-06-15 Yuji Nakatsukasa