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Related papers: Modeling Cosmic-Ray Transport: A CRPropa based sto…

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Stochastic difference equations and a stochastic partial differential equation (SPDE) are simultaneously derived for the time-dependent neutron angular density in a general three-dimensional medium where the neutron angular density is a…

Numerical Analysis · Mathematics 2010-04-16 Edward J. Allen

We propose algorithms for solving convective-diffusion partial differential equations (PDEs), which model surfactant concentration and heat transport on evolving surfaces, based on intrinsic kernel-based meshless collocation methods. The…

Numerical Analysis · Mathematics 2023-12-14 Meng Chen , Leevan Ling

We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms…

Numerical Analysis · Mathematics 2024-06-04 Leticia Mattos Da Silva , Oded Stein , Justin Solomon

In this paper we present the theoretical framework needed to justify the use of a kernel-based collocation method (meshfree approximation method) to estimate the solution of high-dimensional stochastic partial differential equations…

Numerical Analysis · Mathematics 2012-09-11 Igor Cialenco , Gregory E. Fasshauer , Qi Ye

Cosmic ray transport on galactic scales depends on the detailed properties of the magnetized, multiphase interstellar medium (ISM). In this work, we post-process a high-resolution TIGRESS magnetohydrodynamic simulation modeling a local…

High Energy Astrophysical Phenomena · Physics 2021-11-24 Lucia Armillotta , Eve C. Ostriker , Yan-Fei Jiang

Reaction-diffusion equations (RDEs) are often derived as continuum limits of lattice-based discrete models. Recently, a discrete model which allows the rates of movement, proliferation and death to depend upon whether the agents are…

Dynamical Systems · Mathematics 2021-05-19 Yifei Li , Peter van Heijster , Matthew J. Simpson , Martin Wechselberger

The combination of Monte Carlo methods and deep learning has recently led to efficient algorithms for solving partial differential equations (PDEs) in high dimensions. Related learning problems are often stated as variational formulations…

Machine Learning · Computer Science 2022-08-08 Lorenz Richter , Julius Berner

The problems of high linear conductivity in an electric field, as well as nonlinear conductivity, are considered for plasma-like systems. First, we recall several observations of nonlinear fast charge transport in dusty plasma, molecular…

Plasma Physics · Physics 2015-06-23 S. A. Trigger , W. Ebeling , G. J. F. van Heijst , D. Litinski

We present a framework and algorithms to learn controlled dynamics models using neural stochastic differential equations (SDEs) -- SDEs whose drift and diffusion terms are both parametrized by neural networks. We construct the drift term to…

Machine Learning · Computer Science 2023-10-17 Franck Djeumou , Cyrus Neary , Ufuk Topcu

A popular numerical method to model the dynamics of a 'full spectrum' of cosmic rays (CRs), also applicable to radiation/neutrino hydrodynamics (RHD), is to discretize the spectrum at each location/cell as a piecewise power law in 'bins' of…

High Energy Astrophysical Phenomena · Physics 2022-11-30 Philip F. Hopkins

Analytical modeling of field-assisted molecular communication under dynamic electric fields is fundamentally challenging due to the coupling between stochastic transport and complex boundary geometries, which renders conventional partial…

Information Theory · Computer Science 2026-04-02 Po-Chun Chou , Yen-Chi Lee , Chun-An Yang , Chia-Han Lee , Ping-Cheng Yeh

Numerical simulations shed light onto earlier not trackable problem of magnetohydrodynamic (MHD) turbulence. They allowed to test the predictions of different models and choose the correct ones. Inevitably, this progress calls for revisions…

Astrophysics · Physics 2007-12-27 Huirong Yan , A. Lazarian

Recent advances in understanding of magnetohydrodynamic (MHD) turbulence call for substantial revisions in the picture of cosmic ray transport. In this paper we use recently obtained scaling laws for MHD modes to calculate the scattering…

Astrophysics · Physics 2007-05-23 Huirong Yan , A. Lazarian

The secondary-to-primary ratios are unique tools to investigate cosmic ray propagation mechanisms. In this work, we use the latest data of deuteron-to-helium~4 ratio and helium~3-to-helium~4 ratio measured by PAMELA combined with other…

High Energy Astrophysical Phenomena · Physics 2018-12-31 Juan Wu , Chen Huan

Fractional differential approach to cosmic ray physics problems is discussed. A short review in this field is given, some results are represented, analyzed and criticized. A new model called the bounded anomalous diffusion model is offered.…

Astrophysics of Galaxies · Physics 2015-03-19 Vladimir V. Uchaikin , Renat T. Sibatov

Supernova remnants (SNRs), as the major contributors to the galactic cosmic rays (CR), are believed to maintain an average CR spectrum by diffusive shock acceleration (DSA) regardless of the way they release CRs into the interstellar medium…

High Energy Astrophysical Phenomena · Physics 2016-10-11 M. A. Malkov , P. H. Diamond , R. Z. Sagdeev , F. A. Aharonian , I. V. Moskalenko

The coarse-grained propagation of Galactic cosmic rays (CRs) is traditionally constrained by phenomenological models of Milky Way CR propagation fit to a variety of direct and indirect observables; however, constraining the fine-grained…

Astrophysics of Galaxies · Physics 2024-02-07 Chad Bustard , John Wu

Cosmic ray (CR) transport and acceleration is determined by the properties of magnetic turbulence. Recent advances in MHD turbulence call for revisions in the paradigm of cosmic ray transport. We use the models of magnetohydrodynamic…

High Energy Astrophysical Phenomena · Physics 2015-06-15 Huirong Yan

In this paper we study the dynamics of a fast-slow Fokker-Planck partial differential equation (PDE) viewed as the evolution equation for the density of a multiscale planar stochastic differential equation (SDE). Our key focus is on the…

Analysis of PDEs · Mathematics 2025-02-03 Christian Kuehn , Jan-Eric Sulzbach

Partial differential equations (PDEs) govern a wide range of physical systems, but solving them efficiently remains a major challenge. The idea of a scientific foundation model (SciFM) is emerging as a promising tool for learning…

Machine Learning · Computer Science 2025-03-26 Amin Totounferoush , Serge Kotchourko , Michael W. Mahoney , Steffen Staab