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A new methodology is developed to integrate numerically the equations of motion for classical many-body systems in molecular dynamics simulations. Its distinguishable feature is the possibility to preserve, independently on the size of the…

Statistical Mechanics · Physics 2009-10-31 I. P. Omelyan , I. M. Mryglod , R. Folk

Because of the finiteness of the life span and boundedness of the physical space, the more reasonable or physical choice is the tempered power-law instead of pure power-law for the CTRW model in characterizing the waiting time and jump…

Numerical Analysis · Mathematics 2018-05-01 Weihua Deng , Zhijiang Zhang

We develop a purely hydrodynamic formalism to describe collisional, anisotropic instabilities in a relativistic plasma, that are usually described with kinetic theory tools. Our main motivation is the fact that coarse-grained models of high…

High Energy Physics - Phenomenology · Physics 2017-01-04 Esteban Calzetta , Alejandra Kandus

In this paper, we consider a class of time-optimal control problems governed by linear parabolic equations with mixed control-state constraints and end-point constraints, and without Tikhonov regularization term in the objective function.…

Optimization and Control · Mathematics 2025-09-04 Huynh Khanh , Bui Trong Kien

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase space due to their better scalability than continuum approaches with respect to dimension. Complex processes…

Plasma Physics · Physics 2025-12-23 Mark F. Adams , Daniel S. Finn , Matthew G. Knepley , Joseph V. Pusztay

This paper is devoted to hydrodynamic limits of linear kinetic equations when the thermodynamical equilibrium is described by a heavy-tail distribution function rather than a Maxwellian distribution. We show that the long time/small mean…

Analysis of PDEs · Mathematics 2009-10-09 Antoine Mellet

We propose a systematic methodology to derive the regularized thirteen-moment equations in the rarefied gas dynamics for a general class of linearized collision models. Detailed expressions of the moment equations are written down for all…

Fluid Dynamics · Physics 2020-05-13 Zhenning Cai , Yanli Wang

Starting from first principles quantum kinetic theory for ideal plasmas with exchange effects, the quantum hydrodynamic equations are derived taking moments of the corresponding exchange-Vlasov equation. The case of an electron-ion plasma…

Plasma Physics · Physics 2021-04-22 Fernando Haas

Linear stationary reaction-convection-diffusion equations with Dirichlet boundary conditions are approximated using a simple finite difference method corresponding to central differences and the addition of a high-order stabilization term…

Numerical Analysis · Mathematics 2025-02-07 T. Lewis , X. Xue

Drift-diffusion plasma fluid models are commonly used to simulate electric discharges. Such models can computationally be very efficient if they are combined with explicit time integration. This paper deals with two issues that often arise…

Computational Physics · Physics 2020-02-19 Jannis Teunissen

We make a brief historical review to the moment model reduction to the kinetic equations, particularly the Grad's moment method for Boltzmann equation. The focus is on the hyperbolicity of the reduced model, which is essential to the…

Statistical Mechanics · Physics 2020-05-26 Zhenning Cai , Yuwei Fan , Ruo Li

The phase-field crystal equation, a parabolic, sixth-order and nonlinear partial differential equation, has generated considerable interest as a possible solution to problems arising in molecular dynamics. This is because the phase-field…

Mathematical Physics · Physics 2015-07-29 Philippe Vignal , Lisandro Dalcin , Donald L. Brown , Nathan Collier , Victor M. Calo

Spectral methods of moments provide a powerful tool for learning the parameters of latent variable models. Despite their theoretical appeal, the applicability of these methods to real data is still limited due to a lack of robustness to…

Machine Learning · Statistics 2018-10-18 Matteo Ruffini , Guillaume Rabusseau , Borja Balle

Describing long-ranged electrostatics using short-ranged pair potentials is appealing since the computational complexity scales linearly with the number of particles. The foundation of this approach is to mimic the long-ranged medium…

Statistical Mechanics · Physics 2020-05-13 Björn Stenqvist , Vidar Aspelin , Mikael Lund

We develop moment estimators for the parameters of affine stochastic volatility models. We first address the challenge of calculating moments for the models by introducing a recursive equation for deriving closed-form expressions for…

Statistical Finance · Quantitative Finance 2024-08-20 Yan-Feng Wu , Xiangyu Yang , Jian-Qiang Hu

Stochastic dynamical systems often contain nonlinearities which make it hard to compute probability density functions or statistical moments of these systems. For the moment computations, nonlinearities in the dynamics lead to unclosed…

Optimization and Control · Mathematics 2017-03-28 Khem Raj Ghusinga , Mohammad Soltani , Andrew Lamperski , Sairaj Dhople , Abhyudai Singh

We prove sharp estimates for the decay in time of solutions to a rather general class of non-local in time subdiffusion equations on a bounded domain subject to a homogeneous Dirichlet boundary condition. Important special cases are the…

Analysis of PDEs · Mathematics 2013-10-02 Vicente Vergara , Rico Zacher

We present the standard electromagnetic Particle-in-Cell method, starting from the discrete approximation of derivatives on a uniform grid. The application to second-order, centered, finite-difference discretization of the equations of…

Computational Physics · Physics 2020-08-18 J. L. Vay

Moment methods are classical approaches that approximate the mesoscopic radiative transfer equation by a system of macroscopic moment equations. An expansion in the angular variables transforms the original equation into a system of…

Mathematical Physics · Physics 2023-08-17 Martin Frank , Benjamin Seibold

Method of moment estimators exhibit appealing statistical properties, such as asymptotic unbiasedness, for nonconvex problems. However, they typically require a large number of samples and are extremely sensitive to model misspecification.…

Computation · Statistics 2016-03-30 Dustin Tran , Minjae Kim , Finale Doshi-Velez
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