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In this paper, we propose a novel Dual Inexact Splitting Algorithm (DISA) for distributed convex composite optimization problems, where the local loss function consists of a smooth term and a possibly nonsmooth term composed with a linear…

Optimization and Control · Mathematics 2023-04-25 Luyao Guo , Xinli Shi , Shaofu Yang , Jinde Cao

The general synthetic iterative scheme (GSIS) has proven its efficacy in modeling rarefied gas dynamics, where the steady-state solutions are obtained after dozens of iterations of the Boltzmann equation, with minimal numerical dissipation…

Computational Physics · Physics 2024-07-10 Liyan Luo , Lei Wu

The numerical simulation of rarefied gas mixtures with disparate mass and concentration is a huge research challenge. Based on our recent kinetic modelling for monatomic gas mixture flows, this problem is tackled by the general synthetic…

Computational Physics · Physics 2024-05-03 Jianan Zeng , Qi Li , Lei Wu

We explore the connections between Green's functions for certain differential equations, covariance functions for Gaussian processes, and the smoothing splines problem. Conventionally, the smoothing spline problem is considered in a setting…

Statistics Theory · Mathematics 2021-02-08 Lars Lau Raket

We present a general theory to calculate the steady-state heat and electronic currents for nonlinear systems using a perturbative expansion in the system-bath coupling. We explicitly demonstrate that using the truncated Dyson-series leads…

Statistical Mechanics · Physics 2014-11-18 Juzar Thingna , Hangbo Zhou , Jian-Sheng Wang

Critical points of energy functionals, which are of broad interest, for instance, in physics and chemistry, in solid and quantum mechanics, in material science, or in general diffusion-reaction models arise as solutions to the associated…

Numerical Analysis · Mathematics 2025-10-20 Pascal Heid , Thomas P. Wihler

Resolving numerically Vlasov-Poisson equations for initially cold systems can be reduced to following the evolution of a three-dimensional sheet evolving in six-dimensional phase-space. We describe a public parallel numerical algorithm…

Computational Physics · Physics 2016-06-29 Thierry Sousbie , Stéphane Colombi

This paper is devoted to the investigation of inertial dynamical systems with implicit Hessian-driven damping for strongly quasiconvex optimization which is a specific class of nonconvex optimization problems. We first establish exponential…

Optimization and Control · Mathematics 2026-02-27 Zeying Gao , Xiangkai Sun , Liang He

In recent years, several particle-based stochastic simulation algorithms (PSSA) have been developed to study the spatially resolved dynamics of biochemical networks at a molecular scale. A challenge all these approaches have to address is…

Quantitative Methods · Quantitative Biology 2011-07-04 Thorsten Prüstel , Martin Meier-Schellersheim

In this paper, we first establish the convergence criteria of the residual iteration method for solving quadratic eigenvalue problem- s. We analyze the impact of shift point and the subspace expansion on the convergence of this method. In…

Numerical Analysis · Mathematics 2017-01-12 Liu Yang , Yuquan Sun , Fanghui Gong

Krylov subspace, which is generated by multiplying a given vector by the matrix of a linear transformation and its successive powers, has been extensively studied in classical optimization literature to design algorithms that converge…

Machine Learning · Computer Science 2024-02-20 Hyungjin Chung , Suhyeon Lee , Jong Chul Ye

This paper presents a new algorithm KIOPS for computing linear combinations of $\varphi$-functions that appear in exponential integrators. This algorithm is suitable for large-scale problems in computational physics where little or no…

Numerical Analysis · Mathematics 2021-11-12 Stéphane Gaudreault , Greg Rainwater , Mayya Tokman

We present a novel deep learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. These systems arise from many problems in applied science, e.g., in numerical methods for…

Machine Learning · Computer Science 2022-10-04 Ayano Kaneda , Osman Akar , Jingyu Chen , Victoria Kala , David Hyde , Joseph Teran

In this paper we want to propose practical numerical methods to solve a class of initial-boundary problem of time-space fractional convection-diffusion equations (TSFCDEs). To start with, an implicit difference method based on two-sided…

Numerical Analysis · Mathematics 2021-07-26 Xian-Ming Gu , Ting-Zhu Huang , Cui-Cui Ji , Bruno Carpentieri , Anatoly A. Alikhanov

This introduction to Green's functions is based on their role as kernels of differential equations. The procedures to construct solutions to a differential equation with an external source or with an inhomogeneity term are put together to…

Mesoscale and Nanoscale Physics · Physics 2008-02-22 Ursula Schröter

The use of deep learning methods for solving PDEs is a field in full expansion. In particular, Physical Informed Neural Networks, that implement a sampling of the physical domain and use a loss function that penalizes the violation of the…

Machine Learning · Computer Science 2021-12-08 Valentin Mercier , Serge Gratton , Pierre Boudier

An iterative orbital interaction (iOI) approach is proposed to solve, in a bottom-up fashion, the self-consistent field problem in quantum chemistry. While it belongs grossly to the family of fragment-based quantum chemical methods, iOI is…

Chemical Physics · Physics 2021-05-04 Zikuan Wang , Wenjian Liu

Gain-dissipative platforms consisting of lasers, optical parametric oscillators and nonequilibrium condensates operating at the condensation/coherence threshold have been recently proposed as efficient analog simulators of 2-local spin…

Disordered Systems and Neural Networks · Physics 2021-02-10 Nikita Stroev , Natalia G. Berloff

A coarse grid correction (CGC) approach is proposed to enhance the efficiency of the matrix exponential and $\varphi$ matrix function evaluations. The approach is intended for iterative methods computing the matrix-vector products with…

Numerical Analysis · Mathematics 2024-04-23 Mike A. Botchev

This work delves into solving the two dimensional Poisson problem through the Finite Element Method which is relevant in various physical scenarios including heat conduction, electrostatics, gravity potential, and fluid dynamics. However,…

Numerical Analysis · Mathematics 2024-07-04 Charuka D. Wickramasinghe , Priyanka Ahire
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