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The Legendre spectral Galerkin method of self-adjoint second order elliptic equations usually results in a linear system with a dense and ill-conditioned coefficient matrix. In this paper, the linear system is solved by a preconditioned…

Numerical Analysis · Mathematics 2020-04-30 Xuhao Diao , Jun Hu , Suna Ma

A new Fokker-Planck equation is developed for treating resonance line scattering, especially relevant to the treatment of Lyman alpha in the early universe. It is a "corrected" form of the equation of Rybicki & Dell'Antonio that now obeys…

Astrophysics · Physics 2010-11-11 George B. Rybicki

We introduce a new tensor integration method for time-dependent PDEs that controls the tensor rank of the PDE solution via time-dependent diffeomorphic coordinate transformations. Such coordinate transformations are generated by minimizing…

Numerical Analysis · Mathematics 2023-08-08 Alec Dektor , Daniele Venturi

Inspired by the gradient flow viewpoint of the Landau equation and the corresponding dynamic formulation of the Landau metric in [arXiv:2007.08591], we develop a novel implicit particle method for the Landau equation in the framework of the…

Numerical Analysis · Mathematics 2026-04-01 Yan Huang , Li Wang

A spectral method is developed for the direct solution of linear ordinary differential equations with variable coefficients. The method leads to matrices which are almost banded, and a numerical solver is presented that takes O(m^2n)…

Numerical Analysis · Mathematics 2012-08-16 Sheehan Olver , Alex Townsend

We propose an adaptive Hermite spectral method for the three-dimensional velocity space of the Boltzmann equation guided by a newly developed frequency indicator. For the homogeneous problem, the indicator is defined by the contribution of…

Numerical Analysis · Mathematics 2025-09-23 Sihong Shao , Yanli Wang , Jie Wu

We present a novel yet simple deep learning approach, called input gradient annealing neural network (IGANN), for solving stationary Fokker-Planck equations. Traditional methods, such as finite difference and finite elements, suffer from…

Dynamical Systems · Mathematics 2024-09-04 Liangkai Hang , Dan Hu , Zhi-Qin John Xu

We introduce a new algorithm to solve a regularized spatial-spectral image estimation problem. Our approach is based on the linearized alternating directions method of multipliers (LADMM), which is a variation of the popular ADMM algorithm.…

Signal Processing · Electrical Eng. & Systems 2025-02-25 Yunsong Liu , Debdut Mandal , Congyu Liao , Kawin Setsompop , Justin P. Haldar

This paper proposes a novel numerical integrator for modeling multispecies Coulomb collisions in kinetic plasmas. The proposed scheme provides an energy-, momentum-, and positivity-preserving particle discretization of the nonlinear Landau…

Plasma Physics · Physics 2022-12-28 Filippo Zonta , Joseph V. Pusztay , Eero Hirvijoki

There are two usual computational methods for linear (waves and instabilities) problem: eigenvalue (dispersion relation) solver and initial value solver. In fact, we can introduce an idea of the combination of them, i.e., we keep time…

Plasma Physics · Physics 2012-11-27 Hua-sheng Xie

We present a simple and constructive method to find $N$-soliton solutions of the equation suggested by Davydova and Lashkin to describe the dynamics of nonlinear ion-cyclotron waves in a plasma and subsequently known (in a more general form…

Pattern Formation and Solitons · Physics 2022-12-14 V. M. Lashkin

We present a new adaptive method for electronic structure calculations based on novel fast algorithms for reduction of multivariate mixtures. In our calculations, spatial orbitals are maintained as Gaussian mixtures whose terms are selected…

Numerical Analysis · Mathematics 2019-06-19 Gregory Beylkin , Lucas Monzon , Xinshuo Yang

We introduce a fast Fourier spectral method to compute linearized collision operators of the Boltzmann equation for variable hard-sphere gases. While the state-of-the-art method provides a computational cost O(MN^4 log N), with N being the…

Numerical Analysis · Mathematics 2025-09-16 Tianai Yin , Zhenning Cai , Yanli Wang

In this work we are interested in stochastic particle methods for multi-objective optimization. The problem is formulated using parametrized, single-objective sub-problems which are solved simultaneously. To this end a consensus based…

Optimization and Control · Mathematics 2022-08-03 Giacomo Borghi , Michael Herty , Lorenzo Pareschi

Spectral Graph Neural Networks (GNNs) suffer from two critical limitations: poor performance on "heterophilic" graphs and performance collapse at high polynomial degrees (K), known as over-smoothing. Both issues stem from the static,…

Machine Learning · Computer Science 2025-11-20 Huseyin Goksu

We present an adaptive finite element method for the incompressible Navier--Stokes equations based on a standard splitting scheme (the incremental pressure correction scheme). The presented method combines the efficiency and simplicity of a…

Numerical Analysis · Mathematics 2012-05-15 Kristoffer Selim , Anders Logg , Mats G. Larson

In this work we design and analyze a free energy satisfying finite difference method for solving Poisson-Nernst-Planck equations in a bounded domain. The algorithm is of second order in space, with numerical solutions satisfying all three…

Numerical Analysis · Mathematics 2015-06-17 Hailiang Liu , Zhongming Wang

This paper proposes an efficient algorithm for solving the Hartree--Fock equation combining a multilevel correction scheme with an adaptive refinement technique to improve computational efficiency. The algorithm integrates a multilevel…

Numerical Analysis · Mathematics 2025-10-14 Fei Xu

We propose an open-boundary molecular dynamics method in which an atomistic system is in contact with an infinite particle reservoir at constant temperature, volume and chemical potential. In practice, following the Hamiltonian adaptive…

Statistical Mechanics · Physics 2020-06-24 Maziar Heidari , Kurt Kremer , Ramin Golestanian , Raffaello Potestio , Robinson Cortes-Huerto

Adapting large-scale pre-trained generative models in a parameter-efficient manner is gaining traction. Traditional methods like low rank adaptation achieve parameter efficiency by imposing constraints but may not be optimal for tasks…

Computer Vision and Pattern Recognition · Computer Science 2024-06-03 Xinxi Zhang , Song Wen , Ligong Han , Felix Juefei-Xu , Akash Srivastava , Junzhou Huang , Hao Wang , Molei Tao , Dimitris N. Metaxas