English
Related papers

Related papers: A Neural Score-Based Particle Method for the Vlaso…

200 papers

We have developed a deterministic conservative solver for the inhomogeneous Fokker-Planck-Landau equation coupled with the Poisson equation, which is a {classical mean-field} primary model for collisional plasmas. Two subproblems, i.e. the…

Computational Physics · Physics 2017-06-19 Chenglong Zhang , Irene M. Gamba

Machine learning techniques have been quite popular recently in the high-energy physics community and have led to numerous developments in this field. In heavy-ion collisions, one of the crucial observables, the impact parameter, plays an…

High Energy Physics - Phenomenology · Physics 2021-10-11 Aditya Nath Mishra , Neelkamal Mallick , Sushanta Tripathy , Suman Deb , Raghunath Sahoo

A starting point for deriving the Vlasov equation is the BBGKY hierarchy that describes the dynamics of coupled marginal distribution functions. With a large value of the plasma parameter one can justify eliminating 2-point correlations in…

Plasma Physics · Physics 2022-10-11 F. Pegoraro , P. J. Morrison

Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such landscapes are difficult to learn from data and, once learned, hard to sample from.…

Machine Learning · Computer Science 2026-05-19 Christoph Griesbacher , Lea Bogensperger , Andreas Habring , Thomas Pock

In this paper, we first extend the micro-macro decomposition method for multiscale kinetic equations from the BGK model to general collisional kinetic equations, including the Boltzmann and the Fokker-Planck Landau equations. The main idea…

Numerical Analysis · Mathematics 2019-02-20 Irene M. Gamba , Shi Jin , Liu Liu

Multiscale dynamical systems characterized by interacting fast and slow processes are ubiquitous across scientific domains, from climate dynamics to fluid mechanics. Accurate modeling of such systems requires capturing both the long-term…

Chaotic Dynamics · Physics 2025-11-07 Giulio Del Felice , Ludovico Theo Giorgini

Model-based methods have recently shown great potential for off-policy evaluation (OPE); offline trajectories induced by behavioral policies are fitted to transitions of Markov decision processes (MDPs), which are used to rollout simulated…

Machine Learning · Computer Science 2023-02-06 Qitong Gao , Ge Gao , Min Chi , Miroslav Pajic

This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work…

Geophysics · Physics 2025-01-24 Jun Kurima , Bodhinanda Chandra , Kenichi Soga

Online video super-resolution (VSR) is an important technique for many real-world video processing applications, which aims to restore the current high-resolution video frame based on temporally previous frames. Most of the existing online…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Qiang Zhu , Xiandong Meng , Yuxian Jiang , Fan Zhang , David Bull , Shuyuan Zhu , Bing Zeng , Ronggang Wang

We propose an efficient evaluation protocol for large vision-language models (VLMs). Given their broad knowledge and reasoning capabilities, multiple benchmarks are needed for comprehensive assessment, making evaluation computationally…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Teppei Suzuki , Keisuke Ozawa

Magnetization dynamics in magnetic materials is often modeled by the Landau-Lifshitz equation, which is solved numerically in general. In micromagnetic simulations, the computational cost relies heavily on the time-marching scheme and the…

Numerical Analysis · Mathematics 2022-09-09 Panchi Li , Zetao Ma , Rui Du , Jingrun Chen

In this paper, we develop a set of efficient methods to compute stationary states of the spherical Landau-Brazovskii (LB) model in a discretization-then-optimization way. First, we discretize the spherical LB energy functional into a…

Numerical Analysis · Mathematics 2026-04-03 Qun Qiu , Wei Si , Guanghua Ji , Kai Jiang

We consider the Vlasov-Poisson-Landau system, a classical model for a dilute collisional plasma interacting through Coulombic collisions and with its self-consistent electrostatic field. We establish global stability and well-posedness near…

Analysis of PDEs · Mathematics 2022-01-19 Hongjie Dong , Yan Guo , Zhimeng Ouyang

Computational imaging has been revolutionized by compressed sensing algorithms, which offer guaranteed uniqueness, convergence, and stability properties. Model-based deep learning methods that combine imaging physics with learned…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Aniket Pramanik , M. Bridget Zimmerman , Mathews Jacob

We introduce the Multilevel Euler-Maruyama (ML-EM) method compute solutions of SDEs and ODEs using a range of approximators $f^1,\dots,f^k$ to the drift $f$ with increasing accuracy and computational cost, only requiring a few evaluations…

Machine Learning · Computer Science 2026-03-26 Arthur Jacot

Traditional Automatic License Plate Recognition (ALPR) systems employ multi-stage pipelines consisting of object detection networks followed by separate Optical Character Recognition (OCR) modules, introducing compounding errors, increased…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Karthik Sivakoti

Central moment lattice Boltzmann method (LBM) is one of the more recent developments among the lattice kinetic schemes for computational fluid dynamics. A key element in this approach is the use of central moments to specify collision…

Computational Physics · Physics 2012-02-29 Yang Ning , Kannan N. Premnath

We present a Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous multispecies Landau-Fokker-Planck equation. The scheme is derived from a first-order approximation of the multispecies Boltzmann operator in the grazing…

Computational Physics · Physics 2026-02-10 Andrea Medaglia

Policy-based methods currently dominate reinforcement learning (RL) pipelines for large language model (LLM) reasoning, leaving value-based approaches largely unexplored. We revisit the classical paradigm of Bellman Residual Minimization…

Machine Learning · Computer Science 2025-11-13 Yurun Yuan , Fan Chen , Zeyu Jia , Alexander Rakhlin , Tengyang Xie

Modern datasets often contain ballast as redundant or low-utility information that increases dimensionality, storage requirements, and computational cost without contributing meaningful analytical value. This study introduces a generalized,…

Machine Learning · Computer Science 2026-02-20 Yaroslav Solovko