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Solving the Boltzmann Equation with a Neural Sparse Representation

Published:2024-03-11 Issue:2 Volume:46 Page:C186-C215
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Li Zhengyi¹^ORCID,Wang Yanli²,Liu Hongsheng³,Wang Zidong³,Dong Bin⁴^ORCID

Affiliation:

1. School of Mathematical Science, Peking University, Beijing, 100084, China.

2. Beijing Computational Science Research Center, Beijing, 100193, China.

3. Huawei Technologies Co. Ltd., Longgang District, Shenzhen, Guangdong, 518100, China.

4. Beijing International Center for Mathematical Research & Center for Machine Learning Research, Peking University, Beijing, 100871, China.

Funder

Foundation of President of China Academy of Engineering Physics

National Natural Science Foundation of China

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference40 articles.

1. Fast evaluation of the Boltzmann collision operator using data driven reduced order models

2. A Model for Collision Processes in Gases. I. Small Amplitude Processes in Charged and Neutral One-Component Systems

3. Molecular Gas Dynamics And The Direct Simulation Of Gas Flows

4. Tensor methods for the Boltzmann-BGK equation

5. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition

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1. Separable Physics-Informed Neural Networks for Solving the Bgk Model of the Boltzmann Equation;2024

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