Weak Adversarial Neural Pushforward Method for Boltzmann Equation

• URL: http://arxiv.org/abs/2608.06823v1
• Date: Fri, 07 Aug 2026 05:28:53 GMT
• Title: Weak Adversarial Neural Pushforward Method for Boltzmann Equation
• Abstract summary: An invertible neural pushforward mapping is used to generate samples given by the distribution governed by the Boltzmann equation.<n>The training of the pushforward mapping is learnt by enforcing the weak form of the Boltzmann equation.
• Score: 2.64811975262819
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we extend a weak adversary neural network pushforward method for solving time dependent Boltzmann equation and a weak formulation of the collision operator is proposed where an invertible neural pushforward mapping is used to generating samples given by the distribution governed by the Boltzmann equation. The training of the pushforward mapping is learnt by enforcing the weak form of the Boltzmann equation. Numerical results have demonstrated the effectiveness of the proposed method.

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