Novel Quantitative Analysis of Gas Dynamics Equations using Physics Informed Neural Network (PINN) Raj Rashmi and Kojiro Suzuki (Univ. of Tokyo）
The discovery of governing equations using the Physics Informed Neural Network (PINN) based on spatial-temporal data is revolutionizing the field of statistical physics. This study combines neural network technology with deterministic model equations and molecular simulation to find an appropriate description of stochastic phenomena. Conventional stochastic solvers rely on molecular interactions and enforce basic conservation laws on a microscopic level. Data-driven algorithms like PINN, when...