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Neural Boltzmann Equations
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arXiv Statistics ML
Aug 25
Neural Boltzmann Equations
arXiv:2608.23022v1 Announce Type: cross Abstract: The dynamics of particles in the early universe are described by Boltzmann equations, which involve high-dimensional phase-space integrals. Classical...
Hugging Face Trending Papers
Jun 25
Autoregressive Boltzmann Generators
Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics. This challenge has driven the development of Boltzmann Generators (BGs), which allow rapid generation of uncorrelated equilibrium samples by combining a generative model with exact likelihoods and an importance sampling correction.
arXiv Machine Learning
Aug 11
Leveraging generative models to assist Monte Carlo sampling
arXiv:2608. 07648v1 Announce Type: cross Abstract: Sampling high-dimensional probability distributions is a central task in scientific computing, with applications ranging from Bayesian inference to statistical physics and molecular simulation.
arXiv Machine Learning
Aug 28
Generative Monte Carlo Sampling for Constant-Cost Particle Transport
Generative Monte Carlo (GMC) is a new particle transport simulation method that embeds generative AI into solving the linear Boltzmann equation. By treating cell transmission as a conditional generation task, neural networks trained with conditional flow matching produce particle exit states—position, direction, and path length—without simulating scattering histories. GMC generalizes across materials using optical coordinate scaling, matches standard Monte Carlo’s statistical accuracy and convergence, and achieves constant‑cost per cell transmission, offering significant speedups in optically thick regimes.
arXiv Machine Learning
Jun 16
GPT-Based Fast Simulation of CLAS12 Detector Hits via Conditional Autoregressive Generation
arXiv:2606. 16035v1 Announce Type: cross Abstract: Modern particles physics experiments have demonstrated an increasing need for fast, high-fidelity detector simulation as detector components have improved and subsequent computational requirements approach the limits of available resources.
arXiv AI
Jun 26
Autoregressive Boltzmann Generators
arXiv:2606. 27361v1 Announce Type: cross Abstract: Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics.