3 papers
gr-qc2026
Physics informed operator learning of parameter dependent spectra
Haohao Gu, Sensen He, Hanlin Song +6
Spectral problems governed by differential operators underpin a wide range of physical systems, yet remain computationally challenging because their spectra depend sensitively on c…
astro-ph.IM2026
FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations
Bo Liang, Chang Liu, Hanlin Song +11
Bayesian inference in the physical sciences faces a fundamental challenge: the imperative for high-fidelity physical modeling often clashes with the intrinsic limitations of stocha…
physics.chem-ph2025
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials
Jinzhe Zeng, Duo Zhang, Anyang Peng +44
In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for m…