activity
20242026
collaborators

9 papers

physics.comp-ph2026

Towards stable and accurate electron dynamics via neural network based time-dependent variational Monte Carlo

Weizhong Fu, Zhe Li, Yubing Qian +3

Real-time dynamics of interacting electrons lies at the interface between quantum mechanics and non-equilibrium physics, governing the microscopic origin of ultrafast phenomena of…

cond-mat.str-el2026

Topological invariant of periodic many body wavefunction from charge pumping simulation

Haoxiang Chen, Yubing Qian, Weiluo Ren +2

Many-body topological quantum states host exotic quantum phenomena and lie at the forefront of developing next-generation quantum technologies. Recently emerged neural network wave…

physics.chem-ph2026

Dataset Distillation for Machine Learning Force Field in Phase Transition Regime

Ruiyang Chen, Qingyuan Zhang, Ji Chen

Machine learning force field (MLFF) has emerged as a powerful data-driven tool for atomistic simulations, enabling large-scale and complex atomic systems to be simulated with accur…

physics.chem-ph2026

Permutation invariant multi-scale full quantum neural network wavefunction

Pengzhen Cai, Yubing Qian, Li Deng +8

Solving the intricate quantum behavior of interacting particles is key to unlocking the mysteries of condensed matter, but capturing their complex correlations across different sca…

physics.chem-ph2025

Spin-Adapted Neural Network Wavefunctions in Real Space

Ruichen Li, Yuzhi Liu, Du Jiang +7

Spin plays a fundamental role in understanding electronic structure, yet many real-space wavefunction methods fail to adequately consider it. We introduce the Spin-Adapted Antisymm…

physics.chem-ph2025

A particle view of many-body electronic structure with neural network wavefunction

Zichen Wang, Weizhong Fu, Zhe Li +2

In the study of electronic structure, the wavefunction view dominates the current research landscape and forms the theoretical foundation of modern quantum mechanics. In contrast,…