12 papers
A Unified Generative Framework for Scalable Chemical Reaction Network Exploration
Zechang Sun, Chenxi Hu, Kailai Lin +6
Chemical reaction networks (CRNs) are crucial for understanding reaction mechanisms and guiding chemical synthesis, yet the computational exploration remains limited by the combina…
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…
Agentic Discovery of Exchange-Correlation Density Functionals
Titouan Duston, Jiashu Liang, Yuanheng Wang +6
The development of accurate exchange-correlation (XC) functionals remains a longstanding challenge in density functional theory (DFT). The vast majority of XC functionals have been…
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…
Hessian-informed machine learning interatomic potential towards bridging theory and experiments
Bangchen Yin, Jian Ouyang, Zhen Fan +7
Local curvature of potential energy surfaces is critical for predicting certain experimental observables of molecules and materials from first principles, yet it remains far beyond…
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…