18 citations · 50 across the 9 of their papers we have counts for
10 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…
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…
Digital adiabatic evolution is universally accurate
Yangyu Lu, Yifei Huang, Dong An +3
Adiabatic evolution is a central paradigm in quantum physics. Digital simulations of adiabatic processes are generally viewed as costly, since algorithmic errors typically accumula…
Quantum Many-Body Simulations of Catalytic Metal Surfaces
Changsu Cao, Hung Q. Pham, Zhen Guo +5
Quantum simulations of metal surfaces are critical for catalytic innovation. Yet existing methods face a cost-accuracy dilemma: density functional theory is efficient but system-de…
Solving the Hubbard model with Neural Quantum States
Yuntian Gu, Wenrui Li, Heng Lin +9
The rapid development of neural quantum states (NQS) has established it as a promising framework for studying quantum many-body systems. In this work, by leveraging the cutting-edg…
ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems
Zhen Guo, Zigeng Huang, Qiaorui Chen +7
Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaled with the system size and the desired accuracy. To address this, Byt…
Fault-tolerant quantum algorithms for quantum molecular systems: A survey
Yukun Zhang, Xiaoming Zhang, Jinzhao Sun +4
Solving quantum molecular systems presents a significant challenge for classical computation. The advent of early fault-tolerant quantum computing (EFTQC) devices offers a promisin…
Advancing Surface Chemistry with Large-Scale Ab-Initio Quantum Many-Body Simulations
Zigeng Huang, Zhen Guo, Changsu Cao +5
Predictive simulation of surface chemistry is of paramount importance for progress in fields from catalysis to electrochemistry and clean energy generation. Ab-initio quantum many-…
GPU-accelerated Auxiliary-field quantum Monte Carlo with multi-Slater determinant trial states
Yifei Huang, Zhen Guo, Hung Q. Pham +1
The accuracy of phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be systematically improved with better trial states. Using multi-Slater determinant trial states, ph-AF…
A Non-stochastic Optimization Algorithm for Neural-network Quantum States
Xiang Li, Jia-Cheng Huang, Guang-Ze Zhang +4
Neural-network quantum states (NQS) employ artificial neural networks to encode many-body wave functions in second quantization through variational Monte Carlo (VMC). They have rec…