17 citations · 39 across the 8 of their papers we have counts for
9 papers
Quantum Markov State Models for Metastable Dynamics
Hao-En Li, Lin Lin, Michael Ragone
Open quantum systems can rapidly lose most microscopic information, leaving only a few degrees of freedom to govern their long-time dynamics. Classical Markov state models (MSMs) d…
Dissipative phase decision without ground-state preparation
Hao-En Li, Yilun Yang, Lin Lin
We propose a dynamical approach to identifying ground-state quantum phases through short-time dissipative cooling. Rather than determining the phase by preparing highly accurate ap…
Dissipative quantum algorithms for excited-state quantum chemistry
Hao-En Li, Lin Lin
Electronic excited states are central to a vast array of physical and chemical phenomena, yet accurate and efficient methods for preparing them on quantum devices remain challengin…
Infinite-dimensional Extension of the Linear Combination of Hamiltonian Simulation: Theorems and Applications
Rundi Lu, Hao-En Li, Zhengwei Liu +1
We generalize the Linear Combination of Hamiltonian Simulation (LCHS) formula [An, Liu, Lin, Phys. Rev. Lett. 2023] to simulate time-evolution operators in infinite-dimensional spa…
Towards robust variational quantum simulation of Lindblad dynamics via stochastic Magnus expansion
Jia-Cheng Huang, Hao-En Li, Yi-Cheng Wang +3
In this paper, we introduce a novel and general framework for the variational quantum simulation of Lindblad equations. Building on the close relationship between the unraveled Lin…
Dissipative ground state preparation in ab initio electronic structure theory
Hao-En Li, Yongtao Zhan, Lin Lin
Dissipative engineering is a powerful tool for quantum state preparation, and has drawn significant attention in quantum algorithms and quantum many-body physics in recent years. I…
Variational Quantum Imaginary Time Evolution for Matrix Product State Ansatz with Tests on Transcorrelated Hamiltonians
Hao-En Li, Xiang Li, Jia-Cheng Huang +5
The matrix product state (MPS) ansatz offers a promising approach for finding the ground state of molecular Hamiltonians and solving quantum chemistry problems. Building on this co…
Improved Optimization for the Neural-network Quantum States and Tests on the Chromium Dimer
Xiang Li, Jia-Cheng Huang, Guang-Ze Zhang +5
The advent of Neural-network Quantum States (NQS) has significantly advanced wave function ansatz research, sparking a resurgence in orbital space variational Monte Carlo (VMC) exp…
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…