Resource-efficient quantum-classical hybrid algorithm for energy gap evaluation

作     者：Yongdan Yang Ying Li Xiaosi Xu Xiao Yuan 

作者机构：Graduate School of China Academy of Engineering Physics Beijing 100193 China Center on Frontiers of Computing Studies Peking University Beijing 100871 China School of Computer Science Peking University Beijing 100871 China 

出 版 物：《Physical Review A》 (Phys. Rev. A)

年 卷 期：2024年第109卷第5期

页      面：052416-052416页

核心收录：

基　　金：National Natural Science Foundation of China, NSFC, (12347124, 12175003, 12361161602) National Natural Science Foundation of China, NSFC National Safety Academic Fund, NSAF, (U2330401, U2330201) National Safety Academic Fund, NSAF 

主　　题：Quantum algorithms Quantum computation 

摘      要：Estimating the eigenvalue or energy gap of a Hamiltonian H is vital for studying quantum many-body systems. Particularly, many of the problems in quantum chemistry, condensed-matter physics, and nuclear physics investigate the energy gap between two eigenstates. Hence, how to efficiently solve the energy gap becomes an important motive for researching new quantum algorithms. In this work, we propose a hybrid nonvariational quantum algorithm that uses the Monte Carlo method and real-time Hamiltonian simulation to evaluate the energy gap of a general quantum many-body system. Compared to conventional approaches, our algorithm does not require controlled real-time evolution, thus making its implementation much more experimental friendly for near-term quantum devices and early fault-tolerant quantum computers. To verify the efficiency of our algorithm, we conduct numerical simulations for the Heisenberg model and molecule systems on a classical emulator.