Shallow quantum circuits for efficient preparation of Slater determinants and correlated states on a quantum computer

作     者：Chong Hian Chee Daniel Leykam Adrian M. Mak Dimitris G. Angelakis 

作者机构：Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore 117543 Institute of High Performance Computing Agency for Science Technology & Research (A*STAR) 1 Fusionopolis Way 16-16 Connexis Singapore 138632 School of Electrical and Computer Engineering Technical University of Crete 73100 Chania Greece AngelQ Quantum Computing 531A Upper Cross Street 04-95 Hong Lim Complex Singapore 051531 

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

年 卷 期：2023年第108卷第2期

页      面：022416-022416页

核心收录：

基　　金：National Research Foundation Singapore, NRF European Union's Horizon Programme, (HORIZON-CL4-2021-DIGITALEMERGING-02-10, 101080085) European Commission, EC, (101080085) Agency for Science, Technology and Research, A*STAR, (21709, NRF2021-QEP2-02-P02) 

主　　题：Quantum algorithms for chemical calculations 

摘      要：Fermionic Ansatz state preparation is a critical subroutine in many quantum algorithms such as the variational quantum eigensolver for quantum chemistry and condensed-matter applications. The shallowest circuit depth needed to prepare Slater determinants and correlated states to date scales at least linearly with respect to the system size N. Inspired by data-loading circuits developed for quantum machine learning, we propose an alternate paradigm that provides shallower, yet scalable, O(dlog22N) two-qubit gate-depth circuits to prepare such states with d fermions, offering a subexponential reduction in N over existing approaches in second quantization, enabling high-accuracy studies of d≪O(N/log22N) fermionic systems with larger basis sets on near-term quantum devices.