TY - JOUR
T1 - Unitary block optimization for variational quantum algorithms
AU - Slattery, Lucas
AU - Villalonga, Benjamin
AU - Clark, Bryan K.
N1 - B.K.C. acknowledges useful discussions with Aram Harrow and Edgar Solomonik. We acknowledge support from the Department of Energy through Grant DOE DE-SC0020165. This project is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (Awards No. OCI-0725070 and No. ACI-1238993) and the State of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This work also made use of the Illinois Campus Cluster, a computing resource that is operated by the Illinois Campus Cluster Program (ICCP) in conjunction with the National Center for Supercomputing Applications (NCSA), which is supported by funds from the University of Illinois at Urbana-Champaign.
PY - 2022/6
Y1 - 2022/6
N2 - Variational quantum algorithms are a promising hybrid framework for solving chemistry and physics problems with broad applicability to optimization as well. They are particularly well suited for noisy intermediate-scale quantum computers. In this paper we describe the unitary block optimization scheme (UBOS) and apply it to two variational quantum algorithms: the variational quantum eigensolver (VQE) and variational time evolution. The goal of VQE is to optimize a classically intractable parameterized quantum wave function to target a physical state of a Hamiltonian or solve an optimization problem. UBOS is an alternative to other VQE optimization schemes with a number of advantages, including fast convergence, less sensitivity to barren plateaus, the ability to tunnel through some local minima, and no hyperparameters to tune. We additionally describe how UBOS applies to real and imaginary time-evolution (TUBOS).
AB - Variational quantum algorithms are a promising hybrid framework for solving chemistry and physics problems with broad applicability to optimization as well. They are particularly well suited for noisy intermediate-scale quantum computers. In this paper we describe the unitary block optimization scheme (UBOS) and apply it to two variational quantum algorithms: the variational quantum eigensolver (VQE) and variational time evolution. The goal of VQE is to optimize a classically intractable parameterized quantum wave function to target a physical state of a Hamiltonian or solve an optimization problem. UBOS is an alternative to other VQE optimization schemes with a number of advantages, including fast convergence, less sensitivity to barren plateaus, the ability to tunnel through some local minima, and no hyperparameters to tune. We additionally describe how UBOS applies to real and imaginary time-evolution (TUBOS).
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U2 - 10.1103/PhysRevResearch.4.023072
DO - 10.1103/PhysRevResearch.4.023072
M3 - Article
AN - SCOPUS:85130618792
SN - 2643-1564
VL - 4
JO - Physical Review Research
JF - Physical Review Research
IS - 2
M1 - 023072
ER -