Quantum mean-value approximator for hard integer-value problems Article Swipe
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David Joseph
,
Antonio Martinez
,
Cong Ling
,
Florian Mintert
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1103/physreva.105.052419
· OA: W3165292928
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1103/physreva.105.052419
· OA: W3165292928
Evaluating the expectation of a quantum circuit is a classically difficult\nproblem known as the quantum mean value problem (QMV). It is used to optimize\nthe quantum approximate optimization algorithm and other variational quantum\neigensolvers. We show that such an optimization can be improved substantially\nby using an approximation rather than the exact expectation. Together with\nefficient classical sampling algorithms, a quantum algorithm with minimal gate\ncount can thus improve the efficiency of general integer-value problems, such\nas the shortest vector problem (SVP) investigated in this work.\n
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