Latency considerations for stochastic optimizers in variational quantum algorithms

Menickelly, Matt; Ha, Yunsoo; Otten, Matthew

doi:10.22331/q-2023-03-16-949

Latency considerations for stochastic optimizers in variational quantum algorithms

Journal Article · Thu Mar 16 04:00:00 EDT 2023 · Quantum

DOI:https://doi.org/10.22331/q-2023-03-16-949· OSTI ID:1961875

Menickelly, Matt ^[1]; Ha, Yunsoo ^[2]; Otten, Matthew ^[3]

Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Lemont, IL 60439
Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, 915 Partners Way, Raleigh, NC 27601
HRL Laboratories, LLC, 3011 Malibu Canyon Road, Malibu, CA 90265

Variational quantum algorithms, which have risen to prominence in the noisy intermediate-scale quantum setting, require the implementation of a stochastic optimizer on classical hardware. To date, most research has employed algorithms based on the stochastic gradient iteration as the stochastic classical optimizer. In this work we propose instead using stochastic optimization algorithms that yield stochastic processes emulating the dynamics of classical deterministic algorithms. This approach results in methods with theoretically superior worst-case iteration complexities, at the expense of greater per-iteration sample (shot) complexities. We investigate this trade-off both theoretically and empirically and conclude that preferences for a choice of stochastic optimizer should explicitly depend on a function of both latency and shot execution times.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1961875

Alternate ID(s):: OSTI ID: 2368573

Journal Information:: Quantum, Journal Name: Quantum Vol. 7; ISSN 2521-327X

Publisher:: Verein zur Forderung des Open Access Publizierens in den QuantenwissenschaftenCopyright Statement

Country of Publication:: Austria

Language:: English

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