Latency considerations for stochastic optimizers in variational quantum algorithms

Matt Menickelly

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

Latency considerations for stochastic optimizers in variational quantum algorithms

2023-03-16

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DOI：10.22331/q-2023-03-16-949

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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 re-search has employed algorithms based on the stochastic gradient iteration as the stochas-tic classical optimizer. In this work we pro-pose instead using stochastic optimization al-gorithms that yield stochastic processes em-ulating the dynamics of classical determin-istic algorithms. This approach results in methods with theoretically superior worst -case iteration complexities, at the expense of greater per-iteration sample (shot) complex-ities. We investigate this trade-off both theo-retically and empirically and conclude that preferences for a choice of stochastic opti-mizer should explicitly depend on a function of both latency and shot execution times.

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Latency considerations for stochastic optimizers in variational quantum algorithms

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