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Operator Sampling for Shot-frugal Optimization in Variational Algorithms · Around

2020

Operator Sampling for Shot-frugal Optimization in Variational Algorithms

Arrasmith, Andrew, Cincio, Lukasz, Somma, Rolando D. et al.

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Quantum chemistry is a near-term application for quantum computers.

This application may be facilitated by variational quantum-classical algorithms (VQCAs), although a concern for VQCAs is the large number of measurements needed for convergence, especially for chemical accuracy.
Here we introduce a strategy for reducing the number of measurements (i.e., shots) by randomly sampling operators $h_i$ from the overall Hamiltonian $H = \sum_i c_i h_i$.
In particular, we employ weighted sampling, which is important when the $c_i$'s are highly non-uniform, as is typical in chemistry.

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