Latency-aware adaptive shot allocation for run-time efficient variational quantum algorithms

Understand

Efficient classical optimizers are crucial in practical implementations of Variational Quantum Algorithms (VQAs).

• In particular, to make Stochastic Gradient Descent (SGD) resource efficient, adaptive strategies have been proposed to determine the number of measurement shots used to estimate the gradient.
• However, existing strategies overlook the overhead that occurs in each iteration.
• In terms of wall-clock runtime, significant circuit-switching and communication latency can slow the optimization process when using a large number of iterations.