Accelerated Variational Quantum Eigensolver

TL;DR

This paper introduces a generalized variational quantum eigensolver that balances circuit depth and sampling efficiency, offering a flexible approach to finding ground state energies on quantum computers.

Contribution

It proposes a new VQE algorithm parameterized by alpha, interpolating between QPE and traditional VQE, and introduces a novel expectation estimation routine for limited quantum resources.

Findings

Reduces the number of samples needed for energy estimation

Balances circuit depth and sampling complexity via a tunable parameter

Provides a new expectation estimation method for resource-constrained quantum computing

Abstract

The problem of finding the ground state energy of a Hamiltonian using a quantum computer is currently solved using either the quantum phase estimation (QPE) or variational quantum eigensolver (VQE) algorithms. For precision $\epsilon$, QPE requires $O(1)$ repetitions of circuits with depth $O(1/\epsilon)$, whereas each expectation estimation subroutine within VQE requires $O(1/\epsilon^{2})$ samples from circuits with depth $O(1)$. We propose a generalised VQE algorithm that interpolates between these two regimes via a free parameter $\alpha\in[0,1]$ which can exploit quantum coherence over a circuit depth of $O(1/\epsilon^{\alpha})$ to reduce the number of samples to $O(1/\epsilon^{2(1-\alpha)})$. Along the way, we give a new routine for expectation estimation under limited quantum resources that is of independent interest.