OnionVQE Optimization Strategy for Ground State Preparation on NISQ Devices

TL;DR

This paper introduces a new VQE optimization strategy tailored for NISQ devices that uses shallow circuits to effectively approximate ground states of complex Hamiltonians, addressing key hardware and algorithmic challenges.

Contribution

The paper presents a novel VQE optimization method with shallow circuits specifically designed for modeling cuprate superconductor Hamiltonians on NISQ hardware.

Findings

Effective ground state approximations achieved with shallow circuits.

Addresses barren plateaus and hardware noise issues.

Demonstrates potential for NISQ device applications.

Abstract

The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of issues, such as barren plateaus, local minima, quantum hardware noise, and limited qubit connectivity, thus posing challenges for their successful deployment on hardware and simulators. In this work, we propose a VQE optimization strategy that builds upon recent advances in the literature, and exhibits very shallow circuit depths when applied to the specific system of interest, namely a model Hamiltonian representing a cuprate superconductor. These features make our approach a favorable candidate for generating good ground state approximations on current NISQ devices. Our findings illustrate the potential of VQE algorithmic development for leveraging the full capabilities of NISQ devices.