Variational Quantum Eigensolvers with Quantum Gaussian Filters for solving ground-state problems in quantum many-body systems

TL;DR

This paper introduces a new quantum algorithm combining Variational Quantum Eigensolvers with Quantum Gaussian Filters, enhancing the efficiency and accuracy of ground-state approximations in quantum many-body systems on NISQ devices.

Contribution

The paper proposes integrating Quantum Gaussian Filters with VQE, providing an iterative, optimized approach that improves convergence and noise resilience in quantum simulations.

Findings

Demonstrated improved convergence speed on Transverse Field Ising models

Achieved higher accuracy under noisy conditions

Showed potential for complex quantum simulations in NISQ era

Abstract

We present a novel quantum algorithm for approximating the ground-state in quantum many-body systems, particularly suited for Noisy Intermediate-Scale Quantum (NISQ) devices. Our approach integrates Variational Quantum Eigensolvers (VQE) with Quantum Gaussian Filters (QGF), utilizing an iterative methodology that discretizes the application of the QGF operator into small, optimized steps through VQE. Demonstrated on the Transverse Field Ising models, our method shows improved convergence speed and accuracy, particularly under noisy conditions, compared to conventional VQE methods. This advancement highlights the potential of our algorithm in effectively addressing complex quantum simulations, marking a significant stride in quantum computing applications within the NISQ era.