Abstract

Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challenges in quantum chemistry, physics and material science. Proof-of-principle quantum chemistry simulations for small molecules have been demonstrated on NISQ devices. While several approaches have been theoretically proposed for correlated materials, NISQ simulations of interacting periodic models on current quantum devices have not yet been demonstrated. Here, we develop a hybrid quantum-classical simulation framework for correlated electron systems based on the Gutzwiller variational embedding approach. We implement this framework on Rigetti quantum processing units (QPUs) and apply it to the periodic Anderson model, which describes a correlated heavy electron band hybridizing with non-interacting conduction electrons. Our simulation results quantitatively reproduce the known ground state quantum phase diagram including metallic, Kondo and Mott insulating phases. This is the first fully self-consistent hybrid quantum-classical simulation of an infinite correlated lattice model executed on QPUs, demonstrating that the Gutzwiller hybrid quantum-classical embedding framework is a powerful approach to simulate correlated materials on NISQ hardware. This benchmark study also puts forth a concrete pathway towards practical quantum advantage on NISQ devices.

Highlights

  • Quantum computing holds the promise to revolutionize modern high-performance computations in physics by providing exponential speedups compared to currently known classical algorithms for a variety of important problems such as simulating interacting quantum models [1,2,3,4]

  • Our results show that Gutzwiller quantum-classical embedding (GQCE) correctly describes the periodic Anderson model (PAM) ground state phase diagram, which contains Kondo insulator, correlated metal, and Mott insulator phases [25,38,39]

  • We demonstrate that variational quantum eigensolver (VQE) calculations performed on Rigetti’s Aspen-4 quantum processing units (QPUs) with standard readout symmetrization and calibration yields sufficiently accurate results to reach self-consistency of the GQCE calculation

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Summary

Introduction

Quantum computing holds the promise to revolutionize modern high-performance computations in physics by providing exponential speedups compared to currently known classical algorithms for a variety of important problems such as simulating interacting quantum models [1,2,3,4]. One example is the variational quantum eigensolver (VQE) algorithm to solve the eigenvalue problem [12,13].

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