Abstract

Achieving an accurate description of fermionic systems typically requires considerably many more orbitals than fermions. Previous resource analyses of quantum chemistry simulation often failed to exploit this low fermionic number information in the implementation of Trotter-based approaches and overestimated the quantum-computer runtime as a result. They also depended on numerical procedures that are computationally too expensive to scale up to large systems of practical interest. Here we propose techniques that solve both problems by using various factorized decompositions of the electronic structure Hamiltonian. We showcase our techniques for the uniform electron gas, finding substantial (over 100x) improvements in Trotter error for low-filling fraction and pushing to much higher numbers of orbitals than is possible with existing methods. Finally, we calculate the T-count to perform phase-estimation on Jellium. In the low-filling regime, we observe improvements in gate complexity of over 10x compared to the best Trotter-based approach reported to date. We also report gate counts competitive with qubitization-based approaches for Wigner-Seitz values of physical interest.

Highlights

  • IntroductionThere is considerable interest in whether quantum computers—both those available at present and those under development—can be used to solve problems of scientific and commercial importance

  • There is considerable interest in whether quantum computers—both those available at present and those under development—can be used to solve problems of scientific and commercial importance. This is evident in the field of quantum simulation of chemical systems; for recent reviews of progress in this area, we direct the reader to Refs. [1,2,3]

  • IV for 2D uniform electron gas systems with up to 49 electrons in 512 plane wave dual spin orbitals. These calculations were performed as outlined in Appendix E, with the help of subroutines present in OpenFermion [57], an electronic structure package for quantum computational chemistry

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Summary

Introduction

There is considerable interest in whether quantum computers—both those available at present and those under development—can be used to solve problems of scientific and commercial importance. This is evident in the field of quantum simulation of chemical systems; for recent reviews of progress in this area, we direct the reader to Refs. Several algorithms have been developed to obtain the eigenstates of chemical systems These include variational quantum algorithms [4,5] that aim to maximize the limited coherence times of currently available hardware. This comes at the cost of introducing heuristic aspects, making it difficult to obtain rigorous performance guarantees. Approaches based on quantum phase estimation [6,7] provide a route to calculate eigenstates to within a specifiable error, assuming only that we can efficiently prepare approximate eigenstates with sufficiently high overlap with the true eigenstates

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