Resource estimate for quantum many-body ground-state preparation on a quantum computer

TL;DR

This paper estimates the resources needed for quantum ground-state preparation in many-body systems, introduces an optimized procedure, and demonstrates significant reductions in circuit T-depth for intermediate-size lattices.

Contribution

It provides a resource estimation framework combining quantum many-body methods with analytic bounds and proposes an improved, more efficient quantum state preparation procedure.

Findings

Reduced circuit T-depth by up to a factor of 10^6

Resource estimates enable better design of quantum algorithms for many-body systems

Benchmark results show significant efficiency improvements

Abstract

We estimate the resources required to prepare the ground state of a quantum many-body system on a quantum computer of intermediate size. This estimate is made possible using a combination of quantum many-body methods and analytic upper bounds. Our routine can also be used to optimize certain design parameters for specific problem instances. Lastly, we propose and benchmark an improved quantum state preparation procedure. We find that it reduces the circuit T-depth by a factor as large as $10^6$ for intermediate-size lattices.