Applications and resource estimates for open system simulation on a quantum computer

TL;DR

This paper explores open system quantum simulation applications, demonstrating scientific and industrial utilities, estimating resources, proposing optimizations, and introducing benchmarks for future quantum devices.

Contribution

It introduces concrete applications with utility estimates, resource analysis, algorithm optimizations, and benchmark problems for open system quantum simulation.

Findings

Predicted $400M utility for materials with Metal-Insulator Transition

Developed methodology for economic value estimation of emerging quantum technologies

Proposed algorithm optimizations leveraging translation invariance and parallelism

Abstract

We present two applications where open system quantum simulation is the preferred approach on a quantum computer. We choose concrete parameters for the problems in such a way that the application value, which we call utility, can be obtained from the solution directly. The scientific utility is exemplified by a computation of nonequilibrium behavior of Ca$_3$Co$_2$O$_6$, which is studied in \$2M MagLab experiments. For industrial utility, we develop a methodology that allows researchers of various backgrounds to estimate the economic value of an emerging technology consistently. Our approach predicts \$400M utility for the applications of materials with a Metal-Insulator Transition. We focus on the transport calculation in the Hubbard model as the simplest problem that needs to be solved in a large-scale material search. The resource estimates for both problems suffer from a large required runtime, which motivates us to propose novel algorithm optimizations, taking advantage of the translation invariance and the parallelism of the T-gate application. Finally, we introduce several planted solution problems and their obfuscated versions as a benchmark for future quantum devices.