Toward the first quantum simulation with quantum speedup

TL;DR

This paper explores how to leverage emerging quantum computers for practical quantum simulation of spin systems, identifying efficient algorithms and circuit designs that outperform classical methods in resource requirements.

Contribution

It provides explicit optimized circuits for three quantum simulation algorithms, comparing their performance and establishing a pathway toward quantum advantage in simulation tasks.

Findings

Quantum signal processing offers rigorous performance guarantees.

Higher-order product formulas are effective with empirical error estimates.

Quantum circuits for spin simulations are significantly smaller than those for factoring and chemistry.

Abstract

With quantum computers of significant size now on the horizon, we should understand how to best exploit their initially limited abilities. To this end, we aim to identify a practical problem that is beyond the reach of current classical computers, but that requires the fewest resources for a quantum computer. We consider quantum simulation of spin systems, which could be applied to understand condensed matter phenomena. We synthesize explicit circuits for three leading quantum simulation algorithms, employing diverse techniques to tighten error bounds and optimize circuit implementations. Quantum signal processing appears to be preferred among algorithms with rigorous performance guarantees, whereas higher-order product formulas prevail if empirical error estimates suffice. Our circuits are orders of magnitude smaller than those for the simplest classically-infeasible instances of factoring and quantum chemistry.