Optimized Quantum Program Execution Ordering to Mitigate Errors in Simulations of Quantum Systems

TL;DR

This paper introduces a compilation strategy for Hamiltonian Simulation on quantum computers that optimizes execution order to reduce circuit depth by 40%, enhancing accuracy and efficiency in quantum system simulations.

Contribution

It proposes a novel classical optimization approach that groups and rearranges Hamiltonian terms to improve quantum simulation accuracy and gate cancellation simultaneously.

Findings

Achieved an average 40% reduction in circuit depth.

Improved simulation accuracy by better term grouping.

Enhanced quantum simulation performance for physical systems.

Abstract

Simulating the time evolution of a physical system at quantum mechanical levels of detail -- known as Hamiltonian Simulation (HS) -- is an important and interesting problem across physics and chemistry. For this task, algorithms that run on quantum computers are known to be exponentially faster than classical algorithms; in fact, this application motivated Feynman to propose the construction of quantum computers. Nonetheless, there are challenges in reaching this performance potential. Prior work has focused on compiling circuits (quantum programs) for HS with the goal of maximizing either accuracy or gate cancellation. Our work proposes a compilation strategy that simultaneously advances both goals. At a high level, we use classical optimizations such as graph coloring and travelling salesperson to order the execution of quantum programs. Specifically, we group together mutually commuting terms in the Hamiltonian (a matrix characterizing the quantum mechanical system) to improve the accuracy of the simulation. We then rearrange the terms within each group to maximize gate cancellation in the final quantum circuit. These optimizations work together to improve HS performance and result in an average 40% reduction in circuit depth. This work advances the frontier of HS which in turn can advance physical and chemical modeling in both basic and applied sciences.