From Promise to Practice: Benchmarking Quantum Chemistry on Quantum Hardware

TL;DR

This paper systematically evaluates the quantum diagonalization method for electronic structure calculations across diverse chemical reactions, providing a benchmark on quantum hardware and highlighting its current limitations and potential for future improvements.

Contribution

It offers the largest assessment of a quantum-hybrid algorithm's accuracy on real quantum devices across various molecular systems and reactions, with open-source tools for community use.

Findings

SQD shows large statistical deviations but can reach CCSD-level accuracy with energy extrapolation.

Bond-breaking reactions improve with more resources, unlike nucleophilic substitution.

The study provides a benchmark and open-source tools for future quantum chemistry research.

Abstract

We provide a systematic evaluation of the sample-based quantum diagonalization (SQD) method for electronic structure based on the W4-11 thermochemistry dataset, comprising 124 total atomization, 83 bond dissociation, 20 isomerization, 505 heavy-atom transfer, and 13 nucleophilic substitution processes, covering diverse bonding situations and reaction mechanisms. This is the largest study assessing the accuracy and precision of a quantum-hybrid algorithm on a digital quantum device across a variety of molecular systems and chemical reactions, using 16.85 hours on the superconducting quantum processor ibm_rensselaer and 724.22 node hours on the supercomputer AiMOS. To ensure a fair comparison, our study employs commensurate resource allocation for both classical and quantum simulations. Although SQD exhibits large statistical deviations from ground-state reference energies, energy extrapolations yield CCSD-level accuracy. While bond-breaking reactions show a systematic improvement as computational resources increase, nucleophilic substitution or heavy atom transfer reactions do not. The limitations quantified in this manuscript indicate opportunities for improvement in SQD-based algorithms. This work provides a benchmark and community resource for exploring new quantum algorithms and devices, supported by an online benchmark challenge and an open-source Python library for direct comparison.