Utility-scale quantum computational chemistry

TL;DR

This paper discusses the potential of quantum computing in chemistry and materials science, emphasizing the need for algorithms that support routine, high-throughput molecular calculations to deliver societal benefits.

Contribution

It advocates for quantum algorithms that enable practical, high-throughput applications in computational chemistry, beyond just challenging strongly correlated molecules.

Findings

Quantum algorithms should support routine high-throughput molecular calculations.

Integration of quantum computing into practical pipelines is essential.

Quantum advantage in chemistry depends on utility-scale applications.

Abstract

Chemistry and materials science are widely regarded as potential killer application fields for quantum hardware. While the dream of unlocking unprecedented simulation capabilities remains compelling, quantum algorithm development must adapt to the evolving constraints of the emerging quantum hardware in order to accomplish any advantage for the computational chemistry practice. At the same time, the continuous advancement of classical wavefunction-theory methods narrows the window for a broad quantum advantage. Here, we explore potential benefits of quantum computation from the broader perspective of utility-scale applications. We argue that quantum algorithms need not only enable accurate calculations for a few challenging, that is strongly correlated, molecular structures, that might be hard to describe with traditional methods. Instead, they must also support the practical integration of quantum-accelerated computations into high-throughput pipelines for routine calculations on arbitrary molecules, ultimately delivering a tangible value to society.