Abstract
The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25–100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.
| Original language | English |
|---|---|
| Pages (from-to) | 11335-11357 |
| Number of pages | 23 |
| Journal | Journal of Chemical Theory and Computation |
| Volume | 21 |
| Issue number | 22 |
| DOIs | |
| State | Published - Nov 25 2025 |
Funding
This article grew out of discussions at the Workshop on Quantum Computing Applications in Quantum Chemistry, held in April 2025 in Seattle, Washington, USA. The authors gratefully acknowledge the agencies and programs whose support of their individual research efforts made this work possible. In particular, we acknowledge Nathan Baker, Brian Bilodeau, Tamas Gorbe, Hongbin Liu, and David Williams-Young from Microsoft Azure Quantum for their inputs that form fruitful discussions during the workshop. We hope this paper offers a perspective that contributes to ongoing, pressing discussions on the near-future integration of quantum computing and computational chemistry to enable new scientific advances. We thank the Quantum Algorithms and Architecture for Domain Science Initiative (QuAADS), a Laboratory Directed Research and Development (LDRD) program at PNNL, for providing the support for organizing the workshop, and in particular, we are grateful to Alison Erickson for her invaluable assistance with workshop logistics and transcription. A.L., C.L., M.Z., and D.C. are supported by the “Embedding QC into Many-body Frameworks for Strongly Correlated Molecular and Materials Systems” project, which is funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (BES), the Division of Chemical Sciences, Geosciences, and Biosciences (under award 72689). J.L. is supported in part by the University of Pittsburgh, School of Computing and Information, Department of Computer Science, Pitt Cyber, PQI Community Collaboration Awards, John C. Mascaro Faculty Scholar in Sustainability, NASA under award number 80NSSC25M7057, and Fluor Marine Propulsion LLC (U.S. Naval Nuclear Laboratory) under award number 140449-R08. B.P. acknowledges the support from the Early Career Research Program by the U.S. Department of Energy, Office of Science, under Grant No. FWP 83466. MvS is supported by the Computational Chemical Sciences program within the Office of Basic Energy Sciences, U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. M.R. is grateful to the Novo Nordisk Foundation for financial support through the Quantum for Life center in Copenhagen/Zurich, NNF20OC0059939. Y.Z. acknowledges the support from the Laboratory Directed Research and Development (LDRD) program of Los Alamos National Laboratory (LANL). LANL is operated by Triad National Security, LLC, for the National Nuclear Security Administration of the US Department of Energy (contract no. 89233218CNA000001). T.V. acknowledges the support from the Pioneer Center for Accelerating P2X Materials Discovery (CAPeX), DNRF grant number P3. L.G. and M.R.H. are partially supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers and as part of the Computational Chemical Sciences Program, under Award DE-SC0023382, funded by the U.S. Department of Energy, Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division.