Shortcut to chemically accurate quantum computing via density-based basis-set correction

Abstract Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections to obtain quantitative quantum-chemistry results on molecules that would otherwise require brute-force quantum calculations usi...

Full description

Saved in:
Bibliographic Details
Main Authors: Diata Traore, Olivier Adjoua, César Feniou, Ioanna-Maria Lygatsika, Yvon Maday, Evgeny Posenitskiy, Kerstin Hammernik, Alberto Peruzzo, Julien Toulouse, Emmanuel Giner, Jean-Philip Piquemal
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Communications Chemistry
Online Access:https://doi.org/10.1038/s42004-024-01348-3
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections to obtain quantitative quantum-chemistry results on molecules that would otherwise require brute-force quantum calculations using hundreds of logical qubits. Indeed, accessing a quantitative description of chemical systems while minimizing quantum resources is an essential challenge given the limited qubit capabilities of current quantum processors. We provide a shortcut towards chemically accurate quantum computations by approaching the complete-basis-set limit through coupling the density-based basis-set corrections approach, applied to any given variational ansatz, to an on-the-fly crafting of basis sets specifically adapted to a given system and user-defined qubit budget. The resulting approach self-consistently accelerates the basis-set convergence, improving electronic densities, ground-state energies, and first-order properties (e.g. dipole moments), but can also serve as a classical, a posteriori, energy correction to quantum hardware calculations with expected applications in drug design and materials science.
ISSN:2399-3669