Nonadiabatic molecular dynamics on quantum computers: challenges and opportunities

Publications: Contribution to journalArticlePeer Reviewed

Abstract

In this Perspective, we discuss how quantum computers may advance the simulation of nonadiabatic molecular dynamics, a framework central to describing excited-state processes in photochemistry, biology, and materials science. Classical approaches span from exponentially scaling full quantum dynamics to more approximate mixed quantum-classical techniques such as surface hopping and Ehrenfest dynamics. Hybrid quantum-classical algorithms - particularly those based on the variational quantum eigensolver - offer a transformative alternative by providing access to the key electronic properties needed to drive nonadiabatic molecular dynamics simulations, including energies, gradients, and nonadiabatic couplings. We examine recent proof-of-principle quantum simulations of reduced model systems which, despite being restricted to small molecules and limited active spaces due to constraints of qubit number and device noise, already showcase the potential of quantum devices to capture phenomena such as conical intersections and ultrafast relaxation. Although practical applications are not yet feasible in the present noisy intermediate-scale quantum era, these efforts underline the conceptual and methodological advances of quantum algorithms paving the way for large-scale quantum simulations of nonadiabatic processes. Framed within the 2025 International Year of Quantum Science and Technology, such progress exemplifies how quantum computing may open new horizons for chemistry and beyond.
Original languageEnglish
JournalPure and Applied Chemistry
DOIs
Publication statusPublished - 2025

Austrian Fields of Science 2012

  • 104027 Computational chemistry
  • 104022 Theoretical chemistry

Keywords

  • Noadiabatic molecular dynamics
  • quantum chemistry
  • quantum computing
  • quantum mechanics
  • Quantum Science and Technology
  • ELECTRONICALLY EXCITED-STATES
  • GEOMETRIC-PHASE
  • EIGENSOLVER
  • ALGORITHM
  • ENERGY

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