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Efficient calculation of nuclear forces on noisy intermediate-scale quantum computers

ORAL

Abstract

Accurate nuclear forces are required to simulate the movement of atoms and molecules over time, an essential computational tool for drug discovery.

However, most current quantum computing algorithms only focus on determining an accurate estimate of the ground state energy. In contrast to the ground state problem, calculating the nuclear forces of Na atoms requires to estimate 3Na expectation values of operators which do not commute with the Hamiltonian.

In this talk, we show how to use noisy intermediate-scale quantum (NISQ) computers to extract nuclear forces and optimize the number of required samples from the quantum computer by using basis rotation groupings, importance sampling and fermionic shadows. We perform numerical simulations on hydrogen chains and water clusters, compare our findings to the cost of measuring the ground state energy and discuss the consequences of our results for quantum-enhanced molecular dynamics simulations.

Publication: https://arxiv.org/abs/2111.12437

Presenters

  • Michael Streif

    Boehringer Ingelheim

Authors

  • Michael Streif

    Boehringer Ingelheim

  • Thomas E O'Brien

    Google LLC

  • Nicholas C Rubin

    Google

  • Raffaele Santagati

    Boehringer-Ingelheim Quantum Lab

  • Yuan Su

    Microsoft Quantum, Google Research, Google

  • William J Huggins

    Google, Google Quantum AI

  • Joshua Goings

    IonQ, Inc, IonQ, Google

  • Nikolaj Moll

    Boehringer Ingelheim

  • Elica Kyoseva

    Boehringer Ingelheim, Boehringer-Ingelheim

  • Matthias Degroote

    Boehringer Ingelheim, Boehringer-Ingelheim

  • Christofer Tautermann

    Boehringer Ingelheim, Boehringer Ingelheim Pharma Inc., Boehringer-Ingelheim

  • Joonho Lee

    Columbia University

  • Dominic W Berry

    Macquarie University

  • Nathan Wiebe

    University of Toronto, Pacific Northwest National Laboratory, University of Toronto, Pacific Northwest Natl Lab

  • Ryan Babbush

    Google