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Efficient calculation of energy derivatives on a Fault-Tolerant Quantum Computer

ORAL

Abstract

Energy derivatives underpin many fundamental properties of molecular systems, from the dipole moments to the hyperfine couplings and forces.

Here, we present new algorithms for efficiently calculating energy derivatives on fault-tolerant quantum computers, exploiting existing state-of-the-art techniques, including block encoding of fermionic operators, use of higher order finite difference formula, and Heisenberg-limited expectation value estimation methods. We optimize the algorithms' parameters to reduce their computational cost and discuss their asymptotic scalings. We show how these approaches can achieve Heisenberg's limited scaling of the errors and compare their different performance, supporting the results with numerical simulations. We will discuss the limits of such techniques and their direct dependence on the cost of state preparation and the calculation of the expectation value of the energy. We will finally explore their applicability to problems of practical relevance, such as the geometry optimization of molecules.

Publication: Efficient quantum computation of molecular forces and other energy gradients - Thomas E O'Brien, Michael Streif, Nicholas C Rubin, Raffaele Santagati, Yuan Su, William J Huggins, Joshua J Goings, Nikolaj Moll, Elica Kyoseva, Matthias Degroote, Christofer S Tautermann, Joonho Lee, Dominic W Berry, Nathan Wiebe, Ryan Babbush - arXiv preprint arXiv:2111.12437 https://arxiv.org/abs/2111.12437

Presenters

  • Raffaele Santagati

    Boehringer-Ingelheim Quantum Lab

Authors

  • Raffaele Santagati

    Boehringer-Ingelheim Quantum Lab

  • Thomas E O'Brien

    Google LLC

  • Michael Streif

    Boehringer Ingelheim

  • Nicholas C Rubin

    Google

  • 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