Simulating chemical energies to high precision with fully-scalable quantum algorithms on superconducting qubits

ORAL

Abstract

Quantum simulations of molecules have the potential to calculate industrially-important chemical parameters beyond the reach of classical methods with relatively modest quantum resources. Recent years have seen dramatic progress both superconducting qubits and quantum chemistry algorithms. Here, we present experimental demonstrations of two fully-scalable algorithms for finding the dissociation energy of hydrogen: the variational quantum eigensolver and iterative phase estimation. This represents the first calculation of a dissociation energy to chemical accuracy with a non-precompiled algorithm. These results show the promise of chemistry as the ``killer app" for quantum computers, even before the advent of full error-correction.

Authors

  • Peter O'Malley

    • UC Santa Barbara
  • Ryan Babbush

    • Google Inc., Venice, CA
  • Ian Kivlichan

    • Harvard University
  • Jhonathan Romero

    • Harvard University
  • Jarrod McClean

    • Lawrence Berkeley National Lab
  • Andrew Tranter

    • Tufts University
  • Rami Barends

    • Google Inc., Santa Barbara, CA
  • Julian Kelly

    • Google Inc., Santa Barbara, CA
  • Yu Chen

    • Google Inc., Santa Barbara, CA
  • Zijun Chen

    • UC Santa Barbara
  • Evan Jeffrey

    • Google Inc., Santa Barbara, CA
  • Austin Fowler

    • Google Inc., Santa Barbara, CA
  • Anthony Megrant

    • UC Santa Barbara
  • Josh Mutus

    • Google Inc., Santa Barbara, CA
  • Charles Neill

    • UC Santa Barbara
  • Christopher Quintana

    • UC Santa Barbara
  • Pedram Roushan

    • Google Inc., Santa Barbara, CA
  • Daniel Sank

    • Google Inc., Santa Barbara, CA
  • Amit Vainsencher

    • UC Santa Barbara
  • James Wenner

    • UC Santa Barbara
  • Theodore White

    • Google Inc., Santa Barbara, CA
  • Peter Love

    • Tufts University
  • Alan Aspuru-Guzik

    • Harvard University
  • Hartmut Neven

    • Google Inc., Venice, CA
  • John Martinis

    • UC Santa Barbara and Google Inc.