Simulating Dynamic Material Properties on Near-Term Quantum Computers

ORAL

Abstract

Dynamic simulation of controllable electronic properties of materials offers insight into how to harness such tunability for use in myriad technologies. Recent successes have been achieved in computing static properties of small molecules on currently available quantum computers, however, simulating dynamical properties still remains a challenge. In this work, we demonstrate successful simulation of time-dependent magnetization in a simplified model of an atomically-thin two-dimensional material on IBM’s Q16 Melbourne quantum processor and Rigetti’s Aspen quantum processor. Near overlap between experimental results from the quantum computer and those theoretically derived from simulated noisy qubits indicates there is a good understanding of the largest sources of error currently faced on available quantum computers. This early proof-of-concept gives hope that near-future quantum computers, capable of simulating larger systems, may soon be able to give insights into the dynamic control of tunable electronic properties in material.

*This work was supported as part of the Computational Materials Sciences Program funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award Number DE-SC0014607.

Presenters

  • Lindsay Bassman

    • Univ of Southern California

Authors

  • Lindsay Bassman

    • Univ of Southern California
  • Kuang Liu

    • Univ of Southern California
  • Yifan Geng

    • Univ of Southern California
  • Daniel Shebib

    • Univ of Southern California
  • Aravind Krishnamoorthy

    • Univ of Southern California
  • Shogo Fukushima

    • Kumamoto University
    • Department of Physics, Kumamoto University
  • Fuyuki Shimojo

    • Department of Physics, Kumamoto University
    • Kumamoto University
  • Rajiv Kalia

    • Mork Family Department of Chemical Engineering and Materials Science, University of Southern California
    • Univ of Southern California
    • Collaboratory for Advanced Computing and Simulations, University of Southern California
  • Aiichiro Nakano

    • Mork Family Department of Chemical Engineering and Materials Science, University of Southern California
    • Univ of Southern California
    • Collaboratory for Advanced Computing and Simulations, University of Southern California
  • Priya Vashishta

    • Mork Family Department of Chemical Engineering and Materials Science, University of Southern California
    • Univ of Southern California
    • University of Southern California
    • Collaboratory for Advanced Computing and Simulations, University of Southern California