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Simulations of frustrated Ising Hamiltonians using quantum approximate optimization.

Phillip C Lotshaw1, Hanjing Xu2, Bilal Khalid2,3,4

  • 1Quantum Information Sciences Section, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|December 4, 2022
PubMed
Summary
This summary is machine-generated.

The quantum approximate optimization algorithm (QAOA) can efficiently find ground states of magnetic materials, even complex ones. This quantum approach requires fewer measurements, paving the way for discovering novel materials.

Keywords:
Frustrated magnetismIsingquantum approximate optimizationquantum computingquantum simulation

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Area of Science:

  • Condensed Matter Physics
  • Quantum Computing
  • Materials Science

Background:

  • Understanding magnetic materials is crucial for technological advancement.
  • Computational complexity limits traditional methods for calculating ground-state properties.
  • Near-term quantum computers offer a potential solution for these complex calculations.

Purpose of the Study:

  • To investigate the use of the quantum approximate optimization algorithm (QAOA) for preparing ground states of magnetic materials.
  • To explore the feasibility of QAOA on near-term quantum hardware for materials science applications.

Main Methods:

  • Studied classical Ising spin models on various lattice structures (square, Shastry-Sutherland, triangular).
  • Employed the quantum approximate optimization algorithm (QAOA) on simulated and trapped-ion quantum computers.
  • Analyzed the relationship between QAOA success probability and ground-state structure.

Main Results:

  • Established a correlation between QAOA success probability and ground-state properties.
  • Demonstrated that a modest number of measurements are sufficient to determine ground states, even with magnetic frustration.
  • Successfully recovered ground states of a Shastry-Sutherland unit cell on a trapped-ion quantum computer with high accuracy.

Conclusions:

  • QAOA is a viable method for preparing ground states of magnetic materials, particularly in the frustrated Ising limit.
  • This work represents a significant step towards using quantum computation for systematic materials understanding.
  • Quantum advantage may be essential for tackling larger and more complex material Hamiltonians in the future.