Permutation Matrix Representation Quantum Monte Carlo

ORAL

Abstract

We present a quantum Monte Carlo algorithm for the simulation of general quantum and classical many-body models within a single unifying framework. The algorithm builds on a power series expansion of the quantum partition function in its off-diagonal terms and is both parameter-free and Trotter error-free. It allows for the study of a wide variety of models on an equal footing. We showcase the flexibility of our algorithm and the advantages it offers over existing state-of-the-art by simulating transverse- field Ising model Hamiltonians and comparing the performance of our technique against that of the stochastic series expansion algorithm.

*IH is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR) Quantum Computing Application Teams (QCATS) program, under field work proposal number ERKJ347. Work by LG was supported by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES) under Award No. DE-SC0020280. Work by TA is supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via the U.S. Army Research Office contract W911NF-17-C-0050.

Presenters

  • Lalit Gupta

    • Univ of Southern California

Authors

  • Lalit Gupta

    • Univ of Southern California
  • Tameem Albash

    • Electrical and Computer Engineering, University of New Mexico
    • University of New Mexico
  • Itay Hen

    • Univ of Southern California
    • University of Southern California