Improved state preparation for first-quantized simulation of electronic structure

ORAL

Abstract

In this talk, we present several improvements to state preparation algorithms for the first-quantized simulation of electronic structure. We show that the cost of preparing physically meaningful initial states, either for ground state energy estimation or for dynamical simulation, can be dramatically reduced when compared with the naive linear scaling in the basis set size. We address the preparation of both Hartree-Fock and post-Hartree-Fock states derived from efficient classical calculations, and provide a general prescription that allows for a variety of work on second-quantized simulations in a typical Gaussian basis set to be used to construct initial states for first-quantized simulations in a plane wave basis. The main improvements come from leveraging tensor network methods, but we also use modern compilation techniques designed to reduce the number of non-Clifford gates required for our state preparation scheme.

Presenters

  • William J Huggins

    Google Quantum AI

Authors

  • William J Huggins

    Google Quantum AI

  • Oskar Leimkuhler

    Department of Chemistry, University of California, Berkeley, University of California, Berkeley

  • Torin F Stetina

    Simons Institute for the Theory of Computing, Berkeley CA

  • Birgitta Whaley

    University of California, Berkeley, Department of Chemistry, University of California, Berkeley