White-box and black-box macromodeling for superconducting quantum circuits [Part I]

ORAL

Abstract

As superconducting qubit architectures increase in size and complexity, the ability to build and analyze numerical quantum mechanical models of global chip parameters is becoming increasingly important. White-box models, in which the circuit topology is assumed known, are useful for finding the mapping between geometrical design parameters and Hamiltonian parameters. In contrast, black-box models (e.g. Foster’s or Brune’s circuit synthesis methods) hide the connection between geometry and Hamiltonian parameters, though they can be far more accurate. In this talk we present a unified framework for building and analyzing white-box and black-box models of superconducting circuits.

Authors

  • Michael Scheer

    • Rigetti Quantum Computing
  • Maxwell Block

    • Rigetti Quantum Computing
  • Eyob Sete

    • Rigetti Quantum Computing
  • Nicholas Rubin

    • Rigetti Quantum Computing
  • Nikolas Tezak

    • Rigetti Quantum Computing
  • Matthew Reagor

    • Rigetti Quantum Computing
  • Chad Rigetti

    • Rigetti Quantum Computing