Predicting and measuring device quality in a micromachined flip-chip architecture

ORAL

Abstract

To meet the coherence and open-design-space requirements of quantum information processing systems, we further our work on a compact, lumped-element, bosonic superconducting circuit architecture by fabricating high-quality-factor LC resonators using flip-chip capacitors. Through silicon micromachining, we control the effective flip-chip gap, allowing for optimization of resonators' geometry for improved coherence based on known material quality. We use the participation model to predict the total loss rate through a comprehensive loss characterization study, and directly compare this prediction to measurements of these resonators on a 10mm × 10mm chip. Based on this study, we design flip-chip transmons and memories in this architecture to realize compact, high-Q, lumped-element bosonic superconducting circuit elements.

Presenters

  • Nico Zani

    • Yale University

Authors

  • Nico Zani

    • Yale University
  • Yanhao Wang

    • Yale University
  • Heekun Nho

    • Yale University
  • Julia Berndtsson

    • Google Quantum AI
  • Alexander P Read

    • Yale University
  • Luigi Frunzio

    • Yale University
  • Robert J Schoelkopf

    • Yale University