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Laser-Annealing-Assisted Josephson Junction Resistance Tuning

ORAL

Abstract

As superconducting quantum devices increase in complexity, the Josephson junction critical current needs to be fabricated to higher precision. However, current fabrication processes often exhibit large dispersion between junctions, and can lead to frequency collisions amongst qubits in fixed-frequency transmon quantum processors. One effective post-fabrication technique for adjusting the frequency of transmons is laser annealing, which can reduce junction variability down to 0.15%, thereby increasing the number of working qubits in a quantum processor. We present a laser annealer for Josephson junctions based on conventional microscopy components. With this tool, we conduct a thorough study of the annealing parameters and demonstrate that we can tune our junctions up to 6%, which provides sufficient dynamic range to fine-tune our native 3% wafer-scale fabrication variations. We demonstrate that annealing is stable against temporal drifts (aging) and that annealing does not impact the material quality of our junctions. Finally, we investigate the coherence stability of transmons before and after annealing. We present two-level system (TLS) spectroscopy to observe how laser annealing affects the environment of these qubits.

Presenters

  • Hyunseong Kim

    University of California, Berkeley

Authors

  • Hyunseong Kim

    University of California, Berkeley

  • Alexis Morvan

    Lawrence Berkeley National Laboratory

  • Edward S Barnard

    Lawrence Berkeley National Laboratory, LBNL, Berkeley Lab

  • Maria Virginia P Altoe

    Lawrence Berkeley National Laboratory

  • William P Livingston

    University of California, Berkeley

  • Yosep Kim

    Lawrence Berkeley National Laboratory

  • Larry Chen

    University of California, Berkeley

  • Christian Juenger

    Lawrence Berkeley National Laboratory

  • John Mark Kreikebaum

    Lawrence Berkeley National Laboratory

  • D. Frank F Ogletree

    Lawrence Berkeley National Laboratory

  • David I Santiago

    Lawrence Berkeley National Laboratory, Computational Research Division, Lawrence Berkeley National Lab

  • Irfan Siddiqi

    University of California, Berkeley, Applied Mathematics and Computational Research and Materials Sciences Divisions, LBNL, Lawrence Berkeley National Laboratory, Applied Mathematics, Computational Research and Materials Sciences Divisions, Lawrence Berkeley National Lab