Extraction and Modeling of TLS Losses in TiN Qubits

ORAL

Abstract

Predictive modeling of microwave loss due to dielectric two-level-systems allows for design optimization and targeted fabrication-process development to improve the performance of transmon qubits. We have previously used isotropically-trenched TiN and Al resonators to extract TLS-loss characteristics of material interfaces and the Si substrate [1, 2]. Applying this knowledge to the design and modeling of TiN qubits is complicated by the additional processing needed to fabricate high-quality Josephson junctions, which can induce additional defects at the various surfaces and interfaces. In this talk, we discuss the iterative process development that reduced the effect of these additional fabrication steps. With the resulting improved process, we determined the surface-loss contributions in TiN resonators and constructed a predictive loss model for co-fabricated TiN transmon qubits.
[1] Woods, Phys. Rev. Appl. 12, 014012 (2019)
[2] Melville, Appl. Phys. Lett. 117, 124004 (2020)

*This research was supported by the Department of Defense (DOD) under Air Force Contract No. FA8702-15-D-0001. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements of the DOD or the U.S. Government.

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Presenters

  • Wayne Woods

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory
    • Lincoln Laboratory, MIT
    • MIT - Lincoln Laboratory

Authors

  • Wayne Woods

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory
    • Lincoln Laboratory, MIT
    • MIT - Lincoln Laboratory

  • Alexander Melville

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory
    • Lincoln Laboratory, MIT
    • MIT - Lincoln Laboratory

  • Greg Calusine

    • MIT Lincoln Lab

  • Kyle Serniak

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory
    • MIT-Lincoln Lab
    • Lincoln Laboratory, MIT
    • MIT - Lincoln Laboratory

  • Evan Golden

    • MIT Lincoln Lab
    • Lincoln Laboratory, MIT

  • Bethany Huffman

    • MIT Lincoln Lab

  • David K Kim

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory
    • Lincoln Laboratory, MIT
    • MIT - Lincoln Laboratory
    • Massachusetts Institute of Technology MIT

  • Arjan Sevi

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • Jonilyn Yoder

    • MIT Lincoln Lab
    • MIT Lincoln Laboratory

  • William Oliver

    • MIT
    • MIT Lincoln Lab