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Improving the characterization of low loss rate superconducting qubits

ORAL

Abstract

Superconducting qubits are a leading technology in the race to create commercially viable quantum computers. However, challenges remain in improving the materials and fabrication processes used to make qubits with sufficiently long coherence times to enable quantum advantage. Superconducting qubits suffer from well-known losses due to two level systems (TLS). TLS losses exhibit 1/f-like behavior. These fluctuations occur at time scales similar to typical measurement durations and T1 can vary dramatically over timescales of hours and days. Large variations in individual qubit T1 over long times scales make it difficult to characterize the T1 of a qubit that results from a given fabrication process without measuring large numbers of qubits for prohibitive amounts of time. This problem appears worse as T1 times increase.

Here we review our efforts to overcome the temporal fluctuations of TLS losses to characterize qubits more accurately and quickly for feedback onto materials and fabrication protocols. By varying the energies of the ensemble of TLS that couple to our qubit, we are able to better characterize the full T1 distribution and long-term behavior. Varying TLS energies continuously during measurement or varying the TLS energy discretely between measurements both appear to be viable options for reducing the time needed to characterize the T1 of a given qubit. These techniques should enable better decision making about qubit fabrication with small numbers of qubits.

Presenters

  • KARTHIK BALAKRISHNAN

    IBM Thomas J. Watson Research Center

Authors

  • Andrew E Dane

    IBM Thomas J. Watson Research Center

  • KARTHIK BALAKRISHNAN

    IBM Thomas J. Watson Research Center

  • Brent Wacaser

    IBM Thomas J. Watson Research Center

  • Li-Wen Hung

    IBM Thomas J. Watson Research Center

  • John Mamin

    IBM Thomas J. Watson Research Center

  • Daniel Rugar

    IBM Thomas J. Watson Research Center

  • Robert M Shelby

    IBM Thomas J. Watson Research Center

  • Conal E Murray

    IBM Thomas J. Watson Research Center

  • Kenneth Rodbell

    IBM Thomas J. Watson Research Center

  • Jeffrey William Sleight

    IBM Thomas J. Watson Research Center