Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session B53: Autonomous Control
11:30 AM–2:18 PM,
Monday, March 6, 2023
Room: Room 307
Sponsoring
Units:
GDS DQI
Chair: Maria Longobardi, University of Basel, Switzerland
Abstract: B53.00001 : System optimization of superconducting qubit readout for quantum error correction
11:30 AM–11:42 AM
Presenter:
Andreas Bengtsson
(Google LLC)
Authors:
Andreas Bengtsson
(Google LLC)
Alexander M Opremcak
(Google LLC)
Mostafa Khezri
(Google LLC)
Daniel T Sank
(Google LLC)
Paul V Klimov
(Google LLC)
Julian Kelly
(Google LLC)
Jimmy Chen
(Google LLC)
Collaboration:
Google Quantum AI
The parameter space for superconducting qubit readout is too large to map out fully, and effects such as qubit-qubit crosstalk impose non-locality. In other words, we can’t optimize each qubit separately and expect good results for simultaneous qubit readout. Instead, we need to consider the performance of the system as a whole and employ a global optimization algorithm to find the minimum of the sum of all readout errors.
In this talk, we discuss optimizing a 49 qubit readout suitable for quantum error correction by performing an offline and model based optimization. The search space is ~10^249 and we achieve a mean readout error of 1.95% for a total readout time of 500 ns, with a minimal amount of calibrations performed on the quantum processor itself.
Additionally, there are subtle and detrimental effects from the measurement process that don’t show up in the readout error numbers but can increase logical error rates. By accurately modeling these effects and including them as cost functions in the optimization we are able to significantly reduce their impact, which was a key part in our recent demonstration of a distance-5 surface code.
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