Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session X32: Quantum Machine Learning III
8:00 AM–11:00 AM,
Friday, March 19, 2021
Sponsoring Units: DQI GDS
Chair: Guillaume Verdon, Google
Abstract: X32.00015 : Machine-learning tools for rapid control, calibration and characterization of QPUs and other quantum devices*
10:48 AM–11:00 AM
Anurag Saha Roy
Frank K Wilhelm
To rectify the situation, we provide a new integrated open-source tool-set for Control, Calibration and Characterization (C3) . We present a methodology to combine these tools to find a quantitatively accurate system model, high-fidelity gates and an approximate error budget.
In this talk I shall present the overall concept, and insights into future directions. Follow-up talks by Nicolas Wittler and Federico Roy will expand some of the details and walk through an example of C3 usage.
 Wittler, N., Roy, F., Pack, K. ... & Machnes, S. (2020). An integrated tool-set for Control, Calibration and Characterization of quantum devices applied to superconducting qubits. arXiv:2009.09866
*European Commission: Marie Curie ETN QuSCo (Grant 765267) & OpenSuperQ (Grant 820363)
IARPA: LogiQ Grant W911NF-16-1-0114
BMBF: VERTICONS Grant 13N14872
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