Scott Aaronson: Gentle Measurement of Quantum States and Differential Privacy

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United States QuICS
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A talk by Scott Aaronson at the Quantum Machine Learning Workshop, hosted September 24-28, 2018 by the Joint Center for Quantum Information and Computer Science at the University of Maryland (QuICS).

Abstract: We prove a surprising connection between gentle measurement (where one wants to measure n quantum states, in a way that damages the states only by a little) and differential privacy (where one wants to query a database about n users, in a way that reveals only a little about any individual user). The connection is bidirectional, though with loss of parameters in going from DP to gentle measurement. By exploiting this connection, together with the Private Multiplicative Weights algorithm of Hardt and Rothblum, we're able to give a new protocol for so-called "shadow tomography" of quantum states, which improves over the parameters of a previous protocol for that task due to Aaronson, and which has the additional advantage of being "online" (that is, the measurements are processed one at a time).

Joint work with Guy Rothblum (Weizmann Institute); paper still in preparation.



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machine learning