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New directions in quantum state learning and testing
Ryan O'Donnell - Carnegie Mellon University
Friday, October 6, 2023, 2:30-3:30 pm Calendar
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Abstract

I will talk about:

. New efficient algorithms for quantum state tomography (the quantum analogue of estimating a probability distribution).

. Why you should care about the difference between total variation distance and Hellinger distance and KL divergence and chi-squared divergence.

. Quantum-inspired improvements to the classical problem of independence testing.

Includes joint work with Steven T. Flammia (Amazon)

*We strongly encourage attendees to use their full name (and if possible, their UMD credentials) to join the zoom session.*

This talk is organized by Andrea F. Svejda