Ryan O'Donnell:New directions in quantum state learning and testing
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Published on ● Video Link: https://www.youtube.com/watch?v=MnxQ3oqTWgQ
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)
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quantum computing