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DTSTART;TZID=America/New_York:20240913T143000
DTEND;TZID=America/New_York:20240913T170000
DTSTAMP:20260523T175542
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SUMMARY:Freedman CMSA Seminar
DESCRIPTION:Freedman CMSA Seminar \n  \n2:00-3:30 pm ET \nSpeaker: Mike Freedman\, Harvard CMSA \nTitle: Detecting hidden structures in linear maps \nAbstract: I’ll consider the problem of detecting spectral features and tensor structures within linear maps both in a quantum and classical contexts. In the quantum context there is the question of whether a Hamiltonian is local\, and if so\, local in distinct coordinate systems (a “duality”). Also\, in the case of a unitary described by a quantum circuit\, does it possess unusual spectral features or tensor structure? In ML one optimizes many linear maps. How would we know – and would we care – if the resulting maps (approximately) tensor factored? \n  \n3:30-4:00 pm ET \nBreak/Discussion \n  \n4:00-5:30 pm ET \nSpeaker: Ryan O’Donnell\, Carnegie Mellon University \nTitle: Quartic quantum speedups for planted inference \nAbstract: Consider the following task (“noisy 4XOR”)\, arising in CSPs\, optimization\, and cryptography. There is a ‘secret’ Boolean vector x in {-1\,+1}^n. One gets m randomly chosen pairs (S\, b)\, where S is a set of 4 coordinates from [n] and b is x^S := prod_{i in S} x_i with probability 1-eps\, and -x^S with probability eps. Can you tell the difference between the cases eps = 0.1 and eps = 0.5? \nIt depends on m. The best known algorithms use the “Kikuchi method” and run in time ~n^L when m ~ n^2/L. We will review this method\, and also show that the running time can be improved to roughly n^{L/4} with a quantum algorithm. \nJoint work with Alexander Schmidhuber (MIT)\, Robin Kothari (Google)\, and Ryan Babbush (Google).
URL:https://cmsa.fas.harvard.edu/event/freedman_91324/
LOCATION:CMSA Room G10\, CMSA\, 20 Garden Street\, Cambridge\, MA\, 02138\, United States
CATEGORIES:Freedman Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Freedman-Seminar-09.13.2024.png
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