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DTSTART;TZID=America/New_York:20211207T093000
DTEND;TZID=America/New_York:20211207T103000
DTSTAMP:20260730T031043
CREATED:20240213T070713Z
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UID:10002160-1638869400-1638873000@cmsa.fas.harvard.edu
SUMMARY:The singularity probability of random symmetric matrices
DESCRIPTION:Abstract: Let M_n be drawn uniformly from all n by n symmetric matrices with entries in {-1\,1}. In this talk I’ll consider the following basic question: what is the probability that M_n is singular? I’ll discuss recent joint work with Marcelo Campos\, Marcus Michelen and Julian Sahasrabudhe where we show that this probability is exponentially small. I hope to make the talk accessible to a fairly general audience.
URL:https://cmsa.fas.harvard.edu/event/the-singularity-probability-of-random-symmetric-matrices/
CATEGORIES:Combinatorics Physics and Probability
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Combinatorics-Physics-and-Probability-Seminar-12.07.2021.png
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DTSTART;TZID=America/New_York:20211214T093000
DTEND;TZID=America/New_York:20211214T103000
DTSTAMP:20260730T031043
CREATED:20240213T112343Z
LAST-MODIFIED:20240304T102729Z
UID:10002495-1639474200-1639477800@cmsa.fas.harvard.edu
SUMMARY:The longest induced path in a sparse random graph
DESCRIPTION:Abstract: A long-standing problem in random graph theory has been to determine asymptotically the length of a longest induced path in sparse random graphs. Independent work of Luczak and Suen from the 90s showed the existence of an induced path of roughly half the optimal size\, which seems to be a barrier for certain natural approaches. Recently\, in joint work with Draganic and Krivelevich\, we solved this problem. In the talk\, I will discuss the history of the problem and give an overview of the proof.
URL:https://cmsa.fas.harvard.edu/event/12-14-21-combinatorics-physics-and-probability-seminar/
CATEGORIES:Combinatorics Physics and Probability
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Combinatorics-Physics-and-Probability-Seminar-12.14.2021.png
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