{"id":53460,"date":"2025-08-20T08:38:55","date_gmt":"2025-08-20T12:38:55","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ams\/?post_type=tribe_events&p=53460"},"modified":"2025-10-13T10:56:52","modified_gmt":"2025-10-13T14:56:52","slug":"ams-weekly-seminar-joel-tropp","status":"publish","type":"tribe_events","link":"https:\/\/engineering.jhu.edu\/ams\/event\/ams-weekly-seminar-joel-tropp\/","title":{"rendered":"AMS Special Seminar Series | Joel Tropp"},"content":{"rendered":"

Location: <\/strong>Krieger 205<\/p>\n

When:<\/strong> October 16th at 1:30 p.m.<\/p>\n

Title: <\/strong>Positive Random Walks and Positive-Semidefinite Random Matrices<\/p>\n

Abstract:<\/strong>\u00a0On the real line, a random walk that can only move in the positive direction is very unlikely to remain close to its starting point. After a fixed number of steps, the left tail has a Gaussian profile, under minimal assumptions. Remarkably, the same phenomenon occurs when we consider a positive random walk on the cone of positive-semidefinite matrices. After a fixed number of steps, the minimum eigenvalue is also described by a Gaussian model.<\/p>\n

This talk introduces a new way to make this intuition rigorous. The methodology provides the solution to an open problem in computational mathematics about sparse random embeddings. The presentation is targeted at a general mathematical audience.<\/p>\n

Preprint:\u00a0https:\/\/arxiv.org\/abs\/2501.16578<\/a><\/p>\n

Zoom link:<\/strong> https:\/\/wse.zoom.us\/j\/93600407710?pwd=JBL8VsObRxX6MkhdjAUxCadqJDoZrZ.1<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Location: Krieger 205 When: October 16th at 1:30 p.m. Title: Positive Random Walks and Positive-Semidefinite Random Matrices Abstract:\u00a0On the real line, a random walk that can only move in 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