[Sds-seminars] [Sds-announce] S&DS Seminar, Theo McKenzie, 1/13/25, KT 13th Floor, Rm. 1327, 12pm-1pm, "Random Matrices as a Model of Discrete Quantum Chaos"

[elizavette.torres at yale.edu]

 <https://statistics.yale.edu/>     <https://statistics.yale.edu/>
Department of Statistics and Data Science  

 

Theo McKenzie, Stanford University 

Date: Monday, January 13, 2025

Time: 12:00PM to 1:00PM

Location: Kline Tower, 13th Floor, Rm. 1327A  See map
<http://maps.google.com/?q=219+Prospect+Street%2C+New+Haven%2C+CT%2C+06511%2
C+us>  

219 Prospect Street

New Haven, CT 06511

 

Webcast:
https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=2b4393dd-4e98-4
1d0-b025-b233012bccf5 

Website <https://virtualmath1.stanford.edu/~theom/> 

 

 

Random Matrices as a Model of Discrete Quantum Chaos

 

Information and Abstract: 

The spectral theory of random matrices provides powerful tools for analyzing
high-dimensional data in statistical contexts. Seventy years ago, Nobel
Prize-winning physicist Eugene Wigner observed that the spectra of heavy
nuclei resemble those of random matrices. This observation not only advanced
our understanding of the quantum chaos of these large atoms but also
inspired significant mathematical development in random matrix theory
through techniques adapted from physics.

 

This talk provides an overview of the historical evolution of this field and
highlights recent advances, including work with applications to community
detection and error-correction. I will focus on a result that gives the
limiting distribution of the largest eigenvalues of the adjacency matrix of
a randomly selected regular graph, which proves the existence of optimal
spectral expanders of every degree. These findings offer new insights into
the interplay between randomness and structure in discrete systems.

 

Speaker bio: Theo McKenzie is a Stanford Science Fellow in the Department of
Mathematics. From 2022 to 2023, he served as an NSF MPS-Ascend Postdoctoral
Fellow at Harvard. Between 2017 and 2022, he pursued his Ph.D. at UC
Berkeley, where he had the privilege of being advised by Nikhil Srivastava
and Luca Trevisan. His research focuses on the spectral geometry of discrete
systems, with broader interests in analysis and probability, particularly in
questions inspired by statistical physics and computer science. Prior to his
doctoral studies, McKenzie earned his bachelor's degree from Harvard and
spent two years working as a trader.

 

 

Lunch at 11:30am in room 1307
Talk at 12:00-1:00pm in room 1327A

 

 

For more details and upcoming events visit our website at
<https://statistics.yale.edu/calendar> https://statistics.yale.edu/calendar.


 

Department of Statistics and Data Science

Yale University
Kline Tower

219 Prospect Street
New Haven, CT 06511

 <https://statistics.yale.edu/> https://statistics.yale.edu/

 

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