XI School in Probability and Stochastic processes>

Talks' abstracts > Garza Vargas Jorge

Strong convergence of random matrices
Jorge Garza Vargas  1  
1 : Princeton University

In the early 90's Voiculescu realized that certain natural tuples of random matrices converge, in some suitable sense, to certain natural tuples of bounded operators. He then leveraged this fact to tackle some, until then, intractable problems in von Neumann algebras. Since Voiculescu's discovery, researchers have realized that this sort of convergence happens in a much stronger sense (hence the term "strong convergence") than anticipated and is far more ubiquitous in mathematics than it initially appeared.
This mini-course will be about strong convergence. It will begin discussing classical examples from the theory of random graphs and will put emphasis on a new technique for establishing strong convergence. Time permitting, we will also discuss applications in spectral geometry, differential geometry, and/or operator algebras.


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