The workshop will explore large-N asymptotics of random matrices, in connection with the operator-algebra models of their limiting behavior that appear in free probability theory. The behavior or random matrices has found increasing applications in mathematics, with connections to combinatorics, analysis and probability theory, as well as fields outside mathematics such as physics and computer science.
Topics of the workshop include asymptotics behavior of various observables of random single-matrix and multi-matrix models, including behavior of eigenvalues and eigenvectors, as well as connections to properties of operators describing the large-N limit. Of particular emphasis will be links to applications, ranging from graph theory to statistical analysis of data.
Alice Guionnet
(École Normale Supérieure de Lyon)
Dima Shlyakhtenko
(University of California, Los Angeles (UCLA))
Terence Tao
(University of California, Los Angeles (UCLA))
Roman Vershynin
(University of California, Irvine (UCI))
Jun Yin
(University of California, Los Angeles (UCLA))
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