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Seminar

Mini-Course: Riemann-Hilbert problems application in the random matrix theory September 02, 2021 (01:30 PM PDT - 04:30 PM PDT)
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Location: SLMath: Online/Virtual, Eisenbud Auditorium
Speaker(s) Andrei Prokhorov (University of Michigan; Saint-Petersburg State University)
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Mini-Course: Riemann-Hilbert Problems Application In The Random Matrix Theory

Abstract/Media

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One of the first achievements of random matrix theory was the orthogonal polynomials method developed by Gaudin and Mehta (1960). It was discovered later by Fokas, Its and Kitaev (1992) that general orthogonal polynomials can be computed via the solution of a Riemann–Hilbert problem. We will review the story of analysis of this Riemann-Hilbert problem, compute the large degree asymptotic of orthogonal polynomials and note the consequences for the random matrix theory. We will follow the book by Bleher and Liechty "Random Matrices and the Six-Vertex Model" (2014).

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Mini-Course: Riemann-Hilbert Problems Application In The Random Matrix Theory