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1
Recap - Rot inv ensembles Gaussian
2
Two approaches - finite N approach
3
Large N continuum approach
4
What is the typical scale of lambda?
5
Large N - coarse graining
6
Step 1: Introduce an empirical density
7
Step 2: Coarse graining - Partial tracing
8
Saddle point method
9
Finite support of the charged density
10
Cauchy singular value equation
11
F.G. Tricomi, 1957
12
Famous Wigner semi-circular law
13
Scale of interparticle distance
14
Asymptotic properties
15
Tracy & Widom, 1994
Description:
Explore the fifth lecture in a series on Random Matrix Theory and its Applications, delivered by Satya Majumdar at the Bangalore School on Statistical Physics - X. Delve into advanced topics including rotational invariant Gaussian ensembles, finite N and large N approaches, coarse-graining techniques, and the famous Wigner semi-circular law. Learn about empirical density introduction, partial tracing, saddle point method, and the Cauchy singular value equation. Examine the scale of interparticle distance, asymptotic properties, and the work of Tracy & Widom from 1994. This 84-minute lecture is part of a comprehensive program aimed at bridging the gap between masters-level courses and cutting-edge research in statistical physics, suitable for PhD students, postdoctoral fellows, and interested faculty members.

Random Matrix Theory and Its Applications - Lecture 5

International Centre for Theoretical Sciences
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