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1
Recap: Random matrices with real spectrum
2
Complex quaternionic matrices
3
Other examples of rotationally invariant ensembles
4
Exercise: 2x2 - generic orthonormal transit
5
Specific orthonormal transit
6
Joint distribution of eigenvalues
7
Trick - Right set of variables to change
8
Remarks
9
Rotational Invariant Ensemble
10
3x3 - Gaussian case
11
Counting degrees of fraction
12
Special property of rotationally invariant ensembles
13
Real symmetric rotationally invariant ensemble
14
Complex Hermitian Case
15
Complex Quaternionic
16
For rotationally Invariant ensemble =eigenvalues & eigenvectors decouple
17
1 d disordered model - GOE and Anderson model
Description:
Explore the third lecture in the Random Matrix Theory and its Applications series, delivered by Satya Majumdar at the Bangalore School on Statistical Physics - X. Delve into advanced topics such as complex quaternionic matrices, rotationally invariant ensembles, and joint distribution of eigenvalues. Learn about specific orthonormal transits, tricks for changing variables, and special properties of rotationally invariant ensembles. Examine real symmetric, complex Hermitian, and complex quaternionic cases, understanding how eigenvalues and eigenvectors decouple in rotationally invariant ensembles. Conclude with an exploration of 1D disordered models, including GOE and Anderson models. This comprehensive 1 hour 32 minute lecture is part of a broader program aimed at bridging the gap between masters-level courses and cutting-edge research in statistical physics.

Random Matrix Theory and Its Applications - Lecture 3

International Centre for Theoretical Sciences
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