"Random matrix"의 두 판 사이의 차이

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<h5>introduction</h5>
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==introduction</h5>
  
 
* The ensembles of random matrices obtained are called Gaussian Orthogonal (GOE), Unitary (GUE), and Symplectic (GSE) Ensembles for = 1, = 2, and = 4 respectively.
 
* The ensembles of random matrices obtained are called Gaussian Orthogonal (GOE), Unitary (GUE), and Symplectic (GSE) Ensembles for = 1, = 2, and = 4 respectively.
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<h5>random self-adjoint matrices</h5>
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==random self-adjoint matrices</h5>
  
 
* Wigner matrices
 
* Wigner matrices
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<h5>Gaussian Wigner matrices</h5>
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==Gaussian Wigner matrices</h5>
  
 
* [http://www.math.ucla.edu/%7Eshlyakht/berkeley-07/conference/contrib/peche-talk.pdf http://www.math.ucla.edu/~shlyakht/berkeley-07/conference/contrib/peche-talk.pdf]
 
* [http://www.math.ucla.edu/%7Eshlyakht/berkeley-07/conference/contrib/peche-talk.pdf http://www.math.ucla.edu/~shlyakht/berkeley-07/conference/contrib/peche-talk.pdf]
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<h5>Gaussian Unitary Ensemble(GUE) hypothesis</h5>
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==Gaussian Unitary Ensemble(GUE) hypothesis</h5>
  
 
* Wigner's work on neutron scattering resonances
 
* Wigner's work on neutron scattering resonances
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<h5>determinantal processes</h5>
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==determinantal processes</h5>
  
 
* Random matrices and determinantal processes http://arxiv.org/abs/math-ph/0510038
 
* Random matrices and determinantal processes http://arxiv.org/abs/math-ph/0510038
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<h5>history</h5>
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==history</h5>
  
 
* 1920-30 studied by statisticians
 
* 1920-30 studied by statisticians
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<h5>related items</h5>
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==related items</h5>
  
* [[non-intersecting paths]][[3091026|]]
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* [[non-intersecting paths]][[3091026|3091026]]
 
* [[Macdonald theory]]
 
* [[Macdonald theory]]
 
* [http://pythagoras0.springnote.com/pages/4161721 리만가설]
 
* [http://pythagoras0.springnote.com/pages/4161721 리만가설]
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<h5>books</h5>
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==books</h5>
  
 
* Large random matrices: lectures on macroscopic asymptotics [http://www.mathematik.uni-muenchen.de/%7Elerdos/SS09/Random/guionnetcours.pdf http://www.mathematik.uni-muenchen.de/~lerdos/SS09/Random/guionnetcours.pdf]
 
* Large random matrices: lectures on macroscopic asymptotics [http://www.mathematik.uni-muenchen.de/%7Elerdos/SS09/Random/guionnetcours.pdf http://www.mathematik.uni-muenchen.de/~lerdos/SS09/Random/guionnetcours.pdf]
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<h5>expositions</h5>
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==expositions</h5>
  
 
* Random matrices as a paradigm
 
* Random matrices as a paradigm
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<h5>question and answers(Math Overflow)</h5>
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==question and answers(Math Overflow)</h5>
  
 
* http://mathoverflow.net/search?q=
 
* http://mathoverflow.net/search?q=
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<h5>blogs</h5>
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==blogs</h5>
  
 
*  구글 블로그 검색<br>
 
*  구글 블로그 검색<br>
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<h5>experts on the field</h5>
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==experts on the field</h5>
  
 
* http://arxiv.org/
 
* http://arxiv.org/
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<h5>links</h5>
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==links</h5>
  
 
* [http://detexify.kirelabs.org/classify.html Detexify2 - LaTeX symbol classifier]
 
* [http://detexify.kirelabs.org/classify.html Detexify2 - LaTeX symbol classifier]

2012년 10월 28일 (일) 14:57 판

==introduction

  • The ensembles of random matrices obtained are called Gaussian Orthogonal (GOE), Unitary (GUE), and Symplectic (GSE) Ensembles for = 1, = 2, and = 4 respectively.
  • Catalan numbers and random matrices

 

 

==random self-adjoint matrices

  • Wigner matrices
  • Band magtrices
  • Wishart matrix
  • Heavy tails matrices
  • Adjacency matrix of Erdos-Renyi graph

 

 

==Gaussian Wigner matrices

 

 

==Gaussian Unitary Ensemble(GUE) hypothesis

  • Wigner's work on neutron scattering resonances
  • Hugh Montgomety and Freeman Dyson
    • pair correlation function of zeroes of riemann zeta function
  • GUE is a big open problem but proven for random matrix models
  • GUE Tracy-Widom distribution
    • eigenvalue distributions of the classical Gaussian random matrices ensembles
    • distribution of their largest eigenvalue in the limit of large matrices
    • \(q''(s)=sq(s)+2q(s)^3\) Painleve II equation
      \(F_2(s)=\exp\left(-\int_{s}^{\infty}(x-s)q^2(x)dx\right)\)
      \(F_1(s)=\exp\left(-\frac{1}{2}\int_{s}^{\infty}q(x)dx\right)F_2(s)^{1/2}\)
      \(F_4(s/\sqrt{2})=\cosh\left(\frac{1}{2}\int_{s}^{\infty}q(x)dx\right)F_2(s)^{1/2}\)

 

 

 

==determinantal processes

 

 

==history

 

 

==related items

 

 

encyclopedia

 

 

==books

 

 

==expositions

 

 

articles

 

 

==question and answers(Math Overflow)

 

 

==blogs

 

 

==experts on the field

 

 

==links