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What are the Eigenvalues of a Sum of (Non- Commuting) Random Symmetric Matrices? : A "Quantum Information" Inspired Answer. Alan Edelman Ramis Movassagh July 14, 2011 FOCM Random Matrices

Alan Edelman Ramis Movassagh July 14, 2011 FOCM Random Matrices

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What are the Eigenvalues of a Sum of (Non-Commuting) Random Symmetric Matrices? : A "Quantum Information" Inspired Answer. Alan Edelman Ramis Movassagh July 14, 2011 FOCM Random Matrices. Example Result p=1  classical probability p=0 isotropic convolution (finite free probability). - PowerPoint PPT Presentation

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Page 1: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

What are the Eigenvalues of a Sum of (Non-Commuting) Random Symmetric Matrices? : A "Quantum Information" Inspired Answer.

Alan EdelmanRamis Movassagh

July 14, 2011FOCM Random Matrices

Page 2: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Example Resultp=1 classical probabilityp=0 isotropic convolution (finite free probability)

We call this “isotropic entanglement”

Page 3: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Simple Question

The eigenvalues of

where the diagonals are random, and randomly ordered. Too easy?

Page 4: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Another Question

where Q is orthogonal with Haar measure. (Infinite limit = Free probability)

The eigenvalues of

T

Page 5: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Quantum Information Question

where Q is somewhat complicated. (This is the general sum of two symmetric matrices)

The eigenvalues of

T

Page 6: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Preview to the Quantum Information Problem

mxm nxn mxm nxn

Summands commute, eigenvalues addIf A and B are random eigenvalues are classical sum of random variables

Page 7: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Closer to the true problem

d2xd2 dxd dxd d2xd2

Nothing commutes, eigenvalues non-trivial

Page 8: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Actual Problem Hardness =(QMA complete)

di-1xdi-1 d2xd2 dN-i-1xdN-i-1

The Random matrix could be Wishart, Gaussian Ensemble, etc (Ind Haar Eigenvectors)The big matrix is dNxdN

Interesting Quantum Many Body System Phenomena tied to this overlap!

Page 9: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Intuition on the eigenvectors

Classical Quantum Isostropic

Kronecker Product of Haar Measures for A and B

Page 10: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Moments?

Page 11: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Matching Three Moments Theorem

Page 12: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

A first try:Ramis “Quantum Agony”

Page 13: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

The Departure Theorem

A “Pattern Match”

Hardest to Analyze

Page 14: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

The Istropically Entangled Approximation

But this one is hard

The kurtosis

Page 15: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

The convolutions

• Assume A,B diagonal. Symmetrized ordering.

• A+B:

• A+Q’BQ:

• A+Qq’BQq

(“hats” indicate joint density is being used)

Page 16: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

The Slider Theorem

p only depends on the eigenvectors! Not the eigenvalues

Page 17: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Wishart

Page 18: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices
Page 19: Alan Edelman Ramis Movassagh July 14, 2011 FOCM  Random Matrices

Summary