Distribution of 2 matrices with the same eigenvalues

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Discussion Overview

The discussion revolves around the relationship between two matrices that share the same eigenvalues, specifically whether they also share the same probability density function (PDF). The context includes theoretical considerations related to matrices with complex Gaussian entries and their distributions.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant questions the meaning of 'PDF' in relation to matrices, suggesting that matrices do not have a widely accepted PDF.
  • Another participant introduces a specific case involving a matrix with i.i.d. complex Gaussian entries and proposes that both matrices follow the complex Wishart distribution, anticipating they share the same nonzero eigenvalues.
  • A different participant challenges the assumption that the nonzero eigenvalues of the two matrices will be the same, pointing out that they have different dimensions and thus different numbers of eigenvalues.
  • In response, a participant asserts that the nonzero eigenvalues are indeed the same and suggests verifying this with MATLAB, while reiterating the question about the equality of their probability density functions.

Areas of Agreement / Disagreement

Participants express differing views on the relationship between the eigenvalues of the matrices and their probability density functions. There is no consensus on whether the matrices share the same PDF, and the discussion remains unresolved.

Contextual Notes

The discussion highlights the dependence on specific definitions and assumptions regarding the properties of matrices and their eigenvalues, as well as the implications for their distributions.

nikozm
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Hi,

I was wondering if two matrices with the same eigenvalues share the same PDF.

Any ideas and/or references would be helpful.
Thanks in advance
 
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You'll have to provide some more information about what you're seeking.
Matrices in general don't have anything that is widely referred to as a 'PDF'.
The only PDF I know is 'probability density function' in probability theory. Is that what you mean? If so, how do you want to relate it to a matrix? Matrices are used in probability theory and statistics in numerous different ways.
 
Hello,

Assume that H is a n \times m matrix with i.i.d. complex Gaussian entries each with zero mean and variance \sigma. Also, let n>=m. I ' m interested in finding the relation between the distribution of HHH and HHH, where H stands for the Hermittian transposition. I anticipate that both follow the complex wishart distribution with the same parameters (since they share the same nonzero eigenvalues), but I m not sure about this.

Any ideas ? Thanks in advance..
 
The matrix ##H^HH## will be ##m\times m## while ##HH^H## will be ##n\times n##. They will have different numbers of eigenvalues. Why do you think the nonzero ones will be the same?
 
Indeed, they have different dimensions. However their non-zero eigenvalues are the same. This is a fact. If you hold reservations about the latter just implement it in Matlab and see with the command eig their corresponding eigenvalues.

My question is: if they also have the same probability density function.
 

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