How Accurate Are the Bounds for Eigenvalues in Circulant Matrices?

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Discussion Overview

The discussion revolves around the accuracy of bounds for eigenvalues in circulant matrices, specifically focusing on two proposed inequalities related to the eigenvalues of an N-by-N circulant matrix A. The scope includes mathematical reasoning and technical exploration of eigenvalue properties.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents an equation for gamma involving the eigenvalues of a circulant matrix and proposes two bounds for the equation.
  • Another participant confirms the validity of the first bound, which states that the arithmetic mean bounds the geometric mean, but challenges the second bound, providing a counterexample.
  • A third participant reiterates the previous points regarding the bounds and introduces a trace identity related to the eigenvalues, questioning its validity for positive integers k.
  • A fourth participant expresses unfamiliarity with the trace identity and supports the challenge to the second bound, suggesting that the proposed relationship may only hold for positive integers.

Areas of Agreement / Disagreement

Participants generally agree on the correctness of the first bound but disagree on the validity of the second bound, which remains contested. The discussion about the trace identity also shows uncertainty regarding its applicability.

Contextual Notes

The discussion includes assumptions about the properties of eigenvalues and the conditions under which the proposed bounds may hold. There is also a lack of consensus on the trace identity's validity for different values of k.

EngWiPy
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Hi,

I have the following equation:

[tex]\gamma=\frac{1}{\frac{1}{N}\sum_{n=1}^N|\lambda_n|^{-2}}[/tex]

where lambdas are the eigenvalues of an N-by-N circulant matrix A.

I used two properties to bound the above equation:

[tex]\frac{1}{N}\sum_{n=1}^N|\lambda_n|^{-2}\geq\left(\prod_{n=1}^N|\lambda_n|^{-2}\right)^{1/N}[/tex]

[tex]\sum_{n=1}^N|\lambda_n|^{-2}\leq\left(\sum_{n=1}^N|\lambda_n|^{2}\right)^{-1}[/tex]

Are these two bounds correct?

Thanks
 
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The first one is a a statement that the arithmetic mean bounds the geometric mean (true).

The second is false - simple example: 2 terms on the left 1 + 2 = 3. Right side is 1/(1+1/2) = 2/3.
 
mathman said:
The first one is a a statement that the arithmetic mean bounds the geometric mean (true).

The second is false - simple example: 2 terms on the left 1 + 2 = 3. Right side is 1/(1+1/2) = 2/3.

But we have the identity for the trace that:

[tex]\sum_{n=1}^N\lambda_n^k=\text{Tr}\left(\mathbf{A}^k\right)\leq\left[\text{Tr}\left(\mathbf{A}\right)\right]^k=\left(\sum_{n=1}^N\lambda_n\right)^k[/tex]

or it just works for k>=1?
 
I am not familiar with the trace equation, but as my example shows, what you propose is just wrong. It may be that your guess is correct, k is positive integer.
 

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