How can I analyse and classify a matrix?

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Discussion Overview

The discussion revolves around the analysis and classification of a matrix associated with an ordinary differential equation (ODE) that yields complex eigenvalues and eigenvectors. Participants explore the implications of these properties in the context of stability analysis within a Hilbert space, as well as the challenges of classifying the matrix given its non-Hermitian nature.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant notes that the stability properties of the matrix can be inferred from the position of its eigenvalues in the complex plane, where a modulus greater than 1 indicates exponential growth.
  • Another participant questions whether the presence of complex eigenvalues limits the classification of the matrix, given its non-Hermitian, non-unitary, and non-skew Hermitian characteristics.
  • A suggestion is made to describe the matrix in terms of its individual eigenvalues and eigenvectors, as well as to examine its separability and condition number, although uncertainty exists regarding the condition number due to the matrix's non-normality.
  • One participant describes their attempt to derive eigenvalues from a matrix that includes operators, expressing confusion about the regular procedure for solving secular equations in this context.
  • There is a discussion about using singular value decomposition (SVD) to measure the condition number, with a note that singular values relate to the magnitudes of eigenvalues in the case of normal matrices.

Areas of Agreement / Disagreement

Participants express differing views on the classification of the matrix and the implications of its complex eigenvalues. There is no consensus on the classification or the methods to analyze the matrix further.

Contextual Notes

Participants mention limitations regarding the condition number due to the matrix's non-normality and the challenges posed by the inclusion of operators in the matrix elements, which complicates the derivation of eigenvalues.

SeM
Hi, I have a matrix of an ODE which yields complex eigenvalues and eigenvectors. It is therefore not Hermitian. How can I further analyse the properties of the matrix in a Hilbert space?
The idea is to reveal the properties of stability and instability of the matrix. D_2 and D_1 are the second and first order derivatives respectively, and a and b are real numbers.
I thought of treating the two operators as x² and x and solve the quadratic equation, however, this does not really give much more information.
 
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The stability properties are indicated by the position of the eigenvalues on the complex plane. A modulus greater than 1 indicates exponential growth when applied to the associated eigenvector. If an eigenvalue is complex, its argument indicates a rotation and a cyclic behavior.
 
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Thanks. Does this imply that there is no more classification I can actually do, given that the eigenvalue is complex, and the Matrix appears as neither hermitian, unitary, norm or Skew Hermitian?
 
It sounds like you are looking for a name to describe your matrix. I'm not aware of any others to try.

If you want to describe the nature of the matrix, you should describe it in terms of the individual eigenvalues and associated eigenvectors. You can describe the dynamic modes of the system. You could examine if the matrix is separable (see https://en.wikipedia.org/wiki/Singular-value_decomposition ). You can also check if the matrix is ill-conditioned. If it was normal, the condition number would be the ratio of the modulus of the largest and smallest eigenvalues. But since it is not normal, I am not sure how to determine the condition number. (see https://en.wikipedia.org/wiki/Condition_number )
 
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Thanks Fastchecker, this was very clear. I have tried to derive the eigenvalues, but given that the matrix contains two numbers and two operators, hence like:

\begin{bmatrix}
D_4 & D_1 \\
i5 & 6 \\
\end{bmatrix}

where D4 is the fourth derivative and D1 is the first derivative, I end up with a secular solution but not based on numbers, but with the operators in the roots. Is this the regular procedure to solve a secular equation with operators and numbers in the elements and if it is, how can one use this result to say something about the matrix? I have only worked with numbers in the elements before, so I am no sure here. Sorry!

In this case there are parts of the secular equation solution which look like:

D4 (x_1x_2), so the fourth derivative of the two eigenvector coordinates multiplied by one another. Does one treat that as D4x^2 , which is 0?

Thanks
 
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FactChecker said:
...(see https://en.wikipedia.org/wiki/Singular-value_decomposition ). You can also check if the matrix is ill-conditioned. If it was normal, the condition number would be the ratio of the modulus of the largest and smallest eigenvalues. But since it is not normal, I am not sure how to determine the condition number. (see https://en.wikipedia.org/wiki/Condition_number )

You mentioned SVD -- just need to make the connection here. As long as we're using an L2/ euclidean norm for measuring variations, use singular values to measure condition number. In the special case of a normal matrix, your singular values map exactly to magnitudes of eigenvalues. In general for square matrices, your largest singular value is always ##\geq ## magnitude of largest eigenvalue and smallest singular values is always ##\leq## smallest eigenvalues magnitude. (why?)
 
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