Finding Eigenvectors for Two Matrices using the Generalized Jacobi Method

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Discussion Overview

The discussion revolves around the process of finding eigenvectors for two matrices using the Generalized Jacobi Method, specifically in the context of simultaneous diagonalization. Participants explore the implications of simultaneous diagonalizability and the relationships between the matrices involved.

Discussion Character

  • Exploratory
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions how to find an eigenvector for two matrices A and B.
  • Another participant asserts that eigenvectors are specific to each matrix, indicating that A has its own eigenvectors distinct from those of B.
  • A clarification is made regarding the intention to discuss simultaneous diagonalization of the two matrices.
  • One participant argues that simultaneous diagonalization does not affect the procedure for obtaining eigenvectors of A and B.
  • Examples from quantum mechanics are provided to illustrate simultaneous diagonalization, specifically mentioning coordinate operators that commute.
  • A specific example of matrices K and M is presented, with a request to apply the Generalized Jacobi Method to solve the eigensystem problem.
  • Concerns are raised about the inability to simultaneously diagonalize matrices K and M due to their non-commutativity, although the participant expresses uncertainty about their understanding of the Jacobi method.
  • Another example of matrices K and M is introduced, which are shown to commute, suggesting that they can be simultaneously diagonalized.
  • A participant proposes a relationship between matrices M and K, indicating that diagonalization of K could also diagonalize M.

Areas of Agreement / Disagreement

Participants express differing views on the relevance and implications of simultaneous diagonalization, with some asserting it does not affect the eigenvector calculation while others suggest it is crucial. The discussion remains unresolved regarding the conditions under which simultaneous diagonalization can occur.

Contextual Notes

There are limitations regarding the assumptions made about the matrices and the conditions for simultaneous diagonalization, as well as the application of the Generalized Jacobi Method. The discussion does not resolve these mathematical nuances.

hoshangmustafa
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TL;DR
If I have two matrices A and B, how can I find an eigenvector for the two matrices?
If I have two matrices A and B, how can I find an eigenvector for the two matrices?
 
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Eigenvectors belong to a matrix. Matrix A has its eigenvectors. Matrix B has its eigenvectors.
 
Hi,
I meant simultaneous diagonalization of two matrices.
 
I do not think simultaneously diagonalizable matters in procedure of getting eigenvectors of A and B for each.

As examples in QM, x coordinate operator X and y coordinate operator Y are simultaneously diagonarizable.
XY=YX
X has eigenvectors of {|x>}. Y has eigenvectors of {|y>}.

XX^2=X^2X
X^2 has denenerated eigenbectors of |x> and |-x> for eigenvalue x^2
 
Last edited:
Hi,
for example

K=2,1;1,2
M=2,0;0,0
use the generalized Jacobi method to calculate the eigensystem problem
KΦ=λMΦ
 
As KM \neq MK, I am afraid that we cannot simultaneously diagonalize them. I might be wrong due to scarce knowledge on Jacobi method.
 
K=1,-1;-1,1
M=2,1;1,2
 
Then KM=MK. M=K+2I where I is identity matrix. Diagonalization of K by product of unitary matrix ##P, P^{-1}## would also diagonalize M. Why don't you try to get it ?
 

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