Find the symmetric matrix from eigen vectors

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Discussion Overview

The discussion revolves around finding a symmetric matrix A from given orthogonal eigenvectors represented in matrix H. Participants explore the relationship between eigenvectors, eigenvalues, and the construction of matrix A, addressing both theoretical and practical aspects of the problem.

Discussion Character

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

Main Points Raised

  • Michael inquires about deriving matrix A from the orthogonal eigenvectors in matrix H.
  • One participant suggests writing the eigenvectors as columns of matrix A and analyzing the transformation of a specific vector.
  • Another participant questions the notation and the choice of the vector [1,0].
  • A participant assumes that matrix A should be symmetric due to the orthogonality of the eigenvectors.
  • There is a discussion about the lack of fixed eigenvalues, leading to an infinite number of matrices with the same eigenvectors but different eigenvalues.
  • One participant proposes using the relationship between the eigenvalues and the eigenvectors to derive equations for the parameters of matrix A.
  • A later reply details the process of obtaining equations for the eigenvalues based on the structure of matrix A and the eigenvectors.
  • Another participant claims to have solved the problem, providing a specific form for matrix A and a relationship for parameter b in terms of a and d.
  • The solution includes a validation step using statistical programming in R to confirm the results.

Areas of Agreement / Disagreement

Participants express differing views on the necessity of fixed eigenvalues, with some arguing that without them, the matrix cannot be uniquely determined. The discussion remains unresolved regarding the implications of not having fixed eigenvalues.

Contextual Notes

Participants note that the absence of fixed eigenvalues introduces significant freedom in determining matrix A, leading to multiple valid matrices that share the same eigenvectors.

mihalisla
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Hello to all of you,

Is there a way to get the matrix A=[a b c d] from the eigenvectors (orthogonal) matrix
H= sin(x) cos(x)
cos(x) -sin(x)
or to pose it differently to find a matrix that has these 2 eigenvectors ?

Thank you in advance .
Michael
 
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Just write the eigenvectors as columns of your matrix and watch what A*(1,0)^T does.
 
^T is the transpose? and why [1,0]? thanks!
 
I have made the assumption that matrix A should be symmetric because of the orthogonality of eigen vectors matrix! is this true? so matrix A = (a,b ;b, d) rows separated by ;
 
Oh sorry, ignore my first post.
Do you have fixed eigenvalues for those eigenvectors? Otherwise, there is a lot of freedom: all multiplies of the identity matrix (including the identity matrix) have all vectors as eigenvectors, for example.
With fixed eigenvalues, I get 4 equations for 4 unknown parameters, so I would expect that there is a unique solution.
 
no there are not fixed eigen values! how do I proceed?
 
If you don't know the eigenvalues, it is impossible to find the matrix. There are an infinite number of matrices having the same eigenvectors but different eigenvalues.
If D is the diagonal matrix, having the eigenvalues on the main diagonal and A is the matrix having the corresponding eigenvectors of the matrix as columns then [tex]ADA^{-1}[/tex] is the matrix having those eigenvalues and eigenvectors.
 
I started from the eq A*H.1= lamda1*H.1 where H.1 is the first column of H (the A matrix of user HallsofIvy) .
Then I did the same for lamda2 (the second eigen value that is unknown) and I got lamda1=]a*sin(x)+b*cos(x)]/sin(x) and another value lamda1=[b*sin(x)+d*cos(x)]/cos(x).
Also two values for lamda2.
Should I try to get 4 equations for the four pairs of lamda1 and lamda2 doing A=H*L*H^-1?
my main objective is to set a,b,d from A as functios of sin and cos and not set numbers I suppose. . .
 
Solved

Problem solved !
Matrix A=[a ,b]
[b, d]
From A*H.1=lamda1*H.1 I took
lamda1=(a*sin(x)+b*cos(x))/sin(x)
and lamda1=(b*sin(x)+d*cos)/cos(x)

From A*H.2=lamda2*H.2 I took
lamda2=(a*cos(x)-b*sin(x))/cos(x)
and lamda2=(d*sin(x)-b*cos(x))/sin(x)

For each set of lamda(i) i=1,2
i do next [A-lamda(i)]*H.i=0
All four sets of equations give me with free a ,d

b=((a-d)*cos(x)*sin(x))/(sin(x)^2-cos(x)^2)

It must be cos(x),sin(x) and sin(x)^2-cos(x)^2 not equal to zero

Thus matrix A takes the form A= a b=((a-d)*cos(x)*sin(x))/(sin(x)^2-cos(x)^2)

b=((a-d)*cos(x)*sin(x))/(sin(x)^2-cos(x)^2) d

(This is a square symmetric matrix )

In statistical program R i wrote a small script so as to validate the results

Code:
#test1

x=(pi)
a=7
d=1
b=((a-d)*cos(x)*sin(x))/(sin(x)^2-cos(x)^2)

l1=(a*sin(x)+b*cos(x))/sin(x)
l2=(a*cos(x)-b*sin(x))/cos(x)
  
A=matrix(c(a,b,b,d),2,2)
H=matrix(c(sin(x),cos(x),cos(x),-sin(x)),2,2)
L=matrix(c(l1,0,0,l2),2,2)
#it must be A*H=H*L where L is the diagonial matrix with lamda1 and lamda2 as l1 and l2 #respectively 

A%*%H
H%*%L

#here I get A from H*L*H^-1
H%*%L%*%ginv(H)
#here I get A from H*L*H^T
H%*%L%*%t(H)
A
 
Last edited:
  • #10
I have one more but i ll post it in new thread !
P.S I m new here so posting the solution is good , isn't it ?
 

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