How Do You Determine Eigenstates and Eigenvalues for a Given Matrix Operator?

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SUMMARY

The discussion focuses on determining eigenstates and eigenvalues for a specific matrix operator represented as a 4x4 matrix. The eigenstate \frac{1}{\sqrt{2}} \left( \begin{array}{cccc}1 & 0 & 1 & 0\end{array} \right) is confirmed as an eigenstate with an eigenvalue of 1 + a. The method for finding additional eigenstates involves using the eigenvalue equation Ax = ax and solving the determinant condition det(A - aI) = 0. The discussion concludes that guessing additional eigenstates based on the matrix structure can be a valid approach.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically eigenvalues and eigenstates.
  • Familiarity with matrix operations and determinants.
  • Knowledge of the eigenvalue equation Ax = ax.
  • Experience with solving linear equations and matrix inversions.
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  • Study the process of calculating determinants for 4x4 matrices.
  • Learn about the characteristic polynomial and its role in finding eigenvalues.
  • Explore methods for finding eigenvectors corresponding to given eigenvalues.
  • Investigate the implications of eigenstates in quantum mechanics and their applications.
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Homework Statement



The matrix representation of an operator is

[tex] <br /> \left(<br /> \begin{array}{cccc}<br /> 1 & 0 & a & 0\\<br /> 0 & 1 & 0 & b\\<br /> a & 0 & 1 & 0\\<br /> 0 & b & 0 & 1\\<br /> \end{array}<br /> \right)<br /> [/tex]

Show that [tex]\frac{1}{\sqrt{2}} \left( \begin{array}{cccc}1 & 0 & 1 & 0\end{array} \right)[/tex] is an eigenstate of the operator and derive its eigenvalue. Give one other eigenstate of the operator with its eigenvalue.

The Attempt at a Solution



I can easily show that [tex]\frac{1}{\sqrt{2}} \left( \begin{array}{cccc} 1 & 0 & 1 & 0 \end{array} \right)[/tex] is the eigenstate of the operator and found that it's eigenvalue is [tex]1+a[/tex]. I however don't understand how to work out the other eigenstates of the operator. Do you have to simply guess the other eigenstates and then check to see if they are correct by checking if it fulfills the condition [Operator][eigenstate]=[eigenvalue][eigenstate] ?, thanks for the help
 
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Well there is a procedure for finding eigenvalues and eigenstates. The eigenvalue equation is Ax=ax <=> (A-aI)x=0 where I is the identity matrix. This has non-trivial solutions if the matrix (A-aI) is not invertible. So the condition for the existence of eigenvalues is det(A-aI)=0 and they are found as the roots of this equation. Once you know the eigenvalues you can find the corresponding eigenvectors by plugging a general vector into the eigenstate equation and solving for the components of the vector.

However, in your case it easy to guess another eigenstate just by looking at the matrix and the given eigenstate. That is obviously a lot easier and sufficient since you aren't asked to derive the vectors.
 

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