Know Eigenvalue and Eigenvector, How Do I Figure Out a Possible Original Matrix?

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SUMMARY

The discussion focuses on reconstructing an original matrix A from its eigenvalues and eigenvectors. It establishes that if matrix A has n independent eigenvectors, the relationship A = P^{-1}DP holds, where P is the matrix of eigenvectors and D is the diagonal matrix of eigenvalues. In cases where A is not diagonalizable, the Jordan Normal Form matrix D is used, which includes eigenvalues on the diagonal and potentially "1"s above the diagonal. Generalized eigenvectors are necessary to complete the matrix P in such scenarios.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with matrix diagonalization
  • Knowledge of Jordan Normal Form
  • Basic linear algebra concepts
NEXT STEPS
  • Study the process of matrix diagonalization in detail
  • Learn about Jordan Normal Form and its applications
  • Explore the concept of generalized eigenvectors
  • Practice reconstructing matrices from eigenvalues and eigenvectors using software tools like MATLAB or Python's NumPy
USEFUL FOR

Students and professionals in mathematics, particularly those studying linear algebra, as well as data scientists and engineers working with matrix computations and transformations.

MikeDietrich
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Homework Statement


This is a general question... I can easily go from a matrix A to its eigenvalues and then eigenvectors but how would I go from the eigenvalues and eigenvectors to a feasible original matrix?

Any thoughts appreciated!
 
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Start with how are the original matrix A and the diagonal matrix D related and then solve for A.
 
To expand on vela's response- presumably you know that if A has n independent eigenvectors (where A is an n by n matrix) then, with P the matrix having those eigenvectors as columns, PAP^{-1}= D where D is the diagonal matrix with the eigenvalues of A on the diagonal. From that, A= P^{-1}DP. If you are given the eigenvalues and eigenvectors of A, you can form both P and D from that information and so find A.

If A is not diagonalizable (does not have n independent eigenvectors), then it is a little harder but the same idea- D will be the Jordan Normal Form matrix with eigenvalues along the diagonal and possibly "1"s above the diagonal. There will be fewer than n eigenvectors so you will have to supplement them with "generalized eigenvectors" to form the matrix P. Fortunately, the generalized eigenvectors of A are the same as those of D so that can be done.
 

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