Proof of Eigenvector Property with Simple Linear Algebra

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SUMMARY

The discussion centers on proving that if x is an eigenvector of matrices A and B with eigenvalues λ and λ2 respectively, then x is also an eigenvector of the matrix C = A + B. The conclusion drawn is that the corresponding eigenvalue for C is the sum of the eigenvalues of A and B, specifically λ + λ2. The proof is established through the linear combination of eigenvectors and the properties of eigenvalues.

PREREQUISITES
  • Understanding of eigenvectors and eigenvalues in linear algebra
  • Familiarity with matrix operations and properties
  • Knowledge of linear combinations of matrices
  • Basic proficiency in solving linear equations
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  • Study the properties of eigenvectors and eigenvalues in detail
  • Learn about linear combinations of matrices and their implications
  • Explore proofs involving eigenvectors in different matrix contexts
  • Investigate the implications of eigenvalue sums in linear transformations
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Students and professionals in mathematics, particularly those studying linear algebra, as well as educators looking for examples of eigenvector properties and proofs.

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Homework Statement


Let x be an eigenvector of A with eigenvalue \lambda and suppose x is also an eigenvector of B, corresponding to the eigenvalue \lambda2. Let C = A + B. Show that x is an eigenvector of C. What is the corresponding eigenvalue?

to the eigenvalue 2


Homework Equations





The Attempt at a Solution



{\lambdaI - A} = {\lambda2I - B}

C = 2{\lambdaI - A}
C is just a linear combination of the first eigenvector so it's got the same eigenvector.

Is this enough to complete the proof?

Is the corresponding eigenvalue just twice the original eigenvalue?
 
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why not just start by examining the product:
Cx
 
Last edited:
Start like this: you know Ax = \lambda x and Bx = \lambda_{2} x from the definition of an eigenvector

Thus Cx = (A + B)x = ... and go from there. I think it will be straightforward.
 

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