Symmetric Matrix Eigenvector Proof

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For a symmetric matrix A, if Ax = λx for a non-zero vector x, then the eigenvalue λ is real. The proof begins by utilizing the property of symmetric matrices, specifically that A equals its transpose. This leads to the conclusion that the inner product (v, Av) is equal to (Av, v), reinforcing the reality of the eigenvalue. Additionally, the real part of the eigenvector x can be shown to be an eigenvector of A. Understanding these properties is crucial for proving the characteristics of eigenvalues and eigenvectors in symmetric matrices.
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Eigenvalue and eigenvector for a symmetric matrix

Homework Statement



Let A be a n by n real matrix with the property that the transpose of A equals A. Show that if Ax = lambda x, for some non-zero vector x in C(n) then lambda is real, and the real part of x is an eigenvector of A.


Homework Equations





The Attempt at a Solution



Since transpose of A equals A, A must be a symmetric matrix. But beyond that, I don't know where to start. Any help would be appreciated!
 
Last edited:
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Can anyone offer any insight?
 
Start out with (\boldsymbol{v},A \boldsymbol{v}). In case this notation is unknown to you it's supposed to represent the complex inner product.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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