Eigenvectors of a symmetric matrix.

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An nxn symmetric matrix indeed has n linearly independent eigenvectors, even when eigenvalues are not distinct. To prove this, one can demonstrate that if an eigenvalue has multiplicity k, the matrix's rank is (n - k). Establishing the existence of k linearly independent eigenvectors corresponding to the eigenvalue 0 allows for the application of the rank-nullity theorem. This supports the conclusion that symmetric matrices are diagonalizable, as they possess the required number of linearly independent eigenvectors. Therefore, the properties of symmetric matrices ensure their diagonalizability and the independence of their eigenvectors.
chocolatefrog
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Is it true that an nxn symmetric matrix has n linearly independent eigenvectors even for non-distinct eigenvalues? How can we show it rigorously? Basically, I want to prove that if an nxn symmetric matrix has eigenvalue 0 with multiplicity k, then its rank is (n - k). If we can prove that there exist k linearly independent eigenvectors which solve Ax = 0, then we can use the rank-nullity theorem to directly show the result, right?
 
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