Solution

ID: past-exam-of-the-algebra-analysis-and-differential-equations-1-course-of-the-university-of-oxford/2009/2/solution

A self-adjoint operator satisfies for every . The finite-dimensional finite-dimensional spectral theorem gives an orthonormal basis of eigenvectors and real eigenvalues; eigenvectors for distinct eigenvalues are orthogonal. Consequently a matrix represents a self-adjoint transformation in some, possibly nonorthonormal, basis exactly when it is diagonalizable with real eigenvalues.
For , the eigenvalues are , all distinct and real. Eigenvectors are , , and . Thus can represent a self-adjoint transformation after choosing a suitable basis.
For , the eigenvalue one has algebraic multiplicity two but its eigenspace has dimension one. The lower block is a nontrivial Jordan block, so the matrix is not diagonalizable. Hence cannot represent a self-adjoint transformation in any basis.
For , the eigenspace for two is spanned by and , and the eigenvalue-one eigenspace is spanned by . These three vectors form an eigenbasis. Therefore can represent a self-adjoint transformation. To see sufficiency on the given inner product space, first define the real diagonal transformation in an orthonormal basis and then apply the inverse of a diagonalizing basis change to obtain the requested matrix. Symmetry of the displayed matrix itself would be required only for an orthonormal representing basis.

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