Chapter 6: Problem 17
Show that a hermitian operator is positive iff its eigenvalues are positive.
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Chapter 6: Problem 17
Show that a hermitian operator is positive iff its eigenvalues are positive.
These are the key concepts you need to understand to accurately answer the question.
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Consider the matrix $$A=\left(\begin{array}{cc} 2 & 1+i \\\1-i & 3\end{array}\right) .$$ (a) Find the eigenvalues and the orthonormal eigenvectors of A. (b) Calculate the projection operators (matrices) \(\mathrm{P}_{1}\) and \(\mathrm{P}_{2}\) and verify that \(\sum_{i} P_{i}=1\) and \(\sum_{i} \lambda_{i} P_{i}=\mathrm{A} .\) (c) Find the matrices \(\sqrt{\mathrm{A}}, \sin (\theta \mathrm{A})\), and \(\cos (\theta \mathrm{A})\) and show directly that $$\sin ^{2}(\theta \mathrm{A})+\cos ^{2}(\theta \mathrm{A})=1$$ (d) Is A invertible? If so, find \(A^{-1}\) using spectral decomposition of A.
Show that \(\|\mathbf{A} x\|=\left\|\mathbf{A}^{\dagger} x\right\|\) if and only if \(\mathbf{A}\) is normal.
Show that an arbitrary matrix A can be "diagonalized" as \(\mathrm{D}=\) UAV, where \(U\) is unitary and \(D\) is a real diagonal matrix with only nonnegative eigenvalues. Hint: There exists a unitary matrix that diagonalizes \(\mathrm{AA}^{\dagger}\).
Show that (a) the coefficient of \(\lambda^{N}\) in the characteristic polynomial of any linear operator is \((-1)^{N}\), where \(N=\operatorname{dim} \mathcal{V}\), and (b) the constant in the characteristic polynomial of an operator is its determinant.
Show that a \(2 \times 2\) rotation matrix does not have a real eigenvalue (and, therefore, eigenvector) when the rotation angle is not an integer multiple of \(\pi\). What is the physical interpretation of this?
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