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Steven G. Johnson
2023-02-19 13:48:55 -05:00
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"# 18.085 Problem Set 2\n",
"\n",
"Due Friday **March 3** at 1pm."
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"## Problem 1\n",
"\n",
"**(a)** The eigenvalues of a real *anti-Hermitian* matrix $A = -A^T$ must be \\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_\\_. Derive this by considering $\\overline{x^T} A x$ for an eigenvector $Ax = \\lambda x$, and demonstrate it numerically by constructing a random anti-Hermitian matrix `A = randn(n,n); A = A - A'` in Julia and looking at its eigenvalues `using LinearAlgebra; eigvals(A)` for `n=4` and `n=5`. (You might want to try the numerical experiment first if you aren't sure what the answer is.)\n",
"\n",
"**(b)** Suppose $A$ is a $3 \\times 3$ real-symmetric matrix with eigenvalues $\\lambda_1 = -2$, $\\lambda_2 = 3$, and $\\lambda_3 = -1$, with corresponding orthonormal eigenvectors $q_1, q_2, q_3$. In terms of these quantities, give the (full) SVD of $A$.\n",
"\n",
"**(c)** Construct a random $5 \\times 3$ matrix `A = randn(5, 3)` and form a related *real-symmetric* matrix `B = [ 0I A; A' 0I ]`, corresponding to\n",
"$$\n",
"B = \\begin{pmatrix} 0 & A \\\\ A^T & 0 \\end{pmatrix} .\n",
"$$\n",
"Compare the eigenvalues of $B$ (`eigvals(B)`) to the singular values of $A$ (`svdvals(A)`). What do you notice? Explain it by using the SVD $A = U \\Sigma V^T$ to construct eigenvalues and eigenvectors of $B$."
]
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"source": [
"## Problems 2, 3, etc: coming soon"
]
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