What are the singular values of a matrix multiplied by the identity matrix?

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The discussion focuses on determining the singular values of a matrix formed by augmenting a real mxn matrix A with the identity matrix I_n. It is established that the singular values of the combined matrix are expressed as \sqrt{1+\sigma_j^2}, where \sigma_j are the singular values of A. Participants express confusion about deriving this result from the singular value decomposition (SVD) of A. The conversation highlights the need for a clearer understanding of SVD and its application to the augmented matrix. Overall, the thread seeks guidance on the mathematical breakdown of this concept.
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Homework Statement


Let A be a real mxn matrix, m>=n, with singular values \sigmaj.Show that the singular values of (\stackrel{I_{n}}{A}) are equal to \sqrt{1+\sigma_j^2}.


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The Attempt at a Solution


I know that an SVD for A is A = U(\stackrel{\Sigma}{0})v^T and so, the singular values of A are \sigma_j. I have no idea how to break this down. I assume I want to look at an SVD for (\stackrel{I_n}{A}), but I don't know how to figure out that the singular values would be \sqrt{1+\sigma_j^2}. Does anyone have any ideas? Thanks so much.
 
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Also, sorry, I'm having a hard time figuring out how to have it typeset correctly to show you guys what's going on.
 
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Oh wow, thank you so much. It looks great.
 
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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