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Exercise 2.76 #5

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antodbb opened this issue Aug 14, 2019 · 2 comments
Open

Exercise 2.76 #5

antodbb opened this issue Aug 14, 2019 · 2 comments

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@antodbb
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antodbb commented Aug 14, 2019

ex2-76
I'm not sure about the correctness of the formalism, but this is my main idea: extend the smaller bases with null coefficients in the expansion in order to reach a situation similar to that in the standard proof.

@leonardocppn
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Thanks for this solution.

@antoine-bussy
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Unless I'm mistaken, the proof given in the book already works for the case of different dimensions, if you use the general SVD that also applies to non-square matrices: https://en.wikipedia.org/wiki/Singular_value_decomposition
I don't know why Nielsen and Chuang limited to the square matrices case for SVD... Maybe it is easier to prove?

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