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Jan 31, 2021 at 21:26 vote accept glS
Jan 31, 2021 at 20:50 history edited Adam Zalcman CC BY-SA 4.0
added 61 characters in body
Jan 31, 2021 at 17:06 history bumped CommunityBot This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
Oct 3, 2020 at 16:08 history bumped CommunityBot This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
Sep 7, 2020 at 10:12 comment added Markus Heinrich What I actually meant was that inverting is trivial for $|u\rangle\langle v|$, thus for any matrix $M=\sum_k x_k |u_k\rangle\langle v_k|$ the associated superoperator has to be $\Phi(X) = \sum_k x_k U_k X V_k^\dagger$ (operators not necessarily unitary). The only thing to justify is the inversion formula Eq. (2), which you already did in you first post.
Sep 7, 2020 at 9:46 comment added Markus Heinrich It is clear how the inverse should look like on rank-one matrices $|u\rangle\langle u|$, or even more generally $|u\rangle\langle v|$. Thus, one only needs to check that Eq. (3) gives the right result for those which is straightforward. The general result follows via a decomposition into those (e.g. SVD for general matrices). But that's basically what you did.
Sep 7, 2020 at 8:42 comment added glS @MarkusHeinrich can you expand as to which part exactly follows from linearity?
Sep 7, 2020 at 8:06 comment added Markus Heinrich This follows from linearity of the isomorphism.
S Sep 3, 2020 at 15:19 answer added glS timeline score: 1
S Sep 3, 2020 at 15:19 history asked glS CC BY-SA 4.0