Make kraus_to_choi faster by using numpy
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Ericgig
requested changes
Jan 8, 2024
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Thank for for the optimization.
The test failure for 3.6 is due to np.asarray(Qobj) failing with old version of numpy.
We don't want to remove support for older version of python and numpy for v4.
Could you fix it by using Qobj.full as you did in the v5 version.
Other than that, it's looking good.
Other tests failure are not related to your changes.
Ericgig
approved these changes
Jan 8, 2024
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Thanks for merging! |
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Hi @theodotk, the 4.7.4 release is in progress. |
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np.tensordotis faster than a triple loop. On my applications the function became up to 100 times faster.Also, the way to handle
dimsof the Choi matrix was incorrect (or I misunderstood something). It is explained in the comments.This was coded in collab with Rafael Haenel.
Also, please, could you make a release of the qutip 4 with all the new changes after this PR passes?