WIP: leakage-aware gauge optimization #410
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…inearOperator (not just plain numpy ndarrays)
…frobenius norm computation. Bugfix in test_optools.py.
…lots of in-line comments explaining the logic.
…anch that omitted jac as a keyword argument to scipy.minimize, even if jac was None.
…nt fidelity from the calculation of that metric itself. This makes it easier to reuse the setup code in other metrics. While making this change, also make the setup more efficient by using TensorProduct bases from the beginning.
…imizers. Right now only entanglement fidelity and jtracedist have implementations that can consider leakage. (So there are no leakage-aware metrics for SPAM.)
…dded annotations to all gauage optimization objectives used in the non-LS optimizer, indicating if that particular objective has support for leakage-aware metrics.
… while. The tests only consider when no leakage is modeled. New tests wil be needed for when theres a leakage dimension
… that various gauge optimization functions don`t raise errors.
…robenius distance
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rileyjmurray
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rileyjmurray
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…d-norm expressions or (concave) root-fidelity expressions. Add a "normalize" keyword argument to the various functions for computing(/uncomputing) Jamiolkowski isomorphisms of operation matrices. Added option to return all optimization model variables used in computing diamonddist.
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(I said I'd close this PR due to awful commit history. But then everything fixed itself when I changed the target branch from master to develop. So I'm keeping open.)