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VictorVanthilt
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VictorVanthilt
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Great addition to the code! I like the new drawings of the derivative operators, they make it way easier to spot which of the operators you need and what you are exactly calculating without having to reverse-engineer the contraction using the @Plansor call.
Is there a definitive answer as to how much faster the new JordanMPO derivatives make things like DMRG?
leburgel
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Looks great! Left some comments, but nothing major.
Co-authored-by: Lander Burgelman <39218680+leburgel@users.noreply.github.com>
leburgel
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This is quite a large refactor of the
derivativesobjects.In particular, I rewrote the hamiltonian derivatives to make use of the particular Jordan block structure, which leads to very large speedups, especially for nearest-neighbor Hamiltonians.
While on the topic, I also immediately specialized a blocktensor type for this Jordan block structure, mostly so this information is stored at the type level, and we don't have to assume that the MPOTensors have the correct properties.
Finally, I also noticed that the
SVDimplementation is a lot slower than theSDDone, so I made this accessible from the relevant algorithms, and restored the default toSDDeverywhere but in the Grassmann implementation. This might lead to spurious LAPACK errors again, but at least this can now be resolved by changing the settings.In principle this could do with some more documentation, but this might be left for a dedicated docs update session...