Note that the mkl and mkl-devel packages (and cython) needs to be installed in the environment for TeNPy to be compiled against MKL for faster performance, see https://tenpy.readthedocs.io/en/latest/install/extra.html I'm not sure of the best way to incorporate this. It works fine without it, but power users need to make sure that TeNPy is compiled optimally.

Note that by default, i.e. after running pip install physics-tenpy, the cython code will be compiled, but the numpy/scipy versions will be linked against OpenBLAS, and not MKL. It seems debatable whether MKL is better than OpenBLAS. If we did want MKL, it is better to use conda rather than pip, since conda ships numpy/scipy packages linked against MKL (and these packages are maintained). pip does have packages like intel-numpy and intel-scipy but these packages are out-of-date (i.e. do not support the latest python version).

I think that this issue transcends tenpy and becomes a more general question of whether or not to link numpy/scipy against MKL, which is a matter of personal preference. Therefore, I suggest that we leave this as is.

Thank you Bart! I'll begin with some high-level comments that will involve some code restructuring.

Thank you for reviewing this! 😃 I will implement these changes asap