# To-Do list¶

You can check https://github.com/tenpy/tenpy/issues for things to be done.

The following list is auto-generated by sphinx, extracting .. todo :: blocks from doc-strings of the code.

Todo

TDVP is currently not implemented with the sweep class.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/algorithms/mps_common.py:docstring of tenpy.algorithms.mps_common.Sweep, line 6.)

Todo

• implement or wrap netcon.m, a function to find optimal contractionn sequences

• _do_trace: trace over all pairs of legs at once. need the corresponding npc function first.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/algorithms/network_contractor.py:docstring of tenpy.algorithms.network_contractor, line 10.)

Todo

This is still a beta version, use with care. The interface might still change.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/algorithms/tdvp.py:docstring of tenpy.algorithms.tdvp, line 12.)

Todo

long-term: Much of the code is similar as in DMRG. To avoid too much duplicated code, we should have a general way to sweep through an MPS and updated one or two sites, used in both cases.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/algorithms/tdvp.py:docstring of tenpy.algorithms.tdvp, line 16.)

Todo

add further terms (e.g. c^dagger c^dagger + h.c.) to the Hamiltonian.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/models/fermions_spinless.py:docstring of tenpy.models.fermions_spinless, line 3.)

Todo

WARNING: These models are still under development and not yet tested for correctness. Use at your own risk! Replicate known results to confirm models work correctly. Long term: implement different lattices. Long term: implement variable hopping strengths Jx, Jy.

Todo

This is a naive, expensive implementation contracting the full network. Try to follow arXiv:1711.01104 for a better estimate; would that even work in the infinite limit?

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/networks/mpo.py:docstring of tenpy.networks.mpo.MPO.variance, line 5.)

Todo

might be useful to add a “cleanup” function which removes operators cancelling each other and/or unused states. Or better use a ‘compress’ of the MPO?

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/networks/mpo.py:docstring of tenpy.networks.mpo.MPOGraph, line 17.)

Todo

Make more general: it should be possible to specify states as strings.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/networks/mps.py:docstring of tenpy.networks.mps.build_initial_state, line 14.)

Todo

One can also look at the canonical ensembles by defining the conserved quantities differently, see [barthel2016] for details. Idea: usual charges on p, trivial charges on q; fix total charge to desired value. I think it should suffice to implement another from_infiniteT.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/networks/purification_mps.py:docstring of tenpy.networks.purification_mps, line 106.)

Todo

test, provide more.

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/simulations/measurement.py:docstring of tenpy.simulations.measurement, line 7.)

Todo

provide examples, document options give user guide

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/simulations/simulation.py:docstring of tenpy.simulations.simulation, line 8.)

Todo

update figure displaying the “layers of TeNPy”

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/simulations/simulation.py:docstring of tenpy.simulations.simulation, line 13.)

Todo

For memory caching with big MPO environments, we need a Hdf5Cacher clearing the memo’s every now and then (triggered by what?).

(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/tools/hdf5_io.py:docstring of tenpy.tools.hdf5_io, line 65.)