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.
This is still under development and lacks rigorous tests.
(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/algorithms/mpo_evolution.py:docstring of tenpy.algorithms.mpo_evolution.TimeDependentExpMPOEvolution, line 8.)
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 7.)
- implement or wrap netcon.m, a function to find optimal contractionn sequences
improve helpfulness of Warnings
_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.)
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.)
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.)
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.)
Long term: implement different lattices. Long term: implement variable hopping strengths Jx, Jy.
(The original entry is located in /home/docs/checkouts/readthedocs.org/user_builds/tenpy/checkouts/latest/tenpy/models/hofstadter.py:docstring of tenpy.models.hofstadter, line 3.)
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.)
Right now, for infinite/long range it just limits the number of iterations. In general, we could calculate the exact $X = C + CA + CAA +…$ with the geometric series by solving the set of linear equation $ X(1-A) = C$ for X, (and analogously $(1-A)X = B$ for the right environment RP).
(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.MPOEnvironment.init_LP, line 22.)
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.)
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.)
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.)
provide examples, 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.)
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.)