[0.4.0] - 2019-04-28

Backwards incompatible changes

  • The argument order of tenpy.models.lattice.Lattice could be a tuple (priority, snake_winding) before. This is no longer valid and needs to be replaced by ("standard", snake_winding, priority).

  • Moved the boundary conditions bc_coupling from the tenpy.models.model.CouplingModel into the tenpy.models.lattice.Lattice (as bc). Using the parameter bc_coupling will raise a FutureWarning, one should set the boundary conditions directly in the lattice.

  • Added parameter permute (True by default) in tenpy.networks.mps.MPS.from_product_state() and tenpy.networks.mps.MPS.from_Bflat(). The resulting state will therefore be independent of the “conserve” parameter of the Sites - unlike before, where the meaning of the p_state argument might have changed.

  • Generalize and rename tenpy.networks.site.DoubleSite to tenpy.networks.site.GroupedSite, to allow for an arbitrary number of sites to be grouped. Arguments site0, site1, label0, label1 of the __init__ can be replaced with [site0, site1], [label0, label1] and op0, op1 of the kronecker_product with [op0, op1]; this will recover the functionality of the DoubleSite.

  • Restructured callstructure of Mixer in DMRG, allowing an implementation of other mixers. To enable the mixer, set the DMRG parameter "mixer" to True or 'DensityMatrixMixer' instead of just 'Mixer'.

  • The interaction parameter in the tenpy.models.bose_hubbbard_chain.BoseHubbardModel (and tenpy.models.bose_hubbbard_chain.BoseHubbardChain) did not correspond to \(U/2 N (N-1)\) as claimed in the Hamiltonian, but to \(U N^2\). The correcting factor 1/2 and change in the chemical potential have been fixed.

  • Major restructuring of tenpy.linalg.np_conserved and tenpy.linalg.charges. This should not break backwards-compatibility, but if you compiled the cython files, you need to remove the old binaries in the source directory. Using bash cleanup.sh might be helpful to do that, but also remove other files within the repository, so be careful and make a backup beforehand to be on the save side. Afterwards recompile with bash compile.sh.

  • Changed structure of tenpy.models.model.CouplingModel.onsite_terms and tenpy.models.model.CouplingModel.coupling_terms: Each of them is now a dictionary with category strings as keys and the newly introduced tenpy.networks.terms.OnsiteTerms and tenpy.networks.terms.CouplingTerms as values.

  • tenpy.models.model.CouplingModel.calc_H_onsite() is deprecated in favor of new methods.

  • Argument raise_op2_left of tenpy.models.model.CouplingModel.add_coupling() is deprecated.



  • moved toycodes from the folder examples/ to a new folder toycodes/ to separate them clearly.

  • major remodelling of the internals of tenpy.linalg.np_conserved and tenpy.linalg.charges.
    • Introduced the new module tenpy/linalg/_npc_helper.pyx which contains all the Cython code, and gets imported by

    • Array now rejects addition/subtraction with other types

    • Array now rejects multiplication/division with non-scalar types

    • By default, make deep copies of npc Arrays.

  • Restructured lanczos into a class, added time evolution calculating exp(A*dt)|psi0>

  • Warning for poorly conditioned Lanczos; to overcome this enable the new parameter reortho.

  • Simplified call strucutre of extend(), and extend().

  • Restructured tenpy.algorithms.dmrg:

    • run() is now just a wrapper around the new run(), run(psi, model, pars) is roughly equivalent to eng = EngineCombine(psi, model, pars); eng.run().

    • Added init_env() and reset_stats() to allow a simple restart of DMRG with slightly different parameters, e.g. for tuning Hamiltonian parameters.

    • Call canonical_form() for infinite systems if the final state is not in canonical form.

  • Changed default values for some parameters:

    • set trunc_params['chi_max'] = 100. Not setting a chi_max at all will lead to memory problems. Disable DMRG_params['chi_list'] = None by default to avoid conflicting settings.

    • reduce to mixer_params['amplitude'] = 1.e-5. A too strong mixer screws DMRG up pretty bad.

    • increase Lanczos_params['N_cache'] = N_max (i.e., keep all states)

    • set DMRG_params['P_tol_to_trunc'] = 0.05 and provide reasonable …_min and …_max values.

    • increased (default) DMRG accuracy by setting DMRG_params['max_E_err'] = 1.e-8 and DMRG_params['max_S_err'] = 1.e-5.

    • don’t check the (absolute) energy for convergence in Lanczos.

    • set DMRG_params['norm_tol'] = 1.e-5 to check whether the final state is in canonical form.

  • Verbosity of get_parameter() reduced: Print parameters only for verbosity >=1. and default values only for verbosity >= 2.

  • Don’t print the energy during real-time TEBD evolution - it’s preserved up to truncation errors.

  • Renamed the SquareLattice class to tenpy.models.lattice.Square for better consistency.

  • auto-determine whether Jordan-Wigner strings are necessary in add_coupling().

  • The way the labels of npc Arrays are stored internally changed to a simple list with None entries. There is a deprecated propery setter yielding a dictionary with the labels.

  • renamed first_LP and last_RP arguments of MPSEnvironment and MPOEnvironment to init_LP and init_RP.

  • Testing: insetad of the (outdated) nose, we now use pytest <https://pytest.org> for testing.


  • issue #22: Serious bug in tenpy.linalg.np_conserved.inner(): if do_conj=True is used with non-zero qtotal, it returned 0. instead of non-zero values.

  • avoid error in tenpy.networks.mps.MPS.apply_local_op()

  • Don’t carry around total charge when using DMRG with a mixer

  • Corrected couplings of the FermionicHubbardChain

  • issue #2: memory leak in cython parts when using intelpython/anaconda

  • issue #4: incompatible data types.

  • issue #6: the CouplingModel generated wrong Couplings in some cases

  • issue #19: Convergence of energy was slow for infinite systems with N_sweeps_check=1

  • more reasonable traceback in case of wrong labels

  • wrong dtype of npc.Array when adding/subtracting/… arrays of different data types

  • could get wrong H_bond for completely decoupled chains.

  • SVD could return outer indices with different axes

  • tenpy.networks.mps.MPS.overlap() works now for MPS with different total charge (e.g. after psi.apply_local_op(i, 'Sp')).

  • skip existing graph edges in MPOGraph.add() when building up terms without the strength part.