All notable changes to the project will be documented in this file. The project adheres semantic versioning


Backwards incompatible changes


  • grid_concat() allows for None entries (representing zero blocks).



[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 This is no longer valid and needs to be replaced by ("standard", snake_winding, priority).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 to, 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 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

  • 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);

    • 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 <> 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.


[0.3.0] - 2018-02-19

This is the first version published on github.


  • Cython modules for np_conserved and charges, which can optionally be compiled for speed-ups

  • tools.optimization for dynamical optimization

  • Various models.

  • More predefined lattice sites.

  • Example toy-codes.

  • Network contractor for general networks


  • Switch to python3


  • Python 2 support.

[0.2.0] - 2017-02-24

  • Compatible with python2 and python3 (using the 2to3 tool).

  • Development version.

  • Includes TEBD and DMRG.

Changes compared to previous TeNPy

This library is based on a previous (closed source) version developed mainly by Frank Pollmann, Michael P. Zaletel and Roger S. K. Mong. While allmost all files are completely rewritten and not backwards compatible, the overall structure is similar. In the following, we list only the most important changes.

Global Changes

  • syntax style based on PEP8. Use $>yapf -r -i ./ to ensure consitent formatting over the whole project. Special comments # yapf: disable and # yapf: enable can be used for manual formatting of some regions in code.

  • Following PEP8, we distinguish between ‘private’ functions, indicated by names starting with an underscore and to be used only within the library, and the public API. The puplic API should be backwards-compatible with different releases, while private functions might change at any time.

  • all modules are in the folder tenpy to avoid name conflicts with other libraries.

  • withing the library, relative imports are used, e.g., from import (toiterable, tonparray) Exception: the files in tests/ and examples/ run as __main__ and can’t use relative imports

    Files outside of the library (and in tests/, examples/) should use absolute imports, e.g. import tenpy.algorithms.tebd

  • renamed tenpy/mps/ to tenpy/networks, since it containes various tensor networks.

  • added Site describing the local physical sites by providing the physical LegCharge and onsite operators.


  • pure python, no need to compile!

  • in module tenpy.linalg instead of algorithms/linalg.

  • moved functionality for charges to charges

  • Introduced the classes ChargeInfo (basically the old q_number, and mod_q) and LegCharge (the old qind, qconj).

  • Introduced the class LegPipe to replace the old leg_pipe. It is derived from LegCharge and used as a leg in the array class. Thus any inherited array (after tensordot etc still has all the necessary information to split the legs. (The legs are shared between different arrays, so it’s saved only once in memory)

  • Enhanced indexing of the array class to support slices and 1D index arrays along certain axes

  • more functions, e.g. grid_outer()


  • Introduced TruncationError for easy handling of total truncation error.

  • some truncation parameters are renamed and may have a different meaning, e.g. svd_max -> svd_min has no ‘log’ in the definition.


  • separate Lanczos module in tenpy/linalg/. Strangely, the old version orthoganalized against the complex conjugates of orthogonal_to (contrary to it’s doc string!) (and thus calculated ‘theta_o’ as bra, not ket).

  • cleaned up, provide prototypes for DMRG engine and mixer.


  • added, which contains ‘random stuff’ from old tools.math like to_iterable and to_array (renamed to follow PEP8, documented)

  • moved stuff for fitting to

  • enhanced for nice formatting

  • moved (parts of) old cluster/ to

  • added for a simplified handling of parameter/arguments for models and/or algorithms. Similar as the old models.model.set_var, but use it also for algorithms. Also, it may modify the given dictionary.