The Tensor Network Python (TeNPy) Library

We present TeNPy [1], a Python library for the simulation of strongly correlated quantum many body systems with the ansatz of tensor networks, and in particular matrix product states (MPS). The library aims to provide a good balance between code readability, easy implementation of custom models and algorithms, and numerical efficiency for large-scale simulations. After a short overview of the features (and limitations) of the library, we demonstrate how to setup the density matrix renormalization group (DMRG) algorithm for a custom model on a long cylinder geometry as a concrete example. Further, we showcase some applications of TeNPy, present benchmarks, and discuss the roadmap for future developments.
[1] https://github.com/tenpy/tenpy