https://github.com/jcmgray/quimb

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quimb is an easy but fast python library for 'quantum information many-body' calculations, focusing primarily on tensor networks. The code is hosted on github, and docs are hosted on readthedocs. Functionality is split in two:

The quimb.tensor module contains tools for working with tensors and tensor networks. It has a particular focus on automatically handling arbitrary geometry, e.g. beyond 1D and 2D lattices. With this you can:

• construct and manipulate arbitrary (hyper) graphs of tensor networks
• automatically contract, optimize and draw networks
• use various backend array libraries such as jax and torch via autoray
• run specific MPS, PEPS, MERA and quantum circuit algorithms, such as DMRG & TEBD

The core quimb module contains tools for reference 'exact' quantum calculations, where the states and operator are represented as either numpy.ndarray or scipy.sparse matrices. With this you can:

• construct operators in complicated tensor spaces
• find groundstates, excited states and do time evolutions, including with slepc