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[](https://codecov.io/gh/jcmgray/quimb)
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[](https://doi.org/10.21105/joss.00819)
[](https://pypi.org/project/quimb/)
[](https://anaconda.org/conda-forge/quimb)
[`quimb`](https://github.com/jcmgray/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](https://github.com/jcmgray/quimb), and docs are hosted on [readthedocs](http://quimb.readthedocs.io/en/latest/). 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](https://cotengra.readthedocs.io), optimize and draw networks
- use various backend array libraries such as [jax](https://jax.readthedocs.io) and [torch](https://pytorch.org/) via [autoray](https://github.com/jcmgray/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](https://slepc.upv.es/)
- compute various quantities including entanglement measures
- take advantage of [numba](https://numba.pydata.org) accelerations
- stochastically estimate $\mathrm{Tr}f(X)$ quantities
---
The **full documentation** can be found at: [quimb.readthedocs.io](https://quimb.readthedocs.io). Contributions of any sort are very welcome - please see the [contributing guide](https://github.com/jcmgray/quimb/blob/main/.github/CONTRIBUTING.md). [Issues](https://github.com/jcmgray/quimb/issues) and [pull requests](https://github.com/jcmgray/quimb/pulls) are hosted on [github](https://github.com/jcmgray/quimb). For other questions and suggestions, please use the [discussions page](https://github.com/jcmgray/quimb/discussions).
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