https://github.com/jcmgray/quimb

A python library for quantum information and many-body calculations including tensor networks.
https://github.com/jcmgray/quimb

dmrg entanglement mera peps physics python python3 quantum quantum-circuit quantum-circuit-simulator quantum-computing tebd tensor-network tensor-networks tensors

Last synced: 2 days ago
JSON representation

A python library for quantum information and many-body calculations including tensor networks.

• Host: GitHub
• URL: https://github.com/jcmgray/quimb
• Owner: jcmgray
• License: other
• Created: 2015-12-09T14:02:41.000Z (over 9 years ago)
• Default Branch: main
• Last Pushed: 2025-03-15T08:04:25.000Z (about 1 month ago)
• Last Synced: 2025-04-14T23:16:04.066Z (2 days ago)
• Topics: dmrg, entanglement, mera, peps, physics, python, python3, quantum, quantum-circuit, quantum-circuit-simulator, quantum-computing, tebd, tensor-network, tensor-networks, tensors
• Language: Python
• Homepage: http://quimb.readthedocs.io
• Size: 39.1 MB
• Stars: 536
• Watchers: 15
• Forks: 117
• Open Issues: 64
• Metadata Files:
  • Readme: README.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE.txt

Awesome Lists containing this project

• awesome-quantum-software - quimb - Easy but fast python library for quantum information and many-body calculations, including with tensor networks. (Quantum simulators)

README

        
![quimb logo](https://github.com/jcmgray/quimb/blob/HEAD/docs/_static/logo-banner.png?raw=true)

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[![Documentation Status](https://readthedocs.org/projects/quimb/badge/?version=latest)](http://quimb.readthedocs.io/en/latest/?badge=latest)

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[`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

![tensor pic](https://github.com/jcmgray/quimb/blob/HEAD/docs/_static/rand-tensor.svg?raw=true)

---

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

![matrix pic](https://github.com/jcmgray/quimb/blob/HEAD/docs/_static/rand-herm-matrix.svg?raw=true)

---

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).