Strawberry Fields Documentation



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Strawberry Fields is a full-stack Python library for designing, optimizing, and utilizing photonic quantum computers.


  • High-level functions for solving practical problems including graph and network optimization, machine learning, and chemistry

  • Includes a suite of world-class simulators—based on cutting edge algorithms—to compile and simulate photonic algorithms

  • Train and optimize your quantum programs with our end-to-end differentiable TensorFlow backend

How to cite

If you are doing research using Strawberry Fields, please cite our papers:

Nathan Killoran, Josh Izaac, Nicolás Quesada, Ville Bergholm, Matthew Amy, and Christian Weedbrook. “Strawberry Fields: A Software Platform for Photonic Quantum Computing”, Quantum, 3, 129 (2019).

Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri, Josh Izaac, Nicolás Quesada, Alain Delgado Gran, Maria Schuld, Jeremy Swinarton, Zeid Zabaneh, and Nathan Killoran. “Applications of Near-Term Photonic Quantum Computers: Software and Algorithms”, arxiv:1912.07634 (2019).


If you are having issues, please let us know by posting the issue on our Github issue tracker.

To chat directly with the team designing and building Strawberry Fields, as well as members of our community—ranging from quantum computing researchers, to students, to those just interested in being a part of a rapidly growing industry—you can join our discussion forum and Slack channel.

For more details on contributing or performing research with Strawberry Fields, please see Research and contribution.


Strawberry Fields is free and open source, released under the Apache License, Version 2.0.