Merge pull request #82 from AnonSar/master

Add Black Opal, Boulder Opal and Fire Opal
This commit is contained in:
Desiree 2023-08-12 13:02:11 +10:00 committed by GitHub
commit 441a8cd438
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 3 additions and 0 deletions

View File

@ -25,6 +25,7 @@ For further resources related to Open Source Quantum Software Projects, please c
## Learning
- [An Interactive Introduction to Quantum Computing](https://davidbkemp.github.io/QuantumComputingArticle/) - Interactive learning for quantum gate computing by David Kemp.
- [Black Opal](https://q-ctrl.com/black-opal) - An interactive platform for learning the fundamentals of quantum computing.
- [CNOT](https://cnot.io/) - Easy to understand, step by step introduction to quantum computing concepts.
- [Chris Ferrie](https://csferrie.medium.com/) - Univeristy Professor in Sydney, Australia, author of Quantum Computing for babies (and many more) as well as excellent Quantum Computing lectures on Medium.
- [Documentation for Forest and pyQuil](http://pyquil.readthedocs.io/en/latest/) - Tutorials for Rigetti Computing's SDK.
@ -74,8 +75,10 @@ For further resources related to Open Source Quantum Software Projects, please c
- [Amazon Braket](https://aws.amazon.com/braket/) - Fully managed service providing a development environment to run quantum circuits on quantum simulators and computers.
- [Blueqat](https://github.com/Blueqat/Blueqat) - Software development kit in Python for quantum gate computing.
- [Boulder Opal](https://q-ctrl.com/boulder-opal) - Python toolset for automating and optimizing quantum hardware performance.
- [Cirq](https://github.com/quantumlib/Cirq) - Python library for writing, manipulating, and optimizing NISQ circuits to run on quantum computers.
- [Covalent](https://github.com/AgnostiqHQ/covalent) - Framework for distributed computing on heterogeneous infrastructure from CPUs to GPUs to quantum computers.
- [Fire Opal](https://q-ctrl.com/fire-opal) - Python package for improving the quality of quantum algorithm results.
- [IBM Quantum Experience](https://quantum-computing.ibm.com) - Online quantum composer to run experiments on real quantum computing hardware.
- [Mitiq](https://mitiq.readthedocs.io/) - Python toolkit for implementing error mitigation techniques on quantum computers.
- [NISQAI](https://github.com/quantumai-lib/nisqai) - Library for performing quantum artificial intelligence on near-term quantum computers.