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Quanlse (量脉) is a cloud-based platform for quantum control developed by the Institute for Quantum Computing at Baidu Research. Quanlse aims to bridge the gap between quantum software and hardware. It provides efficient and professional quantum control solutions via an open-source SDK strengthened by Quanlse Cloud Service.

Quanlse supports the pulse generation and scheduling of arbitrary single-qubit and two-qubit gates. With the help of toolkits in Quanlse, one can also use Quanlse for modeling physical devices, simulating dynamical evolution, and visualizing error analysis. More interestingly, users can achieve pulse-level control of quantum algorithms using Quanlse. Furthermore, Quanlse also supports advanced research and development (R&D) in the field of quantum control.


We strongly recommend using Anaconda for your R&D environment and upgrading the requirements to the latest versions for the best experience.

Install via pip

We recommend the following way of installing Quanlse with pip,

pip install Quanlse

Download and install via GitHub

You can also download all the files and install Quanlse locally,

git clone http://github.com/baidu/Quanlse
cd Quanlse
pip install -e .

Run programs

Now, you can try to run a program to verify whether Quanlse has been installed successfully.

cd Example
python 1-Example-Pi-Pulse.py

Introduction and developments


To get started with Quanlse, users are recommended to go through the Overview firstly to acquire the whole picture of this platform. Quick Start could then be a good place to guide you on how to use Quanlse Cloud Service step by step and how to construct your first program using Quanlse. Next, users are encouraged to learn more functions and applications from the tutorials Quanlse provided. Finally, it would be great if users could solve their own problems using Quanlse. For complete and detailed documentation of the Quanlse API, please refer to our API documentation.


Quanlse provides detailed and comprehensive tutorials from fundamental to advanced topics. Each tutorial currently supports reading on our website. For interested developers, we recommend them to download Jupyter Notebooks and play with it. The tutorial list is as follows:

In addition, Quanlse also supports quantum control for nuclear magnetic resonance (NMR) quantum computing. For more information about QuanlseNMR, please refer to the tutorial: QuanlseNMR.


Users are encouraged to contact us through Github Issues or quanlse@baidu.com with general questions, bugs, and potential improvements. We hope to make Quanlse better together with the community!

Frequently Asked Questions

Q: How should I get started with Quanlse?

A: We recommend users go to our website and follow the roadmap.

Q: What should I do when I run out of my credit points?

A: Please contact us on Quantum Hub. First, you should log into Quantum Hub, then enter the "User Management -> Feedback" page, and input the necessary information (choose "Get More Credit Points"). Submit your feedback and wait for a reply.

Q: How should I cite Quanlse in my research?

A: We encourage developers to use Quanlse to do research & development in the field of quantum control. Please cite us by including BibTeX file.


The changelog of this project can be found in CHANGELOG.md.

Copyright and License

Quanlse uses Apache-2.0 license.


[1] Quantum Computing - Wikipedia.

[2] Nielsen, Michael A., and Isaac L. Chuang. Quantum Computation and Quantum Information: 10th Anniversary Edition. Cambridge: Cambridge UP, 2010. Print.

[3] Werschnik, J., and E. K. U. Gross. "Quantum optimal control theory." Journal of Physics B: Atomic, Molecular and Optical Physics 40.18 (2007): R175.

[4] Wendin, Göran. "Quantum information processing with superconducting circuits: a review." Reports on Progress in Physics 80.10 (2017): 106001.

[5] Krantz, Philip, et al. "A quantum engineer's guide to superconducting qubits." Applied Physics Reviews 6.2 (2019): 021318.

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