Skip to content

elicharlese/amazon-braket-algorithm-library

 
 

Repository files navigation

Amazon Braket Algorithm Library

Build

The Braket Algorithm Library provides Amazon Braket customers with pre-built implementations of prominent quantum algorithms and experimental workloads as ready-to-run example notebooks.


Currently, Braket algorithms are tested on Linux, Windows, and Mac.

Running notebooks locally requires additional dependencies located in notebooks/textbook/requirements.txt. See notebooks/textbook/README.md for more information.


The Amazon Braket Algorithm Library can be installed from source by cloning this repository and running a pip install command in the root directory of the repository.

git clone https://github.com/aws-samples/amazon-braket-algorithm-library.git
cd amazon-braket-algorithm-library
pip install .

To run the notebook examples locally on your IDE, first, configure a profile to use your account to interact with AWS. To learn more, see Configure AWS CLI.

After you create a profile, use the following command to set the AWS_PROFILE so that all future commands can access your AWS account and resources.

export AWS_PROFILE=YOUR_PROFILE_NAME

Configure your AWS account with the resources necessary for Amazon Braket

If you are new to Amazon Braket, onboard to the service and create the resources necessary to use Amazon Braket using the AWS console.

Support

Issues and Bug Reports

If you encounter bugs or face issues while using the algorithm library, please let us know by posting the issue on our Github issue tracker.
For other issues or general questions, please ask on the Quantum Computing Stack Exchange and add the tag amazon-braket.

Feedback and Feature Requests

If you have feedback or features that you would like to see on Amazon Braket, we would love to hear from you!
Github issues is our preferred mechanism for collecting feedback and feature requests, allowing other users to engage in the conversation, and +1 issues to help drive priority.

License

This project is licensed under the Apache-2.0 License.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 79.4%
  • Python 20.6%