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## General Guidelines
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- **Format:** Demos are written as executable Python scripts.
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- **Jupyter Notebook Conversion:** If you prefer writing your demo in a Jupyter notebook, you can convert it to the required executable Python format by following the [Notebook to Demo Converter](https://github.com/PennyLaneAI/qml/tree/master/notebook_converter).
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- **Jupyter Notebook Conversion:** If you prefer writing your demo in a Jupyter notebook, you can convert it to the required executable Python format by following the [Notebook to Demo Converter](https://github.com/PennyLaneAI/demos/tree/master/notebook_converter).
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- **Naming Convention:** All demo directories must be saved in the `demonstrations_v2` directory. For example: `demonstrations_v2/my_demo`.
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- **Frameworks:** New demos should avoid using `autograd` or `TensorFlow`. `JAX` and `PyTorch` are recommended instead. Whenever possible, the use of `lightning.qubit` is also encouraged.
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- **Restructured Text (ReST):** ReST sections can be included anywhere within the script by beginning the comment with 79 hash characters (`#`). These are useful for breaking up large code blocks and providing extensive explanations.
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## Metadata Guidelines
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Every demo requires an accompanying `metadata.json` file located in its directory. This JSON file stores crucial information about the demo. Refer to [this example](https://github.com/PennyLaneAI/qml/blob/master/demonstrations_v2/tutorial_here_comes_the_sun/metadata.json) for the required fields:
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Every demo requires an accompanying `metadata.json` file located in its directory. This JSON file stores crucial information about the demo. Refer to [this example](https://github.com/PennyLaneAI/demos/blob/master/demonstrations_v2/tutorial_here_comes_the_sun/metadata.json) for the required fields:
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- **Filename:** Ensure the file is named `metadata.json`.
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- **Authors:** Ensure that the `"authors"` field is populated with the `"username"` of the author(s) as registered on pennylane.ai. This should match the username provided when creating the bio.
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# Bermejo, Pablo, Paolo Braccia, Antonio Anna Mele, Nahuel L. Diaz, Andrew E. Deneris, Martin Larocca, and M. Cerezo. "Characterizing quantum resourcefulness via group-Fourier decompositions." arXiv preprint arXiv:2506.19696 (2025).
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