masKIT: Ensemble-based gate dropouts for quantum circuits
MasKIT is a framework that provides masking functionality in the context of parameterized quantum circuits (PQC) for PennyLane. It targets scientists and simplifies researching trainability and expressivity of circuits by enabling to dynamically mask gates within the circuit. The framework is designed to act as a drop-in replacement and therefore allows to enhance your existing PennyLane projects with low effort.
The masking is supported on different axes, i.e. layers, wires, parameters, and entangling gates, for different modes, i.e. adding, removing, inverting.
The current version is still in a development stage and therefore does not cover the whole functionality one might imagine for masking PQCs. Please feel invited to submit your contributions and ideas.
Installation
The framework can be installed via pypi:
python -m pip install maskit
Contributing
You love research as much as we do? Anything missing? We welcome all support, whether on bug reports, feature requests, code, reviews, tests, documentation, blog posts, and more. Please have a look at our contribution guidelines.
Contributors ✨
Thanks goes to these wonderful people (emoji key):
 cDenius 💻 🤔 🚧 🐛 👀 |
 Eileen Kuehn 💻 🤔 🚧 ⚠️ 📖 |
 Max Fischer 👀 |
 Niklas Metz 💻 ⚠️ |
This project follows the all-contributors specification. Contributions of any kind welcome!
1 maintainer
Metadata
1 maintainer
Release files for maskit 0.1.0
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