Aqora has launched the Aqora Datasets Hub, a platform designed for publishing, discovering, and reusing datasets for reproducible benchmarks and quantum machine learning (QML) experiments. The hub is intended to address the fragmentation in the quantum software landscape by providing a common foundation for experimentation and innovation.
The hub supports a variety of quantum-relevant data types, including graph sets for MaxCut/QAOA, molecular Hamiltonians for VQE, and circuit corpora in OpenQASM 3. The platform provides immutable versions and public or private access, allowing researchers to cite fixed dataset versions for reproducible results. The data can be loaded using standard libraries like pandas or polars, and the platform supports pushdown of column selections and row filters before data transfer.
By providing a dedicated hub for quantum-relevant data, Aqora is bringing a workflow from classical machine learning to quantum research. The hub’s open-source model is intended to encourage contributions from academia, startups, and industry. The platform is designed to formalize the basics of quantum-relevant data so that researchers can focus on algorithms.
Read the full announcement here.
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