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Published August 17, 2021 | Version 2
Dataset Open

Supplemental data for "Large-scale quantum machine learning"

  • 1. Imperial College London

Description

This data supports "Large-scale quantum machine learning" by Tobias Haug, Chris N. Self, M. S. Kim (arxiv:2108.01039) https://arxiv.org/abs/2108.01039

Related code can be found in the GitHub repository: (https://github.com/chris-n-self/large-scale-qml). The 'studies' folder here can be dropped inside the code repository in order to run the analysis scripts.

Both 'processed' and 'unprocessed' data is provided. Unprocessed data is the qiskit measurement results for each case study, executed on the IBM Quantum device ibmq_guadalupe and ibmq_toronto. Processed is the Gram matrix evaluated from the measurements and the data vectors needed to fit support vector machine classifiers.

Files

studies.zip

Files (391.7 MB)

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