pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry

Autor: Anton Andreev, Grégoire Cattan, Sylvain Chevallier, Quentin Barthélemy
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Research Ideas and Outcomes, Vol 9, Iss , Pp 1-8 (2023)
Druh dokumentu: article
ISSN: 2367-7163
DOI: 10.3897/rio.9.e101006
Popis: Quantum computing is a promising technology for machine learning, in terms of computational costs and outcomes. In this work, we intend to provide a framework that facilitates the use of quantum machine learning in the domain of brain-computer interfaces – where biomedical signals, such as brain waves, are processed.To this end, we integrated Qiskit, a well-known quantum library, with pyRiemann, a framework for the analysis of biomedical signals using Riemannian Geometry. In this paper, we describe our approach, the main elements of our implementation and our research directions. A key result is the creation of a standardised pipeline (QuantumClassifierWithDefaultRiemannianPipeline) for the binary classification of brain waves. The git repository reported in this paper also contains a complete test suite and examples to guide practitioners. We believe that this software will enable further research on the joint field of brain-computer interfaces and quantum computing.
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