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Variational Quantum and Quantum-Inspired Clustering
- Source :
- Scientific Reports 13, 13284 (2023)
- Publication Year :
- 2022
-
Abstract
- Here we present a quantum algorithm for clustering data based on a variational quantum circuit. The algorithm allows to classify data into many clusters, and can easily be implemented in few-qubit Noisy Intermediate-Scale Quantum (NISQ) devices. The idea of the algorithm relies on reducing the clustering problem to an optimization, and then solving it via a Variational Quantum Eigensolver (VQE) combined with non-orthogonal qubit states. In practice, the method uses maximally-orthogonal states of the target Hilbert space instead of the usual computational basis, allowing for a large number of clusters to be considered even with few qubits. We benchmark the algorithm with numerical simulations using real datasets, showing excellent performance even with one single qubit. Moreover, a tensor network simulation of the algorithm implements, by construction, a quantum-inspired clustering algorithm that can run on current classical hardware.<br />Comment: 5 pages, 3 figures, revised version
- Subjects :
- Quantum Physics
Computer Science - Artificial Intelligence
Subjects
Details
- Database :
- arXiv
- Journal :
- Scientific Reports 13, 13284 (2023)
- Publication Type :
- Report
- Accession number :
- edsarx.2206.09893
- Document Type :
- Working Paper