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Variational quantum and quantum-inspired clustering
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DOI：10.1038/s41598-023-39771-6.png)
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摘要
En 中文
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 devices. The idea of the algorithm relies on reducing the clustering problem to an optimization, and then solving it via a Variational Quantum Eigensolver 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.
Keyword:
TENSOR NETWORKS
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期刊
IF:
3.9
论文数:
28.3W
被引数:
83.5W
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引用论文
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NATURE COMMUNICATIONSOAAI
NATURE COMMUNICATIONSIF15.7
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