Variational quantum and quantum-inspired clustering
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 devices. The idea of the algorithm relies on reducing the clu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-39771-6 |
| _version_ | 1797576640904036352 |
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| author | Pablo Bermejo Román Orús |
| author_facet | Pablo Bermejo Román Orús |
| author_sort | Pablo Bermejo |
| collection | DOAJ |
| description | 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 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. |
| first_indexed | 2024-03-10T21:55:43Z |
| format | Article |
| id | doaj.art-9eb0a68c38c64922af8a8a5060460ba2 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T21:55:43Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-9eb0a68c38c64922af8a8a5060460ba22023-11-19T13:08:27ZengNature PortfolioScientific Reports2045-23222023-08-011311710.1038/s41598-023-39771-6Variational quantum and quantum-inspired clusteringPablo Bermejo0Román Orús1Multiverse ComputingMultiverse ComputingAbstract 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.https://doi.org/10.1038/s41598-023-39771-6 |
| spellingShingle | Pablo Bermejo Román Orús Variational quantum and quantum-inspired clustering Scientific Reports |
| title | Variational quantum and quantum-inspired clustering |
| title_full | Variational quantum and quantum-inspired clustering |
| title_fullStr | Variational quantum and quantum-inspired clustering |
| title_full_unstemmed | Variational quantum and quantum-inspired clustering |
| title_short | Variational quantum and quantum-inspired clustering |
| title_sort | variational quantum and quantum inspired clustering |
| url | https://doi.org/10.1038/s41598-023-39771-6 |
| work_keys_str_mv | AT pablobermejo variationalquantumandquantuminspiredclustering AT romanorus variationalquantumandquantuminspiredclustering |