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Data re-uploading for a universal quantum classifier

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Pérez-Salinas, Adrián, Cervera-Lierta, Alba, Gil-Fuster, Elies, Latorre, José I.·2020·Quantum

DOI 10.22331/q-2020-02-06-226

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Abstract

A single qubit provides sufficient computational capabilities to construct a universal quantum classifier when assisted with a classical subroutine. This fact may be surprising since a single qubit only offers a simple superposition of two states and single-qubit gates only make a rotation in the Bloch sphere. The key ingredient to circumvent these limitations is to allow for multiple data re-uploading . A quantum circuit can then be organized as a series of data re-uploading and single-qubit processing units. Furthermore, both data re-uploading and measurements can accommodate multiple dimensions in the input and several categories in the output, to conform to a universal quantum classifier. The extension of this idea to several qubits enhances the efficiency of the strategy as entanglement expands the superpositions carried along with the classification. Extensive benchmarking on different examples of the single- and multi-qubit quantum classifier validates its ability to describe and classify complex data.

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Authors: Pérez-Salinas, A., Cervera-Lierta, A., Gil-Fuster, E., & Latorre, J. I.
Affiliations: Barcelona Supercomputing Center (ES)
Universitat de Barcelona (ES)
Centre for Quantum Technologies (SG)
ORCID: Pérez-Salinas, Adrián
Cervera-Lierta, Alba
Gil-Fuster, Elies
Latorre, José I.
Venue: Quantum
Publisher: Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
Published: 2020-02-06
Volume: 4
Pages: 226
ISSN: 2521-327X (ISSN-L)
DOI: 10.22331/q-2020-02-06-226
OpenAlex: W2954939433
Cited by: 713
References: 18
Citations by year: 2026: 204 · 2025: 167 · 2024: 121 · 2023: 93 · 2022: 61 · 2021: 57 · 2020: 10
FWCI: 21.70
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: Quantum (publishedVersion, cc-by)
LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (acceptedVersion, cc-by)
arXiv (Cornell University) (submittedVersion)
National University of Singapore (submittedVersion, cc-by)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by)
arXiv (Cornell University) (cc-by)
Bulletin of the American Physical Society
Funders: QuantIC
Barcelona Supercomputing Center
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
Keywords: quantum machine learning, quantum classifiers, data re-uploading, multiqubit entanglement, quantum circuit design, multi-class classification, benchmarking

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Data re-uploading for a universal quantum classifier

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