Unlocking the high dimensional’ potential: Comparative analysis of qubits and qutrits in variational quantum neural networks

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dc.contributor.authorAcar, Erdi
dc.contributor.authorYılmaz, İhsan
dc.date.accessioned2025-01-27T18:53:31Z
dc.date.available2025-01-27T18:53:31Z
dc.date.issued2025
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractQuantum machine learning is a promising research area with great potential. In particular, Variational quantum neural networks (VQNN) have shown high performance in many applications. However, while qubits, which are 2-level quantum systems, are the standard building blocks of quantum computing, the development of qudits, i.e. d-level quantum systems, has opened up new opportunities in VQNNs thanks to many properties such as robustness to noise and more quantum information processing with fewer quantum resources. In this study, we present a comparative analysis of qubits and qutrits (3-level quantum systems) systems performance in VQNNs while also exploring the effect of encoding strategies and entanglement on classifier performance. Our findings contribute to a better understanding the benefits and limitations of using qutrits in VQNN and pave the way for future developments in this field. © 2025 Elsevier B.V.
dc.identifier.doi10.1016/j.neucom.2025.129404
dc.identifier.issn0925-2312
dc.identifier.scopus2-s2.0-85215109984
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.neucom.2025.129404
dc.identifier.urihttps://hdl.handle.net/20.500.12428/12742
dc.identifier.volume623
dc.identifier.wosWOS:001414172900001
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofNeurocomputing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250125
dc.subjectQubit; Qutrit; Variational quantum circuit; Variational quantum neural networks
dc.titleUnlocking the high dimensional’ potential: Comparative analysis of qubits and qutrits in variational quantum neural networks
dc.typeArticle

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