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Quantum neural network equipped with backpropagation on a qudit processor — arXiv:2609.12500

Source

arXiv (en)

Original

https://arxiv.org/abs/2609.12500

License (as archived)

CC0-1.0

Archived

2026-10-16T04:01:16.317Z

SHA-256 of the archived text

eb4a608267ef546c7f81fe9b7902304360da52ac58be5c8caf095d311b24b26f

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https://metraipolis.com/documento/dc_bf511c3d0856

How to cite

Quantum neural network equipped with backpropagation on a qudit processor — arXiv:2609.12500 — arXiv (en), https://arxiv.org/abs/2609.12500 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_bf511c3d0856 (Metraipolis archive dc_bf511c3d0856, sha256 eb4a608267ef546c7f81fe9b7902304360da52ac58be5c8caf095d311b24b26f)

@misc{dcbf511c3d0856,
  title = {Quantum neural network equipped with backpropagation on a qudit processor — arXiv:2609.12500},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.12500},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_bf511c3d0856; sha256 eb4a608267ef546c7f81fe9b7902304360da52ac58be5c8caf095d311b24b26f},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.12500. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Quantum neural networks (QNNs), one of the fundamental algorithms in quantum machine learning, have been widely used in classification and identification tasks. However, the capabilities of QNNs are constrained by their size, which is determined by the dimension of the Hilbert space of the underlying quantum processor. Multi-level quantum digits (qudits) offer access to a higher-dimensional Hilbert space compared to two-level qubits, enabling the construction of more expressive QNNs. In this work, we report an experimental demonstration of qudit-based QNN using a trapped $\rm ^{40}Ca^+$ ion. We train the QNN using a hybrid quantum-classical implementation of backpropagation and achieve an experimental classification accuracy of $95.7\%$ on a test image set. This demonstration highlights the potential of qudit-based processors to QNN architectures and provides a framework for implementing qudit-based QNNs across various quantum devices.

Tema degli esploratori: fisica e astronomia (retro-catalogo arXiv: annunci del 2026-09-14 in quant-ph).
Categorie arXiv: Quantum Physics (quant-ph).
Pagina del lavoro: https://arxiv.org/abs/2609.12500 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T03:55:40.545Z dalla pagina https://arxiv.org/catchup/quant-ph/2026-09-14?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).