PreprintCC BY 4.0arXiv
Comment on "Supervised Learning with Quantum Hamiltonian Embeddings" (arXiv:2610.26833)
Abstract
We discuss the relationship between quantum Hamiltonian embeddings (arXiv:2610.26833) and prior developments in Quantum Cognition Machine Learning (QCML), including QCML's earlier implementation on IBM quantum hardware. We consider the novelty claims and the computational role of encoding an entire dataset in a single ground state.
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BibTeX
@misc{abanov2026comment,
title = {{Comment on "Supervised Learning with Quantum Hamiltonian Embeddings" (arXiv:2610.26833)}},
author = {Alexander G. Abanov and Luca Candelori and Kharen Musaelian},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.05105},
eprint = {2611.05105},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.05105},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Comment on "Supervised Learning with Quantum Hamiltonian Embeddings" (arXiv:2610.26833)
AU - Alexander G. Abanov
AU - Luca Candelori
AU - Kharen Musaelian
PY - 2026
DA - 2026/11/03
PB - arXiv
DO - 10.48550/arxiv.2611.05105
UR - https://arxiv.org/abs/2611.05105
AB - We discuss the relationship between quantum Hamiltonian embeddings (arXiv:2610.26833) and prior developments in Quantum Cognition Machine Learning (QCML), including QCML's earlier implementation on IBM quantum hardware. We consider the novelty claims and the computational role of encoding an entire dataset in a single ground state.
ER -