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Harnessing problem structure for end-to-end quantum speed-ups — arXiv:2609.40105

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.40105
License (as archived): CC0-1.0
Archived: 2026-10-07T15:22:06.176Z
SHA-256 of the archived text: 3a71012b949a1afeab2a765b992d1435f501804bf948f25de9671f47a70dd2d0
Stable URL of this page: https://metraipolis.com/documento/dc_edc5445ea4e9

How to cite

Harnessing problem structure for end-to-end quantum speed-ups — arXiv:2609.40105 — arXiv (en), https://arxiv.org/abs/2609.40105 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_edc5445ea4e9 (Metraipolis archive dc_edc5445ea4e9, sha256 3a71012b949a1afeab2a765b992d1435f501804bf948f25de9671f47a70dd2d0)

BibTeX

@misc{dcedc5445ea4e9,
  title = {Harnessing problem structure for end-to-end quantum speed-ups — arXiv:2609.40105},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.40105},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_edc5445ea4e9; sha256 3a71012b949a1afeab2a765b992d1435f501804bf948f25de9671f47a70dd2d0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.40105. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Quantum algorithms can offer substantial computational speed-ups, yet these advantages may disappear once the cost of structure-agnostic classical data encoding is taken into account. Real-world problem instances, however, often possess rich internal structure. This raises a fundamental question: can such structure be harnessed to make quantum speed-ups survive end-to-end cost accounting? Here we show that it can. We introduce a general framework for structure-aware quantum data encoding that compiles compact recursive descriptions of problem structure into efficient state-preparation circuits, translating structural information directly into reduced encoding complexity. For the uncapacitated facility-location problem, structure-agnostic encoding admits a classical dequantization that eliminates the quadratic quantum speed-up, whereas exploiting the underlying problem structure restores this advantage even when state-preparation costs are included. More broadly, the same framework prepares structured quantum states for combinatorial optimization that capture non-trivial relations among constraints, including group balance, conflicts and synergistic rewards, extending previously reported super-polynomial quantum advantages to broader classes of objectives. These results establish exploitable problem structure as a computational resource for quantum algorithms and provide a systematic route towards realizing quantum advantage in data-intensive problems.

Tema degli esploratori: fisica e astronomia (retro-catalogo arXiv: annunci del 2026-10-01 in quant-ph).
Categorie arXiv: Quantum Physics (quant-ph).
Pagina del lavoro: https://arxiv.org/abs/2609.40105 — 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 2026-10-07T14:53:56.805Z dalla pagina https://arxiv.org/catchup/quant-ph/2026-10-01?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).