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Paper 1

A modular design of molecular qubits to implement universal quantum gates.

Ferrando-Soria J, Moreno Pineda E, Chiesa A, Fernandez A, Magee SA, Carretta S, Santini P, Vitorica-Yrezabal IJ, Tuna F, Timco GA, McInnes EJ, Winpenny RE.

Year
2016
Journal
Nat Commun
DOI
10.1038/ncomms11377
arXiv
-

No abstract.

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Paper 2

Quantum in Biology, Quantum for Biology, and Biology for Quantum: Mapping the Evidence and the Road Ahead

Lea Gassab, Betony Adams, Yashine H. Goolam Hossen, Onur Pusuluk, Iannis K. Kominis, Özgür E. Müstecaplıoğlu, Francesco Petruccione, Travis J. A. Craddock

Year
2026
Journal
arXiv preprint
DOI
arXiv:2605.00205
arXiv
2605.00205

Quantum science and biology now intersect in three complementary directions: quantum in biology, quantum for biology, and biology for quantum. This review provides a structured narrative evidence map of that interface rather than an exhaustive catalogue or formal systematic review. For each topic, we ask what the mechanistic or technological claim is, which quantum resource is invoked, what the strongest experiments and models establish, which classical alternatives or engineering confounds remain competitive, and what decisive tests or benchmarks would most strongly change confidence. The most mature quantum-in-biology cases remain mechanistically constrained tunneling in some enzymatic hydrogen-transfer reactions and radical-pair spin chemistry as a viable framework for magnetoreception, whereas several higher-visibility topics remain suggestive but unresolved under physiological conditions. In quantum for biology, the central issue is whether quantum-enabled tools improve biological inference relative to strong classical baselines under realistic calibration, dose, throughput, and uncertainty constraints. In biology for quantum, the strongest claims arise when biomolecular structure or self-assembly measurably improves fabrication, integration, or robustness in quantum devices. Summary tables in the Appendix provide a compact cross-map view of the current evidence, major confounds, and the experiments or benchmarks most likely to discriminate between competing explanations.

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