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

• URL: http://arxiv.org/abs/2605.00205v1
• Date: Thu, 30 Apr 2026 20:29:30 GMT
• Title: Quantum in Biology, Quantum for Biology, and Biology for Quantum: Mapping the Evidence and the Road Ahead
• Abstract summary: Quantum science and biology now intersect in three complementary directions: quantum in biology, quantum for biology, and biology for quantum.<n>This review provides a structured narrative evidence map of that interface rather than an exhaustive catalogue or formal systematic review.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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