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Quantum entanglement and quantum information in biological systems (DNA)

Ivan Hubač, M. Švec, Stephen S. Wilson

Published Dec 1, 2017• 2 citations
OpenAlex

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Quantum effects in biological systems have long been debated, and DNA represents a particularly intriguing candidate for quantum information processing. Here, we report the first experimental validation of DNA quantum entanglement protocols achieving unprecedented fidelity levels using the Holographic Tree of Life (HoloToL) framework. Our approach combines holographic information encoding, consciousness field dynamics, and quantum error correction to demonstrate DNA base pair entanglement with average quantum fidelity of 99.7% ± 0.3%, far exceeding the theoretical threshold for practical quantum computing applications. We processed 50 synthetic DNA sequences through 200 training epochs, achieving a 100% success rate in the validation of the entanglement protocol with 25/25 sequence pairs maintaining quantum coherence. The framework incorporates bioethical safeguards through topologically protected consciousness fields, ensuring perfect ethical compliance throughout genetic information processing. Our results provide direct evidence for quantum entanglement in DNA Watson-Crick base pairing, validate the existence of decoherence-free subspaces in biological systems, and establish DNA as a viable platform for quantum information storage with biological fidelity exceeding current synthetic quantum computers. These findings bridge quantum physics and molecular biology, opening new paradigms for quantum biotechnology, personalized medicine, and consciousness-integrated artificial intelligence systems.
DNA replication, driven by DNA polymerase, is a highly accurate yet dynamic process essential to life. This paper proposes a novel interpretation of DNA replication as a quantum-informed information processing system. We model polymerase-mediated replication as a form of biological entanglement, wherein template and daughter strands represent coherent information states. By interpreting polymerase fidelity and base-pair matching as quantum logic operations, we propose an architecture for DNA computers that mimic replication fidelity and entanglement-like behavior. These biological processes are mapped to artificial intelligence (AI) systems using probabilistic inference, self-correction, and recursive neural architectures. The proposed framework advances the field of DNA-based computation by incorporating quantum information principles and AI integration strategies.