Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Entanglement-Weighted Operator Geometry for Coherence Stabilization in Biological Radical Pairs: A Comparative Statistical Analysis with Standard Decoherence Models

Chavis Srichan

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.13140/rg.2.2.10841.99680

Related papers

Review of Entanglement-Weighted Operator Geometry for Coherence Stabilization in Biological Radical Pairs: Implications, Algebraic and Geometric Interpretations, and Future Directions (Vol-I)

Syed Muntasir Mamun

This review examines the recent theoretical framework proposed by Srichan (2026) on Entanglement-Weighted Operator Geometry (EWOG) as a mechanism for stabilizing quantum coherence in biological radical pairs, particularly in the MagLOV2 protein model for avian magnetoreception. The key postulate of EWOG is that entanglement entropy dynamically modifies the effective Hamiltonian through coupling with protein structural operators, leading to suppressed decoherence rates that align with experimental observations of microsecond coherence times. We highlight the hypotheses, methodology, and results from Srichan's comparative statistical analysis against standard Lindblad decoherence models, demonstrating decisive empirical support for EWOG via Akaike and Bayesian Information Criteria. Algebraic interpretations reveal EWOG as a state-dependent perturbation to the Hamiltonian, while geometric views frame it as an entanglement-modulated projection onto protein anisotropy. Secondary research contextualizes EWOG within broader quantum biology, including similar mechanisms like vibrational assistance and quantum Zeno effects in photosynthesis and magnetoreception. Also available on Academia.edu: https://www.academia.edu/attachments/132030862/download_file?s=portfolio

•Jan 1, 2026•0 citations

Entanglement-Weighted Operator Geometry: Quantum Measurement

Chavis Srichan

•Jan 1, 2025•0 citations

Quantum Defense Technologies Reimagined: A Geometric, Fractal, and Information-Theoretic Assessment (Vol-I)

Syed Muntasir Mamun

This assessment challenges the prevailing classical, isolationist paradigm of defense quantum engineering, which regards quantum states as inherently fragile and susceptible to thermal decoherence. It introduces an active, topological, and biological framework by synthesizing quantum-biological mechanisms—such as the radical-pair mechanism for coherence stabilization—with advanced mathematical constructs. The methodology integrates Entanglement-Weighted Operator Geometry (EWOG), multi-parameter Topological Data Analysis (TDA) via G-LoG bi-filtration, Information Geometry on Fisher-Rao manifolds, and the spectral realization of Riemann zeta zeros. This synthesis constructs a blueprint for resilient, emergent informational manifolds capable of active decoherence suppression. The resulting hybrid architectures accelerate the timeline for mission-relevant quantum sensing, computing, and communications, providing a robust, noise-resistant foundation that can bypass current limitations outlined in reports like the Congressional Research Service Defense Primer. KSCCN Mamun, SM (2026) …………………………….1 Quantum Defense Technologies Reimagined: A Geometric, Fractal, and Information-Theoretic Assessment (Vol-I) Also available on Academia.edu: https://www.academia.edu/attachments/132889757/download_file?s=portfolio

•Jan 1, 2026•0 citations

Quantifying Entanglement with Coherence

Neha Pathania, Tabish Qureshi

arXiv:2011.12976•International Journal of Theoretical Physics•Feb 1, 2022•8 citations

An Effective Model of Spatially Correlated Decoherence in Entangled Quantum Systems

shaher haddad

•Jan 1, 2026•0 citations

Biologically Plausible Quantum Error Correction\\in a Three-Layer Neural Spin Model

Hikaru Wakaura

Abstract Whether quantum coherence plays a functional role in neural information processing remains contested, largely because biological environments are deemed too noisy for quantum states to sur- vive at relevant timescales. We construct a three-layer model—nuclear spin memory, radical pair interface, classical electrochemistry—and identify five quantum error correction (QEC) paradigms that map onto known biophysical mechanisms: decoherence-free subspaces (DFS) via 31P singlet states, dynamical decoupling (DD) via protein motional narrowing, purification QEC (PQEC) ex- ploiting enzymatic redundancy (∼104 copies/cell), gauging symmetry protection via radical-pair spin conservation, and catalytic coherence recovery (ICEC) at enzyme active sites. We parametrize the model for two molecular systems: monoamine oxidase A (MAO-A; γeff = 4.55, radical pair un- confirmed) and Drosophila cryptochrome (CRY; γeff = 3.25, radical pair experimentally confirmed, |J| < 1 MHz). We quantify each mechanism individually: DFS provides complete protection against collective dephasing (F = 1.000), DD yields a B−2 0 -dependent relaxation suppression (4.6×107-fold at Earth field vs X-band), and PQEC achieves near-unity fidelity using 64 of ∼104 available copies. We integrate gauging, PQEC, and covariant recovery into a unified three-layer stabilizer and benchmark it on pattern classification, time-series prediction, and quantum-coherent decision dynamics. For MAO-A, the stabilizer significantly outperforms standard covariant QEC in classification (accuracy 85.2% vs 80.0%, p = 0.017, Cohen’s d = 1.19) and coherence preservation (+40% at moderate noise), while for time-series prediction the improvement is not statistically significant (p = 0.79). CRY yields statistically equivalent stabilizer performance (MNIST 86.2% vs 85.2%, p = 0.67; spike median MSE 7.31 vs 7.65, Mann–Whitney p = 0.99), demonstrating that the QEC framework is robust across molecular substrates. CRY’s decisive advantages are experimental: a confirmed radical pair and immunity to homeostatic neurotransmitter buffering. Four falsifiable experiments are proposed.

•Apr 13, 2026•0 citations
This review examines the recent theoretical framework proposed by Srichan (2026) on Entanglement-Weighted Operator Geometry (EWOG) as a mechanism for stabilizing quantum coherence in biological radical pairs, particularly in the MagLOV2 protein model for avian magnetoreception. The key postulate of EWOG is that entanglement entropy dynamically modifies the effective Hamiltonian through coupling with protein structural operators, leading to suppressed decoherence rates that align with experimental observations of microsecond coherence times. We highlight the hypotheses, methodology, and results from Srichan's comparative statistical analysis against standard Lindblad decoherence models, demonstrating decisive empirical support for EWOG via Akaike and Bayesian Information Criteria. Algebraic interpretations reveal EWOG as a state-dependent perturbation to the Hamiltonian, while geometric views frame it as an entanglement-modulated projection onto protein anisotropy. Secondary research contextualizes EWOG within broader quantum biology, including similar mechanisms like vibrational assistance and quantum Zeno effects in photosynthesis and magnetoreception. Also available on Academia.edu: https://www.academia.edu/attachments/132030862/download_file?s=portfolio
This assessment challenges the prevailing classical, isolationist paradigm of defense quantum engineering, which regards quantum states as inherently fragile and susceptible to thermal decoherence. It introduces an active, topological, and biological framework by synthesizing quantum-biological mechanisms—such as the radical-pair mechanism for coherence stabilization—with advanced mathematical constructs. The methodology integrates Entanglement-Weighted Operator Geometry (EWOG), multi-parameter Topological Data Analysis (TDA) via G-LoG bi-filtration, Information Geometry on Fisher-Rao manifolds, and the spectral realization of Riemann zeta zeros. This synthesis constructs a blueprint for resilient, emergent informational manifolds capable of active decoherence suppression. The resulting hybrid architectures accelerate the timeline for mission-relevant quantum sensing, computing, and communications, providing a robust, noise-resistant foundation that can bypass current limitations outlined in reports like the Congressional Research Service Defense Primer. KSCCN Mamun, SM (2026) …………………………….1 Quantum Defense Technologies Reimagined: A Geometric, Fractal, and Information-Theoretic Assessment (Vol-I) Also available on Academia.edu: https://www.academia.edu/attachments/132889757/download_file?s=portfolio
Abstract Whether quantum coherence plays a functional role in neural information processing remains contested, largely because biological environments are deemed too noisy for quantum states to sur- vive at relevant timescales. We construct a three-layer model—nuclear spin memory, radical pair interface, classical electrochemistry—and identify five quantum error correction (QEC) paradigms that map onto known biophysical mechanisms: decoherence-free subspaces (DFS) via 31P singlet states, dynamical decoupling (DD) via protein motional narrowing, purification QEC (PQEC) ex- ploiting enzymatic redundancy (∼104 copies/cell), gauging symmetry protection via radical-pair spin conservation, and catalytic coherence recovery (ICEC) at enzyme active sites. We parametrize the model for two molecular systems: monoamine oxidase A (MAO-A; γeff = 4.55, radical pair un- confirmed) and Drosophila cryptochrome (CRY; γeff = 3.25, radical pair experimentally confirmed, |J| < 1 MHz). We quantify each mechanism individually: DFS provides complete protection against collective dephasing (F = 1.000), DD yields a B−2 0 -dependent relaxation suppression (4.6×107-fold at Earth field vs X-band), and PQEC achieves near-unity fidelity using 64 of ∼104 available copies. We integrate gauging, PQEC, and covariant recovery into a unified three-layer stabilizer and benchmark it on pattern classification, time-series prediction, and quantum-coherent decision dynamics. For MAO-A, the stabilizer significantly outperforms standard covariant QEC in classification (accuracy 85.2% vs 80.0%, p = 0.017, Cohen’s d = 1.19) and coherence preservation (+40% at moderate noise), while for time-series prediction the improvement is not statistically significant (p = 0.79). CRY yields statistically equivalent stabilizer performance (MNIST 86.2% vs 85.2%, p = 0.67; spike median MSE 7.31 vs 7.65, Mann–Whitney p = 0.99), demonstrating that the QEC framework is robust across molecular substrates. CRY’s decisive advantages are experimental: a confirmed radical pair and immunity to homeostatic neurotransmitter buffering. Four falsifiable experiments are proposed.