Quantum-Enabled Decision Architectures in Cellular Systems: Mitochondrial Compartmentalisation, Synaptic Quantum Effects, and Non-Perturbative Transport Models
K SC This paper synthesises a multi-layered enquiry into quantum-enabled decision architectures within cellular systems. Beginning from the modular ultracold cryogenic and biomimetic principles that illuminate mitochondrial compartmentalisation, calcium microdomains and electron tunnelling, it proceeds to an examination of proposed quantum effects at neural synapses (SNARE-complex soliton tunnelling, ion-channel quantum transport, microtubule coherence) and culminates in the rigorous formalism of non-perturbative quantum transport models—transfer-matrix methods, nonequilibrium Green's functions and non-Markovian quantum Langevin equations. A unifying pattern emerges: hierarchical modular isolation of steep physical or electrochemical gradients coupled to controlled, distance-tuned exchange, operating at the quantum–classical boundary. This architecture is shown to support readable, threshold-governed decision processes (release or not; open or closed; flux or isolation). Ontological priority is accorded to the combinatorial and physical structures that exist independently of geometric realisation, while the epistemological trajectory traces progressive internalisation of geometric and quantum principles into cellular language. Limitations—decoherence, model reduction, absence of definitive in-vivo functional proof—are catalogued alongside concrete research vectors. Also available on Academia.edu: https://www.academia.edu/attachments/133931970/download_file?s=portfolio
K SC This paper synthesises a multi-layered enquiry into quantum-enabled decision architectures within cellular systems. Beginning from the modular ultracold cryogenic and biomimetic principles that illuminate mitochondrial compartmentalisation, calcium microdomains and electron tunnelling, it proceeds to an examination of proposed quantum effects at neural synapses (SNARE-complex soliton tunnelling, ion-channel quantum transport, microtubule coherence) and culminates in the rigorous formalism of non-perturbative quantum transport models—transfer-matrix methods, nonequilibrium Green's functions and non-Markovian quantum Langevin equations. A unifying pattern emerges: hierarchical modular isolation of steep physical or electrochemical gradients coupled to controlled, distance-tuned exchange, operating at the quantum–classical boundary. This architecture is shown to support readable, threshold-governed decision processes (release or not; open or closed; flux or isolation). Ontological priority is accorded to the combinatorial and physical structures that exist independently of geometric realisation, while the epistemological trajectory traces progressive internalisation of geometric and quantum principles into cellular language. Limitations—decoherence, model reduction, absence of definitive in-vivo functional proof—are catalogued alongside concrete research vectors. Also available on Academia.edu: https://www.academia.edu/attachments/133931970/download_file?s=portfolio
This paper synthesizes categorical logic, combinatorial topology, and cellular sheaf theory to formalize cellular decision-making, specifically synaptic transmission and mitochondrial threshold mechanisms. It moves beyond classical geometric and physical models—which struggle to explain phenomena like ion channel selectivity and probabilistic neurotransmitter release—by utilizing the Abramsky-Brandenburger framework for quantum contextuality and the Bohrification of algebraic quantum mechanics. By integrating the minimal extension sheaf of Barthel-Brasselet-Fieseler-Kaup (BBFK) and Jacob Wood's Combinatorial Hodge Index Theorem, the author demonstrates how biological thresholds remain topologically invariant despite fluid, molecular-level geometry. Finally, the deployment of Sheaf and Tarski Laplacians over cellular structures provides a computable model for how decentralized biological agents, such as SNARE complexes and MCU holocomplexes, achieve global consensus. KSCCN Mamun, SM (2026) ………………………………………….1 Sheaf-Theoretic Architectures of Cellular Decision-Making: A Second Volume Synthesis of Topos-Theoretic Quantum Mechanics and Cellular Sheaf Laplacians Also available on Academia.edu: https://www.academia.edu/attachments/133966008/download_file?s=portfolio
This analysis addresses the critical decoherence paradox in quantum biology, where observed microsecond coherence times in living cells vastly exceed the nanosecond predictions of standard open quantum systems theory. The study synthesizes theoretical and empirical advancements, establishing that the information geometry of biological macromolecules provides the mechanism for long-lived quantum states, where cellular structures function as optimized topological constraints that actively harness environmental noise. Key theoretical frameworks integrated include the Quantum Fisher Information (QFI) metric, which quantifies biological coherence and sets absolute limits on sensory precision (e.g., avian magnetoreception), and the Entanglement-Weighted Operator Geometry (EWOG). EWOG is empirically validated to resolve the decoherence discrepancy by demonstrating that quantum entanglement dynamically modifies the effective Hamiltonian, achieving a calculated 58% suppression of decoherence in proteins like MagLOV2. Furthermore, the study applies Quantum Geometrical Molecular Dynamics (QGMD) to show that the non-Abelian quantum geometric tensor drives nonadiabatic enzymatic catalysis, enabling quantum mechanical tunneling to provide profound energetic advantages, such as reducing the required energy for proton transport in mitochondrial Complex I by over 55%. Also available on Academia.edu: https://www.academia.edu/attachments/132032425/download_file?s=portfolio
This paper evaluates the breakthrough in computational biophysics marked by the successful ab initio quantum simulation of protein complexes up to 12,635 atoms, achieved through a heterogeneous Quantum-Centric Supercomputing (QCSC) paradigm. By leveraging advanced quantum processors (IBM Heron r2) and classical HPC (Miyabi-G) with the novel EWF-TrimSQD algorithm, researchers surpassed previous simulation size limits by over 40-fold, enabling accurate calculation of fragment energies and ligand-binding affinities for systems like Trypsin-benzamidine. Beyond drug Mamun, SM (2026) ……………………………….1 Quantum-Centric Supercomputing and Photonic Bio-Quantum Architectures: An Exhaustive Evaluation of High-Fidelity Biomolecular Simulation and Mitochondrial Quantum Dynamics (Vol-II) K S C discovery, this capacity provides the empirical foundation for rigorous investigation into quantum biology. The paper details non-classical phenomena, including proton tunneling in ribosomal peptide bond formation and the highly efficient electron/proton tunneling within the mitochondrial electron transport chain (ETC), highlighting how oxidative damage to these quantum pathways drives neurodegenerative pathology. Also available on Academia.edu: https://www.academia.edu/attachments/132704084/download_file?s=portfolio
This academic review synthesizes the methodological breakthrough of the May 2026 quantum-centric supercomputing (QCSC) milestone, which utilized the Embedded Wave Function (EWF) and Trimmed Sample-based Quantum Diagonalization (TrimSQD) algorithmic framework to achieve coupled-cluster-level accuracy in simulating protein-ligand complexes exceeding 12,000 atoms. This unprecedented computational capability provides the rigorous analytical foundation for quantum biology, specifically validating the indispensable role of quantum tunnelling in mitochondrial bioenergetics. Atomistic calculations confirm that electron tunnelling in Respiratory Complex III is governed by highly optimized superexchange pathways and conformational gating. Concurrently, mathematical modelling using the Wentzel-Kramers-Brillouin (WKB) approximation demonstrates that proton tunnelling through Complex I substantially reduces the required Mamun, SM (2026) ……………………………….1 Quantum-Centric Supercomputing and Quantum Tunnelling in Mitochondrial Bioenergetics: An Expanded Academic Review of Biomolecular Simulation Milestones and Photonic Bio-Quantum Horizons (Vol-III) K S C thermal activation energy for chemiosmosis by up to 45%, a finding supported by real-time optical detection using bio-nanoantennae. Also available on Academia.edu: https://www.academia.edu/attachments/132704155/download_file?s=portfolio
This comprehensive second volume mathematically formalizes the Orchestrated Objective Reduction (Orch OR) theory, advancing it from its conceptual foundations into a rigorous operational framework for biological learning and memory. By synthesizing concepts from open quantum systems, non-Hermitian dynamics, and quantum active inference, the report defines the total unified Hamiltonian operator (Ĥ_Total) that dictates the structure of learning. The core finding establishes that conscious, temporally deep active inference—the continuous optimization of internal generative models to minimize expected free energy—is mathematically indistinguishable from the quantum path integral. This equivalence leads to the derivation of the Master Learning Hamiltonian Mamun, SM (2026) ……………………………….1 Quantum Foundations of Cognition: A Hamiltonian Framework for Learning, Memory, and Active Inference within the Orchestrated Objective Reduction Paradigm (Vol-II) K S C (Ĥ_Learning), where the Schrödinger potential (V(ϕ)) physically represents the dynamic landscape of long-term memory and prior beliefs. The document further addresses classical decoherence challenges by modeling Microtubules as Qudit Hopfield Networks governed by a Lindbladian framework (exhibiting superradiant and subradiant states) and by scaling the theory to macroscopic cognition using Neural Spinfoam Networks (NSNs). Also available on Academia.edu: https://www.academia.edu/attachments/132658997/download_file?s=portfolio
K SC This teaching note synthesises recent advances in superconducting quantum thermodynamics—specifically the world's first cyclic superconducting quantum heat engine (Aalto University, 2026) and the associated technologies of quantum-circuit refrigerators (QCRs) and autonomous quantum heat engines—with emerging concepts of thermal connectivity in neural networks and biological mitochondrial organisation as templates for post-silicon computing architectures. It examines how engineered heat flows, dissipation control, and gradient-driven energy conversion can serve simultaneously as computational resources, interconnect modalities, and organisational principles for artificial intelligence systems. The note is intended for researchers, policy makers, and advanced students working at the intersection of quantum technology, neuromorphic computing, thermodynamic computing, and bio-inspired AI. Also available on Academia.edu: https://www.academia.edu/attachments/133844967/download_file?s=portfolio