Quantum-Centric Supercomputing and Quantum Tunnelling in Mitochondrial Bioenergetics: An Expanded Academic Review of Biomolecular Simulation Milestones and Photonic Bio-Quantum Horizons (Vol-III)
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 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 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
The pursuit of exact solutions to the many-body electronic Schrödinger equation is constrained by the exponential scaling of the Hilbert space. While Quantum-Selected Configuration Interaction (QSCI) provides a robust, hybrid quantum-classical alternative to standard Variational Quantum Eigensolvers, it is hampered by significant sampling inefficiencies and finite-shot bottlenecks in strongly correlated regimes. This report analyzes the integration of generative machine-learning models—including autoregressive transformers, Neural-Network Quantum States (NQS), and discrete diffusion models—as a transformative approach to the QSCI paradigm. By treating classical diagonalization outputs as high-quality training data, these generative architectures internalize complex electron correlation patterns, enabling active configuration discovery, dramatic wavefunction compression, and optimized quantum circuit design. This synthesis provides a scalable blueprint for achieving chemical accuracy in KSCCN Mamun, SM (2026) ………………………………..1 Integration of Generative Machine-Learning Models with Quantum-Selected Configuration Interaction: An Academic Extension K S C electronic structure simulations while maintaining the strict variational upper-bound guarantee of classical diagonalization. KSCCN Mamun, SM (2026) ………………………………..2 Integration of Generative Machine-Learning Models with Quantum-Selected Configuration Interaction: An Academic Extension Also available on Academia.edu: https://www.academia.edu/attachments/133495242/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 review critically examines the paper by Mamun (2026) on fractal-quantum architectures in exascale computational biology, which proposes the integration of the Cerebras Wafer-Scale Engine 3 (WSE-3) with non-Markovian dynamics and autopoietic cybernetics to simulate complex biological systems. Key salient points are summarized, including theoretical foundations, hardware architecture, quantum simulations, and future implications. Comparisons with existing research highlight alignments with fractal patterns in quantum biology and non-Markovian models in biochemical reactions, while contrasting the speculative nature of autopoietic AI with empirical advancements in multi-agent systems. The review evaluates strengths in innovative synthesis and weaknesses in empirical validation. Extensions are proposed into quantum error correction, drug discovery applications, ethical considerations, and hybrid hardware integrations. This coherent framework underscores the potential for transformative simulations while advocating cautious, evidence-based development. Mamun, SM & Grok xAI (2026)……………………………………..1 Advancing Exascale Computational Biology: A Critical Review and Extension of Fractal-Quantum Architectures Integrating WSE-3, Non-Markovian Dynamics, and Autopoietic Systems Also available on Academia.edu: https://www.academia.edu/attachments/131657978/download_file?s=portfolio
The fundamental challenge in electronic structure theory is the factorial scaling of the Full Configuration Interaction (FCI) method. While Quantum-Selected Configuration Interaction (QSCI) has emerged as a promising alternative that utilizes quantum hardware to navigate this Hilbert space, benchmarking studies have identified significant scaling bottlenecks, specifically multinomial sampling inefficiencies and poor wavefunction compactness. This work presents the "hybrid adaptive pipeline" framework, which reconfigures the division of labor between quantum and classical systems. By utilizing quantum processors exclusively as initialization oracles to establish a topological seed of static correlation, and delegating the intensive recovery of dynamic correlation to classical iterative refinement algorithms (such as CIPSI or MCCI), this approach overcomes the limitations of pure sampling-based methods. The hybrid pipeline preserves the essential variational upper-bound guarantee while enabling the efficient, noise-resilient simulation of complex molecular systems on contemporary quantum-centric supercomputing architectures. KSCCN Mamun, SM (2026) …………………………….1 Hybrid Adaptive Pipelines in Quantum Chemistry: Synthesizing Quantum-Selected Configuration Interaction with Classical Iterative Refinement Also available on Academia.edu: https://www.academia.edu/attachments/133434503/download_file?s=portfolio
As artificial intelligence compute demands push silicon CMOS architectures toward insurmountable thermodynamic limits, the search for post-silicon computational paradigms has become an existential imperative. This paper presents an exhaustive analysis of emerging computational paradigms spanning room-temperature thermodynamic sampling units, superconducting quantum circuit heat engines, and living biological organoid intelligence. We examine how non-trivial quantum biological phenomena—including environment-assisted quantum transport (ENAQT), enzymatic quantum tunneling, and open-system DNA proton dynamics—enable biological neural networks to achieve radical energy efficiency and sample efficiency. Furthermore, we deploy a closed-system game-theoretic framework to model the strategic behavior of state actors and tech conglomerates competing in the post-silicon intelligence race, highlighting the bio-quantum breakaway strategy and the geopolitical, ethical, and dual-use implications of wetware computing. KSCCN Mamun, SM (2026) …………………….…1 KSCCN The Architecture of Post-Silicon Intelligence: Quantum Thermodynamics, Biological Computing, and the Game-Theoretic Race for the Next Computational Paradigm Also available on Academia.edu: https://www.academia.edu/attachments/133849341/download_file?s=portfolio