Adaptive Low-Rank Variational Quantum Algorithm for Simulating Dissipative Dynamics in Photosynthetic Complexes

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Abstract Simulating open quantum system dynamics faces exponential complexity limiting classical methods to 15 chromophores. Wedevelop a low-rank variational quantum algorithm achieving polynomial scaling through adaptive tensor compression and dissipation-engineered optimization. Benchmarking on Fenna-Matthews-Olson complexes from 5 to 12 sites yields mean f idelities 0.92-0.98 across 50 independent trials with comprehensive statistical validation. Noisy simulations using IBM Heron specifications demonstrate practical NISQ device viability (fidelity 0.94 for 7-site). Comparative analysis establishes computational crossover at 14 chromophores beyond which our method provides the sole tractable approach. Agreement with experimental energy transfer timescales within 3Complete open-source implementation achieves sub-90-second runtimes on commodity hardware. This framework enables quantum advantage in quantum biology with direct extensions to nonMarkovian dynamics and experimental antenna systems containing 50-300 chromophores
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Adaptive Low-Rank Variational Quantum Algorithm for Simulating Dissipative Dynamics in Photosynthetic Complexes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Adaptive Low-Rank Variational Quantum Algorithm for Simulating Dissipative Dynamics in Photosynthetic Complexes Atiye Zeynali, Zahra Bakhshi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7967523/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Simulating open quantum system dynamics faces exponential complexity limiting classical methods to 15 chromophores. Wedevelop a low-rank variational quantum algorithm achieving polynomial scaling through adaptive tensor compression and dissipation-engineered optimization. Benchmarking on Fenna-Matthews-Olson complexes from 5 to 12 sites yields mean f idelities 0.92-0.98 across 50 independent trials with comprehensive statistical validation. Noisy simulations using IBM Heron specifications demonstrate practical NISQ device viability (fidelity 0.94 for 7-site). Comparative analysis establishes computational crossover at 14 chromophores beyond which our method provides the sole tractable approach. Agreement with experimental energy transfer timescales within 3Complete open-source implementation achieves sub-90-second runtimes on commodity hardware. This framework enables quantum advantage in quantum biology with direct extensions to nonMarkovian dynamics and experimental antenna systems containing 50-300 chromophores Biological sciences/Biophysics Physical sciences/Physics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Mar, 2026 Reviewers agreed at journal 20 Jan, 2026 Reviewers agreed at journal 18 Jan, 2026 Reviews received at journal 23 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers invited by journal 03 Dec, 2025 Editor assigned by journal 03 Dec, 2025 Editor invited by journal 03 Dec, 2025 Submission checks completed at journal 25 Nov, 2025 First submitted to journal 25 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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