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

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