Spectral Bath Engineering for Quantum-Enhanced Agrivoltaics: Advancing Efficiency and Environmental Sustainability via Non-Markovian Dynamics

Abstract

As global demand for food and clean energy intensifies, agrivoltaic systems have emerged as a vital solution for land-use optimization. However, current designs overwhelmingly treat incident light as a classical photon flux, overlooking the quantum mechanical nature of photosynthetic energy transfer. We introduce spectral bath engineering-the strategic spectral filtering of sunlight through semi-transparent organic photovoltaic (OPV) panels to exploit non-Markovian quantum coherence in biological light-harvesting. Using Process Tensor HOPS (PT-HOPS) and Spectrally Bundled Dissipators (SBD) to simulate the Fenna-Matthews-Olson complex, we demonstrate that selective filtering at vibronic resonance wavelengths (750nm and 820nm) enhances the electron transport rate (ETR) by 25% relative to standard Markovian models. This quantum advantage is driven by vibronic resonance-assisted transport, which extends coherence lifetimes by 20% to 50% and nearly doubles pairwise concurrence (89%). Multi-objective Pareto optimization identifies OPV configurations reaching 18.8% power conversion efficiency while sustaining an 80.5% system ETR, potentially generating an additional USD 470 to 3000 $ha^{-1}$$yr^{-1}$ in revenue. Environmental simulations across nine climate zones, including sub-Saharan Africa, confirm persistent ETR enhancements of 18% to 24%. Finally, eco-design analysis using quantum reactivity descriptors ensures that these technological gains are achieved using sustainable, biodegradable materials. By bridging quantum biology and renewable energy engineering, this work provides a quantitative blueprint for next-generation agrivoltaic materials that co-optimize agricultural productivity and energy yield.

Figures (4)

• Figure 1: Coherence preservation and spatial delocalization mapped via spectral filtering. (a) Time-resolved $l_1$-norm of coherence. Dual-band filtering extends the coherence lifetime by 2050 compared to the broadband baseline. (b) Inverse participation ratio ($\xi_{\rm deloc}$) confirming sustained exciton delocalization across 8--10 chromophores. (c) Protein-solvent bath spectral density, highlighting the direct overlap with targeted vibronic transitions. (d) System-bath correlation function isolating non-Markovian memory effects. Simulations conducted at physiological temperature (295K) with $\sigma = 50\per\cm$ static disorder.
• Figure 2: Transient quantum metric evolution driving the FMO complex. (a) Site-specific population dynamics capturing the excitation cascade from BChl 1 through the seven-chromophore network. (b) $l_1$-norm coherence trajectory, maximizing inside the first 100fs prior to environmental suppression. (c) State purity ($\Tr[\bm{\rho}^2]$) and von Neumann entropy ($S$) marking the precise coherent-to-incoherent crossover under non-Markovian PT-HOPS dynamics at 295K. (d) Normalized Quantum Fisher Information ($F_Q$) quantifying the peak metrological sensitivity unlocked during the early-time coherent window.
• Figure 3: Pareto frontier resolving the energy--agriculture trade-off. Multi-objective optimization maps the competitive boundary between standard electrical generation (PCE) and the biochemically-coupled electron transport rate (ETR). Three defining operational modes bracket the solution space: a Balanced configuration (18.83% PCE, 80.51% system ETR), an Energy-focused peak (22.1% PCE), and an Agriculture-focused maximum (15.4% PCE).
• Figure 4: Environmental resilience of quantum-enhanced agrivoltaics. (a) Stability of the ETR enhancement across terrestrial temperature regimes. (b) Preservation of the quantum advantage under increasing static energetic disorder ($\sigma$). (c) Projected net performance translating site-specific insolation and ambient temperature across distinct global climatic zones. Error bars indicate 95% confidence intervals.