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<p>Phytoplankton blooms in the western North Pacific exhibit high diversity with complex underlying regulatory mechanisms. This study applies a quantum graph-theoretic framework combining continuous-time quantum walk (CTQW) with vector autoregressive (VAR) models to identify dominant phytoplankton blooms pathways and regulatory shifts across eight large marine ecosystems. Unlike traditional modal decomposition methods, the CTQW framework is applied here as a mathematical network tool that intrinsically captures inter-scale coupling. This is achieved through the constructive and destructive interference of probability amplitudes among multiple transport pathways, analogous to wave propagation, enabling a synergistic reconstruction of multi-scale variability. Modal analysis reveals a seasonal alternation in control between the Kuroshio and Oyashio currents. Sub-seasonal feedbacks, including wind mixing and nutrient recirculation, further structure this asymmetry. Notably, the Yellow Sea exhibits a “missing mode” pattern, absent from shared connectivity modes, highlighting its isolation due to terrestrial drivers and coastal currents. These findings demonstrate that CTQW-VAR not only captures multiscale signal propagation but also resolves cross-scale coupling and structural disconnections within the regional connectivity network. This approach advances bloom predictability by integrating physical connectivity and ecological coupling, providing a transferable framework for marine ecosystem monitoring under climate variability.</p>

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Quantum walk model reveals the propagation path of phytoplankton blooms along the Kuroshio-Oyashio system in the western North Pacific

  • 期刊论文

  • 发表日期：

    2026年7月11日

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  • Zhenxia Liu,
  • Yanhui Dai,
  • Luojian Tan,
  • Binru Zhao,
  • Xu Hu,
  • Wen Luo,
  • Linwang Yuan,
  • Zhaoyuan Yu

摘要

Phytoplankton blooms in the western North Pacific exhibit high diversity with complex underlying regulatory mechanisms. This study applies a quantum graph-theoretic framework combining continuous-time quantum walk (CTQW) with vector autoregressive (VAR) models to identify dominant phytoplankton blooms pathways and regulatory shifts across eight large marine ecosystems. Unlike traditional modal decomposition methods, the CTQW framework is applied here as a mathematical network tool that intrinsically captures inter-scale coupling. This is achieved through the constructive and destructive interference of probability amplitudes among multiple transport pathways, analogous to wave propagation, enabling a synergistic reconstruction of multi-scale variability. Modal analysis reveals a seasonal alternation in control between the Kuroshio and Oyashio currents. Sub-seasonal feedbacks, including wind mixing and nutrient recirculation, further structure this asymmetry. Notably, the Yellow Sea exhibits a “missing mode” pattern, absent from shared connectivity modes, highlighting its isolation due to terrestrial drivers and coastal currents. These findings demonstrate that CTQW-VAR not only captures multiscale signal propagation but also resolves cross-scale coupling and structural disconnections within the regional connectivity network. This approach advances bloom predictability by integrating physical connectivity and ecological coupling, providing a transferable framework for marine ecosystem monitoring under climate variability.