适应与自组织系统：2025–2026 年度综述

An annual survey of the nlin.AO arXiv category, covering research published from September 2025 – August 2026. Built on a close-reading set of 108 papers and organised into 40 chapters, it maps the year by the field's research sub-directions.

Book framework (share of the year's output):

• Complex Systems and Emergent Dynamics (26.7%) — This cluster focuses on the fundamental principles of self-organization, emergent behavior, and statistical equilibria in complex physical and dynamical systems.
• Collective Behavior in Active Matter and Multi-Agent Systems (13.9%) — This cluster investigates collective motion, alignment, and information processing in active matter and multi-agent systems, including swarming and decision-making.
• Phase Reduction and Dimensional Reduction in Coupled Oscillators (11.0%) — This cluster develops mathematical methods for reducing high-dimensional coupled oscillator systems to lower-dimensional phase models, including delay and swarmalator effects.
• Synchronization Dynamics in Kuramoto and Inertial Oscillator Networks (10.7%) — This cluster studies synchronization phenomena in Kuramoto-type models with inertia, focusing on cluster formation, entrainment, and stability in networked oscillators.
• Evolutionary Game Theory and Social Cooperation Dynamics (10.5%) — This cluster explores cooperation, punishment, and social phase transitions in evolutionary games, including eco-evolutionary and collective risk scenarios.
• Network Dynamics, Epidemic Spread, and Resilience (9.5%) — This cluster examines dynamical processes on networks, including epidemic transmission, synchronization optimization, and structural resilience in evolving systems.
• Neural Networks and Physics-Inspired Learning Systems (7.3%) — This cluster bridges neural computation and physical principles, focusing on learning dynamics, resonance, and hybrid computational models in deep neural networks.
• Higher-Order Interactions and Topological Network Dynamics (6.5%) — This cluster investigates collective dynamics on higher-order networks, including simplicial complexes and topological interactions beyond pairwise coupling.
• Chimera States and Adaptive Cluster Dynamics (3.9%) — This cluster focuses on chimera states, adaptive rewiring, and symmetry-induced activity patterns in networks with mixed coherent and incoherent clusters.

Each sub-direction is covered across three chapters — how it framed its questions, the strength of its key findings, and its open debates and frontiers — so the reader gets a traceable picture of what this part of the field actually produced over the year.