标题： 集体趋化搜索策略 显示英文标题

标题： Collective chemotactic search strategies

摘要： 趋化性生物或合成活性物质通过其自推进组分（如细胞、生物体或活性胶体）分泌化学信号来塑造其环境。这种间接相互作用产生了集体效应，可以使代理者共同迁移、形成图案或更高效地寻找目标。在这里，我们使用典型的模型来研究一群运动代理在移动过程中释放排斥性自趋化信号的集体搜索策略效率，这些信号迫使它们远离化学线索的高浓度区域。我们显示，排斥性趋化相互作用通过平均首次通过时间来衡量搜索效率，根据趋化耦合的强度，可以提高几个数量级。这种改进的机制依赖于两个因素：由于代理与其自身趋化场的自相互作用导致的持久长度增加，以及由于趋化场介导的相互间接排斥导致的代理更均匀分布。在更强的粒子-场耦合下，趋化搜索者会自我组织成弹道运动的条带，类似于搜救行动中形成的搜索链，其效率取决于参与的搜索者数量。我们对大量相互作用代理的集体搜索策略的全面研究不仅对趋化活性物质相关，也对伦理学、信息工程、机器人学和社会工程等多个领域具有重要意义。 显示英文摘要

摘要： Chemotactic biological or synthetic active matter shapes its environment by secretions of chemical signals from its self-propelled constituents, like cells, organisms or active colloids. From this indirect interaction collective effects emerge that can be used by the agents to migrate collectively, to form patterns or to search for targets more efficiently. Here, we use paradigmatic models to study the efficiency of collective search strategies of a large group of motile agents that release during their movement repulsive auto-chemotactic signals forcing them to move away from high concentrations of the chemical clue. We show that the repulsive chemotactic interactions improve the search efficiency, measured by the mean first passage time to find a randomly located target, by orders of magnitude depending on the strength of the chemotactic coupling. The mechanism for this improvement relies on two factors: the increase of the persistence length due to the agent's self-interaction with its own chemotactic field and by a more homogeneous distribution of the agents due to their mutual indirect repulsion mediated by the chemotactic field. At stronger particle-field coupling the chemotactic searchers self-organize into ballistically moving bands reminiscent of search-chains formed in search and rescue operations, whose efficiency depends on the number of searchers involved. Our comprehensive study of collective search strategies of large groups of interacting agents is not only relevant for chemotactic active matter but also for a wide range of fields like ethology, information engineering, robotics, and social engineering.