标题： 活性物质轨迹的逆统计量以区分相互作用核各向异性与涌现相关性 显示英文标题

标题： Inverse statistics of active matter trajectories to distinguish interaction kernel anisotropy from emergent correlations

摘要： 高分辨率成像提供了迁移细胞、群体动物和合成活性粒子的密集轨迹，从中可以使用各种方法确定相互作用定律。 然而，区分在这些数据中观察到的前后或侧向偏差是反映相互作用核中的固有各向异性，还是由各向同性成对相互作用力产生的涌现相关性，仍然是一个开放挑战。 我们通过推导一个将可测量的两点速度相关性与未知的距离和角度依赖的相互作用核联系起来的线性偏微分方程来解决这一歧义。 可能出现类似图灵的不稳定性，这使得即使代理按照一个与角度无关的吸引力-排斥力定律相互作用，也可以出现偶极子或四极子模式。 然后我们表明，引入一个弱速度对齐力可能会通过抑制偶极子模式而干扰各向异性模式的形成。 我们通过基于代理的模拟验证了这些预测，并为试图区分固有各向异性与涌现效应的实验提供了设计指导。 显示英文摘要

摘要： High-resolution imaging provides dense trajectories of migrating cells, flocking animals, and synthetic active particles, from which interaction laws can be determined with a wide variety of methods. Yet, distinguishing whether front-back or lateral biases seen in such data reflect intrinsic anisotropy in the interaction kernel or emergent correlations that are nevertheless produced by isotropic pairwise interaction forces remains an open challenge. We resolve this ambiguity by deriving a linear partial differential equation that connects measurable two-point velocity correlations to an unknown, distance- and angle-dependent interaction kernel. Turing-like instabilities can occur which allows for dipolar or quadrupolar patterns to arise even when agents interact according to an underlying attraction-repulsion law that is angle-independent. We then show that incorporating a weak velocity-alignment force can interfere with anisotropic pattern formation by suppressing dipolar patterns. We validate these predictions with agent-based simulations and provide design guidance for experiments that seek to discriminate intrinsic anisotropy from emergent effects.