[论文解读] Measurement-Induced Phase Transitions in Informational Active Matter

Bryan VanSaders, Fruchart, Michel+1 more|arXiv (Cornell University)|Feb 14, 2023

Micro and Nano Robotics被引用 4

一句话总结

本文提出了‘信息性活性物质’——一类多体系统，其中微观粒子通过基于测量的反馈机制，将热噪声整流为定向运动与形态形成。作者借助信息论原理与动理学理论，表明自推进与形态分辨率随环境噪声增强而提升，其模拟结果展示了‘思考者’粒子通过动态改变自身尺寸来偏置散射跃迁。

ABSTRACT

Various biological and synthetic media out of equilibrium can be viewed as many-ratchet systems that rectify environmental noise through local measurements and information processing, like in Maxwell's prototypical demon. These systems pose a challenge to standard coarse-graining approaches because they are better described in terms of decision-making protocols similar to computer programs rather than force laws. Here, we study a many-body generalization of the Maxwell demon problem: a fluid composed of adaptive particles that achieve collective behavior by biasing noise-driven scattering events subject to measurements. Using a combination of information-theoretic, kinetic, and hydrodynamic tools, we elucidate how microscopic decision-making protocols, rather than microscopic forces, generate macroscopic active states sustained by continuous measurements. These include an informational version of flocking whose order parameter is bounded by the information measured, and the onset of which may be viewed as a measurement-induced phase transition. We find that the signature of such microscopic choices is an `informational activity' that selectively compresses phase space, without work, and causes deviations from equilibrium scaling with the magnitude of environmental noise. We envision applications to noise-induced patterning performed by collections of microrobots guided by reinforcement learning or programmable phoretic colloids in turbulent flows that exploit local measurements and control actions to counteract the scrambling of information by chaos.

研究动机与目标

• 开发一个理论框架，用于描述扩展系统中，微观粒子通过测量与跃迁偏置之间的反馈，生成宏观有序结构。
• 证明自推进与形态分辨率并非因噪声而受阻，反而因信息驱动的控制机制而产生。
• 与传统活性物质对比，表明此类系统中作用力随噪声增加而增强，而传统‘工蜂’粒子则因能量耗散而表现减弱。
• 建立并模拟一个‘思考者’粒子的最小化系统，通过改变直径来调控散射，实现噪声到运动的转换。
• 探索其在微机器人、集体迁移以及生物体在湍流或噪声环境中导航的强化学习中的应用。

提出的方法

• 构建动理学理论框架，从涉及测量、跃迁偏置与反馈回路的微观粒子策略中推导宏观行为。
• 应用信息论论证，量化测量在打破细致平衡与实现非平衡动力学中的作用。
• 模拟由‘思考者’粒子构成的流体，其根据源自目标形态的局部场梯度，动态在小尺寸与大尺寸之间切换。
• 在周期性区域内使用带噪声分辨的随机力的朗之万动力学，模拟热涨落与粒子相互作用。
• 通过清空阶段实现图案书写协议，以降低帧间相关性，确保粒子在模拟域中分布均匀。
• 将‘思考者’粒子与施加恒定作用力的‘工蜂’粒子进行对比，使用相同的取向场与模拟条件，以隔离反馈控制的影响。

Figure 1: Information ratchets in biology and active matter. a Schematic representation of an information ratchet process. After measuring the fluctuating forces on the ratchet, a pawl is selectively inserted (withdrawn) to block (allow) counterclockwise (clockwise) rotations. With sufficient finess

实验结果

研究问题

• RQ1 在多体系统中，基于测量的反馈如何在不施加外部功的前提下，将环境噪声转化为定向自推进？
• RQ2 在扩展活性物质中，信息处理与噪声驱动跃迁的相互作用会涌现出何种宏观特性？
• RQ3 此类系统中的形态分辨率如何依赖于噪声水平？能否随涨落增加而改善？
• RQ4 ‘思考者’粒子（具备自适应尺寸调节能力）相较于依赖恒定作用力的‘工蜂’粒子，在性能上有哪些优势？
• RQ5 信息处理在打破细致平衡与实现活性物质非平衡稳态中扮演何种角色？

主要发现

• 信息性活性物质中自推进的出现不依赖净功，仅由对热噪声的测量与反馈驱动。
• 自推进力随环境噪声增加而增强，与传统活性物质中因对抗涨落而耗散能量的表现相反。
• 形态分辨率随噪声增加而提升，归因于测量反馈机制带来的增强灵敏度与控制能力。
• ‘思考者’粒子的模拟成功通过基于局部场梯度的动态直径调节，形成并维持了复杂图案（如字母）。
• 帧间过渡阶段的清空程序有效降低了空间相关性，确保了粒子在模拟域中分布均匀。
• ‘思考者’粒子在图案保真度与适应性方面优于‘工蜂’粒子，尤其在噪声环境中，归因于其通过测量驱动的尺寸变化调节相互作用的能力。

Figure 2: The thinker gas biases collisions to produce flows. a A simple discrete diameter rule for a thinker particle. Thinkers traveling right (left) adopt small (large) diameters. b Collision of a thinker with diameter rule a and an immobile object (blue disk). Diameter changes are prohibited whe