Kachman Tal, Owen Jeremy A, England Jeremy L
Physics of Living Systems Group, Department of Physics, Massachusetts Institute of Technology, 400 Tech Square, Cambridge, Massachusetts 02139, USA.
Machine Learning for Healthcare and Life Sciences, IBM Research Laboratory, Haifa 3498825, Israel.
Phys Rev Lett. 2017 Jul 21;119(3):038001. doi: 10.1103/PhysRevLett.119.038001.
Recent studies of active matter have stimulated interest in the driven self-assembly of complex structures. Phenomenological modeling of particular examples has yielded insight, but general thermodynamic principles unifying the rich diversity of behaviors observed have been elusive. Here, we study the stochastic search of a toy chemical space by a collection of reacting Brownian particles subject to periodic forcing. We observe the emergence of an adaptive resonance in the system matched to the drive frequency, and show that the increased work absorption by these resonant structures is key to their stabilization. Our findings are consistent with a recently proposed thermodynamic mechanism for far-from-equilibrium self-organization.
近期对活性物质的研究激发了人们对复杂结构驱动自组装的兴趣。对特定例子的唯象建模已带来一些见解，但统一所观察到的丰富多样行为的一般热力学原理却难以捉摸。在此，我们研究了受周期驱动的反应性布朗粒子集合对一个简单化学空间的随机搜索。我们观察到系统中出现了与驱动频率匹配的自适应共振，并表明这些共振结构增加的功吸收是其稳定的关键。我们的发现与最近提出的一种远离平衡自组织的热力学机制相一致。
