Deciphering long-range order in active matter: Insights from swimming bacteria in quasi-2D and electrokinetic Janus particles
Daiki Nishiguchi

TL;DR
This paper reviews how active matter systems like bacteria and Janus particles exhibit long-range order in two dimensions, combining theory, simulations, and experiments to understand this phenomenon beyond equilibrium physics.
Contribution
It provides a comprehensive overview of theoretical models, experimental evidence, and critical assessments of long-range order in active matter systems, highlighting future challenges.
Findings
Experimental evidence of long-range order in microswimmers
Theoretical predictions confirmed by experiments and simulations
Discussion of conditions enabling long-range order in active systems
Abstract
Emergent order resulting from spontaneous symmetry breakings has been a central topic in statistical physics. Active matter systems composed of nonequilibrium elements exhibit a diverse range of fascinating phenomena beyond equilibrium physics. One striking example is the emergent long-range orientational order in two dimensions, which is prohibited in equilibrium systems. The existence of long-range order in active matter systems was predicted first by a numerical model and proven analytically by dynamic renormalization group analysis. Experimental evidence for long-range order with giant number fluctuations has been provided in some experimental systems including microswimmers such as swimming bacteria and electrokinetic Janus particles. In this review, we provide a pedagogical introduction to the theoretical descriptions of long-range order in collective motion of active matter…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMicro and Nano Robotics · Advanced Thermodynamics and Statistical Mechanics · Microfluidic and Bio-sensing Technologies
