arXiv subjects

Wei-chen Guo

Publications and source records attributed to Wei-chen Guo.

4 recordsLinked to original sources

arXiv2023

Scaling behavior of transient dynamics of vortex-like states in self-propelled particles

Nonequilibrium many-body transient dynamics play an important role in the adaptation of active matter systems environment changes. However, the generic universal behavior of such dynamics is usually elusive and left as open questions. Here, we investigate the transient dynamics of vortex-like states in a two-dimensional active matter system that consists of self-propelled particles with alignment interactions subjected to extrinsic environmental noise. We identify a universal power-law scaling for the average lifetime of vortex-like states with respect to the speed of the self-propelled particles. This universal scaling behavior manifests strong robustness against the noise, up to the level where influences from environmental fluctuations are large enough to directly randomize the moving directions of particles. Direct experimental observations can be readily performed by related experimental setups operated at a decently low noise level.

cond-mat.stat-mech↗

arXiv2022

Real-space condensation of reciprocal active particles driven by spontaneous symmetry breaking induced nonreciprocity

We investigate the steady-state and dynamical properties of a reciprocal many-body system consisting of self-propelled active particles with local alignment interactions that exists within a fan-shaped neighborhood of each particle. We find that the nonreciprocity can emerge in this reciprocal system once the spontaneous symmetry breaking is present, and the effective description of the system assumes a non-Hermitian structure that directly originates from the emergent nonreciprocity. This emergent nonreciprocity can impose strong influences on the properties the system. In particular, it can even drive a real-space condensation of active particles. Our findings pave the way for identifying a new class of physics in reciprocal systems that is driven by the emergent nonreciprocity.

cond-mat.stat-mech↗

arXiv2022

Scanning-probe and information-concealing machine learning intermediate hexatic phase and critical scaling of solid-hexatic phase transition in deformable particles

We investigate the two-dimensional melting of deformable polymeric particles with multi-body interactions described by the Voronoi model. We report machine learning evidence for the existence of the intermediate hexatic phase in this system, and extract the critical exponent $ν\approx0.65$ for the divergence of the correlation length of the associated solid-hexatic phase transition. Moreover, we clarify the discontinuous nature of the hexatic-liquid phase transition in this system. These findings are achieved by directly analyzing system's spatial configurations with two generic machine learning approaches developed in this work, dubbed "scanning-probe" via which the possible existence of intermediate phases can be efficiently detected, and "information-concealing" via which the critical scaling of the correlation length in the vicinity of generic continuous phase transition can be extracted. Our work provides new physical insights into the fundamental nature of the two-dimensional melting of deformable particles, and establishes a new type of generic toolbox to investigate fundamental properties of phase transitions in various complex systems.

cond-mat.soft↗

arXiv2021

Data-driven criterion for the solid-liquid transition of two-dimensional self-propelled colloidal particles far from equilibrium

We establish an explicit data-driven criterion for identifying the solid-liquid transition of two-dimensional self-propelled colloidal particles in the far from equilibrium parameter regime, where the transition points predicted by different conventional empirical criteria for melting and freezing diverge. This is achieved by applying a hybrid machine learning approach that combines unsupervised learning with supervised learning to analyze over one million of the system's configurations in the nonequilibrium parameter regime. Furthermore, we establish a generic data-driven evaluation function, according to which the performance of different empirical criteria can be systematically evaluated and improved. In particular, by applying this evaluation function, we identify a new nonequilibrium threshold value for the long-time diffusion coefficient, based on which the predictions of the corresponding empirical criterion are greatly improved in the far from equilibrium parameter regime. These data-driven approaches provide a generic tool for investigating phase transitions in complex systems where conventional empirical ones face difficulties.

cond-mat.soft↗