Collective Motion Of Self-propelled Particles Research Articles

The collective motion of self-propelled particles affected by the spatial-dependent noise based on Vicsek rules

The collective motion of self-propelled particles affected by the spatial-dependent noise based on Vicsek rules

Nonvanishing optimal noise in cellular automaton model of self-propelled particles

A minimal cellular automaton model is introduced to describe the collective motion of self-propelled particles on two-dimensional square lattice. The model features discretization of directional and positional spaces and single-particle occupation on one lattice site. Contrary to the Vicsek model and its variants, our model exhibits the nonvanishing optimal noise. When the particle density increases, the collective motion is promoted with optimal noise strength and reduced with noise strength out of optimal region. In addition, when the square lattice undergoes edge percolation process, no abrupt change of alignment behaviors is observed at the critical point of percolation.

Enhancing directed collective motion of self-propelled particles in confined channel

The collective transport of the self-propelled rods (SPRs) is studied by dissipative particle dynamics simulations. Two types of channels (channel I and channel II) are taken into account for various rod concentrations. It is found that in channel I—the asymmetric corrugated channel with periodically varying width, some SPRs are trapped at the corners and form the hedgehog clusters. Other SPRs aggregate at the bottleneck and lead to a traffic jam. Consequently, channel I is inefficient for the directional SPR transport in the case of finite concentration. To achieve efficient collective particle transport, channel II—the channel with constant width and arrays of asymmetric obstacles within it, which can avoid the traffic clogging and hedgehog aggregate is suggested. It is found that the swimmer-obstacle interaction gives rise to the directional motion, the spacing between obstacles can avoid the formation of the hedgehog clusters. The high-efficiency directional collective motion of the SPRs is acquired in channel II. Overall, our simulation study offers an efficient approach for directional collective motion of SPRs.

Monopolar flocking of microtubules in collective motion

Flocking is a fascinating coordinated behavior of living organisms or self-propelled particles (SPPs). Particularly, monopolar flocking has been attractive due to its potential applications in various fields. However, the underlying mechanism behind flocking and emergence of monopolar motion in flocking of SPPs has remained obscured. Here, we demonstrate monopolar flocking of kinesin-driven microtubules, a self-propelled biomolecular motor system. Microtubules with an intrinsic structural chirality preferentially move towards counter-clockwise direction. At high density, the CCW motion of microtubules facilitates monopolar flocking and formation of a spiral pattern. The monopolar flocking of microtubules is accounted for by a torque generated when the motion of microtubules was obstructed due to collisions. Our results shed light on flocking and emergence of monopolar motion in flocking of chiral active matters. This work will help regulate the polarity in collective motion of SPPs which in turn will widen their applications in nanotechnology, materials science and engineering.

Langevin Dynamic Simulation of self-propelled particles in two-dimensional systems

Collective motion of self-propelled particles is one of basic phenomenon observed in large spectra of biological system behavior due to the correlated process evolution in space and time. In this manuscript, we study numerically the kinetic properties and the correlation process in complex systems evolves out equilibrium phase by employing the Langevin dynamics. In this model, we have adopted one zone of orientation where the system evolves spontaneously in presence of quenched stochastic noise. The results show that the system evolves to its equilibrium phase by reaching one orientation. Hence, this evolution is characterized by a correlation process increasing in time but with decelerate profile. However the obtained profile of the correlation function per time unity shows that the collective motion in complex system, can be characterized by a characteristic time when the system change the acceleration of the correlation process. Our result shows that this characteristic time decreases exponentially with the quenched noise. In the additional crossover time at when the system reaches its equilibrium phase, scales with quenched noise as power law. This result is more consisting with the one of Vicsek model

Collective motion of self-propelled particles with complex noise environments

Collective motion of self-propelled particles with complex noise environments is investigated via simulations based on the Vicsek model. In our model, self-propelled particles move in a square divided into one part with noise and the other without noise. Via simulations, it is found that the proportion of noise region p has an important impact on the collective motion of the system. Specifically, there is a transition at the critical pc. When p<pc, all particles of the system can reach the global synchronization; on the contrary, when p>pc, the order parameter of synchronization rapidly decreases. More interestingly, the value of pc decreases as the noise amplitude η increases. Simultaneously, when p<pc, the proportion of the number of particles in the noise region λ approximates zero; conversely, when p>pc, the value of λ increases dramatically. Furthermore, pc gradually increases as the number of particles increases. Our results provide new sights into the study of collective motion in nature.

Linked vehicle model: A simple car-following model for automated vehicles

The expectation from automated vehicles has been increasing in recent years. Potential advantages for automated vehicles include driving safety, traffic efficiency, and positive environmental outcomes. To evaluate the extent to which automated vehicles are advantageous against conventional vehicles, this paper presents a simple car-following model, named the linked vehicle model, which reflects the capabilities of automated vehicles and the interaction between adjacent automated vehicles. The idea behind linked vehicle model is inspired by the collective motion of self-propelled particles in nature and the study of vehicle platooning from the Safe Road Trains for the Environment project. Moreover, the model is integrated into a traffic simulator in order to evaluate the performance of automated vehicles in an ideal circumstance. Comparisons with other representative car-following models are also provided, and they show that linked vehicle model achieves both optimal microscopic and macroscopic performance. Simulated results also show that linked vehicle model attains the best fuel economy and the lowest pollutant emissions.

Collective motion of self-propelled particles with density-dependent switching effect

We study the effect of density-dependent angular response on large scale collective motion, that particles are more likely to switch their moving direction within lower local density region. We show that the presence of density-dependent angular response leads to three typical phases: polar liquid, micro-phase separation and disordered gas states. In our model, the transition between micro-phase separation and disordered gas is discontinuous. Giant number fluctuation is observed in polar liquid phase with statistically homogeneous order. In the micro-phase separation parameter space, high order and high density bands dominate the dynamics. We also compare our results with Vicsek model and show that the density-dependent directional switching response can stabilize the band state to very low noise condition. This band stripe could recruit almost all the particles in the system, which greatly enhances the coherence of the system. Our results could be helpful for understanding extremely coherent motion in nature and also would have practical implications for designing novel self-organization pattern.

Collective Motion of Self-Propelled Particles with Memory

We show that memory, in the form of underdamped angular dynamics, is a crucial ingredient for the collective properties of self-propelled particles. Using Vicsek-style models with an Ornstein-Uhlenbeck process acting on angular velocity, we uncover a rich variety of collective phases not observed in usual overdamped systems, including vortex lattices and active foams. In a model with strictly nematic interactions the smectic arrangement of Vicsek waves giving rise to global polar order is observed. We also provide a calculation of the effective interaction between vortices in the case where a telegraphic noise process is at play, explaining thus the emergence and structure of the vortex lattices observed here and in motility assay experiments.

Elasticity-Based Mechanism for the Collective Motion of Self-Propelled Particles with Springlike Interactions: A Model System for Natural and Artificial Swarms

We introduce an elasticity-based mechanism that drives active particles to self-organize by cascading self-propulsion energy towards lower-energy modes. We illustrate it on a simple model of self-propelled agents linked by linear springs that reach a collectively rotating or translating state without requiring aligning interactions. We develop an active elastic sheet theory, complementary to the prevailing active fluid theories, and find analytical stability conditions for the ordered state. Given its ubiquity, this mechanism could play a relevant role in various natural and artificial swarms.

Optimal noise maximizes collective motion in heterogeneous media.

We study the effect of spatial heterogeneity on the collective motion of self-propelled particles (SPPs). The heterogeneity is modeled as a random distribution of either static or diffusive obstacles, which the SPPs avoid while trying to align their movements. We find that such obstacles have a dramatic effect on the collective dynamics of usual SPP models. In particular, we report about the existence of an optimal (angular) noise amplitude that maximizes collective motion. We also show that while at low obstacle densities the system exhibits long-range order, in strongly heterogeneous media collective motion is quasi-long-range and exists only for noise values in between two critical values, with the system being disordered at both large and low noise amplitudes. Since most real systems have spatial heterogeneities, the finding of an optimal noise intensity has immediate practical and fundamental implications for the design and evolution of collective motion strategies.

Traffic Jams, Gliders, and Bands in the Quest for Collective Motion of Self-Propelled Particles

We study a simple swarming model on a two-dimensional lattice where the self-propelled particles exhibit a tendency to align ferromagnetically. Volume exclusion effects are present: particles can only hop to a neighboring node if the node is empty. Here we show that such effects lead to a surprisingly rich variety of self-organized spatial patterns. As particles exhibit an increasingly higher tendency to align to neighbors, they first self-segregate into disordered particle aggregates. Aggregates turn into traffic jams. Traffic jams evolve toward gliders, triangular high density regions that migrate in a well-defined direction. Maximum order is achieved by the formation of elongated high density regions--bands--that transverse the entire system. Numerical evidence suggests that below the percolation density the phase transition associated with orientational order is of first order, while at full occupancy it is of second order.

Meandering instability in two-dimensional optimal velocity model for collective motion of self-propelled particles

We investigate the stability of a uniform flow of self-propelled particles in a two-dimensional optimal velocity model. As an initial condition, the particles are distributed uniformly in a narrow region of the space. This condition corresponds to a migration of organisms. It is found that the uniform flow is unstable and a meandering motion appears by numerical simulations. We also show the instability exists for any values of parameters by the linear analysis. It means that there is no stable uniform flow in this model.

Nature of the order-disorder transition in the Vicsek model for the collective motion of self-propelled particles

One of the most popular approaches to the study of the collective behavior of self-driven individuals is the well-known Vicsek model (VM) [T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, and O. Shochet, Phys. Rev. Lett. 75, 1226 (1995)]. In the VM one has that each individual tends to adopt the direction of motion of its neighbors with the perturbation of some noise. For low enough noise the individuals move in an ordered fashion with net transport of mass; however, when the noise is increased, one observes disordered motion in a gaslike scenario. The nature of the order-disorder transition, i.e., first-versus second-order, has originated an ongoing controversy. Here, we analyze the most used variants of the VM unambiguously establishing those that lead either to first- or second-order behavior. By requesting the invariance of the order of the transition upon rotation of the observational frame, we easily identify artifacts due to the interplay between finite-size and boundary conditions, which had erroneously led some authors to observe first-order transitionlike behavior.

Collective motion of self-propelled particles interacting without cohesion

We present a comprehensive study of Vicsek-style self-propelled particle models in two and three space dimensions. The onset of collective motion in such stochastic models with only local alignment interactions is studied in detail and shown to be discontinuous (first-order-like). The properties of the ordered, collectively moving phase are investigated. In a large domain of parameter space including the transition region, well-defined high-density and high-order propagating solitary structures are shown to dominate the dynamics. Far enough from the transition region, on the other hand, these objects are not present. A statistically homogeneous ordered phase is then observed, which is characterized by anomalously strong density fluctuations, superdiffusion, and strong intermittency.

Collective Motion of Self-Propelled Particles: Kinetic Phase Transition in One Dimension

We demonstrate that a system of self-propelled particles exhibits spontaneous symmetry breaking and self-organization in one dimension, in contrast with previous analytical predictions. To explain this surprising result we derive a new continuum theory that can account for the development of the symmetry broken state and belongs to the same universality class as the discrete self-propelled particle model.