Large-scale Collective Motion Research Articles

Collective motion in a sheet of microswimmers

Self-propelled particles such as bacteria or algae swimming through a fluid are non-equilibrium systems where particle motility breaks microscopic detailed balance, often resulting in large-scale collective motion. Previous theoretical work has identified long-ranged hydrodynamic interactions as the driver of collective motion in unbounded suspensions of rear-actuated (“pusher”) microswimmers. In contrast, most experimental studies of collective motion in microswimmer suspensions have been carried out in restricted geometries where both the swimmers’ motion and their long-range flow fields become altered due to the proximity of a boundary. Here, we study numerically a minimal model of microswimmers in such a restricted geometry, where the particles move in the midplane between two no-slip walls. For pushers, we demonstrate collective motion with short-ranged order, in contrast with the long-ranged flows observed in unbounded systems. For front-actuated (“puller”) microswimmers, we discover a long-wavelength density instability resulting in the formation of dense microswimmer clusters. Both types of collective motion are fundamentally different from their previously studied counterparts in unbounded domains. Our results show that this difference is dictated by the geometrical restriction of the swimmers’ motion, while hydrodynamic screening due to the presence of a wall is subdominant in determining the suspension’s collective state.

Intelligent Control of Swarm Robotics Employing Biomimetic Deep Learning

The collective motion of biological species has robust and flexible characteristics. Since the individual of the biological group interacts with other neighbors asymmetrically, which means the pairwise interaction presents asymmetrical characteristics during the collective motion, building the model of the pairwise interaction of the individual is still full of challenges. Based on deep learning (DL) technology, experimental data of the collective motion on Hemigrammus rhodostomus fish are analyzed to build an individual interaction model with multi-parameter input. First, a Deep Neural Network (DNN) structure for pairwise interaction is designed. Then, the interaction model is obtained by means of DNN proper training. We propose a novel key neighbor selection strategy, which is called the Largest Visual Pressure Selection (LVPS) method, to deal with multi-neighbor interaction. Based on the information of the key neighbor identified by LVPS, the individual uses the properly trained DNN model for the pairwise interaction. Compared with other key neighbor selection strategies, the statistical properties of the collective motion simulated by our proposed DNN model are more consistent with those of fish experiments. The simulation shows that our proposed method can extend to large-scale group collective motion for aggregation control. Thereby, the individual can take advantage of quite limited local information to collaboratively achieve large-scale collective motion. Finally, we demonstrate swarm robotics collective motion in an experimental platform. The proposed control method is simple to use, applicable for different scales, and fast for calculation. Thus, it has broad application prospects in the fields of multi-robotics control, intelligent transportation systems, saturated cluster attacks, and multi-agent logistics, among other fields.

Interpretable conservation law estimation by deriving the symmetries of dynamics from trained deep neural networks.

Understanding complex systems with their reduced model is one of the central roles in scientific activities. Although physics has greatly been developed with the physical insights of physicists, it is sometimes challenging to build a reduced model of such complex systems on the basis of insight alone. We propose a framework that can infer hidden conservation laws of a complex system from deep neural networks (DNNs) that have been trained with physical data of the system. The purpose of the proposed framework is not to analyze physical data with deep learning but to extract interpretable physical information from trained DNNs. With Noether's theorem and by an efficient sampling method, the proposed framework infers conservation laws by extracting the symmetries of dynamics from trained DNNs. The proposed framework is developed by deriving the relationship between a manifold structure of a time-series data set and the necessary conditions for Noether's theorem. The feasibility of the proposed framework has been verified in some primitive cases in which the conservation law is well known. We also apply the proposed framework to conservation law estimation for a more practical case, that is, a large-scale collective motion system in the metastable state, and we obtain a result consistent with that of a previous study.

Enhanced persistence and collective migration in cooperatively aligning cell clusters

Most cells possess the capacity to locomote. Alone or collectively, this allows them to adapt, to rearrange, and to explore their surroundings. The biophysical characterization of such motile processes, in health and in disease, has so far focused mostly on two limiting cases: single-cell motility on the one hand and the dynamics of confluent tissues such as the epithelium on the other. The in-between regime of clusters, composed of relatively few cells moving as a coherent unit, has received less attention. Such small clusters are, however, deeply relevant in development but also in cancer metastasis. In this work, we use cellular Potts models and analytical active matter theory to understand how the motility of small cell clusters changes with N, the number of cells in the cluster. Modeling and theory reveal our two main findings: cluster persistence time increases with N, whereas the intrinsic diffusivity decreases with N. We discuss a number of settings in which the motile properties of more complex clusters can be analytically understood, revealing that the focusing effects of small-scale cooperation and cell-cell alignment can overcome the increased bulkiness and internal disorder of multicellular clusters to enhance overall migrational efficacy. We demonstrate this enhancement for small-cluster collective durotaxis, which is shown to proceed more effectively than for single cells. Our results may provide some novel, to our knowledge, insights into the connection between single-cell and large-scale collective motion and may point the way to the biophysical origins of the enhanced metastatic potential of small tumor cell clusters.

A combined rheometry and imaging study of viscosity reduction in bacterial suspensions

Suspending self-propelled "pushers" in a liquid lowers its viscosity. We study how this phenomenon depends on system size in bacterial suspensions using bulk rheometry and particle-tracking rheoimaging. Above the critical bacterial volume fraction needed to decrease the viscosity to zero, [Formula: see text], large-scale collective motion emerges in the quiescent state, and the flow becomes nonlinear. We confirm a theoretical prediction that such instability should be suppressed by confinement. Our results also show that a recent application of active liquid-crystal theory to such systems is untenable.

On the hurricane collective molecular dynamics

We study the molecular dynamics underlying the formation and the evolution of hurricanes. The giant global structure of hurricanes cannot be solely the results of random molecular kinematics. We show that the non-stationary, topologically non-trivial hurricane behavior is the manifestation of the collective dynamics at the molecular level. This is described in terms of spontaneous breakdown of the rotational symmetry of the water molecule electrical dipoles. The long range molecular correlations generated as a consequence of the spontaneous breakdown of symmetry are responsible of the large scale collective motion resulting in the hurricane structure. The critical non-stationary dynamics is analyzed in terms of the non-stationary time dependent Ginzburg-Landau equation leading to the vortex equation. Phase transition, criticality, temperature dependence, energy exchanges and entropy are studied. Energy storage and dissipation processes in the coherent state dynamics are analyzed. Finally the self-similar fractal structure of the hurricane is shown to be the manifestation of the coherence of the collective molecular dynamics.

String-like collective motion in the α- and β-relaxation of a coarse-grained polymer melt.

Relaxation in glass-forming liquids occurs as a multi-stage hierarchical process involving cooperative molecular motion. First, there is a "fast" relaxation process dominated by the inertial motion of the molecules whose amplitude grows upon heating, followed by a longer time α-relaxation process involving both large-scale diffusive molecular motion and momentum diffusion. Our molecular dynamics simulations of a coarse-grained glass-forming polymer melt indicate that the fast, collective motion becomes progressively suppressed upon cooling, necessitating large-scale collective motion by molecular diffusion for the material to relax approaching the glass-transition. In each relaxation regime, the decay of the collective intermediate scattering function occurs through collective particle exchange motions having a similar geometrical form, and quantitative relationships are derived relating the fast "stringlet" collective motion to the larger scale string-like collective motion at longer times, which governs the temperature-dependent activation energies associated with both thermally activated molecular diffusion and momentum diffusion.

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.

The transport coefficient of collective motion within the two-center shell model shape parameterization

The transport coefficients of large-scale nuclear collective motion (potential energy, tensors of friction and mass) used in the description of fission process or fusion–fission reactions with the help of Langevin equations are calculated within the two-center shell-model shape parameterization. The transport coefficients are defined both in the macroscopic (wall formula for friction and Werner–Wheeler approximation for the mass tensor) and microscopic (linear response theory and local harmonic approximation) approaches. It is shown that at low excitation energy, the macroscopic and microscopic quantities differ substantially in dependence both on deformation and temperature. Thus, the microscopic effect in transport coefficients should be taken in account by the description of low-energy nuclear collisions and fission process.

Suppressing turbulence of self-propelling rods by strongly coupled passive particles.

The strong turbulence suppression, mainly for large-scale modes, of two-dimensional self-propelling rods, by increasing the long-range coupling strength Γ of low-concentration passive particles, is numerically demonstrated. It is found that large-scale collective rod motion in forms of swirls or jets is mainly contributed from well-aligned dense patches, which can push small poorly aligned rod patches and uncoupled passive particles. The more efficient momentum transfer and dissipation through increasing passive particle coupling leads to the formation of a more ordered and slowed down network of passive particles, which competes with coherent dense active rod clusters. The frustration of active rod alignment ordering and coherent motion by the passive particle network, which interrupt the inverse cascading of forming large-scale swirls, is the key for suppressing collective rod motion with scales beyond the interpassive distance, even in the liquid phase of passive particles. The loosely packed active rods are weakly affected by increasing passive particle coupling due to the weak rod-particle interaction. They mainly contribute to the small-scale modes and high-speed motion.

Inverse-kinematics study of78Kr +40Ca at 10 AMeV

The CHIMERA multi-detector array at LNS Catania has been used to study the inverse-kinematics reaction of 78 Kr + 40 Ca at a bombarding energy of 10 AMeV. Analysis of the experimental data focused on a class of selected events consistent with the complete fusion and subsequent binary split of the of the reacting system. This class of events features a broad A, Z distribution of fission fragments centered about symmetric fission while exhibiting relative velocities significantly higher than given by Viola systematics. The center-ofmass angular distribution (dσ/dΘ) of the fission fragments exhibit an unexpected anisotropy inconsistent with a compound-nucleus reaction and indicates a dynamic fusion-fission like process. The observed angular distribution features an asymmetric forward-backward peaking most prevalent for mass-asymmetric events. Furthermore, the more massive fragment of mass-asymmetric events appears to emerge preferentially in the forward direction, along the beam axis, in analogy to dynamic fragmentation of projectile-like fragments. Analysis of the angular distribution of alpha particles emitted from these fission fragments suggests the events are associated mostly with central collisions. The study of low-energy heavy-ion reaction dynamics in the energy domain moderately in excess of the Coulomb barrier offers a unique insight into the large-scale collective motion of the nucleons in the nucleus. Fusion-fission constitutes an important reaction channel for many such nuclear reactions and is an important probe into the nuclear structure of matter. As the bombarding energy increases, the role of dynamically-induced decay modes

Large-scale molecular dynamics simulations of glancing angle deposition

Using a computationally efficient method, we have carried out large-scale molecular dynamics simulations of Cu/Cu(100) growth up to 20 monolayers (ML) for deposition angles ranging from 50° to 85° and for both random and fixed azimuthal angles. A variety of quantities including the porosity, roughness, lateral correlation length, average grain size, strain, and defect concentration are used to characterize the thin-film morphology. For large deposition angles (θ≥80°), we find well-defined columnar growth while for smaller angles, columnar growth has not yet set in. In addition, for θ=70°−85°, the thin-film porosity and columnar tilt angles (for fixed azimuthal angle ϕ) are in reasonable agreement with experiments. For both random and fixed ϕ, the number of grains, average grain-size, and number of surface atoms belonging to (111) facets increase rapidly with deposition angle. As a result, twin facet formation and budding occur in our simulations, in good agreement with experiments. In good qualitative agreement with recent experimental observations, we also find that the average strain is initially compressive but becomes tensile after the onset of columnar growth. Our simulations also reveal that for large deposition angles a variety of unexpected and complex dynamical processes play a key role in determining the evolution of the surface morphology and microstructure. In particular, due to the existence of deposition-induced events, the vacancy density remains very small, even though the defect density is relatively large and increases with deposition angle. In addition, large-scale re-arrangement events as well as thermal (elastic) vibrations lead to large-amplitude oscillations in the columnar growth regime. These oscillations play a key role in promoting rapid coalescence via additional large-scale collective motion, thus, significantly enhancing the coarsening process.

Viscosity of bacterial suspensions: Hydrodynamic interactions and self-induced noise

The viscosity of a suspension of swimming bacteria is investigated analytically and numerically. We propose a simple model that allows for efficient computation for a large number of bacteria. Our calculations show that long-range hydrodynamic interactions, intrinsic to self-locomoting objects in a viscous fluid, result in a dramatic reduction of the effective viscosity. In agreement with experiments on suspensions of Bacillus subtilis, we show that the viscosity reduction is related to the onset of large-scale collective motion due to interactions between the swimmers. The simulations reveal that the viscosity reduction occurs only for relatively low concentrations of swimmers: Further increases of the concentration yield an increase of the viscosity. We derive an explicit asymptotic formula for the effective viscosity in terms of known physical parameters and show that hydrodynamic interactions are manifested as self-induced noise in the absence of any explicit stochasticity in the system.

Large-scale collective motion of RFGC galaxies in curved space-time

We consider large-scale collective motion of flat edge-on spiral galaxies from the Revised Flat Galaxy Catalogue (RFGC) taking into account the curvature of space-time in the Local Universe at the scale 100 Mpc/h. We analyse how the relativistic model of collective motion should be modified to provide the best possible values of parameters, the effects that impact these parameters and ways to mitigate them. Evolution of galactic diameters, selection effects, and difference between isophotal and angular diameter distances are inadequate to explain this impact. At the same time, measurement error in HI line widths and angular diameters can easily provide such an impact. This is illustrated in a toy model, which allows analytical consideration, and then in the full model using Monte Carlo simulations. The resulting velocity field is very close to that provided by the non-relativistic model of motion. The obtained bulk flow velocity is consistent with {\Lambda}CDM cosmology.

Collective Motion of Vibrated Polar Disks

We experimentally study a monolayer of vibrated disks with a built-in polar asymmetry which enables them to move quasibalistically on a large persistence length. Alignment occurs during collisions as a result of self-propulsion and hard core repulsion. Varying the amplitude of the vibration, we observe the onset of large-scale collective motion and the existence of giant number fluctuations with a scaling exponent in agreement with the predicted theoretical value.

Large-scale collective motion of RFGC galaxies

We processed the data about radial velocities and HI linewidths for 1678 flat edge-on spirals from the Revised Flat Galaxy Catalogue. We obtained the parameters of the multipole components of large-scale velocity field of collective non-Hubble galaxy motion as well as the parameters of the generalized Tully-Fisher relationship in the "HI line width - linear diameter" version. All the calculations were performed independently in the framework of three models, where the multipole decomposition of the galaxy velocity field was limited to a dipole, quadrupole and octopole terms respectively. We showed that both the quadrupole and the octopole components are statistically significant. On the basis of the compiled list of peculiar velocities of 1623 galaxies we obtained the estimations of cosmological parameters Omega_m and sigma_8. This estimation is obtained in both graphical form and as a constraint of the value S_8=sigma_8(Omega_m/0.3)^0.35 = 0.91 +/- 0.05.

Enhanced mixing and spatial instability in concentrated bacterial suspensions

High-resolution optical coherence tomography is used to study the onset of a large-scale convective motion in free-standing thin films of adjustable thickness containing suspensions of swimming aerobic bacteria. Clear evidence is found that beyond a threshold film thickness there exists a transition from quasi-two-dimensional collective swimming to three-dimensional turbulent behavior. The latter state, qualitatively different from bioconvection in dilute bacterial suspensions, is characterized by enhanced diffusivities of oxygen and bacteria. These results emphasize the impact of self-organized bacterial locomotion on the onset of three-dimensional dynamics, and suggest key ingredients necessary to extend standard models of bioconvection to incorporate effects of large-scale collective motion.

Fluctuations and Correlations of Pure Quantum Turbulence in SuperfluidHe3−B

We describe the first measurements of line-density fluctuations and spatial correlations of quantum turbulence in superfluid 3He-B. All of the measurements are performed in the low-temperature regime, where the normal-fluid density is negligible. The quantum turbulence is generated by a vibrating grid. The vortex-line density is found to have large length-scale correlations, indicating large-scale collective motion of vortices. Furthermore, we find that the power spectrum of fluctuations versus frequency obeys a -5/3 power law which verifies recent speculations that this behavior is a generic feature of fully developed quantum turbulence, reminiscent of the Kolmogorov spectrum for velocity fluctuations in classical turbulence.

Swirling motion in a system of vibrated elongated particles

Large-scale collective motion emerging in a monolayer of vertically vibrated elongated particles is studied. The motion is characterized by recurring swirls, with the characteristic scale exceeding several times the size of an individual particle. Our experiments identified a small horizontal component of the oscillatory acceleration of the vibrating plate in combination with orientation-dependent bottom friction (with respect to horizontal acceleration) as a source for the swirl formation. We developed a continuum model operating with the velocity field and local alignment tensor, which is in qualitative agreement with the experiment.

Directed Energy “Funneling" Mechanism for Heme Cooling Following Ligand Photolysis or Direct Excitation in Solvated Carbonmonoxy Myoglobin

The kinetic energy relaxation of photolyzed heme in myoglobin was investigated using molecular dynamics simulations. Following photolysis, the heme was found to lose most of its excess kinetic energy within 10 ps. The kinetic energy decay was found to be a single exponential with a time constant of 5.9 ps in agreement with the experimental observations of Lim, Jackson and Anfinrud [J. Phys. Chem. 100, 12 043 (1996)]. The flow of kinetic energy was found to occur primarily through nonbonded contacts. The heme doming motion causes collisions with nearby residues and large scale collective motion in the protein. However, the strong electrostatic interaction of the isoproprionate side chains, and the solvating water appears to be the single most important “doorway” for dissipation of excess kinetic energy in the heme. Those water molecules in close contact with the heme side chains were found to “warm” in less than 1.0 ps. Direct energy transfer from the heme to the protein is found to occur by “through projectile” (ligand collisions with the distal heme pocket residue), “through bond” (heme bond to proximal histidine), and “through space” (nonbonded collisional) channels. These results provide strong evidence for a spatially directed “funneling” of kinetic energy through the heme side chains to the surrounding solvent suggested by Hochstrasser and co-workers.