Collective Dynamics Research Articles

Correlation of strontium anharmonicity with charge-lattice dynamics of the apical oxygens and their coupling to cuprate superconductivity

By means of Cu K edge x-ray absorption spectra of overdoped high-pressure oxygenated superconducting and , we demonstrate a remarkably strong three way correlation between the superconductivity and the local dynamics of their highly anharmonic Cu–Sr and Cu-apical O pairs. We model the latter as aspects of the Internal Quantum Tunneling Polarons (IQTPs) that give the two-site distributions in extended x-ray absorption fine structure and inelastic pair distribution function measurements. This finding obviates the common assumption that the universal Ba/Sr-apical O dielectric layer, far from only maintaining the separation of charges between the charge reservoir and the conducting domains, plays an unexpectedly active role in the unusual electronic properties of cuprate superconductors. Furthermore, we investigate the effects of the dynamic structure associated with these pairs by means of the exact diagonalization of a prototype Hamiltonian based on a six-atom cluster, with two neighboring Cu-apical O pairs bridged by an anharmonically coupled Sr atom and a planar O atom. In terms of the Kuramoto model for synchronization, these calculations show a first order phase transition, driven by anharmonicity, to a synchronized state of the IQTPs, in which a fraction of the charge originally confined to the apical O sites is transferred onto the planar O in the superconducting plane. This combination of experimental results and theory demonstrates that the Ba/Sr-apical O layer of cuprates most likely plays an important role in high temperature superconductivity via its collective charge dynamics.

Individual dynamics and local heterogeneity provide a microscopic view of the epidemic spreading

The COVID-19 pandemic has caused severe global disasters, highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures. While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features, their treatment usually lacks spatiotemporal variation. Here, we propose a stochastic individual dynamical (SID) model to mimic the random and heterogeneous nature of epidemic propagation. The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual. Using this model, we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak. The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective, enabling a quantitative assessment of different interventions. Seemingly, this model is also applicable to studying stochastic processes at the “meter scale”, e.g., human society’s collective dynamics.

Fluctuation-driven self-trapping in Bose-Bose mixtures

We investigate the collective dynamics of two-component Bose-Einstein condensates in a double well potential. By taking into account the Lee-Huang-Yang (LHY) correction from quantum fluctuation, we find that the LHY term, though much smaller than the mean field interactions, can significantly change the coherent oscillating behaviors of the bosonic Josephson junction in the regime of g12≃−g11g22. Besides the quantitative renormalization to the plasma frequencies of the Josephson oscillations, a series of unexpected nonzero fixed points beyond mean field emerges in the stationary state. More remarkably, unique macroscopic self-trapping states, which are usually absent in the mean field dynamics, can be sustained by the LHY nonlinearity. Our results reveal the nontrivial LHY effect on the Josephson dynamics, which can be tested in the current experiment. Published by the American Physical Society 2024

Magnetically driven confined colloids: From enhanced diffusion to bidirectional transport

Inspired by previous experimental results, we use numerical simulations to investigate the collective dynamics of paramagnetic colloidal particles confined between two plates closer than twice the particle diameter and driven by an external precessing magnetic field. We show that, when the field is spatially isotropic there is no net particle current and the colloids display enhanced diffusive dynamics with an effective diffusion coefficient which raises up to 60 times that of the undriven case. In contrast, when the field is spatially anisotropic due to a small tilt angle δ, the particles organize into a robust bidirectional current, flowing along two parallel planes by periodically exchanging their positions. In this regime, we also analyze how the presence of small impurities which can be described as “magnetic holes” affect the particle current breaking the bidirectional flow. Our system provides a general method to transport magnetic colloids in a viscous fluid, without using any field gradient, but based on the fine balance between confinement and magnetic dipolar interactions.

A Bio-inspired Model for Bee Simulations.

As eusocial creatures, bees display unique macro collective behavior and local body dynamics that hold potential applications in various fields, such as computer animation, robotics, and social behavior. Unlike birds and fish, bees fly in a low-aligned zigzag pattern. Additionally, bees rely on visual cues for foraging and predator avoidance, exhibiting distinctive local body oscillations, such as body lifting, thrusting, and swaying. These inherent features pose significant challenges for realistic bee simulations in practical animation applications. In this paper, we present a bio-inspired model for bee simulations capable of replicating both macro collective behavior and local body dynamics of bees. Our approach utilizes a visually-driven system to simulate a bee's local body dynamics, incorporating obstacle perception and body rolling control for effective collision avoidance. Moreover, we develop an oscillation rule that captures the dynamics of the bee's local bodies, drawing on insights from biological research. Our model extends beyond simulating individual bees' dynamics; it can also represent bee swarms by integrating a fluid-based field with the bees' innate noise and zigzag motions. To fine-tune our model, we utilize pre-collected honeybee flight data. Through extensive simulations and comparative experiments, we demonstrate that our model can efficiently generate realistic low-aligned and inherently noisy bee swarms.

Collective dynamics in active solids

After 25 years of research activity, the physics of collective motions -- flights of starlings, shoals of fish, micro-swimmers or artificial walkers -- is well understood. Here, we describe a new form of self-organization, emerging from the coupling between elasticity and activity: collective actuation, the solid counterpart of collective movements.

Percolation transitions in a binary mixture of active Brownian particles with different softness.

Homogeneous active Brownian particle (ABP) systems with purely repulsive interactions are considered to exhibit a simple phase behavior, but various physical attributes of active entities can lead to variation in the collective dynamics. Recent studies have shown that even homogeneous ABPs exhibit complex behavior due to an interplay between particle softness and motility. However, the heterogeneity in the composition of ABPs has not been explored yet. In this paper, we study the structural properties of a binary mixture of ABPs with different particle softness by varying the relative softness and composition. We found that upon varying the motility parameter, the system underwent a motility-induced phase separation (MIPS) followed by a percolation transition similar to the homogeneous systems. However, we observed a novel feature: the formation of a space-filling structure made of particles with higher stiffness, within the dense cluster of MIPS containing both types of particles. Our systematic analysis shows that this structure formation occurs only if the difference in softness of both types of particles is sufficiently large. Furthermore, the presence of a non-linear scaling for different compositions of binary ABPs suggests that there is a complex relationship between the composition and the structural properties. Our study demonstrates that the composition heterogeneity of ABPs can lead to complex phase behavior.

An experimental overview: Collective dynamics

One of the most studied phenomena in heavy-ion physics is the collective emission of particles. Historically, the observation of collectivity in nucleus-nucleus collisions has been viewed as proof of the creation of a strongly interacting medium, as neither independent particle emission nor hadronic interactions alone could account for measurements. Intriguingly, collective particle emission was recently also measured in small collision systems, ranging from proton-proton to even high-multiplicity e+e− collisions. In these proceedings, I will elaborate on the current status of the experimental findings regarding collectivity and discuss their implications for the future.

Collective Neural Dynamics for Sparse Motion Planning of Redundant Manipulators Without Hessian Matrix Inversion.

Redundant manipulators have been widely used in various industries whose applications not only improve production efficiency and reduce manual labor but also promote innovation in robotics and artificial intelligence. Kinematic control plays a fundamental and crucial role in robot control. Over the past few decades, numerous motion control schemes have been proposed and applied to trajectory tracking tasks. However, most of these schemes do not consider the introduction of sparsity into the motion control of redundant manipulators, resulting in excessive joint movements, which not only consume extra energy but also increase the risk of unexpected collisions in complex environments. To solve this problem, we transform the issue of increasing the sparsity into a nonconvex optimization problem. Furthermore, a collective neural dynamics for sparse motion planning (CNDSMP) scheme for motion planning of redundant manipulators is proposed. By incorporating sparsity into the control scheme, the excessive joint movements are minimized, leading to improved efficiency and reduced collision risks. Through simulations, comparisons, and physical experiments, the effectiveness and superiority of the proposed scheme are demonstrated.

Correlation between Hydration States and Self-assembly Structures of Phospholipid and Surfactant Studied by Terahertz Spectroscopy.

Phospholipids and surfactants form membranes and other self-assembled structures in water. However, it is not fully understood how the surrounding water (hydration water) is involved in their structure formation. In this paper, I summarize the results of our investigation of the long-range hydration state of phospholipids and surfactants at their surfaces by means of terahertz spectroscopy. By observing the collective rotational dynamics of water in the picosecond time scale, this technique allows us to observe not only the water directly bound to the solute, but also the weakly affected water outside of it. For example, PC phospholipids inhibit water dynamics over long distances, whereas PE phospholipids make water more mobile than bulk water. The causes of this difference in hydration and how it is involved in the structural formation of the membrane are reviewed.

Asymptotic behavior of a kinetic approach to the collective dynamics of a rock-paper-scissors binary game

Asymptotic behavior of a kinetic approach to the collective dynamics of a rock-paper-scissors binary game

Interplay of a unit-speed constraint and time-delay in the flocking model with internal variables

<p>We studied the dynamics of thermodynamic Cucker–Smale (TCS) particles moving with a constant speed constraint. The TCS model describes the collective dynamics of the population of birds with a time varying internal variable, and it was first introduced as the generalization of the Cucker–Smale (CS) model. In this paper, we considered a modification of the TCS model in which each agent moves at a constant speed, such as the Vicsek model, and we additionally considered the effect of time-delays due to the finiteness of the information propagation speed between agents. Then, we presented several sufficient conditions in terms of initial data and system parameters to exhibit asymptotic flocking. We presented two kinds of results for this purpose. One was an estimate of the diameter of the velocity and temperature configuration, and the other was an estimate of the diameter of the configuration within the time-delay bound $ \tau $.</p>

Collective dynamics - Theoretical overview

I overview the recent progress of phenomenological studies exploring collective dynamics in relativistic nuclear collisions to understand various QCD properties. Originally, collectivity was interpreted as a manifestation of the hydrodynamic behaviour of the QGP as a response to the initial collision geometry. Over the past decade, however, particularly following the experimental observation of momentum azimuthal anisotropy in small colliding systems, pioneering studies have demonstrated the possibility of other interpretations. In this talk, I highlight recent studies aimed at understanding various QCD properties at different collision stages through the lens of collectivity and emphasize the importance of establishing Monte Carlo event generators for relativistic nuclear collisions.

Confined bicontinuous microemulsions: nanoscale dynamics of the surfactant film.

A confined bicontinuous C10E4-D2O-n-octane microemulsion is studied using neutron spin echo spectroscopy (NSE). Controlled pore glasses serve as confining matrices with pore diameters ranging from 24 to 112 nm. Firstly, the microemulsion in bulk is investigated by NSE and dynamic light scattering, which allows the determination of the unperturbed collective dynamics as well as the observation of the undulation of the surfactant film. In confinement, it is observed that the collective modes are drastically slowed down in all investigated pore sizes. The undulations of the surfactant film in the largest pores are found to be comparable to those of the bulk and decrease with decreasing pore diameter. Fitting procedures of the intermediate scattering function revealed that the long wavelength undulations are cut off from the spectrum of fluctuation modes due to the interactions with the pore walls.

Particle-based model of liquid crystal skyrmion dynamics.

Motivated by recent experimental results that reveal rich collective dynamics of thousands-to-millions of active liquid crystal skyrmions, we have developed a coarse-grained, particle-based model of the dynamics of skyrmions in a dilute regime. The basic physical mechanism of skyrmion motion is related to squirming undulations of domains with high director twist within the skyrmion cores when the electric field is turned on and off. The motion is not related to mass flow and is caused only by the reorientation dynamics of the director field. Based on the results of the "fine-grained" Frank-Oseen continuum model, we have mapped these squirming director distortions onto an effective force that acts asymmetrically upon switching the electrical field on or off. The resulting model correctly reproduces the skyrmion dynamics, including velocity reversal as a function of the frequency of a pulse width modulated driving voltage. We have also obtained approximate analytical expressions for the phenomenological model parameters encoding their dependence upon the cholesteric pitch and the strength of the electric field. This has been achieved by fitting coarse-grained skyrmion trajectories to those determined in the framework of the Frank-Oseen model.

3D Simulation of Active thin Structures in a Viscous Fluid and Application to Mucociliary Transport

We propose a hierarchy of mathematical models for the numerical simulation of active thin structures in a viscous fluid and its application to mucociliary clearance. Our aim is to simulate large forests of cilia and analyze the collective dynamics arising in the flow, as well as their impact on the efficiency of the mucus transport. In a 3D model we describe the cilia individually and study their joint actions on the fluid. The model is built upon a 3D Stokes problem with singular source terms that represent the action of the 1D cilia on the fluid, including the influence of the background flow (making the problem nonlocal). Surface tension between the periciliary layer and the mucus is taken into account. From the 3D model we also derive a 1D space averaged model, describing the dynamics of the mean velocity of the mucus that is propelled by the cilia, hence allowing lower computational costs and still providing useful characterization of the efficiency of the transport. Mathematical properties of the models (existence and uniqueness of solutions in suitable functional spaces) are analyzed. Numerical simulations highlight the influence of critical parameters on the efficiency of the mucociliary transport in the case of dense forests of cilia.

$ H_\infty $ deployment of nonlinear multi-agent systems with Markov switching topologies over a finite-time interval based on T–S fuzzy PDE control

<abstract><p>The deployment of multi-agent systems (MASs) is widely used in the fields of unmanned agricultural machineries, unmanned aerial vehicles, intelligent transportation, etc. To make up for the defect that the existing PDE-based results are overly idealistic in terms of system models and control strategies, we study the PDE-based deployment of clustered nonlinear first-order and second-order MASs over a finite-time interval (FTI). By designing special communication protocols, the collective dynamics of numerous agents are modeled by simple fist-order and second-order PDEs. Two practical factors, external disturbance and Markov switching topology, are considered in this paper to better match actual situations. Besides, T–S fuzzy technology is used to approximate the unknown nonlinearity of MASs. Then, by using boundary control scheme with collocated measurements, two theorems are obtained to ensure the finite-time $ H_\infty $ deployment of first-order and second-order agents, respectively. Finally, numerical examples are provided to illustrate the effectiveness of the proposed approaches.</p></abstract>

Collective dynamics of active dumbbells near a circular obstacle.

In this article, we present the collective dynamics of active dumbbells in the presence of a static circular obstacle using Brownian dynamics simulation. The active dumbbells aggregate on the surface of a circular obstacle beyond a critical radius. The aggregation is non-uniform along the circumference, and the aggregate size increases with the activity (Pe) and the curvature radius (Ro). The dense aggregate of active dumbbells displays persistent rotational motion with a certain angular speed, which linearly increases with activity. Furthermore, we show a strong polar ordering of the active dumbbells within the aggregate. The polar ordering exhibits long-range correlation, with the correlation length corresponding to the aggregate size. Additionally, we show that the residence time of an active dumbbell on the obstacle surface increases rapidly with area fraction due to many-body interactions that lead to a slowdown of the rotational diffusion. This article further considers the dynamical behavior of a tracer particle in the solution of active dumbbells. Interestingly, the speed of the passive tracer particle displays a crossover from monotonically decreasing to increasing with the size of the tracer particle upon increasing the dumbbells' speed. Furthermore, the effective diffusion of the tracer particle displays non-monotonic behavior with the area fraction; the initial increase in diffusivity is followed by a decrease for a larger area fraction.

Synchronisation of the ensemble of nonidentical FitzHugh–Nagumo oscillators with memristive couplings

The aim of the study is to investigate the features of synchronization in ensembles of nonidentical neuron-like FitzHugh–Nagumo oscillators interacting via memristor-based coupling. Methods. The collective dynamics in a ring of FitzHugh–Nagumo oscillators connected via memristive coupling was studied numerically and experimentally. The nonidentity of oscillators was achieved by detuning them by the threshold parameter responsible for the excitation of oscillator, or by detuning them by the parameter characterizing the ratio of time scales, the value of which determines the natural frequency of oscillator. We investigated the synchronization of memristively coupled FitzHugh–Nagumo oscillators as a function of the magnitude of the coupling coefficient, the initial conditions of all variables, and the number of oscillators in the ensemble. As a measure of synchronization, we used a coefficient characterizing the closeness of oscillator trajectories. Results. It is shown that with memristive coupling of FitzHugh–Nagumo oscillators, their synchronization depends not only on the magnitude of the coupling coefficient, but also on the initial states of both the oscillators themselves and the variables responsible for the memristive coupling. We compared the synchronization features of nonidentical FitzHugh–Nagumo oscillators with memristive and diffusive couplings. It is shown that, in contrast to the case of diffusive coupling of oscillators, in the case of meristive coupling, with increasing coupling strength of the oscillators, the destruction of the regime of completely synchronous in-phase oscillations can be observed, instead of which a regime of out-of-phase oscillations appears. Conclusion. The obtained results can be used when solving the problems of synchronization control in ensembles of neuronlike oscillators, in particular, for achieving or destroying the regime of in-phase synchronization of oscillations in an ensemble of coupled oscillators.

Narrating Institutional Logics into Effect: Coherence Across Cognitive, Political, and Emotional Elements

Through an ethnographic study of decision making in a rape crisis center, I explore how institutional logics come to be through interactions. Zooming in on storytelling interactions and slowing down to follow their evolution, I find that collective cognitive, political, and emotional elements mediated the narration of logics into effect. While the interactions unfolded within a space of possibilities determined by logics, co-narrators still put much cognitive effort into negotiating which logic was relevant and how it implicated specific ways of understanding and responding to events. Narrators’ subject positions and their perceived interests and emotions also mediated the work of logics on the ground. Decisions were determined by degrees of coherence across these cognitive, political, and emotional elements. When there was high or moderate coherence, the decision followed the resolution implied by the narration. When coherence was low, decision makers rejected the decision implied by the narration. Coherence, then, constrained people’s agency to invoke institutional logic. These results offer compelling new theory about how institutional logics work: logics are neither deterministic nor freely manipulated but instantiated through collective and situated dynamics that set limits on their strategic use.