In some physical and biological swarms, agents effectively move and interact along curved surfaces. The associated constraints and symmetries can affect collective-motion patterns, but little is known about pattern stability in the presence of surface curvature. To make progress, we construct a general model for self-propelled swarms moving on surfaces using Lagrangian mechanics. We find that the combination of self-propulsion, friction, mutual attraction, and surface curvature produce milling patterns where each agent in a swarm oscillates on a limit cycle with different agents splayed along the cycle such that the swarm's center-of-mass remains stationary. In general, such patterns loose stability when mutual attraction is insufficient to overcome the constraint of curvature, and we uncover two broad classes of stationary milling-state bifurcations. In the first, a spatially periodic mode undergoes a Hopf bifurcation as curvature is increased, which results in unstable spatiotemporal oscillations. This generic bifurcation is analyzed for the sphere and demonstrated numerically for several surfaces. In the second, a saddle-node-of-periodic orbits occurs in which stable and unstable milling states collide and annihilate. The latter is analyzed for milling states on cylindrical surfaces. Our results contribute to the general understanding of swarm pattern formation and stability in the presence of surface curvature and may aid in designing robotic swarms that can be controlled to move over complex surfaces and terrains.

Nowadays, one of the challenges we face when carrying out modeling of epidemic spreading is to develop methods to control disease transmission. In this article we study how the spreading of knowledge of a disease affects the propagation of that disease in a population of interacting individuals. For that, we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information about the disease—and its prevention methods—using the unaware-aware-unaware dynamics, so that informed individuals are less likely to be infected. Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes. We study the behavior of this model using a mean-field approach that gives results in good agreement with Monte Carlo simulations on homogeneous complex networks. We find that increasing the rate of information dissemination reduces the disease prevalence, as one may expect. However, increasing the speed of the information process as compared to that of the epidemic process has the counterintuitive effect of increasing the disease prevalence. This result opens an interesting discussion about the effects of information spreading on disease propagation.

We examine critical adsorption for semi-infinite thermodynamic systems of the Ising universality class when they are in contact with a wall of the so-called normal surface universality class in spatial dimension $d=3$ and in the mean-field limit. We apply local-functional theory and Monte Carlo simulations in order to quantitatively determine the properties of the energy density as the primary scaling density characterizing the critical behaviors of Ising systems besides the order parameter. Our results apply to the critical isochore, near two-phase coexistence, and along the critical isotherm if the surface and the weak bulk magnetic fields are either collinear or anticollinear. In the latter case, we also consider the order parameter, which so far has yet to be examined along these lines. We find the interface between the surface and the bulk phases at macroscopic distances from the surface, i.e., the surface is “wet.” It turns out that in this case the usual property of monotonicity of primary scaling densities with respect to the temperature or magnetic field scaling variable does not hold for the energy density due to the presence of this interface.

The Enskog kinetic theory for moderately dense inertial suspensions under simple shear flow is considered as a model to analyze the rheological properties of the system. The influence of the background fluid on suspended particles is modeled via a viscous drag force plus a Langevin-like term defined in terms of the background temperature. In a previous paper [Hayakawa et al., Phys. Rev. E 96, 042903 (2017)], Grad's moment method with the aid of a linear shear-rate expansion was employed to obtain a theory which gave good agreement with the results of event-driven Langevin simulations of hard spheres for low densities and/or small shear rates. Nevertheless, the previous approach had a limitation of not being applicable to the high-shear-rate and high-density regime. Thus, in the present paper, we extend the previous work and develop Grad's theory including higher-order terms in the shear rate. This improves significantly the theoretical predictions, a quantitative agreement between theory and simulation being found in the high-density region (volume fractions smaller than or equal to 0.4).

Shear flow in one spatial region of a dense granular material—induced, for example, through the motion of a boundary—fluidizes the entire granular material. One consequence is that the yield condition vanishes throughout the granular material—even in regions that are very far from the “primary,” boundary-driven shear flow. This phenomenon may be characterized through the mechanics of intruders embedded in the granular medium. When there is no primary flow, a critical load must be exceeded to move the intruder; however, in the presence of a primary flow, intruder motion occurs even when an arbitrarily small external load is applied to an intruder embedded in a region far from the sheared zone. In this paper, we apply the nonlocal granular fluidity (NGF) model—a continuum model that involves higher-order flow gradients—to simulate the specific case of dense flow in a split-bottom cell with a vane-shape intruder. Our simulations quantitatively capture the key features of the experimentally observed phenomena: (1) the vanishing of the yield condition, (2) an exponential-type relationship between the applied torque and the rotation rate, (3) the effect of the distance between the intruder and the primary flow zone, and (4) the direction-dependence of the torque/rotation-rate relation, in which the observed relation changes depending on whether the intruder is forced to rotate along with or counter to the primary flow. Importantly, this represents the first fully three-dimensional validation test for a nonlocal model for dense granular flow in general and for the NGF model in particular.

A pulse traveling on a uniform nondissipative chain of $N$ masses connected by springs is soon destructured by dispersion. Here it is shown that a proper modulation of the masses and the elastic constants makes it possible to obtain a periodic dynamics and a perfect transmission of any kind of pulse between the chain ends, since the initial configuration evolves to its mirror image in the half period. This makes the chain behave as a Newton's cradle. By a known algorithm based on orthogonal polynomials one can numerically solve the general inverse problem leading from the spectrum to the dynamical matrix and then to the corresponding mass-spring sequence, so yielding all possible “perfect cradles.” As quantum linear systems obey the same dynamics of their classical counterparts, these results also apply to the quantum case: For instance, a wave function localized at one end would evolve to its mirror image at the opposite chain end.

Extensive simulations of the Princeton Magnetorotational Instability (MRI) Experiment with the Spectral/Finite Element code for Maxwell and Navier-Stokes Equations (SFEMaNS) have been performed to map the MRI-unstable region as a function of inner cylinder angular velocity and applied vertical magnetic field. The angular velocities of the outer cylinder and the end-cap rings follow the inner cylinder in fixed ratios optimized for MRI. We first confirm the exponential growth of the MRI linear phase using idealized conducting vertical boundaries (end caps) rotating differentially with a Taylor-Couette profile. Subsequently, we run a multitude of simulations to scan the experimental parameter space and find that the normalized volume-averaged mean-square radial magnetic field, our main instability indicator, rises significantly where MRI is expected. At various locations, the local radial components of fluid velocity and generated magnetic field are well correlated with the volume-averaged indicator. Based on this correlation, a diagnostic system that will measure the radial magnetic field at several locations on the inner cylinder is proposed as the main comparison between simulation and experiment. A detailed analysis of poloidal mode structures in the SFEMaNS code indicates that MRI, rather than Ekman circulation or Rayleigh instability, dominates the fluid behavior in the region where MRI is expected.

We present two-dimensional temperature measurements of magnetized and unmagnetized plasma experiments performed at Z relevant to the preheat stage in magnetized liner inertial fusion. The deuterium gas fill was doped with a trace amount of argon for spectroscopy purposes, and time-integrated spatially resolved spectra and narrow-band images were collected in both experiments. The spectrum and image data were included in two separate multiobjective analysis methods to extract the electron temperature spatial distribution $T_e(r,z)$. The results indicate that the magnetic field increases $T_e$, the axial extent of the laser heating, and the magnitude of the radial temperature gradients. Comparisons with simulations reveal that the simulations overpredict the extent of the laser heating and underpredict the temperature. Temperature gradient scale lengths extracted from the measurements also permit an assessment of the importance of nonlocal heat transport.

This paper presents a study on hotspot parameters in indirect-drive, inertially confined fusion implosions as they proceed through the self-heating regime. The implosions with increasing nuclear yield reach the burning-plasma regime, hotspot ignition, and finally propagating burn and ignition. These implosions span a wide range of alpha heating from a yield amplification of 1.7–2.5. We show that the hotspot parameters are explicitly dependent on both yield and velocity and that by fitting to both of these quantities the hotspot parameters can be fit with a single power law in velocity. The yield scaling also enables the hotspot parameters extrapolation to higher yields. This is important as various degradation mechanisms can occur on a given implosion at fixed implosion velocity which can have a large impact on both yield and the hotspot parameters. The yield scaling also enables the experimental dependence of the hotspot parameters on yield amplification to be determined. The implosions reported have resulted in the highest yield $(1.73\times {10}^{16}\pm 2.6\%)$, yield amplification, pressure, and implosion velocity yet reported at the National Ignition Facility.

Particle populations that have velocity distributions with only a small spread of gyrophase angles are commonly observed in the vicinity of magnetohydrodynamic (MHD) discontinuity surfaces such as collisionless shocks. Previous theoretical particle trajectory studies have concentrated on ion behavior at an ideal planar Earth's bow shock and have either assumed that a gyrotropic incident initial velocity distribution is reflected at the surface or instead focused on unique fixed initial gyrophase and pitch angle values specified by the generation mechanism assumed for the particle. In this analytical study of trajectories of particles departing an ideal planar MHD surface we demonstrate that a particle's initial gyrophase and pitch angle determine completely whether it will escape the surface or return to it, regardless of its initial energy. We identify the region in initial gyrophase-pitch angle space which leads to trajectories that return to the surface of the discontinuity. The speed normal to the surface of a returning particle, which can affect its ability to traverse the discontinuity, is shown to increase or decrease compared to its initial value according only to the orientation of its guiding-center motion in the frame of reference in which the discontinuity is at rest and the incoming plasma flow is aligned with the constant magnetic field. The dependence of our results on the direction of the upstream magnetic field is illustrated. Our general analytical results are discussed in the context of observations at the Earth's bow shock.

The aim of this paper is to investigate the pore-scale mass transfer and desorption behaviors in deformable porous media using a coupling immersed boundary method (IBM)–lattice Boltzmann (LB) scheme. In this numerical model, a three-dimensional multiple-relaxation-time LB model is used to simulate fluid flow in porous media consisting of movable rigid adsorbent particles. To consider the effect of dynamic deformation of a porous structure, an improved immersed boundary method scheme is introduced to describe the fluid-structure interaction at the interface between the carrier gas and moving absorbent particles. Moreover, a LB model for the convection diffusion equation is adopted to consider the mass transfer of adsorbate into the macropores and micropores of the porous adsorbent. This coupled IBM-LB model is used to illustrate the mass transfer and desorption processes in shrinkage deformation of the porous structure caused by the movement of rigid adsorbent particles along different directions. At the initial time, these adsorbent particles have a saturation adsorption amount, and the adsorbate in the macropores has the uniform concentration distribution. The numerical results show that the time history curve of the adsorbate concentration in the macropores can be divided into an upturn period and a downturn period during the dynamic desorption process. In the concentration upturn period governed by Langmuir adsorption kinetics, the shrinkage deformation of the porous structure along different directions has no remarkable effect on the mass transfer and desorption behaviors. However, during the concentration downturn period governed by the mass transfer rate of the adsorbate, the shrinkage deformation of the porous structure obviously decreases the efficiency of the desorption process. In addition, the roles of the deformation direction and morphology of the porous media in the desorption process are illustrated in this work.

Plasma flows encountered in high-energy-density experiments display features that differ from those of equilibrium systems. Nonequilibrium approaches such as kinetic theory (KT) capture many, if not all, of these phenomena. However, KT requires closure information, which can be computed from microscale simulations and communicated to KT. We present a concurrent heterogeneous multiscale approach that couples molecular dynamics (MD) with KT in the limit of near-equilibrium flows. To reduce the cost of gathering information from MD, we use active learning to train neural networks on MD data obtained by randomly sampling a small subset of the parameter space. We apply this method to a plasma interfacial mixing problem relevant to warm dense matter, showing considerable computational gains when compared with the full kinetic-MD approach. We find that our approach enables the probing of Coulomb coupling physics across a broad range of temperatures and densities that are inaccessible with current theoretical models.

We discuss the interplay between the degree of dynamical stochasticity, memory persistence, and violation of the self-averaging property in the aging kinetics of quenched ferromagnets. We show that, in general, the longest possible memory effects, which correspond to the slowest possible temporal decay of the correlation function, are accompanied by the largest possible violation of self-averaging and a quasideterministic descent into the ergodic components. This phenomenon is observed in different systems, such as the Ising model with long-range interactions, including the mean-field, and the short-range random-field Ising model.

We consider a massive particle driven with a constant force in a periodic potential and subjected to a dissipative friction. As a function of the drive and damping, the phase diagram of this paradigmatic model is well known to present a pinned, a sliding, and a bistable regime separated by three distinct bifurcation lines. In physical terms, the average velocity $v$ of the particle is nonzero only if either (i) the driving force is large enough to remove any stable point, forcing the particle to slide or (ii) there are local minima but the damping is small enough, below a critical damping, for the inertia to allow the particle to cross barriers and follow a limit cycle; this regime is bistable and whether $v>0$ or $v=0$ depends on the initial state. In this paper, we focus on the asymptotes of the critical line separating the bistable and the pinned regimes. First, we study its behavior near the “triple point” where the pinned, the bistable, and the sliding dynamical regimes meet. Just below the critical damping we uncover a critical regime, where the line approaches the triple point following a power-law behavior. We show that its exponent is controlled by the normal form of the tilted potential close to its critical force. Second, in the opposite regime of very low damping, we revisit existing results by providing a simple method to determine analytically the exact behavior of the line in the case of a generic potential. The analytical estimates, accurately confirmed numerically, are obtained by exploiting exact soliton solutions describing the orbit in a modified tilted potential which can be mapped to the original tilted washboard potential. Our methods and results are particularly useful for an accurate description of underdamped nonuniform oscillators driven near their triple point.

Physical experiments have long revealed that impact oscillators commonly exhibit large-amplitude chaos over a narrow band of parameter values close to grazing bifurcations. This phenomenon is not explained by the square-root singularity of the Nordmark map, which captures the local dynamics to leading order, because this map does not exhibit such dynamics. In this paper, we compare a Poincaré map for a prototypical impact oscillator model with the corresponding Nordmark map. Though the maps agree to leading order, the Poincaré map exhibits a large-amplitude chaotic attractor while the Nordmark map does not because part of the attractor resides in a region of phase space where the two maps differ significantly.

The frequent emergence of diseases with the potential to become threats at local and global scales, such as influenza A(H1N1), SARS, MERS, and recently COVID-19 disease, makes it crucial to keep designing models of disease propagation and strategies to prevent or mitigate their effects in populations. Since isolated systems are exceptionally rare to find in any context, especially in human contact networks, here we examine the susceptible-infected-recovered model of disease spreading in a multiplex network formed by two distinct networks or layers, interconnected through a fraction $q$ of shared individuals (overlap). We model the interactions through weighted networks, because person-to-person interactions are diverse (or disordered); weights represent the contact times of the interactions. Using branching theory supported by simulations, we analyze a social distancing strategy that reduces the average contact time in both layers, where the intensity of the distancing is related to the topology of the layers. We find that the critical values of the distancing intensities, above which an epidemic can be prevented, increase with the overlap $q$. Also we study the effect of the social distancing on the mutual giant component of susceptible individuals, which is crucial to keep the functionality of the system. In addition, we find that for relatively small values of the overlap $q$, social distancing policies might not be needed at all to maintain the functionality of the system.

In this work we suggest modeling the dynamics of power grids in terms of a two-layer network, and we use the Italian high-voltage power grid as a proof-of-principle example. The first layer in our model represents the power grid consisting of generators and consumers, while the second layer represents a dynamic communication network that serves as a controller of the first layer. In particular, the dynamics of the power grid is modeled by the Kuramoto model with inertia, while the communication layer provides a control signal $P_i^c$ for each generator to improve frequency synchronization within the power grid. We propose different realizations of the communication layer topology and different ways to calculate the control signal. Then we conduct a systematic survey of the two-layer system against a multitude of different realistic perturbation scenarios, such as disconnecting generators, increasing demand of consumers, or generators with stochastic power output. When using a control topology that allows all generators to exchange information, we find that a control scheme aimed to minimize the frequency difference between adjacent nodes operates very efficiently even against the worst scenarios with the strongest perturbations.

Extensive Langevin dynamics simulations are used to characterize the adsorption transition of a flexible magnetic filament grafted onto an attractive planar surface. Our results identify different structural transitions at different ratios of the thermal energy to the surface attraction strength: filament straightening, adsorption, and the magnetic flux closure. The adsorption temperature of a magnetic filament is found to be higher in comparison to an equivalent nonmagnetic chain. The adsorption has been also investigated under the application of a static homogeneous external magnetic field. We found that the strength and the orientation of the field can be used to control the adsorption process, providing a precise switching mechanism. Interestingly, we have observed that the characteristic field strength and tilt angle at the adsorption point are related by a simple power law.

In this paper, the rotational part of the disturbance flow field caused by viscous Rayleigh-Taylor instability (RTI) at the cylindrical interface is considered, and the most unstable mode is revealed to be three-dimensional for interfaces of small radii $R$. With an increase in $R$, the azimuthal wave number of the most unstable mode increases step by step, and the corresponding axial wave number increases as well at each step of the azimuthal wave number. When the amplitude of the wave-number vector is much larger or much smaller than $1/R$, the cylindrical RTI is close to the semi-infinite planar viscous RTI limit or the finite-thickness creeping-flow RTI limit, respectively. The effect of the viscosity ratio is double-edged; it may enhance or suppress the cylindrical RTI, depending on $R$ and the amplitude range of the wave-number vector.

We explore transport properties in a disordered nonlinear chain of classical harmonic oscillators, and thereby identify a regime exhibiting behavior analogous to that seen in quantum many-body-localized systems. Through extensive numerical simulations of this system connected at its ends to heat baths at different temperatures, we computed the heat current and the temperature profile in the nonequilibrium steady state as a function of system size $N$, disorder strength $\mathrm{\Delta }$, and temperature $T$. The conductivity ${\kappa }_N$, obtained for finite length ($N$), saturates to a value ${\kappa }_{\infty }>0$ in the large $N$ limit, for all values of disorder strength $\mathrm{\Delta }$ and temperature $T>0$. We show evidence that for any $\mathrm{\Delta }>0$ the conductivity goes to zero faster than any power of $T$ in the $(T/\mathrm{\Delta })\to 0$ limit, and find that the form ${\kappa }_{\infty }\sim e^{-{B|ln(C\mathrm{\Delta }/T)|}^3}$ fits our data. This form has earlier been suggested by a theory based on the dynamics of multioscillator chaotic islands. The finite-size effect can be ${\kappa }_N<{\kappa }_{\infty }$ due to boundary resistance when the bulk conductivity is high (the weak disorder case), or ${\kappa }_N>{\kappa }_{\infty }$ due to direct bath-to-bath coupling through bulk localized modes when the bulk is weakly conducting (the strong disorder case). We also present results on equilibrium dynamical correlation functions and on the role of chaos on transport properties. Finally, we explore the differences in the growth and propagation of chaos in the weak and strong chaos regimes by studying the classical version of the out-of-time-ordered commutator.