Collective behavior affords several advantages to fish in avoiding predators, foraging, mating, and swimming. Although fish schools have been traditionally considered egalitarian superorganisms, a number of empirical observations suggest the emergence of leadership in gregarious groups. Detecting and classifying leader-follower relationships is central to elucidate the behavioral and physiological causes of leadership and understand its consequences. Here, we demonstrate an information-theoretic approach to infer leadership from positional data of fish swimming. In this framework, we measure social interactions between fish pairs through the mathematical construct of transfer entropy, which quantifies the predictive power of a time series to anticipate another, possibly coupled, time series. We focus on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals. To overcome experimental confounds and generate test data sets on which we can thoroughly assess our approach, we adapt and calibrate a data-driven stochastic model of zebrafish motion for the simulation of a coupled dynamical system of zebrafish pairs. In this synthetic data set, the extent and direction of the coupling between the fish are systematically varied across a wide parameter range to demonstrate the accuracy and reliability of transfer entropy in inferring leadership. Our approach is expected to aid in the analysis of collective behavior, providing a data-driven perspective to understand social interactions.

A precise description of the structural and dielectric properties of liquid water is critical to understanding the physicochemical properties of solutes in electrolyte solutions. In this article, a mixture of ionic and dipolar hard spheres is considered to account for water crowding and polarization effects on ionic electrical double layers near a uniformly charged hard wall. As a unique feature, solvent hard spheres carrying a dipole at their centers were used to model water molecules at experimentally known concentration, molecule size, and dipolar moment. The equilibrium ionic and dipole density profiles of this electrolyte aqueous model were calculated using a polar-solvation classical density-functional theory (PSCDFT). These profiles were used to calculate the charge density distribution, water polarization, dielectric permittivity function, and mean electric potential profiles as well as differential capacitance, excess adsorptions, and wall-fluid surface tension. These results were compared with those corresponding to the pure dipolar model and unpolar primitive solvent model of electrolyte aqueous solutions to understand the role that water crowding and polarization effects play on the structural and thermodynamic properties of these systems. Overall, PSCDFT predictions are in agreement with available experimental data.

The effect of multistability in the mixtures of smectic-$C^{*}$ materials with compensated twisting power, i.e., the existence of a large number of almost equiprobable states in the same mixture under the same conditions, is analyzed in the framework of elastic continuum theory. A simple molecular model is also considered. It is shown that multistability can follow from the bulk properties of the smectic-$C^{*}$ materials with compensated twisting power, but with high spontaneous polarization. Multistability leads to the formation of ferroelectric domains, in which the director oscillates in space. The length and amplitude of this oscillation is tunable smoothly by an electric field. Theoretical results for the domain length agree completely with the experimental data. A suggestion is made as to why each domain structure is remembered without the energy consumption, when the electric field is abruptly switched off. The structural dependence on material parameters, such as the spontaneous polarization, the elastic constant, and the equilibrium wave number, is predicted.

Effect of a polymer network on the threshold voltage of the Fréedericksz transition, Frank elastic constants, switching speed, and the rotational viscosity are investigated in a polymer-stabilized bent-core nematic liquid crystal with different polymer concentrations. These polymer networks form virtual surfaces with a finite anchoring energy. The studies bring out several differences in comparison to similar studies with a calamitic liquid crystal as the nematic host. For example, on varying the polymer content the threshold voltage decreases initially, but exhibits a drastic increase above a critical concentration. A similar feature—reaching a minimum before rising—is seen for the bend elastic constant, which gets enhanced by an order of magnitude for a polymer content of 2.5 wt %. In contrast, the splay elastic constant has a monotonic variation although the overall enhancement is comparable to that of the bend elastic constant. The behavior changing at a critical concentration is also seen for the switching time and the associated rotational viscosity. The presence of the polymer also induces a shape change in the thermal dependence of the bend elastic constant. We explain the features observed here on the basis of images obtained from the optical and atomic force microscopy.

We study the mechanical behavior of two-dimensional, stochastically microcracked continua in the range of crack densities close to, and above, the transport percolation threshold. We show that these materials retain stiffness up to crack densities much larger than the transport percolation threshold due to topological interlocking of sample subdomains. Even with a linear constitutive law for the continuum, the mechanical behavior becomes nonlinear in the range of crack densities bounded by the transport and stiffness percolation thresholds. The effect is due to the fractal nature of the fragmentation process and is not linked to the roughness of individual cracks.

We studied by numerical simulations the effects of compressibility on passive scalar transport in stationary compressible turbulence. The turbulent Mach number varied from zero to unity. The difference in driven forcing was the magnitude ratio of compressive to solenoidal modes. In the inertial range, the scalar spectrum followed the $k^{-5/3}$ scaling and suffered negligible influence from the compressibility. The growth of the Mach number showed (1) a first reduction and second enhancement in the transfer of scalar flux; (2) an increase in the skewness and flatness of the scalar derivative and a decrease in the mixed skewness and flatness of the velocity-scalar derivatives; (3) a first stronger and second weaker intermittency of scalar relative to that of velocity; and (4) an increase in the intermittency parameter which measures the intermittency of scalar in the dissipative range. Furthermore, the growth of the compressive mode of forcing indicated (1) a decrease in the intermittency parameter and (2) less efficiency in enhancing scalar mixing. The visualization of scalar dissipation showed that, in the solenoidal-forced flow, the field was filled with the small-scale, highly convoluted structures, while in the compressive-forced flow, the field was exhibited as the regions dominated by the large-scale motions of rarefaction and compression.

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behavior on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are here used to define and tune a Lagrangian copepod (LC) model. The model is further employed to simulate the behavior of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in turbulence. Second, we quantify the clustering of LC, via the fractal dimension $D_2$. We show that $D_2$ can be as low as $\sim 2.3$ and that it critically depends on the shear-rate sensitivity of the proposed LC model, in particular it exhibits a minimum in a narrow range of shear-rate values. We further investigate the effect of jump intensity, jump orientation, and geometrical aspect ratio of the copepods on the small-scale spatial distribution. At last, possible ecological implications of the observed clustering on encounter rates and mating success are discussed.

Loops undergoing thermal fluctuations are prevalent in nature. Ringlike or cross-linked polymers, cyclic macromolecules, and protein-mediated DNA loops all belong to this category. Stability of these molecules are generally described in terms of free energy, an average quantity, but it may also be impacted by local fluctuating forces acting within these systems. The full distribution of these forces can thus give us insights into mechanochemistry beyond the predictive capability of thermodynamics. In this paper, we study the force exerted by an inextensible semiflexible polymer constrained in a looped state. By using a simulation method termed “phase-space sampling,” we generate the equilibrium distribution of chain conformations in both position and momentum space. We compute the constraint forces between the two ends of the loop in this chain ensemble using Lagrangian mechanics, and show that the mean of these forces is equal to the thermodynamic force. By analyzing kinetic and potential contributions to the forces, we find that the mean force acts in the direction of increasing extension not because of bending stress, but in spite of it. Furthermore, we obtain a distribution of constraint forces as a function of chain length, extension, and stiffness. Notably, increasing contour length decreases the average force, but the additional freedom allows fluctuations in the constraint force to increase. The force distribution is asymmetric and falls off less sharply than a Gaussian distribution. Our work exemplifies a system where large-amplitude fluctuations occur in a way unforeseen by a purely thermodynamic framework, and offers computational tools useful for efficient, unbiased simulation of a constrained system.

We investigate Poiseuille channel flow through intrinsically curved media, equipped with localized metric perturbations. To this end, we study the flux of a fluid driven through the curved channel in dependence of the spatial deformation, characterized by the parameters of the metric perturbations (amplitude, range, and density). We find that the flux depends only on a specific combination of parameters, which we identify as the average metric perturbation, and derive a universal flux law for the Poiseuille flow. For the purpose of this study, we have improved and validated our recently developed lattice Boltzmann model in curved space by considerably reducing discrete lattice effects.

We study numerically the correlations and the distribution of intervals between successive zeros in the fluctuating geometry of stochastic interfaces, described by the Edwards-Wilkinson equation. For equilibrium states we find that the distribution of interval lengths satisfies a truncated Sparre-Andersen theorem. We show that boundary-dependent finite-size effects induce nontrivial correlations, implying that the independent interval property is not exactly satisfied in finite systems. For out-of-equilibrium nonstationary states we derive the scaling law describing the temporal evolution of the density of zeros starting from an uncorrelated initial condition. As a by-product we derive a general criterion of the von Neumann's type to understand how discretization affects the stability of the numerical integration of stochastic interfaces. We consider both diffusive and spatially fractional dynamics. Our results provide an alternative experimental method for extracting universal information of fluctuating interfaces such as domain walls in thin ferromagnets or ferroelectrics, based exclusively on the detection of crossing points.

We present an alternative method for interpreting the velocity autocorrelation function (VACF) of a fluid with application to extracting the entropy in a manner similar to the methods developed by Lin et al. [J. Chem. Phys. 119, 11792 (2003)] and improved upon by Desjarlais [Phys. Rev. E 88, 062145 (2013)]. The liquid VACF is decomposed into two components, one gas and one solid, and each contribution's entropic portion is calculated. However, we fit both the gas and solid portions of the VACF in the time domain. This approach is applied to a single-component liquid (a two-phase model of liquid Al at the melt line) and two different two-component systems: a superionic-to-superionic (bcc to fcc) phase transition in ${\mathrm{H}}_2\mathrm{O}$ at high temperatures and pressures and a metastable liquid state of MgO. For all three examples, comparisons to existing results in the literature demonstrate the validity of our alternative.

Recent experiments probing a new ferroelectric liquid crystal (CLF08) confined in cells with planar alignment have shown dielectric and optic anomalies suggesting the onset of ferrielectric ordering within the surface lattice of dechiralization lines. We present a phenomenological theory describing the corresponding phase transition sequence $\mathrm{Sm}A\to \mathrm{Sm}{C}^{*}\to \mathrm{Ferri}$. Phase diagrams and thermodynamic, dielectric, and optic properties are worked out and compared with experiments. The anomalies are related to the predicted tristability of the experimental cells under applied electric field. The order parameters of Landau theory are reinterpreted in terms of line positions, allowing description of the entrance and exit line behavior, and yielding the prediction and identification of new limit phases within a nonconventional Landau approach.

We consider, computationally and experimentally, the scaling properties of force networks in the systems of circular particles exposed to compression in two spatial dimensions. The simulations consider polydisperse and monodisperse particles, both frictional and frictionless, and in experiments we use monodisperse and bidisperse frictional particles. While for some of the considered systems we observe consistent scaling exponents describing the behavior of the force networks, we find that this behavior is not universal. In particular, we find that frictionless systems, independently of whether they partially crystallize under compression or not, show scaling properties that are significantly different compared to the frictional disordered ones. The findings of nonuniversality are confirmed by explicitly computing fractal dimension for the considered systems. The results of the physical experiments are consistent with the results obtained in simulations of frictional disordered systems.

The normal coefficient of restitution (COR) for a spherical particle bouncing on a wet plane is investigated experimentally and compared with a model characterizing the energy loss at impact. For fixed ratios of liquid film thickness $\delta$ to particle diameter $D$, the wet COR is always found to decay linearly with ${\mathrm{St}}^{-1}$, where St, the Stokes number, measures the particle inertia with respect to the viscous force of the liquid. Such a dependence suggests a convenient way of predicting the wet COR with two fit parameters: a critical COR at infinitely large St and a critical St at zero COR. We characterize the dependence of the two parameters on $\delta /D$ and compare it with a model considering the energy loss from the inertia and the viscosity of the wetting liquid. This investigation suggests an analytical prediction of the COR for wet particles.

We investigate the nonlinear wave dynamics of origami-based metamaterials composed of Tachi-Miura polyhedron (TMP) unit cells. These cells exhibit strain softening behavior under compression, which can be tuned by modifying their geometrical configurations or initial folded conditions. We assemble these TMP cells into a cluster of origami-based metamaterials, and we theoretically model and numerically analyze their wave transmission mechanism under external impact. Numerical simulations show that origami-based metamaterials can provide a prototypical platform for the formation of nonlinear coherent structures in the form of rarefaction waves, which feature a tensile wavefront upon the application of compression to the system. We also demonstrate the existence of numerically exact traveling rarefaction waves in an effective lumped-mass model. Origami-based metamaterials can be highly useful for mitigating shock waves, potentially enabling a wide variety of engineering applications.

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In many situations, the dominant sources of uncertainty must be included into the model for making reliable predictions. This naturally leads to stochastic models. Stochastic models render parameter inference much harder, as the aim then is to find a distribution of likely parameter values. In Bayesian statistics, which is a consistent framework for data-driven learning, this so-called posterior distribution can be used to make probabilistic predictions. We propose a novel, exact, and very efficient approach for generating posterior parameter distributions for stochastic differential equation models calibrated to measured time series. The algorithm is inspired by reinterpreting the posterior distribution as a statistical mechanics partition function of an object akin to a polymer, where the measurements are mapped on heavier beads compared to those of the simulated data. To arrive at distribution samples, we employ a Hamiltonian Monte Carlo approach combined with a multiple time-scale integration. A separation of time scales naturally arises if either the number of measurement points or the number of simulation points becomes large. Furthermore, at least for one-dimensional problems, we can decouple the harmonic modes between measurement points and solve the fastest part of their dynamics analytically. Our approach is applicable to a wide range of inference problems and is highly parallelizable.

We present a computer simulation study of glassy and crystalline states using the standard Lennard-Jones interaction potential that is truncated at a finite cutoff distance, as is typical of many computer simulations. We demonstrate that the discontinuity at the cutoff distance in the first derivative of the potential (corresponding to the interparticle force) leads to the appearance of cutoff nonlinearities. These cutoff nonlinearities persist into the very-low-temperature regime thereby affecting low-temperature thermal vibrations, which leads to a breakdown of the harmonic approximation for many eigenmodes, particularly for low-frequency vibrational modes. Furthermore, while expansion nonlinearities which are due to higher order terms in the Taylor expansion of the interaction potential are usually ignored at low temperatures and show up as the temperature increases, cutoff nonlinearities can become most significant at the lowest temperatures. Anharmonic effects readily show up in the elastic moduli which not only depend on the eigenfrequencies, but are crucially sensitive to the eigenvectors of the normal modes. In contrast, those observables that rely mainly on static structural information or just the eigenfrequencies, such as the vibrational density of states, total potential energy, and specific heat, show negligible dependence on the presence of the cutoff. Similar aspects of nonlinear behavior have recently been reported in model granular materials, where the constituent particles interact through finite-range, purely repulsive potentials. These nonlinearities have been ascribed to the nature of the sudden cutoff at contact in the force law. As a consequence, we demonstrate that cutoff nonlinearities emerge as a general feature of ordered and disordered solid state systems interacting through truncated potentials.