We analyze the migration characteristics of a droplet in an oscillatory flow field in a parallel plate microconfinement. Using phase field formalism, we capture the dynamical evolution of the droplet over a wide range of the frequency of the imposed oscillation in the flow field, drop size relative to the channel gap, and the capillary number. The latter two factors imply the contribution of droplet deformability, commonly considered in the study of droplet migration under steady shear flow conditions. We show that the imposed oscillation brings an additional time complexity in the droplet movement, realized through temporally varying drop shape, flow direction, and the inertial response of the droplet. As a consequence, we observe a spatially complicated pathway of the droplet along the transverse direction, in sharp contrast to the smooth migration under a similar yet steady shear flow condition. Intuitively, the longitudinal component of the droplet movement is in tandem with the flow continuity and evolves with time at the same frequency as that of the imposed oscillation, although with an amplitude decreasing with the frequency. The time complexity of the transverse component of the movement pattern, however, cannot be rationalized through such intuitive arguments. Towards bringing out the underlying physics, we further endeavor in a reciprocal identity based analysis. Following this approach, we unveil the time complexities of the droplet movement, which appear to be sufficient to rationalize the complex movement patterns observed through the comprehensive simulation studies. These results can be of profound importance in designing droplet based microfluidic systems in an oscillatory flow environment.

The Fisher information matrix (FIM) is a widely used measure for applications including statistical inference, information geometry, experiment design, and the study of criticality in biological systems. The FIM is defined for a parametric family of probability distributions and its estimation from data follows one of two paths: either the distribution is assumed to be known and the parameters are estimated from the data or the parameters are known and the distribution is estimated from the data. We consider the latter case which is applicable, for example, to experiments where the parameters are controlled by the experimenter and a complicated relation exists between the input parameters and the resulting distribution of the data. Since we assume that the distribution is unknown, we use a nonparametric density estimation on the data and then compute the FIM directly from that estimate using a finite-difference approximation to estimate the derivatives in its definition. The accuracy of the estimate depends on both the method of nonparametric estimation and the difference $\mathrm{\Delta }\theta$ between the densities used in the finite-difference formula. We develop an approach for choosing the optimal parameter difference $\mathrm{\Delta }\theta$ based on large deviations theory and compare two nonparametric density estimation methods, the Gaussian kernel density estimator and a novel density estimation using field theory method. We also compare these two methods to a recently published approach that circumvents the need for density estimation by estimating a nonparametric $f$ divergence and using it to approximate the FIM. We use the Fisher information of the normal distribution to validate our method and as a more involved example we compute the temperature component of the FIM in the two-dimensional Ising model and show that it obeys the expected relation to the heat capacity and therefore peaks at the phase transition at the correct critical temperature.

The growth of snow crystals is dependent on the temperature and saturation of the environment. In the case of dendrites, Reiter's local two-dimensional model provides a realistic approach to the study of dendrite growth. In this paper we obtain a new geometric rule that incorporates interface control, a basic mechanism of crystallization that is not taken into account in the original Reiter model. By defining two new variables, growth latency and growth direction, our improved model gives a realistic model not only for dendrite but also for plate forms.

We experimentally demonstrate self-excited oscillation and shedding of millimeter-sized water drops, acoustically levitated in a single-node standing waves cavity, by decreasing the steady acoustic wave intensity below a threshold. The perturbation of the acoustic field by drop motion is a possible source for providing an effective negative damping for sustaining the growing amplitude of the self-excited motion. Its further interplay with surface tension, drop inertia, gravity and acoustic intensities, select various self-excited modes for different size of drops and acoustic intensity. The large drop exhibits quasiperiodic motion from a vertical mode and a zonal mode with growing coupling, as oscillation amplitudes grow, until falling on the floor. For small drops, chaotic oscillations constituted by several broadened sectorial modes and corresponding zonal modes are self-excited. The growing oscillation amplitude leads to droplet shedding from the edges of highly stretched lobes, where surface tension no longer holds the rapid expanding flow.

The formation of a stable protein aggregate is regarded as the rate limiting step in the establishment of prion diseases. In these systems, once aggregates reach a critical size the growth process accelerates and thus the waiting time until the appearance of the first critically sized aggregate is a key determinant of disease onset. In addition to prion diseases, aggregation and nucleation is a central step of many physical, chemical, and biological process. Previous studies have examined the first-arrival time at a critical nucleus size during homogeneous self-assembly under the assumption that at time $t=0$ the system was in the all-monomer state. However, in order to compare to in vivo biological experiments where protein constituents inherited by a newly born cell likely contain intermediate aggregates, other possibilities must be considered. We consider one such possibility by conditioning the unique ergodic size distribution on subcritical aggregate sizes; this least-informed distribution is then used as an initial condition. We make the claim that this initial condition carries fewer assumptions than an all-monomer one and verify that it can yield significantly different averaged waiting times relative to the all-monomer condition under various models of assembly.

Equilibrium solutions are believed to structure the pathways for ergodic trajectories in a dynamical system. However, equilibria are atypical for systems with continuous symmetries, i.e., for systems with homogeneous spatial dimensions, whereas relative equilibria (traveling waves) are generic. In order to visualize the unstable manifolds of such solutions, a practical symmetry reduction method is required that converts relative equilibria into equilibria, and relative periodic orbits into periodic orbits. In this article we extend the fixed Fourier mode slice approach, previously applied one-dimensional PDEs, to a spatially three-dimensional fluid flow, and show that it is substantially more effective than our previous approach to slicing. Application of this method to a minimal flow unit pipe leads to the discovery of many relative periodic orbits that appear to fill out the turbulent regions of state space. We further demonstrate the value of this approach to symmetry reduction through projections (projections only possible in the symmetry-reduced space) that reveal the interrelations between these relative periodic orbits and the ways in which they shape the geometry of the turbulent attractor.

We study the influence of dual-cavity optical feedback on the emission dynamics and timing stability of a passively mode-locked semiconductor laser using a delay differential equation model and verify the timing stability results by an initial experiment. By bifurcation analysis in dependence of the feedback delay times and feedback strength bistability, quasiperiodic and chaotic dynamics, as well as fundamental mode-locking are investigated, yielding a comprehensive overview on the nonlinear emission dynamics arising due to dual-cavity optical feedback. Optimum self-locking ranges for improving the timing stability by dual-cavity optical feedback are identified. A timing jitter reduction and an increase of the repetition rate tuning range of up to a factor of three, compared with single-cavity feedback, are predicted for the parameter ranges investigated. Improved timing stability on short and long timescales is predicted for dual-cavity feedback through the suppression of noise-induced fluctuations. Based on the numerical predictions, experimentally, a maximum timing jitter reduction up to a factor of 180 is found, accompanied by a side-band reduction by a factor of 58 dB, when both feedback cavities are resonant.

Using a generalized random recurrent neural network model, and by extending our recently developed mean-field approach [J. Aljadeff, M. Stern, and T. Sharpee, Phys. Rev. Lett. 114, 088101 (2015)], we study the relationship between the network connectivity structure and its low-dimensional dynamics. Each connection in the network is a random number with mean 0 and variance that depends on pre- and postsynaptic neurons through a sufficiently smooth function $g$ of their identities. We find that these networks undergo a phase transition from a silent to a chaotic state at a critical point we derive as a function of $g$. Above the critical point, although unit activation levels are chaotic, their autocorrelation functions are restricted to a low-dimensional subspace. This provides a direct link between the network's structure and some of its functional characteristics. We discuss example applications of the general results to neuroscience where we derive the support of the spectrum of connectivity matrices with heterogeneous and possibly correlated degree distributions, and to ecology where we study the stability of the cascade model for food web structure.

Notable recent works have focused on the multilayer properties of coevolving diseases. We point out that very similar systems play an important role in population ecology. Specifically we study a meta-food-web model that was recently proposed by Pillai et al. [Theor. Ecol. 3, 223 (2009)]. This model describes a network of species connected by feeding interactions, which spread over a network of spatial patches. Focusing on the essential case, where the network of feeding interactions is a chain, we develop an analytical approach for the computation of the degree distributions of colonized spatial patches for the different species in the chain. This framework allows us to address ecologically relevant questions. Considering configuration model ensembles of spatial networks, we find that there is an upper bound for the fraction of patches that a given species can occupy, which depends only on the networks mean degree. For a given mean degree there is then an optimal degree distribution that comes closest to the upper bound. Notably scale-free degree distributions perform worse than more homogeneous degree distributions if the mean degree is sufficiently high. Because species experience the underlying network differently the optimal degree distribution for one particular species is generally not the optimal distribution for the other species in the same food web. These results are of interest for conservation ecology, where, for instance, the task of selecting areas of old-growth forest to preserve in an agricultural landscape, amounts to the design of a patch network.

The interaction of oppositely and asymmetrically charged rods in salt—a simple model of (bio)macromolecular assembly—is observed via simulation to exhibit two free energy minima, separated by a repulsive barrier. In contrast to similar minima in the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, the governing mechanism includes electrostatic attraction at large separation, osmotic repulsion at close range, and depletion attraction near contact. A model accounting for ion condensation and excluded volume is shown to be superior to a mean-field treatment in predicting the effect of charge asymmetry on the free-energy profile.

Recently, frequency-resolved iron opacity measurements at electron temperatures of 170–200 eV and electron densities of $(0.7–4.0)\times {10}^{22}{\mathrm{cm}}^{-3}$ revealed a $30–400\%$ disagreement with the calculated opacities [J. E. Bailey et al., Nature (London) 517, 56 (2015)]. The discrepancies have a high impact on astrophysics, atomic physics, and high-energy density physics, and it is important to verify our understanding of the experimental platform with simulations. Reliable simulations are challenging because the temporal and spatial evolution of the source radiation and of the sample plasma are both complex and incompletely diagnosed. In this article, we describe simulations that reproduce the measured temperature and density in recent iron opacity experiments performed at the Sandia National Laboratories $Z$ facility. The time-dependent spectral irradiance at the sample is estimated using the measured time- and space-dependent source radiation distribution, in situ source-to-sample distance measurements, and a three-dimensional (3D) view-factor code. The inferred spectral irradiance is used to drive 1D sample radiation hydrodynamics simulations. The images recorded by slit-imaged space-resolved spectrometers are modeled by solving radiation transport of the source radiation through the sample. We find that the same drive radiation time history successfully reproduces the measured plasma conditions for eight different opacity experiments. These results provide a quantitative physical explanation for the observed dependence of both temperature and density on the sample configuration. Simulated spectral images for the experiments without the FeMg sample show quantitative agreement with the measured spectral images. The agreement in spectral profile, spatial profile, and brightness provides further confidence in our understanding of the backlight-radiation time history and image formation. These simulations bridge the static-uniform picture of the data interpretation and the dynamic-gradient reality of the experiments, and they will allow us to quantitatively assess the impact of effects neglected in the data interpretation.

The behaviors of large, dynamic assemblies of macroscopic particles are of direct relevance to geophysical and industrial processes and may also be used as easily studied analogs to micro- or nano-scale systems, or model systems for microbiological, zoological, and even anthropological phenomena. We study vibrated mixtures of elongated particles, demonstrating that the inclusion of differing particle “species” may profoundly alter a system's dynamics and physical structure in various diverse manners. The phase behavior observed suggests that our system, despite its athermal nature, obeys a minimum free energy principle analogous to that observed for thermodynamic systems. We demonstrate that systems of exclusively spherical objects, which form the basis of numerous theoretical frameworks in many scientific disciplines, represent only a narrow region of a wide, multidimensional phase space. Thus, our results raise significant questions as to whether such models can accurately describe the behaviors of systems outside this highly specialized case.

Systems with long-range interactions display a short-time relaxation towards quasistationary states (QSSs) whose lifetime increases with the system size. In the paradigmatic Hamiltonian mean-field model (HMF) out-of-equilibrium phase transitions are predicted and numerically detected which separate homogeneous (zero magnetization) and inhomogeneous (nonzero magnetization) QSSs. In the former regime, the velocity distribution presents (at least) two large, symmetric bumps, which cannot be self-consistently explained by resorting to the conventional Lynden-Bell maximum entropy approach. We propose a generalized maximum entropy scheme which accounts for the pseudoconservation of additional charges, the even momenta of the single-particle distribution. These latter are set to the asymptotic values, as estimated by direct integration of the underlying Vlasov equation, which formally holds in the thermodynamic limit. Methodologically, we operate in the framework of a generalized Gibbs ensemble, as sometimes defined in statistical quantum mechanics, which contains an infinite number of conserved charges. The agreement between theory and simulations is satisfying, both above and below the out-of-equilibrium transition threshold. A previously unaccessible feature of the QSSs, the multiple bumps in the velocity profile, is resolved by our approach.

We examine the conditions of validity for the Lifshitz-Matsubara sum formula for the Casimir pressure between magnetic metallic plane mirrors. As in the previously studied case of nonmagnetic materials [Guérout et al., Phys. Rev. E 90, 042125 (2014)], we recover the usual expression for the lossy model of optical response, but not for the lossless plasma model. We also show that the modes associated with the Foucault currents play a crucial role in the limit of vanishing losses, in contrast to expectations.

Dissipative patterns in excitable reaction-diffusion systems can be strongly affected by spatial heterogeneities. Using the photosensitive Belousov-Zhabotinsky reaction, we show a hysteresis effect in the transition between free and pinned spiral rotation. The latter state involves the rotation around a disk-shaped obstacle with an impermeable and inert boundary. The transition is controlled by changes in light intensity. For permeable heterogeneities of higher excitability, we observe spiral drift along both linear and circular boundaries. Our results confirm recent theoretical predictions and, in the case of spiral drift, are further reproduced by numerical simulations with a modified Oregonator model. Additional simulations with a cardiac model show that orbital motion can also exist in anisotropic and three-dimensional systems.

A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.

The interfacial free energy is a central quantity in crystallization from the metastable melt. In suspensions of charged colloidal spheres, nucleation and growth kinetics can be accurately measured from optical experiments. In previous work, from these data effective nonequilibrium values for the interfacial free energy between the emerging bcc nuclei and the adjacent melt in dependence on the chemical potential difference between melt phase and crystal phase were derived using classical nucleation theory (CNT). A strictly linear increase of the interfacial free energy was observed as a function of increased metastability. Here, we further analyze these data for five aqueous suspensions of charged spheres and one binary mixture. We utilize a simple extrapolation scheme and interpret our findings in view of Turnbull's empirical rule. This enables us to present the first systematic experimental estimates for a reduced interfacial free energy, ${\sigma }_{0,bcc}$, between the bcc-crystal phase and the coexisting equilibrium fluid. Values obtained for ${\sigma }_{0,bcc}$ are on the order of a few $k_{B}T$. Their values are not correlated to any of the electrostatic interaction parameters but rather show a systematic decrease with increasing size polydispersity and a lower value for the mixture as compared to the pure components. At the same time, ${\sigma }_0$ also shows an approximately linear correlation to the entropy of freezing. The equilibrium interfacial free energy of strictly monodisperse charged spheres may therefore be still greater.

A liquid-immersed granular medium is shaken vertically under a wide range of accelerations ($\mathrm{\Gamma }$ in dimensionless form) and frequencies $\left(f\right)$ and its fluidization process is studied. The granular medium is formed by settling and consists of two size-graded layers (particle diameter $d$) such that the upper layer is fine grained and is less permeable. When $\mathrm{\Gamma }>{\mathrm{\Gamma }}_{\mathrm{c}}$, a liquid-rich layer formed by the accumulated liquid at the two-layer boundary causes a gravitational instability. The upwellings of the instability are separated horizontally by a distance (wavelength) $\lambda$, and their amplitude grows exponentially with time $[\propto exp\left(pt\right)]$ at a growth rate $p$. We conduct experiments for two liquid viscosity cases such that the particle settling velocity $\left(V_{\mathrm{s}}\right)$ of the same particle differs by a factor of 17. We find that for both cases, ${\mathrm{\Gamma }}_{\mathrm{c}}$ is at a minimum in an optimum frequency band centered at $f\sim 100$ Hz. However, the high-viscosity (HV) case has a smaller ${\mathrm{\Gamma }}_{\mathrm{c}}$, a shorter $\lambda$, and a faster dimensionless growth rate $[p^{\prime }=p/(V_{\mathrm{s}}/d)]$. We also measure granular rheology under an oscillatory shear and find that (i) interparticle friction decreases when the strain amplitude becomes large and (ii) friction is smaller for the HV case. From (i), we infer that the shear strain of the shaking experiments becomes largest at around $f\sim 100$ Hz. We consider that (ii) is a consequence of liquid lubrication and is a reason for a smaller ${\mathrm{\Gamma }}_{\mathrm{c}}$ for the HV case. We show that the low- and high-frequency limits of the optimum frequency band can be explained by introducing critical values of dimensionless jerk (i.e., time derivative of acceleration) $J$ and dimensionless shaking energy $S$. The low-frequency limit corresponds to the requirement that in order to unjam the particles, the period of shaking $\left(1/f\right)$ must be shorter than the time needed for the particles to rearrange by settling $\left(d/V_{\mathrm{s}}\right)$, which also explains why the HV case is fluidized at a lower $f$ compared to the LV case. We apply the results of the linear stability analyses for Rayleigh-Taylor instability. Using the measured $\lambda$ and $p$, we infer that (i) only a thin layer beneath the two-layer boundary is mobile and the rest of the lower layer remains jammed and (ii) the effective viscosity of the upper granular layer relative to the liquid is smaller for the HV case as a result of smaller friction.

Four rigid panels connected by hinges that meet at a point form a four-vertex, the fundamental building block of origami metamaterials. Most materials designed so far are based on the same four-vertex geometry, and little is known regarding how different geometries affect folding behavior. Here we systematically categorize and analyze the geometries and resulting folding motions of Euclidean four-vertices. Comparing the relative sizes of sector angles, we identify three types of generic vertices and two accompanying subtypes. We determine which folds can fully close and the possible mountain-valley assignments. Next, we consider what occurs when sector angles or sums thereof are set equal, which results in 16 special vertex types. One of these, flat-foldable vertices, has been studied extensively, but we show that a wide variety of qualitatively different folding motions exist for the other 15 special and 3 generic types. Our work establishes a straightforward set of rules for understanding the folding motion of both generic and special four-vertices and serves as a roadmap for designing origami metamaterials.

An improved system of Boltzmann model equations is developed for binary gas mixture. This system of model equations has a complete asymptotic preserving property that can strictly recover the Navier-Stokes equations in the continuum limit with the correct constitutive relations and the correct viscosity, thermal conduction, diffusion, and thermal diffusion coefficients. In this equation system, the self- and cross-collision terms in Boltzmann equations are replaced by single relaxation terms. In monocomponent case, this system of equations can be reduced to the commonly used Shakhov equation. The conservation property and the H theorem which are important for model equations are also satisfied by this system of model equations.