We demonstrate that the formation of bicontinuous emulsions stabilized by interfacial particles (bijels) is more robust when nanoparticles rather than microparticles are used. Emulsification via spinodal demixing in the presence of nearly neutrally wetting particles is induced by rapid heating. Using confocal microscopy, we show that nanospheres allow successful bijel formation at heating rates two orders of magnitude slower than is possible with microspheres. In order to explain our results, we introduce the concept of mechanical leeway, i.e., nanoparticles benefit from a smaller driving force towards disruptive curvature. Finally, we suggest that leeway mechanisms may benefit any formulation in which challenges arise due to tight restrictions on a pivotal parameter, but where the restrictions can be relaxed by rationally changing the value of a more accessible parameter.

Collective motion of self-sustained swarming flows has recently provided examples of small-scale turbulence arising where viscous effects are dominant. We report the first observation of universal enstrophy cascade in concentrated swarming sperm consistent with a body of evidence built from various independent measurements. We found a well-defined $k^{-3}$ power-law decay of a velocity field power spectrum and relative dispersion of small beads consistent with theoretical predictions in 2D turbulence. Concentrated living sperm displays long-range, correlated whirlpool structures of a size that provides an integral scale of turbulence. We propose a consistent explanation for this quasi-2D turbulence based on self-structured laminated flow forced by steric interactions and alignment, a state of active matter that we call “swarming liquid crystal.” We develop scaling arguments consistent with this interpretation.

Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics.

We study the propagation of cascading failures in complex supply networks with a focus on nonlocal effects occurring far away from the initial failure. It is shown that a high clustering and a small average path length of a network generally suppress nonlocal overloads. These properties are typical for many real-world networks, often called small-world networks, such that cascades propagate mostly locally in these networks. Furthermore, we analyze the spatial aspects of countermeasures based on the intentional removal of additional edges. Nonlocal actions are generally required in networks that have a low redundancy and are thus especially vulnerable to cascades.

A family of two-dimensional Faraday waves in extremely shallow depth (1 mm to 2 mm) of absolute ethanol are observed experimentally using a Hele-Shaw cell that vibrates vertically. The same phenomena are not observed by means of water, ethanol solution, and silicone oil. These Faraday waves are quite different from the traditional ones. These phenomena are helpful to deepen and enrich our understandings about Faraday waves, and besides provide a challenging problem for computational fluid dynamics.

The generation of a second-harmonic wave, which is one typical nonlinear feature, is enhanced in a composite of plasma and metamaterial. When we generate plasma by an injection of microwaves, whose frequencies are fundamental, we observe intensified second-harmonic waves in the cases of negative-refractive-index states in which both metamaterial permeability and plasma permittivity are negative for the fundamental waves. We performed the measurements at multiple levels of microwave input power up to 300 W to regulate permittivity in the negative polarity for the fundamental wave and in the transient region, including the positive-zero-negative values, for the second-harmonic wave. We clarified that the observed enhancement results from high electron density in negative-permittivity plasma, the propagating fundamental frequency wave not being attenuated in the negative-refractive-index state, and partial phase matching between the fundamental and second-harmonic waves.

Amplitude modulation of a compressional electromagnetic wave in a strongly magnetized electron-positron pair plasma is considered in the quantum magnetohydrodynamic regime. The important ingredients of this study are the inclusion of the external strong magnetic field, Fermi quantum degeneracy pressure, particle exchange potential, quantum diffraction effects via the Bohm potential, and dissipative effect due to collision of the charged carriers. A modified-nonlinear Schödinger equation is developed for the compressional magnetic field of the electromagnetic wave by employing the standard reductive perturbation technique. The linear and nonlinear dispersions of the electromagnetic wave are discussed in detail. For some parameter ranges, relevant to dense astrophysical objects such as the outer layers of white dwarfs, neutron stars, and magnetars, etc., it is found that the compressional electromagnetic wave is modulationally unstable and propagates as a dissipated electromagnetic wave. It is also found that the quantum effects due to the particle exchange potential and the Bohm potential are negligibly small in comparison to the effects of the Fermi quantum degeneracy pressure. The numerical results on the growth rate of the modulation instability is also presented.

We present theoretical calculations of the ensemble-averaged (or effective or coherent) wave field propagating in a heterogeneous medium considered as one realization of a random process. In the literature, it is usually assumed that heterogeneity can be accounted for by a random scalar function of the space coordinates, termed the potential. Physically, this amounts to replacing the constant wave speed in Helmholtz' equation by a space-dependent speed. In the case of acoustic waves, we show that this approach leads to incorrect results for the scattering mean free path, no matter how weak the fluctuations. The detailed calculation of the coherent wave field must take into account both a scalar and an operator part in the random potential. When both terms have identical amplitudes, the correct value for the scattering mean free paths is shown to be more than 4 times smaller (13/3, precisely) in the low-frequency limit, whatever the shape of the correlation function. Based on the diagrammatic approach of multiple scattering, theoretical results are obtained for the self-energy and mean free path within Bourret's and on-shell approximations. They are confirmed by numerical experiments.

We comment on the investigation of the connection between chaos and dynamically generated entanglement in Lombardi and Matzkin [Phys. Rev. E 83, 016207 (2011)]. Whereas, in the referred paper, the authors give an explicit example of a state initially localized in the regular region and still has entanglement properties similar to the states localized in the chaotic region, a few clarifications related to previous works are in order. First, it is crucial to point out that such a behavior can occur for states initially localized near the border between the chaotic region and the regular island, which seems to be the case in the example provided in the referred paper. We comment on the time evolution of such states and the extent to which these can be regarded as having “regular dynamics.” Second, the degree to which entanglement is correlated with the chaos in the system is better understood when we analyze the same initial state and increase the chaoticity in the system gradually. We also discuss in what capacity entanglement can be regarded as a signature of chaos in such studies.

We reply to the preceding Comment that attempts to clarify the connection between chaos and entanglement exposed in our previous paper [Phys. Rev. E 83, 016207 (2011)]. We present additional computations that show the argument exposed in the Comment to explain the entangling power of some regular states is not important in the present case. More fundamentally we argue that the example chosen in the Comment is not the most significant in order to understand why specific regular dynamics can entangle as efficiently as when the corresponding classical dynamics is chaotic.

Classical nucleation theory (CNT) is the most widely used framework to describe the early stage of first-order phase transitions. Unfortunately, the different points of view adopted to derive it yield different kinetic equations for the probability density function, e.g., Zeldovich-Frenkel or Becker-Döring-Tunitskii equations. Starting from a phenomenological stochastic differential equation, a unified equation is obtained in this work. In other words, CNT expressions are recovered by selecting one or another stochastic calculus. Moreover, it is shown that the unified CNT thus obtained produces the same Fokker-Planck equation as that from a recent update of CNT [J. F. Lutsko and M. A. Durán-Olivencia, J. Chem. Phys. 138, 244908 (2013)] when mass transport is governed by diffusion. Finally, we derive a general induction-time expression along with specific approximations of it to be used under different scenarios, in particular, when the mass-transport mechanism is governed by direct impingement, volume diffusion, surface diffusion, or interface transfer.

Criticality reportedly describes brain dynamics. The main critical feature is the presence of scale-free neural avalanches, whose auto-organization is determined by a critical branching ratio of neural-excitation spreading. Other features, directly associated to second-order phase transitions, are: (i) scale-free-network topology of functional connectivity, stemming from suprathreshold pairwise correlations, superimposable, in waking brain activity, with that of ferromagnets at Curie temperature; (ii) temporal long-range memory associated to renewal intermittency driven by abrupt fluctuations in the order parameters, detectable in human brain via spatially distributed phase or amplitude changes in EEG activity. Herein we study intermittent events, extracted from 29 night EEG recordings, including presleep wakefulness and all phases of sleep, where different levels of mentation and consciousness are present. We show that while critical avalanching is unchanged, at least qualitatively, intermittency and functional connectivity, present during conscious phases (wakefulness and REM sleep), break down during both shallow and deep non-REM sleep. We provide a theory for fragmentation-induced intermittency breakdown and suggest that the main difference between conscious and unconscious states resides in the backwards causation, namely on the constraints that the emerging properties at large scale induce to the lower scales. In particular, while in conscious states this backwards causation induces a critical slowing down, preserving spatiotemporal correlations, in dreamless sleep we see a self-organized maintenance of moduli working in parallel. Critical avalanches are still present, and establish transient auto-organization, whose enhanced fluctuations are able to trigger sleep-protecting mechanisms that reinstate parallel activity. The plausible role of critical avalanches in dreamless sleep is to provide a rapid recovery of consciousness, if stimuli are highly arousing.

Some quantitative aspects of laser-irradiated pure metals, while approaching phase explosion, are still not completely understood. Here, we develop a model that describes the main quantities regulating the liquid-vapor explosive phase transition and the expulsion of liquid nanodroplets that, by solidifying, give rise to nanoparticle formation. The model combines both a thermodynamics description of the explosive phase change and a Monte Carlo simulation of the randomly generated critical vapor bubbles. The calculation is performed on a set of seven metals (Al, Fe, Co, Ni, Cu, Ag, and Au) which are frequently used in pulsed laser ablation experiments. Our final predictions about the size distribution of the liquid nanodroplets and the number ratio of liquid/vapor ejected atoms are compared, whenever possible, with available molecular dynamics simulations and experimental data.

We derive expressions for the dispersion for two classes of random variables in Markov processes. Random variables such as current and activity pertain to the first class, which is composed of random variables that change whenever a jump in the stochastic trajectory occurs. The second class corresponds to the time the trajectory spends in a state (or cluster of states). While the expression for the first class follows straightforwardly from known results in the literature, we show that a similar formalism can be used to derive an expression for the second class. As an application, we use this formalism to analyze a cellular two-component network estimating an external ligand concentration. The uncertainty related to this external concentration is calculated by monitoring different random variables related to an internal protein. We show that, inter alia, monitoring the time spent in the phosphorylated state of the protein leads to a finite uncertainty only if there is dissipation, whereas the uncertainty obtained from the activity of the transitions of the internal protein can reach the Berg-Purcell limit even in equilibrium.

We study the scaling behavior of particle densities for Lévy walks whose transition length $r$ is coupled with the transition time $t$ as $\left|r\right|\propto t^{\alpha }$ with an exponent $\alpha >0$. The transition-time distribution behaves as $\psi \left(t\right)\propto t^{-1-\beta }$ with $\beta >0$. For $1<\beta <2\alpha$ and $\alpha \ge 1$, particle displacements are characterized by a finite transition time and confinement to $\left|r\right|<t^{\alpha }$ while the marginal distribution of transition lengths is heavy tailed. These characteristics give rise to the existence of two scaling forms for the particle density, one that is valid at particle displacements $\left|r\right|\ll t^{\alpha }$ and one at $\left|r\right|\lesssim t^{\alpha }$. As a consequence, the Lévy walk displays strong anomalous diffusion in the sense that the average absolute moments $\langle |r{|}^q\rangle$ scale as $t^{q\nu \left(q\right)}$ with $\nu \left(q\right)$ piecewise linear above and below a critical value $q_c$. We derive explicit expressions for the scaling forms of the particle densities and determine the scaling of the average absolute moments. We find that ${\langle \left|r\right|}^q\rangle \propto t^{q\alpha /\beta }$ for $q<q_c=\beta /\alpha$ and ${\langle \left|r\right|}^q\rangle \propto t^{1+\alpha q-\beta }$ for $q>q_c$. These results give insight into the possible origins of strong anomalous diffusion and anomalous behaviors in disordered systems in general.

We derive a general fluctuation theorem for quantum maps. The theorem applies to a broad class of quantum dynamics, such as unitary evolution, decoherence, thermalization, and other types of evolution for quantum open systems. The theorem reproduces well-known fluctuation theorems in a single and simplified framework and extends the Hatano-Sasa theorem to quantum nonequilibrium processes. Moreover, it helps to elucidate the physical nature of the environment that induces a given dynamics in an open quantum system.

Correlation and similarity measures are widely used in all the areas of sciences and social sciences. Often the variables are not numbers but are instead qualitative descriptors called categorical data. We define and study similarity matrix, as a measure of similarity, for the case of categorical data. This is of interest due to a deluge of categorical data, such as movie ratings, top-10 rankings, and data from social media, in the public domain that require analysis. We show that the statistical properties of the spectra of similarity matrices, constructed from categorical data, follow random matrix predictions with the dominant eigenvalue being an exception. We demonstrate this approach by applying it to the data for Indian general elections and sea level pressures in the North Atlantic ocean.

The effect of diffusion in the one-dimensional long-range contact process is investigated by mean-field calculations. Recent works have shown that diffusion decreases the effectiveness of long-range interactions, affecting the character of the phase transition: for higher values of the diffusion coefficient, stronger long-range interactions are required to enable phase coexistence and first-order behavior. Here we apply a generalized mean-field approximation for the master equation of the model that considers states of an aggregate of $L$ lattice sites. The phase diagram of the model for values of $L$ up to 10 is obtained, and for some values of the diffusion rate extrapolations to infinite-sized systems are given. For low-diffusive systems, approximations with $L\ge 3$ are able to reveal the suppression of the phase coexistence induced by diffusion, however, in the high-diffusion regime, larger values of $L$ are necessary to correctly account for the higher range of correlations. We present a very efficient method to study the mean-field equations and determine the nature of the phase transitions that may be of general utility.

Ice-crystallite precursor formation in supercooled water was studied via molecular dynamics for systems ranging from $\sim {10}^6$ to $8.6\times {10}^6$ molecules, using a tetrahedrally biased single-site “mW” model. This has established system-size effects in the early onset of nucleation, so as to study often-transient precursors' beguiling propensity to “flicker” into instantaneous locally ordered molecular arrangements redolent of ice. In addition, the adoption of solidlike and liquidlike bimodal local configurational-energy distributions was observed, characteristic of early nucleation. Larger systems favored a higher probability of precursor formation, although such ones were not usually longer lived relative to those in smaller systems (which themselves are rather transient). It was concluded tentatively that subtle effects of differences in systemwide density fluctuations and accessible lower-frequency modes tend to favor precursor formation in larger systems, although not necessarily the precursor's kinetic stability.