The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis $q$ entropy) and after considering the proper generalization of the statistical complexity ($q$ complexity), we build up a parametric curve (the $q$-complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

In the context of dissipative systems, we show that for any quantum chaotic attractor a corresponding classical chaotic attractor can always be found. We provide a general way to locate them, rooted in the structure of the parameter space (which is typically bidimensional, accounting for the forcing strength and dissipation parameters). In cases where an approximate pointlike quantum distribution is found, it can be associated with exceptionally large regular structures. Moreover, supposedly anomalous quantum chaotic behavior can be very well reproduced by the classical dynamics plus Gaussian noise of the size of an effective Planck constant ${\hslash }_{\mathrm{eff}}$. We give support to our conjectures by means of two paradigmatic examples of quantum chaos and transport theory. In particular, a dissipative driven system becomes fundamental in order to extend their validity to generic cases.

A quantum particle transport induced in a spatially periodic potential by a propagating plane wave has a number of important implications in a range of topical physical systems. Examples include acoustically driven semiconductor superlattices and cold atoms in an optical crystal. Here we apply a kinetic description of the directed transport in a superlattice beyond standard linear approximation, and utilize exact path-integral solutions of the semiclassical transport equation. We show that the particle drift and average velocities have nonmonotonic dependence on the wave amplitude with several prominent extrema. Such nontrivial kinetic behavior is related to global bifurcations developing with an increase of the wave amplitude. They cause dramatic transformations of the system phase space and lead to changes of the transport regime. We describe different types of phase trajectories contributing to the directed transport and analyze their spectral content.

The dynamic shear modulus of magnetoactive elastomers containing 70 and 80 mass % of carbonyl iron microparticles is measured as a function of strain amplitude via dynamic torsion oscillations in various magnetic fields. The results are presented in terms of the mechanical energy density and considered in the framework of the conventional Kraus model. The form exponent of the Kraus model is further related to a physical model of Huber et al. [Huber et al., J. Phys.: Condens. Matter 8, 409 (1996)] that uses a realistic representation for the cluster network possessing fractal structure. Two mechanical loading regimes are identified. At small strain amplitudes the exponent β of the Kraus model changes in an externally applied magnetic field due to rearrangement of ferromagnetic-filler particles, while at large strain amplitudes, the exponent β seems to be independent of the magnetic field. The critical mechanical energy characterizing the transition between these two regimes grows with the increasing magnetic field. Similarities between agglomeration and deagglomeration of magnetic filler under simultaneously applied magnetic field and mechanical shear and the concept of jamming transition are discussed. It is proposed that the magnetic field should be considered as an additional parameter to the jamming phase diagram of rubbers filled with magnetic particles.

Similar to the spontaneous formation of colonies of bacteria, flocks of birds, or schools of fish, “living crystals” can be formed by artificial self-propelled particles such as Janus colloids. Unlike usual solids, these “crystals” are far from thermodynamic equilibrium. They fluctuate in time forming a crystalline structure, breaking apart and re-forming again. We propose a method to stabilize living crystals by applying a weak confinement potential that does not suppress the ability of the particles to perform self-propelled motion, but it stabilizes the structure and shape of the dynamical clusters. This gives rise to such configurations of living crystals as “living shells” formed by Janus colloids. Moreover, the shape of the stable living clusters can be controlled by tuning the potential strength. Our proposal can be verified experimentally with either artificial microswimmers such as Janus colloids, or with living active matter.

Ionic liquids are solvent-free electrolytes, some of which possess an intriguing self-assembly at finite length scale due to Coulombic interactions. Using a continuum framework (based on Onsager's relations), it is shown that bulk nanostructures arise via linear (supercritical) and nonlinear (subcritical) bifurcations (morphological phase transitions), which also directly affect the electrical double layer structure. A Ginzburg-Landau amplitude equation is derived and the bifurcation type is related to model parameters, such as temperature, potential, and interactions. Specifically, the nonlinear bifurcation occurs for geometrically dissimilar ions and, surprisingly, is induced by perturbations on the order of thermal fluctuations. Finally, qualitative insights and comparisons to the experimentally decaying charge layers within the electrical double layer are discussed.

The equilibrium value of an observable defines a manifold in the phase space of an ergodic and equipartitioned many-body system. A typical trajectory pierces that manifold infinitely often as time goes to infinity. We use these piercings to measure both the relaxation time of the lowest frequency eigenmode of the Fermi-Pasta-Ulam chain, as well as the fluctuations of the subsequent dynamics in equilibrium. The dynamics in equilibrium is characterized by a power-law distribution of excursion times far off equilibrium, with diverging variance. Long excursions arise from sticky dynamics close to $q$-breathers localized in normal mode space. Measuring the exponent allows one to predict the transition into nonergodic dynamics. We generalize our method to Klein-Gordon lattices where the sticky dynamics is due to discrete breathers localized in real space.

Contrary to the prevailing notion, we find that the spectrum associated with the extended states in a complex system may belong to the Poisson universality class if the system is subjected to a specific set of constraints. Our results are based on an exact theoretical as well as numerical analysis of column constrained chiral ensembles with circulant off-diagonal blocks and are relevant for a complete understanding of the eigenfunction localization and related physical properties.

With a model for two-dimensional (2D) Brownian rotary ratchets being capable of producing a net torque under athermal random forces, its optimization for mean angular momentum ($L$), mean angular velocity ($\omega$), and efficiency ($\eta$) is considered. In the model, supposing that such a small ratchet system is placed in a thermal bath, the motion of the rotor in the stator is described by the Langevin dynamics of a particle in a 2D ratchet potential, which consists of a static and a time-dependent interaction between rotor and stator; for the latter, we examine a force [randomly directed dc field (RDDF)] for which only the direction is instantaneously updated in a sequence of events in a Poisson process. Because of the chirality of the static part of the potential, it is found that the RDDF causes net rotation while coupling with the thermal fluctuations. Then, to maximize the efficiency of the power consumption of the net rotation, we consider optimizing the static part of the ratchet potential. A crucial point is that the proposed form of ratchet potential enables us to capture the essential feature of 2D ratchet potentials with two closed curves and allows us to systematically construct an optimization strategy. In this paper, we show a method for maximizing $L, \omega$, and $\eta$, its outcome in 2D two-tooth ratchet systems, and a direction of optimization for a three-tooth ratchet system.

An accurate representation of the structural pair correlation functions of the hard sphere (HS) fluid up to the freezing density is proposed which combines the pole expression for the total correlation function $h\left(r\right)$, the Ornstein-Zernike equation, and molecular dynamics (MD) computer simulation data. In the scheme, $h\left(r\right)$ is expressed in terms of a set of pole parameters, which reveals how the tail of the Fourier transform of $h\left(r\right)$ contains information on the discontinuities in the derivatives of the direct correlation function (DCF). This formulation leads to a DCF expressed as the sum of a numerically obtainable part and an analytic part which consists of elementary integral terms, some of which are found to give rise to the discontinuities. An exact formula for the magnitude of these discontinuities is derived, which indicates that there is a particular density ($\rho \cong 0.133$) below which the magnitude of the discontinuities decreases with increasing order of the derivative. With the accurate MD simulation data the set of parameters that specifies $h\left(r\right)$ was determined. These can be used to obtain the different structural functions of the HS fluid, and following the calculation stages of the pole structure scheme the DCF is obtained. From this route to the DCF the second pole of the HS fluid can be determined and the non-negligible role of the “out of core” part of the DCF at high densities is revealed. The density-dependent separation range where the two pole approximation represents well the $h\left(r\right)$ has been determined.

Identifying coherent structures in unsteady flows acting over a finite-time is a well-established research area, in part due to the applicability to realistic velocities obtained from experimental, observational, or numerically generated data. More recently, there is an emerging need to understand the impact of small-scale uncertainties on larger scale structures; for example, the “stochastic parametrization” problem in climate models. This article establishes a rigorous tool in this direction, specifically quantifying the uncertainty of advected curves in the presence of small stochasticity. Explicit expressions are derived for the expectation and the variance of the curves' location. The velocity field may be unsteady and compressible, and the Wiener process driving the stochasticity can have general spatiotemporal dependence. Monte Carlo simulations are used to verify the uncertainty expressions.

The legality of using simple kinetic schemes to determine the stochastic properties of a complex system depends on whether the fluctuations generated from hierarchical equivalent schemes are consistent with one another. To analyze this consistency, we perform lumping processes on the stochastic differential equations and the generalized fluctuation-dissipation theorem and apply them to networks with the frequently encountered Arrhenius-type transition rates. The explicit Langevin force derived from those networks enables us to calculate the state fluctuations caused by the intrinsic and extrinsic noises on the free energy surface and deduce their relations between kinetically equivalent networks. In addition to its applicability to wide classes of network related systems, such as those in structural and systems biology, the result sheds light on the fluctuation relations for general physical variables in Keizer's canonical theory.

Dense colloidal dispersions exhibit complex wave-vector-dependent diffusion, which is controlled by both direct particle interactions and indirect nonadditive hydrodynamic interactions mediated by the solvent. In bulk the hydrodynamic interactions are probed routinely, but in confined geometries their studies have been hitherto hindered by additional complications due to confining walls. Here we solve this issue by combining high-energy x-ray photon correlation spectroscopy and small-angle x-ray-scattering experiments on colloid-filled microfluidic channels to yield the confined fluid's hydrodynamic function in the short-time limit. Most importantly, we find the confined fluid to exhibit a strongly anisotropic hydrodynamic function, similar to its anisotropic structure factor. This observation is important in order to guide future theoretical research.

Transport properties of mixtures of elements in the dense plasma regime play an important role in natural astrophysical and experimental systems, e.g., inertial confinement fusion. We present a series of orbital-free molecular dynamics simulations on dense plasma mixtures with comparison to a global pseudo ion in jellium model. Hydrogen is mixed with elements of increasingly high atomic number (lithium, carbon, aluminum, copper, and silver) at a fixed temperature of 100 eV and constant pressure set by pure hydrogen at $2{\mathrm{g}/\mathrm{cm}}^3$, namely, 370 Mbars. We compute ionic transport coefficients, such as self-diffusion, mutual diffusion, and viscosity for various concentrations. Small concentrations of the heavy atoms significantly change the density of the plasma and decrease the transport coefficients. The structure of the mixture evidences a strong Coulomb coupling between heavy ions and the appearance of a broad correlation peak at short distances between hydrogen atoms. The concept of an effective one component plasma is used to quantify the overcorrelation of the light element induced by the admixture of a heavy element.

We consider a classical and possibly driven composite system $X\otimes Y$ weakly coupled to a Markovian thermal reservoir $R$ so that an unambiguous stochastic thermodynamics ensues for $X\otimes Y$. This setup can be equivalently seen as a system $X$ strongly coupled to a non-Markovian reservoir $Y\otimes R$. We demonstrate that only in the limit where the dynamics of $Y$ is much faster than $X$, our unambiguous expressions for thermodynamic quantities, such as heat, entropy, or internal energy, are equivalent to the strong coupling expressions recently obtained in the literature using the Hamiltonian of mean force. By doing so, we also significantly extend these results by formulating them at the level of instantaneous rates and by allowing for time-dependent couplings between $X$ and its environment. Away from the limit where $Y$ evolves much faster than $X$, previous approaches fail to reproduce the correct results from the original unambiguous formulation, as we illustrate numerically for an underdamped Brownian particle coupled strongly to a non-Markovian reservoir.

A three-dimensional (3D) direct numerical simulation (DNS) study of the propagation of a reaction wave in forced, constant-density, statistically stationary, homogeneous, isotropic turbulence is performed by solving Navier-Stokes and reaction-diffusion equations at various (from 0.5 to 10) ratios of the rms turbulent velocity $U^{\prime }$ to the laminar wave speed, various (from 2.1 to 12.5) ratios of an integral length scale of the turbulence to the laminar wave thickness, and two Zeldovich numbers $\text{Ze}=6.0$ and 17.1. Accordingly, the Damköhler and Karlovitz numbers are varied from 0.2 to 25.1 and from 0.4 to 36.2, respectively. Contrary to an earlier DNS study of self-propagation of an infinitely thin front in statistically the same turbulence, the bending of dependencies of the mean wave speed on $U^{\prime }$ is simulated in the case of a nonzero thickness of the local reaction wave. The bending effect is argued to be controlled by inefficiency of the smallest scale turbulent eddies in wrinkling the reaction-zone surface, because such small-scale wrinkles are rapidly smoothed out by molecular transport within the local reaction wave.

We present the relativistic expressions of standard nonrelativistic microreversibility relations that can be used in collisional-radiative equilibrium models to calculate the transition rates including the free electron degeneracy for collisional excitation and deexcitation, collisional ionization and three-body recombination, dielectronic capture and autoionization, photoexcitation and photodeexcitation, and radiative recombination and photoionization. Semiempirical expressions or more refined calculations can be used for the cross sections of interest as long as they are calculated by taking into account either nonrelativistic, relativistic, or ultrarelativistic effects for both the bound and free electrons. The bound and the free electrons should be treated on the same footing. This is crucial for the internal consistency of the approach valid at arbitrary degeneracy and relativistic degrees.

Pattern of confined chemical garden was controlled by the speed of injected fluid, and their mechanism is discussed. A confined chemical garden system was constructed where an aqueous solution of cobalt chloride was injected into a cell filled with sodium silicate solution. The reaction of these two solutions resulted in the formation of precipitation. The viscosities of the prepared aqueous solutions were set to be similar in order to rule out the possibility of Saffman-Taylor instability. The injection front showed three distinctive patterns: algaes, shells, and filaments, which were dependent on injection speed. The injection pressure and the spatio-temporal pattern of the injected fluid were measured, and a significant increase in the injection pressure was observed when the filament pattern appeared, which indicated the existence of thin lubrication layer between the precipitation and the substrate. The filament pattern was further analyzed quantitatively, and the number of active filaments was determined to be proportional to the injection speed. A mathematical model was constructed that considered both the viscous effect from the thin lubrication layer and the Laplace pressure. This model successfully reproduced the characteristic filament dynamics.

In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

We investigate with experiments and mapping the structure of a hexagonally ordered filament bundle that is held near its ends and progressively twisted around its central axis. The filaments are free to slide relative to each other and are further held under tension-free boundary conditions. Measuring the bundle packing with micro x-ray imaging, we find that the filaments develop the helical rotation $\mathrm{\Omega }$ imposed at the boundaries. We then show that the observed structure is consistent with a mapping of the filament positions to disks packed on a dual non-Euclidean surface with a Gaussian curvature which increases with twist. We further demonstrate that the mean interfilament distance is minimal on the surface, which can be approximated by a hemisphere with an effective curvature $K_{\mathrm{eff}}=3{\mathrm{\Omega }}^2$. Examining the packing on the dual surface, we analyze the geometric frustration of packing in twisted bundles and find the core to remain relatively hexagonally ordered with interfilament strains growing from the bundle center, driving the formation of defects at the exterior of highly twisted bundles.