From numerical simulations, we show that nonrotating magnetohydrodynamic shear flows are unstable to finite amplitude velocity perturbations and become turbulent, leading to the growth and sustenance of magnetic energy, including large scale fields. This supports the concept that sustained magnetic energy from turbulence is independent of the driving mechanism for large enough magnetic Reynolds numbers.

We classify the rare events of structured, memoryful stochastic processes and use this to analyze sequential and parallel generators for these events. Given a stochastic process, we introduce a method to construct a process whose typical realizations are a given process' rare events. This leads to an expression for the minimum memory required to generate rare events. We then show that the recently discovered classical-quantum ambiguity of simplicity also occurs when comparing the structure of process fluctuations.

We study the thermal transport properties of the one-dimensional Fermi-Pasta-Ulam model ($\beta$ type) with long-range interactions. The strength of the long-range interaction decreases with the (shortest) distance between the lattice sites as ${\text{distance}}^{-\delta }$, where $\delta \ge 0$. Two Langevin heat baths at unequal temperatures are connected to the ends of the one-dimensional lattice via short-range harmonic interactions that drive the system away from thermal equilibrium. In the nonequilibrium steady state the heat current, thermal conductivity, and temperature profiles are computed by solving the equations of motion numerically. It is found that the conductivity $\kappa$ has an interesting nonmonotonic dependence with $\delta$ with a maximum at $\delta =2.0$ for this model. Moreover, at $\delta =2.0,\kappa$ diverges almost linearly with system size $N$ and the temperature profile has a negligible slope, as one expects in ballistic transport for an integrable system. We demonstrate that the nonmonotonic behavior of the conductivity and the nearly ballistic thermal transport at $\delta =2.0$ obtained under nonequilibrium conditions can be explained consistently by studying the variation of largest Lyapunov exponent ${\lambda }_{\text{max}}$ with $\delta$, and excess energy diffusion in the equilibrium microcanonical system.

In real networks, the dependency between nodes is ubiquitous; however, the dependency is not always complete and homogeneous. In this paper, we propose a percolation model with weak and heterogeneous dependency; i.e., dependency strengths could be different between different nodes. We find that the heterogeneous dependency strength will make the system more robust, and for various distributions of dependency strengths both continuous and discontinuous percolation transitions can be found. For Erdős-Rényi networks, we prove that the crossing point of the continuous and discontinuous percolation transitions is dependent on the first five moments of the dependency strength distribution. This indicates that the discontinuous percolation transition on networks with dependency is determined not only by the dependency strength but also by its distribution. Furthermore, in the area of the continuous percolation transition, we also find that the critical point depends on the first and second moments of the dependency strength distribution. To validate the theoretical analysis, cases with two different dependency strengths and Gaussian distribution of dependency strengths are presented as examples.

In mammals, the main clock located in the suprachiasmatic nucleus (SCN) of the brain synchronizes the body rhythms to the environmental light-dark cycle. The SCN is composed of about $2\times {10}^4$ neurons which can be classified into three oscillatory phenotypes: self-sustained oscillators, damped oscillators, and arrhythmic neurons. Exposed to an artificial external light-dark cycle with a period of $22h$ instead of $24h$, two subgroups of the SCN can become desynchronized (dissociated). The ventrolateral (VL) subgroup receives photic input and is entrained to the external cycle and a dorsomedial (DM) subgroup oscillates with its endogenous (i.e., free running) period and is synchronized to the external light-dark cycle through coupling from the VL. In the present study, we examined the effects of damped oscillatory neurons on the dissociation between VL and DM under an external $22h$ cycle. We found that, with increasing numbers of damped oscillatory neurons located in the VL, the dissociation between the VL and DM emerges, but if these neurons are increasingly present in the DM the dissociation disappears. Hence, the damped oscillatory neurons in different subregions of the SCN play distinct roles in the dissociation between the two subregions of the SCN. This shows that synchrony between SCN subregions is affected by the number of damped oscillatory neurons and the location of these cells. We suggest that more knowledge on the number and the location of these cells may explain why some species do show a dissociation between the subregions and others do not, as the distribution of oscillatory types of neurons offers a plausible and novel candidate mechanism to explain heterogeneity.

The mechanical behavior of three-dimensional cross-linked random fiber networks composed from fibers of noncircular cross section characterized by two principal moments of inertia is studied in this work. Such fibers store energy in the axial deformation mode and two bending modes of unequal stiffness. We show that the torsional stiffness of fibers becomes important as it determines the relative contribution of the two bending modes to the overall deformation. The scaling of the small strain modulus with the network parameters is established. The large strain deformation of these structures is less sensitive to the shape of the cross section.

We theoretically investigate the thermophoresis of nanocylinders in the free molecule regime, wherein the nonrigid-body effect is taken into account. The analytical formulas of the thermophoretic forces on cylinders suspended in both simple gases and binary gas mixtures are derived for the two limiting collision models, i.e., specular and diffuse scatterings, based on the gas kinetic theory. In the limit of the rigid-body collision, the expressions can be reduced to the theoretical results of Garcia-Ybarra and Rosner [AIChE J. 35, 139 (1989)]. The thermophoretic velocities of the nanocylinders (including carbon nanotubes and long-chain $n$-alkanes) have been evaluated and it is found that the influence of the nonrigid-body effect on thermophoresis is significant for the case of small cylinder radius and low temperatures.

Numerical simulations of laboratory astrophysics experiments on plasma flows require plasma microscopic properties that are obtained by means of an atomic kinetic model. This fact implies a careful choice of the most suitable model for the experiment under analysis. Otherwise, the calculations could lead to inaccurate results and inappropriate conclusions. First, a study of the validity of the local thermodynamic equilibrium in the calculation of the average ionization, mean radiative properties, and cooling times of argon plasmas in a range of plasma conditions of interest in laboratory astrophysics experiments on radiative shocks is performed in this work. In the second part, we have made an analysis of the influence of the atomic kinetic model used to calculate plasma microscopic properties of experiments carried out on magpie on radiative bow shocks propagating in argon. The models considered were developed assuming both local and nonlocal thermodynamic equilibrium and, for the latter situation, we have considered in the kinetic model different effects such as external radiation field and plasma mixture. The microscopic properties studied were the average ionization, the charge state distributions, the monochromatic opacities and emissivities, the Planck mean opacity, and the radiative power loss. The microscopic study was made as a postprocess of a radiative-hydrodynamic simulation of the experiment. We have also performed a theoretical analysis of the influence of these atomic kinetic models in the criteria for the onset possibility of thermal instabilities due to radiative cooling in those experiments in which small structures were experimentally observed in the bow shock that could be due to this kind of instability.

Disordered systems are characterized by the existence of many sample-dependent local-energy minima that cause a step-wise response when the system is perturbed. In this article we use an approach based on elementary probabilistic methods to compute the complete probability distribution of the jumps (static avalanches) in the response of mean-field systems described by replica symmetry breaking; we find a precise condition for having a power-law behavior in the distribution of avalanches caused by small perturbations, and we show that our predictions are in remarkable agreement both with previous results and with what is found in simulations of three-dimensional systems of soft spheres, either at jamming or at slightly higher densities.

Networks with memristive elements (resistors with memory) are being explored for a variety of applications ranging from unconventional computing to models of the brain. However, analytical results that highlight the role of the graph connectivity on the memory dynamics are still few, thus limiting our understanding of these important dynamical systems. In this paper, we derive an exact matrix equation of motion that takes into account all the network constraints of a purely memristive circuit, and we employ it to derive analytical results regarding its relaxation properties. We are able to describe the memory evolution in terms of orthogonal projection operators onto the subspace of fundamental loop space of the underlying circuit. This orthogonal projection explicitly reveals the coupling between the spatial and temporal sectors of the memristive circuits and compactly describes the circuit topology. For the case of disordered graphs, we are able to explain the emergence of a power-law relaxation as a superposition of exponential relaxation times with a broad range of scales using random matrices. This power law is also universal, namely independent of the topology of the underlying graph but dependent only on the density of loops. In the case of circuits subject to alternating voltage instead, we are able to obtain an approximate solution of the dynamics, which is tested against a specific network topology. These results suggest a much richer dynamics of memristive networks than previously considered.

As an unusual type of anomalous diffusion behavior, namely (transient) superballistic transport, has been experimentally observed recently, but it is not yet well understood. In this paper, we investigate the white noise effect (in the Markov approximation) on quantum diffusion in one-dimensional tight-binding models with a periodic, disordered, and quasiperiodic region of size $L$ attached to two perfect lattices at both ends in which the wave packet is initially located at the center of the sublattice. We find that in a completely localized system, inducing noise could delocalize the system to a desirable diffusion phase. This controllable system may be used to investigate the interplay of disorder and white noise, as well as to explore an exotic quantum phase.

Most studies of disease spreading consider the underlying social network as obtained without the contagion, though epidemic influences people's willingness to contact others: A “friendly” contact may be turned to “unfriendly” to avoid infection. We study the susceptible-infected disease-spreading model on signed networks, in which each edge is associated with a positive or negative sign representing the friendly or unfriendly relation between its end nodes. In a signed network, according to Heider's theory, edge signs evolve such that finally a state of structural balance is achieved, corresponding to no frustration in physics terms. However, the danger of infection affects the evolution of its edge signs. To describe the coupled problem of the sign evolution and disease spreading, we generalize the notion of structural balance by taking into account the state of the nodes. We introduce an energy function and carry out Monte Carlo simulations on complete networks to test the energy landscape, where we find local minima corresponding to the so-called jammed states. We study the effect of the ratio of initial friendly to unfriendly connections on the propagation of disease. The steady state can be balanced or a jammed state such that a coexistence occurs between susceptible and infected nodes in the system.

We study a two-filament driven lattice gas model with oppositely directed species of particles moving on two parallel filaments with filament-switching processes and particle inflow and outflow at filament ends. The filament-switching process is correlated with the occupation number of the adjacent site such that particles switch filaments with finite probability only when oppositely directed particles meet on the same filament. This model mimics some of the coarse-grained features observed in context of microtubule-(MT) based intracellular transport, wherein cellular cargo loaded and off-loaded at filament ends are transported on multiple parallel MT filaments and can switch between the parallel microtubule filaments. We focus on a regime where the filaments are weakly coupled, such that filament-switching rate of particles scale inversely as the length of the filament. We find that the interplay of (off-) loading processes at the boundaries and the filament-switching process of particles leads to some distinctive features of the system. These features includes occurrence of a variety of phases in the system with inhomogeneous density profiles including localized density shocks, density difference across the filaments, and bidirectional current flows in the system. We analyze the system by developing a mean field (MF) theory and comparing the results obtained from the MF theory with the Monte Carlo (MC) simulations of the dynamics of the system. We find that the steady-state density and current profiles of particles and the phase diagram obtained within the MF picture matches quite well with MC simulation results. These findings maybe useful for studying multifilament intracellular transport.

Understanding the rheological properties of soft biological tissue is a key issue for mechanical systems used in the health care field. We propose a simple empirical model using fractional dynamics and exponential nonlinearity (FDEN) to identify the rheological properties of soft biological tissue. The model is derived from detailed material measurements using samples isolated from porcine liver. We conducted dynamic viscoelastic and creep tests on liver samples using a plate-plate rheometer. The experimental results indicated that biological tissue has specific properties: (i) power law increase in the storage elastic modulus and the loss elastic modulus of the same slope; (ii) power law compliance (gain) decrease and constant phase delay in the frequency domain; (iii) power law dependence between time and strain relationships in the time domain; and (iv) linear dependence in the low strain range and exponential law dependence in the high strain range between stress-strain relationships. Our simple FDEN model uses only three dependent parameters and represents the specific properties of soft biological tissue.

We have studied the dynamics of the Escherichia coli flagellar motor's angular velocity in response to thermal oscillations. We find that the oscillations’ amplitude of the motor's angular velocity exhibits resonance when the temperature is oscillated at frequencies around 4 Hz. This resonance appears to be due to the existence of a natural mode of oscillation in the state of the motor, specifically in the torque generated by the motor. Natural modes of oscillation in torque generation cannot result from random fluctuations in the state of the motor. Their presence points to the existence of a coupling mechanism between the magnitude of the torque generated by the motor and the rates of transition between the different states of the motor components responsible for torque generation. The results presented here show resonance response in torque generation to external perturbations. They are explained with a simple phenomenological model, which can help future studies identify the source of the feedback mechanism between the torque and the interactions responsible for its generation. It can also help us to quantitatively estimate the strength of these interactions and how they are affected by the magnitude of the torque they generate.

Amorphous solids, such as metallic, polymeric, and colloidal glasses, display complex spatiotemporal response to applied deformations. In contrast to crystalline solids, during loading, amorphous solids exhibit a smooth crossover from elastic response to plastic flow. In this study, we investigate the mechanical response of binary Lennard-Jones glasses to athermal, quasistatic pure shear as a function of the cooling rate used to prepare them. We find several key results concerning the connection between strain-induced particle rearrangements and mechanical response. We show that the energy loss per strain $d{U}_{\mathrm{loss}}/d\gamma$ caused by particle rearrangements for more rapidly cooled glasses is larger than that for slowly cooled glasses. We also find that the cumulative energy loss $U_{\mathrm{loss}}$ can be used to predict the ductility of glasses even in the putative linear regime of stress versus strain. $U_{\mathrm{loss}}$ increases (and the ratio of shear to bulk moduli decreases) with increasing cooling rate, indicating enhanced ductility. In addition, we characterized the degree of reversibility of particle motion during a single shear cycle. We find that irreversible particle motion occurs even in the linear regime of stress versus strain. However, slowly cooled glasses, which undergo smaller rearrangements, are more reversible during a single shear cycle than rapidly cooled glasses. Thus, we show that more ductile glasses are also less reversible.

The paradigm of spontaneous symmetry breaking encompasses the breaking of the rotational symmetries $\text{O}\left(3\right)$ of isotropic space to a discrete subgroup, i.e., a three-dimensional point group. The subgroups form a rich hierarchy and allow for many different phases of matter with orientational order. Such spontaneous symmetry breaking occurs in nematic liquid crystals, and a highlight of such anisotropic liquids is the uniaxial and biaxial nematics. Generalizing the familiar uniaxial and biaxial nematics to phases characterized by an arbitrary point-group symmetry, referred to as generalized nematics, leads to a large hierarchy of phases and possible orientational phase transitions. We discuss how a particular class of nematic phase transitions related to axial point groups can be efficiently captured within a recently proposed gauge theoretical formulation of generalized nematics [K. Liu, J. Nissinen, R.-J. Slager, K. Wu, and J. Zaanen, Phys. Rev. X 6, 041025 (2016)]. These transitions can be introduced in the model by considering anisotropic couplings that do not break any additional symmetries. By and large this generalizes the well-known uniaxial-biaxial nematic phase transition to any arbitrary axial point group in three dimensions. We find in particular that the generalized axial transitions are distinguished by two types of phase diagrams with intermediate vestigial orientational phases and that the window of the vestigial phase is intimately related to the amount of symmetry of the defining point group due to inherently growing fluctuations of the order parameter. This might explain the stability of the observed uniaxial-biaxial phases as compared to the yet to be observed other possible forms of generalized nematic order with higher point-group symmetries.

Using the discrete element method, we study the splash processes induced by the impact of a grain on a randomly packed bed. Good correspondence is obtained between our numerical results and the findings of previous experiments for the movement of ejected grains. Furthermore, the distributions of the ejection angle and ejection speed for individual grains vary depending on the relative timing at which the grains are ejected after the initial impact. Obvious differences are observed between the distributions of grains ejected during the earlier and later splash periods: the form of the vertical ejection-speed distribution varies from a power-law form to a lognormal form with time; this difference may determine grain trajectory after ejection.