Many processes in eukaryotic cells, including cell motility, rely on the growth of branched actin networks from surfaces. Despite its central role the mechanochemical coupling mechanisms that guide the growth process are poorly understood, and a general continuum description combining growth and mechanics is lacking. We develop a theory that bridges the gap between mesoscale and continuum limit and propose a general framework providing the evolution law of actin networks growing under stress. This formulation opens an area for the systematic study of actin dynamics in arbitrary geometries. Our framework predicts a morphological instability of actin growth on a rigid sphere, leading to a spontaneous polarization of the network with a mode selection corresponding to a comet, as reported experimentally. We show that the mechanics of the contact between the network and the surface plays a crucial role, in that it determines directly the existence of the instability. We extract scaling laws relating growth dynamics and network properties offering basic perspectives for new experiments on growing actin networks.

Recently, Gómez et al. proposed a microscopic Markov-chain approach (MMCA) [S. Gómez, J. Gómez-Gardeñes, Y. Moreno, and A. Arenas, Phys. Rev. E 84, 036105 (2011)] to the discrete-time susceptible-infected-susceptible (SIS) epidemic process and found that the epidemic prevalence obtained by this approach agrees well with that by simulations. However, we found that the approach cannot be straightforwardly extended to a susceptible-infected-recovered (SIR) epidemic process (due to its irreversible property), and the epidemic prevalences obtained by MMCA and Monte Carlo simulations do not match well when the infection probability is just slightly above the epidemic threshold. In this contribution we extend the effective degree Markov-chain approach, proposed for analyzing continuous-time epidemic processes [J. Lindquist, J. Ma, P. Driessche, and F. Willeboordse, J. Math. Biol. 62, 143 (2011)], to address discrete-time binary-state (SIS) or three-state (SIR) epidemic processes on uncorrelated complex networks. It is shown that the final epidemic size as well as the time series of infected individuals obtained from this approach agree very well with those by Monte Carlo simulations. Our results are robust to the change of different parameters, including the total population size, the infection probability, the recovery probability, the average degree, and the degree distribution of the underlying networks.

The covariant Lyapunov analysis is generalized to systems attached to deterministic thermal reservoirs that create a heat current across the system and perturb it away from equilibrium. The change in the Lyapunov exponents as a function of heat current is described and explained. Both the nonequilibrium backward and covariant hydrodynamic Lyapunov modes are analyzed and compared. The movement of the converged angle between the hydrodynamic stable and unstable conjugate manifolds with the free flight time of the dynamics is accurately predicted for any nonequilibrium system simply as a function of their exponent. The nonequilibrium positive and negative $\mathbf{LP}$ mode frequencies are found to be asymmetrical, causing the negative mode to oscillate between the two functional forms of each mode in the positive conjugate mode pair. This in turn leads to the angular distributions between the conjugate modes to oscillate symmetrically about $\pi /2$ at a rate given by the difference between the positive and negative mode frequencies.

Viscous fingering formation in flat Hele-Shaw cells is a classical and widely studied fluid mechanical problem. Recently, instead of focusing on the development of the fingering instability, researchers have devised different strategies aiming to suppress its appearance. In this work, we study a protocol that intends to inhibit the occurrence of fingering instabilities in nonflat (spherical and conical) Hele-Shaw cell geometries. By using a mode-coupling theory to describe interfacial evolution, plus a variational controlling technique, we show that viscous fingering phenomena can be minimized in such a confined, curved environment by properly manipulating a time-dependent injection flow rate $Q\left(t\right)$. Explicit expressions for $Q\left(t\right)$ are derived for the specific cases of spherical and conical cells. The suitability of the controlling method is verified for linear and weakly nonlinear stages of the flow.

A case of convection driven by chemical reactions is studied by linear stability theory and direct numerical simulations. In a plane aqueous layer of glucose, the methylene-blue-enabled catalytic oxidation of glucose produces heavier gluconic acid. As the oxygen is supplied through the top surface, the production of gluconic acid leads to an overturning instability. Our results complement earlier experimental and numerical work by Pons et al. First, we extend the model by including the top air layer with diffusive transport and Henry's law for the oxygen concentration at the interface to provide a more realistic oxygen boundary condition. Second, a linear stability analysis of the diffusive basic state in the layers is performed using an optimal perturbation approach. This method is appropriate for the unsteady basic state and determines the onset time of convection and the associated wavelength. Third, the nonlinear evolution is studied by the use of three-dimensional numerical simulations. Three typical parameters sets are explored in detail showing significant differences in pattern formation. One parameter set for which the flow is dominated by viscous forces, displays persistently growing convection cells. The other set with increased reaction rate displays a different flow regime marked by local chaotic plume emission. The simulated patterns are then compared to experimental observations.

This study presents an analytical approach for the electromagnetic characterization of one-dimensional inhomogeneous media. The proposed approach provides the permittivity profile of the medium in terms of the reflection and transmission coefficients. The inverse solution of the permittivity profile is obtained with the help of the state-transition matrix (STM) and its properties, which are presented and proved. The advantage of using this analytic reconstruction technique is its ability to remove complexity and nonlinearity of the inverse problem. Several examples have been considered for validation of the proposed technique and, in each case, quite good agreement has been found between the original and reconstructed profiles. It has been established from the obtained results that when the scattering parameters are combined with the properties of STM, a robust and reliable technique is provided for the electromagnetic characterization of one-dimensional inhomogeneous media.

We ask whether the eigenstate thermalization hypothesis (ETH) is valid in a strong sense: in the limit of an infinite system, every eigenstate is thermal. We examine expectation values of few-body operators in highly excited many-body eigenstates and search for “outliers,” the eigenstates that deviate the most from ETH. We use exact diagonalization of two one-dimensional nonintegrable models: a quantum Ising chain with transverse and longitudinal fields, and hard-core bosons at half-filling with nearest- and next-nearest-neighbor hopping and interaction. We show that even the most extreme outliers appear to obey ETH as the system size increases and thus provide numerical evidences that support ETH in this strong sense. Finally, periodically driving the Ising Hamiltonian, we show that the eigenstates of the corresponding Floquet operator obey ETH even more closely. We attribute this better thermalization to removing the constraint of conservation of the total energy.

We study the $N$-step binary stationary ergodic Markov chain and analyze its differential entropy. Supposing that the correlations are weak we express the conditional probability function of the chain through the pair correlation function and represent the entropy as a functional of the pair correlator. Since the model uses the two-point correlators instead of the block probability, it makes it possible to calculate the entropy of strings at much longer distances than using standard methods. A fluctuation contribution to the entropy due to finiteness of random chains is examined. This contribution can be of the same order as its regular part even at the relatively short lengths of subsequences. A self-similar structure of entropy with respect to the decimation transformations is revealed for some specific forms of the pair correlation function. Application of the theory to the DNA sequence of the R3 chromosome of Drosophila melanogaster is presented.

Sensory hair cells of amphibians exhibit spontaneous activity in their hair bundles and membrane potentials, reflecting two distinct active amplification mechanisms employed in these peripheral mechanosensors. We use a two-compartment model of the bullfrog's saccular hair cell to study how the interaction between its mechanical and electrical compartments affects the emergence of distinct dynamical regimes, and the role of this interaction in shaping the response of the hair cell to weak mechanical stimuli. The model employs a Hodgkin-Huxley-type system for the basolateral electrical compartment and a nonlinear hair bundle oscillator for the mechanical compartment, which are coupled bidirectionally. In the model, forward coupling is provided by the mechanoelectrical transduction current, flowing from the hair bundle to the cell soma. Backward coupling is due to reverse electromechanical transduction, whereby variations of the membrane potential affect adaptation processes in the hair bundle. We isolate oscillation regions in the parameter space of the model and show that bidirectional coupling affects significantly the dynamics of the cell. In particular, self-sustained oscillations of the hair bundles and membrane potential can result from bidirectional coupling, and the coherence of spontaneous oscillations can be maximized by tuning the coupling strength. Consistent with previous experimental work, the model demonstrates that dynamical regimes of the hair bundle change in response to variations in the conductances of basolateral ion channels. We show that sensitivity of the hair cell to weak mechanical stimuli can be maximized by varying coupling strength, and that stochasticity of the hair bundle compartment is a limiting factor of the sensitivity.

We propose an efficient iterative method for generating random correlated binary sequences with a prescribed correlation function. The method is based on consecutive linear modulations of an initially uncorrelated sequence into a correlated one. Each step of modulation increases the correlations until the desired level has been reached. The robustness and efficiency of the proposed algorithm are tested by generating sequences with inverse power-law correlations. The substantial increase in the strength of correlation in the iterative method with respect to single-step filtering generation is shown for all studied correlation functions. Our results can be used for design of disordered superlattices, waveguides, and surfaces with selective transport properties.

The kinetic origin of grain boundary migration, grain coalescence, and defect reduction in the crystallization of quenched two-dimensional Yukawa liquids are numerically investigated. It is found that, in grain coalescence, stick-slip cracking the region in front of the grain boundary into smaller subgrains corotating with small angle, followed by healing, is the key for aligning lattice misorientation and inducing grain boundary stick-slip advance. Cracking is initiated from the weakly interlocked dislocation along its Burgers vector, which in turn causes dislocation motion along the crack. The cascaded scattering and recombination of two dislocations with ${60}^{\circ }$ and ${120}^{\circ }$ Burgers vector angle difference into two and one dislocations are the major processes for dislocation motion and reduction, respectively, in grain boundary migration. A rough grain boundary with large curvature easily supports the above process and induces high grain boundary mobility. Along a straight smooth grain boundary, the parallel Burgers vectors of the string of dislocations hinder defect reduction and induce coalescence stagnation.

Using the tensor network approach, we investigate the monomer-dimer models on a checkerboard lattice, in which there are interactions (with strength $v$) between the parallel dimers on half of the plaquettes. For the fully packed interacting dimer model, we observe a Kosterlitz-Thouless (KT) transition between the low-temperature symmetry breaking and the high-temperature critical phases; for the doped monomer-dimer case with finite chemical potential $\mu$, we also find an order-disorder phase transition which is of second order instead. We use the boundary matrix product state approach to detect the KT and second-order phase transitions and obtain the phase diagrams $v\text{−}T$ and $\mu \text{−}T$. Moreover, for the noninteracting monomer-dimer model (setting $\mu =\nu =0$), we get an extraordinarily accurate determination of the free energy per site (negative of the monomer-dimer constant $h_2$) as $f=-0.662798972833746$ with the dimer density $n=0.638123109228547$, both of 15 correct digits.

Previous studies showed that a higher frequency of bursting results in lower expression noise whereas a larger size of bursting leads to higher expression noise. Here, we show counterintuitive correlations of expression noise with bursting kinetics due to the effect of feedback. Specifically, in the case of increasing the negative feedback strength but keeping the mean expression fixed, both the mean burst frequency and the mean burst size are invariant if the off-switching rate decreases, but expression noise is reduced; or the mean burst frequency is invariant and the burst size decreases if the transcription rate increases, but expression noise is amplified. Similarly, in the case of increasing the positive feedback strength but keeping the mean expression fixed, both the mean burst frequency and the mean burst size are invariant if the on-switching rate decreases; or the mean burst frequency increases and the mean burst size is invariant if the leakage rate decreases, but expression noise is amplified. In addition, we find that the previous conclusion that a larger burst size results in the lower noise in burst size needs to be modified in the case of feedback. Our results not only clarify the confusing relationship between feedback and expression noise but also imply that the mRNA or protein noise is no longer a simple sum of the internal noise and the promoter noise as shown in the case of no feedback.

We study the dynamics of an active polar fluid in the interstitial space between two fixed coaxial cylinders. For sufficiently large expansive or contractive active stresses, the fluid presents roll instabilities of axially symmetric states leading to the spontaneous formation of vortices in the flow field. These vortices are either stationary or travel around the inner cylinder. Increasing the activity further, our numerical solutions indicate the existence of active turbulence that coexists with regular vortex solutions.

Predicting labels of nodes in a network, such as community memberships or demographic variables, is an important problem with applications in social and biological networks. A recently discovered phase transition puts fundamental limits on the accuracy of these predictions if we have access only to the network topology. However, if we know the correct labels of some fraction $\alpha$ of the nodes, we can do better. We study the phase diagram of this semisupervised learning problem for networks generated by the stochastic block model. We use the cavity method and the associated belief propagation algorithm to study what accuracy can be achieved as a function of $\alpha$. For $k=2$ groups, we find that the detectability transition disappears for any $\alpha >0$, in agreement with previous work. For larger $k$ where a hard but detectable regime exists, we find that the easy/hard transition (the point at which efficient algorithms can do better than chance) becomes a line of transitions where the accuracy jumps discontinuously at a critical value of $\alpha$. This line ends in a critical point with a second-order transition, beyond which the accuracy is a continuous function of $\alpha$. We demonstrate qualitatively similar transitions in two real-world networks.

We consider arbitrary, possibly turbulent, Boussinesq flow which is smooth below a dissipative scale $l_d$. It is demonstrated that the stability of the flow with respect to growth of fluctuations with scale smaller than $l_d$ leads to a nontrivial constraint. That involves the dimensionless strength of fluctuations of the gradients of the scalar in the direction of gravity Fl and the Rayleigh scale $L$ depending on the Rayleigh number $\mathrm{Ra}$, the Nusselt number $\mathrm{Nu}$, and $l_d$. The constraint implies that the stratified fluid at rest, which is linearly stable, develops instability in the limit of large $\mathrm{Ra}$. This limits observability of solution for the flow around small swimmer in quiescent stratified fluid that has closed streamlines at scale $L$ [A. M. Ardekani and R. Stocker, Phys. Rev. Lett. 105, 084502 (2010)]. Correspondingly, to study the flow at scale $L$ one has to take turbulence into account. We demonstrate that the resulting turbulent flow around small particles or swimmers can be described by a scalar integro-differential advection-diffusion equation. Describing the solutions, we show that closed streamlines persist with finite probability. Our results seem to be the necessary basis in understanding flows around small particles and swimmers in natural marine environments.

To understand the nature of the electromagnetic resonances of finite metallic surfaces, we formulate a rigorous and rapidly convergent circuit theory for the interaction of a metallic disk and a metallic annulus with an electromagnetic field. Expressions for the current induced and the resonance condition are derived. A new understanding of the nature of the resonances is obtained. For half of the resonances we find a divergent electric field at the edge of the disk, even though it is smooth in shape. For the disk, we compare with previous results using vector spheroidal wave functions and found good agreement for the resonance condition. Our approach can be generalized to other finite surfaces.

We propose a boundary thermodynamic Bethe ansatz calculation technique to obtain the Loschmidt echo and the statistics of the work done when a global quantum quench is performed on an integrable quantum field theory. We derive an analytic expression for the lowest edge of the probability density function and find that it exhibits universal features, in the sense that its scaling form depends only on the statistics of excitations. We perform numerical calculations on the sinh-Gordon model, a deformation of the free boson theory, and we obtain that by turning on the interaction the density function develops fermionic properties. The calculations are facilitated by a previously unnoticed property of the thermodynamic Bethe ansatz construction.

We present a perturbative approach to the problem of computation of mixed-state fidelity susceptibility (MFS) for thermal states. The mathematical techniques used provide an analytical expression for the MFS as a formal expansion in terms of the thermodynamic mean values of successively higher commutators of the Hamiltonian with the operator involved through the control parameter. That expression is naturally divided into two parts: the usual isothermal susceptibility and a constituent in the form of an infinite series of thermodynamic mean values which encodes the noncommutativity in the problem. If the symmetry properties of the Hamiltonian are given in terms of the generators of some (finite-dimensional) algebra, the obtained expansion may be evaluated in a closed form. This issue is tested on several popular models, for which it is shown that the calculations are much simpler if they are based on the properties from the representation theory of the Heisenberg or SU(1, 1) Lie algebra.

We have investigated by rotating drum experiments the influence of a small amount of fine particles on the stability of a granular heap. The fine particles are shown to have a strong and ambivalent influence. For low fine particle content, the heap destabilizes by avalanches, and the fine particles tend to fluidize the heap. In contrast, for high fine particle content, they increase the cohesion of the heap, which destabilizes through stick-slip at the drum wall. We interpret and model the fluidification in the avalanching regime, which we show is independent of humidity, by granular lubrication considerations, whereas the stick-slip behavior, highly dependent on humidity, is understood by a solid friction model.