We show that colloidal molecular crystal states interacting with a periodic substrate, such as an optical-trap array, and a rotating external field can undergo a rapid pattern switching in which the orientation of the crystal changes. In some cases, a martensiticlike symmetry switching occurs. It is also possible to create a polarized state where the colloids in each substrate minimum develop a director field which smoothly rotates with the external drive, similar to liquid-crystal behavior. These results open the possibility for creating different types of devices using photonic band-gap materials, and should be generalizable to a variety of other condensed matter systems with multiple particle trapping.

In this Brief Report, we present a method for the real-time detection of the bases of the deoxyribonucleic acid using their signatures in negative differential conductance measurements. The present methods of electronic detection of deoxyribonucleic acid bases are based on a statistical analysis because the electrical currents of the four bases are weak and do not differ significantly from one base to another. In contrast, we analyze a device that combines the accumulated knowledge in nanopore and scanning tunneling detection and which is able to provide very distinctive electronic signatures for the four bases.

In a finite-size Abelian sandpile model, extreme avalanches are repelling each other. Taking a time series of the avalanche size and using a decision variable derived from that, we predict the occurrence of a particularly large avalanche in the next time step. The larger the magnitude of these target avalanches, the better is their predictability. The predictability which is based on a finite-size effect, is discussed as a function of the system size.

We investigate by numerical simulation a threshold model of social contagion on degree-correlated random networks. We show that the class of networks for which global information cascades occur generally expands as degree-degree correlations become increasingly positive. However, under certain conditions, large-scale information cascades can paradoxically occur when degree-degree correlations are sufficiently positive or negative, but not when correlations are relatively small. We also show that the relationship between the degree of the initially infected vertex and its ability to trigger large cascades is strongly affected by degree-degree correlations.

One of the common routes to chaos is intermittency. Identification of the intermittency type is usually made using the properties of the probability distribution of laminar phases and of the average length of the laminar phases. Both have a statistical character and to obtain them a long time series has to be examined. Here, we present a recurrence plot method applicable to the analysis of short time series and through which the type of intermittency may be identified. The three types of intermittency introduced by Pomeau and Manneville and a chaos-chaos intermittency induced by interior crisis were examined. The identification of the type of intermittency is equivalent to the identification of the bifurcation associated with it. Our result seems particularly interesting as our method allows the analysis of short time series. The effect of the measurement noise on the effectiveness of the method is also discussed. An application of the method to the detection of type I intermittency in measured heart rate variability data is discussed.

We investigate collective behaviors in a two-dimensional array of active elements controlled by time-delayed feedback, where elements are prepared by localizing the Belousov-Zhabotinsky reaction in a gel matrix. We demonstrate that both the spatial and temporal coherence can be effectively controlled by varying feedback parameters, such as the time delay and the gain. For a sufficiently high feedback gain, the fully synchronized state with low temporal coherence appears, which might be the state induced only by the delay feedback. Experimental results are approximately reproduced in a numerical simulation with a forced Oregonator reaction-diffusion model.

We investigate the width of the resonance zone in a degenerate Hamiltonian system with two degrees of freedom, in which the Hamiltonian lacks the quadratic term in the Taylor expansion. This leads to larger excursions of action in the phase space than the nondegenerate one, and corresponding resonance frequency widths would become narrower. However, in contrast to the nonautonomous Hamiltonian system with one and half degree of freedom, we find that the above case is not generic and only occurs at particular resonances. An example relevant to the interaction of resonances is considered. Analytic results are verified in numerical simulations.

A comprehensive set of dual nuclear product observations provides a snapshot of imploding inertial confinement fusion capsules at the time of shock collapse, shortly before the final stages of compression. The collapse of strong convergent shocks at the center of spherical capsules filled with ${\text{D}}_2$ and ${}^3\text{H}\text{e}$ gases induces D-D and $\text{D}\text{−}{}^3\text{H}\text{e}$ nuclear production. Temporal and spectral diagnostics of products from both reactions are used to measure shock timing, temperature, and capsule areal density. The density and temperature inferred from these measurements are used to estimate the electron-ion thermal coupling and demonstrate a lower electron-ion relaxation rate for capsules with lower initial gas density.

Coarse-grained molecular-dynamics simulations were used to study the morphological changes induced in a Nafion®-like ionomer by the imposition of a strong electric field. We observe the formation of structures aligned along the direction of the applied field. The polar head groups of the ionomer sidechains aggregate into clusters, which then form rodlike formations which assemble into a hexatic array aligned with the direction of the field. Occasionally these lines of sulfonates and protons form a helical structure. Upon removal of the electric field, the hexatic array of rodlike structures persists and has a lower calculated free energy than the original isotropic morphology.

We have measured the entropic elasticity of double-stranded-DNA molecules ranging from 247 to 1298 bp in length using axial force-clamp optical tweezers. We show that entropic end effects and excluded-volume forces from surface attachments become significant for such short molecules. The effective persistence length of the shortest molecules decreases by a factor of 2 compared to the established value for long molecules, and excluded-volume forces extend the molecules to about one third of their nominal contour length. We interpret these results in the framework of an inextensible semiflexible rod model.

We study a finite-time Carnot cycle of a weakly interacting gas which we can regard as a nearly ideal gas in the limit of $T_{\text{h}}-T_{\text{c}}\to 0$ where $T_{\text{h}}$ and $T_{\text{c}}$ are the temperatures of the hot and cold heat reservoirs, respectively. In this limit, we can assume that the cycle is working in the linear-response regime and can calculate the Onsager coefficients of this cycle analytically using the elementary molecular kinetic theory. We reveal that these Onsager coefficients satisfy the so-called tight-coupling condition and this fact explains why the efficiency at the maximal power ${\eta }_{\text{max}}$ of this cycle can attain the Curzon-Ahlborn efficiency from the viewpoint of the linear-response theory.

The profile of transmembrane-channel expression in neurons is class dependent and a crucial determinant of neuronal dynamics. Here, a generalization of the experimentally verified exponential integrate-and-fire model is introduced that includes biophysical, nonlinear gated conductance-based currents, and a spike shape. A Fokker-Planck-based method is developed that allows for the rapid numerical calculation of steady-state and linear-response properties for recurrent networks of neurons with gating-variable dynamics slower than that of the voltage. This limit includes many cases of biological interest, particularly under in vivo conditions of high synaptic conductance. The utility of the method is illustrated by applying it to two biophysically detailed models adapted from the literature: an entorhinal layer-II cortical neuron and a neuron featuring both calcium-activated and voltage-activated spike-frequency-adaptation currents. The framework generalizes to networks comprised of different neuronal classes and so will allow for the modeling of emergent states in neural tissue at significantly increased levels of biological detail.

We use a two-state ratchet model to study the cooperative bidirectional motion of molecular motors on cytoskeletal tracks with randomly alternating polarities. Our model is based on a previously proposed model [Badoual et al., Proc. Natl. Acad. Sci. U.S.A. 99, 6696 (2002)] for collective motor dynamics and, in addition, takes into account the cooperativity effect arising from the elastic tension that develops in the cytoskeletal track due to the joint action of the walking motors. We show, both computationally and analytically, that this additional cooperativity effect leads to a dramatic reduction in the characteristic reversal time of the bidirectional motion, especially in systems with a large number of motors. We also find that bidirectional motion takes place only on (almost) apolar tracks, while on even slightly polar tracks the cooperative motion is unidirectional. We argue that the origin of these observations is the sensitive dependence of the cooperative dynamics on the difference between the number of motors typically working in and against the instantaneous direction of motion.

Lateral inhibition resulting from a double-negative feedback loop underlies the assignment of different fates to cells in many developmental processes. Previous studies have shown that the presence of time delays in models of lateral inhibition can result in significant oscillatory transients before patterned steady states are reached. We study the impact of local feedback loops in a model of lateral inhibition based on the Notch signaling pathway, elucidating the roles of intracellular and intercellular delays in controlling the overall system behavior. The model exhibits both in-phase and out-of-phase oscillatory modes and oscillation death. Interactions between oscillatory modes can generate complex behaviors such as intermittent oscillations. Our results provide a framework for exploring the recent observation of transient Notch-pathway oscillations during fate assignment in vertebrate neurogenesis.

We study the shapes of elastic membranes under the simultaneous exertion of tensile and compressive forces when the translational symmetry along the tension direction is broken. We predict a multitude of morphological phases in various regimes of a two-dimensional parameter space $\left(ϵ,\nu \right)$ that defines the relevant mechanical and geometrical conditions. These parameters are, respectively, the ratio between compression and tension, and the wavelength contrast along the tension direction. The predicted patterns emerge through new transition and instability mechanisms and include several types of irregular and smooth cascades composed of wrinkles and sharp folds. In particular, the hierarchical morphology predicted under high tension and large wavelength contrast $\left(ϵ⪡1,\nu ⪢1\right)$, explains recent experimental observations on ultrathin membranes floating on liquid.

We report observations of mechanical energy localization in a strongly nonlinear discrete lattice. The experimental setup we consider is a one-dimensional nonloaded horizontal chain of identical spheres interacting via the nonlinear Hertz potential which contains a mass defect. Our experiments show that the interaction of a solitary wave with a light intruder excites a nonlinear localized mode. In agreement with dimensional analysis, we find that the frequency of localized oscillations exceeds the incident wave frequency spectrum and nonlinearly depends on incident wave strength and on mass and size of the intruder. The absence of tensile stress between grains allows some gaps to open, which in turn induces a significant enhancement of the amplitude of oscillations. We performed numerical simulations that precisely describe our observations without any adjusting parameters.

We study structure, eigenvalue spectra, and random-walk dynamics in a wide class of networks with subgraphs (modules) at mesoscopic scale. The networks are grown within the model with three parameters controlling the number of modules, their internal structure as scale-free and correlated subgraphs, and the topology of connecting network. Within the exhaustive spectral analysis for both the adjacency matrix and the normalized Laplacian matrix we identify the spectral properties, which characterize the mesoscopic structure of sparse cyclic graphs and trees. The minimally connected nodes, the clustering, and the average connectivity affect the central part of the spectrum. The number of distinct modules leads to an extra peak at the lower part of the Laplacian spectrum in cyclic graphs. Such a peak does not occur in the case of topologically distinct tree subgraphs connected on a tree whereas the associated eigenvectors remain localized on the subgraphs both in trees and cyclic graphs. We also find a characteristic pattern of periodic localization along the chains on the tree for the eigenvector components associated with the largest eigenvalue ${\lambda }^L=2$ of the Laplacian. Further differences between the cyclic modular graphs and trees are found by the statistics of random walks return times and hitting patterns at nodes on these graphs. The distribution of first-return times averaged over all nodes exhibits a stretched exponential tail with the exponent $\sigma \approx 1/3$ for trees and $\sigma \approx 2/3$ for cyclic graphs, which is independent of their mesoscopic and global structure.

We introduce the EMC algorithm for reconstructing a particle’s three-dimensional (3D) diffraction intensity from very many photon shot-noise limited two-dimensional measurements, when the particle orientation in each measurement is unknown. The algorithm combines a maximization step $\left(M\right)$ of the intensity’s likelihood function, with expansion $\left(E\right)$ and compression $\left(C\right)$ steps that map the 3D intensity model to a redundant tomographic representation and back again. After a few iterations of the EMC update rule, the reconstructed intensity is given to the difference-map algorithm for reconstruction of the particle contrast. We demonstrate reconstructions with simulated data and investigate the effects of particle complexity, number of measurements, and the number of photons per measurement. The relatively transparent scaling behavior of our algorithm provides an estimate of the data processing resources required for future single-particle imaging experiments.

We propose a model of binary opinion in which the opinion of the individuals changes according to the state of their neighboring domains. If the neighboring domains have opposite opinions then the opinion of the domain with the larger size is followed. Starting from a random configuration, the system evolves to a homogeneous state. The dynamical evolution shows a scaling behavior with the persistence exponent $\theta \simeq 0.235$ and dynamic exponent $z\simeq 1.02\pm 0.02$. Introducing disorder through a parameter called rigidity coefficient $\rho$ (probability that people are completely rigid and never change their opinion), the transition to a heterogeneous society at $\rho =0^{+}$ is obtained. Close to $\rho =0$, the equilibrium values of the dynamic variables show power-law scaling behavior with $\rho$. We also discuss the effect of having both quenched and annealed disorder in the system.

We introduce a switching mechanism in the asymptotic occupations of quantum states induced by the combined effects of a periodic driving and a weak coupling to a heat bath. It exploits one of the ubiquitous avoided crossings in driven systems and works even if both involved Floquet states have small occupations. It is independent of the initial state and the duration of the driving. As a specific example of this general switching mechanism we show how an asymmetric double well potential can be switched between the lower and upper well by a periodic driving that is much weaker than the asymmetry.