Stochastic Pooling Networks (SPNs) are a useful model for understanding and explaining how naturally occurring encoding of stochastic processes can occur in sensor systems ranging from macroscopic social networks to neuron populations and nanoscale electronics. Due to the interaction of nonlinearity, random noise, and redundancy, SPNs support various unexpected emergent features, such as suprathreshold stochastic resonance, but most existing mathematical results are restricted to the simplest case where all sensors in a network are identical. Nevertheless, numerical results on information transmission have shown that in the presence of independent noise, the optimal configuration of a SPN is such that there should be partial heterogeneity in sensor parameters, such that the optimal solution includes clusters of identical sensors, where each cluster has different parameter values. In this paper, we consider a SPN model of a binary hypothesis detection task and show mathematically that the optimal solution for a specific bound on detection performance is also given by clustered heterogeneity, such that measurements made by sensors with identical parameters either should all be excluded from the detection decision or all included. We also derive an algorithm for numerically finding the optimal solution and illustrate its utility with several examples, including a model of parallel sensory neurons with Poisson firing characteristics.

We numerically study fractional Brownian motion (fBm) with an absorbing boundary at the origin for selected values of the Hurst exponent $H\in [0,1]$. Using a Monte Carlo sampling technique, we are able to numerically generate these fBm processes at discrete times for up to ${10}^7$ time steps, even for values as small as $H=1/4$. The results are compatible with previous analytical results that suggest that the distribution of (rescaled) endpoints $y$ follow a power law $P_{+}\left(y\right)\sim y^{\varphi }$ with $\varphi =(1-H)/H$, even for small values of $H$. Furthermore, for $H=0.5$ we study analytically the finite-length corrections to first order, namely a plateau of $P_{+}\left(y\right)$ for $y\to 0$ which decreases with increasing process length. These corrections are compatible with our numerical results.

We analyze diffusion of small particles in a solid polymeric medium taking into account a short-range particle-polymer interaction. The system is modeled by a particle diffusion on a ternary lattice where the sites occupied by polymer segments are blocked, the ones forming the hull of the chains correspond to the places at which the interaction takes place, and the rest are voids, in which the diffusion is free. In the absence of interaction the diffusion coefficient shows only a weak dependence on the polymer chain length and its behavior strongly resembles the usual site percolation. In the presence of interactions the diffusion coefficient (and especially its temperature dependence) shows a nontrivial behavior depending on the sign of interaction and on whether the voids and the hulls of the chains percolate or not. The temperature dependence may be Arrhenius-like or strongly non-Arrhenius, depending on parameters. The analytical results obtained within the effective medium approximation are in qualitative agreement with those of Monte Carlo simulations.

DNA-functionalized particles are promising for complex self-assembly due to their specific controllable thermoreversible interactions. However, there has been little work on the kinetics and the aggregation rate, which depend on the rate of particle encounters and the probability that an encounter results in particles sticking. In this study, we investigate theoretically and experimentally the aggregation times of micron-scale particles as a function of DNA coverage and salt concentration. Our 2-$\mu$m colloids accommodate up to 70 000 DNA strands. For full coverage and high salt concentration, the aggregation time is 5 min while for 0.1 coverage and low salt it is 4 days. A simple model using reaction-limited kinetics and experimental oligomer hybridization rates describes the data well. A controlling factor is the Coulomb barrier at the nanometer scale retarding DNA hybridization. Our model allows easy measurements of microscopic hybridization rates from macroscopic aggregation and enables the design of complex self-assembly schemes with controlled kinetics.

In simulating charged systems, it is often useful to treat some ionic components of the system at the mean-field level and solve the Poisson-Boltzmann (PB) equation to get their respective density profiles. The numerically intensive task of solving the PB equation at each step of the simulation can be bypassed using variational methods that treat the electrostatic potential as a dynamic variable. But such approaches require the access to a true free-energy functional: a functional that not only provides the correct solution of the PB equation upon extremization, but also evaluates to the true free energy of the system at its minimum. Moreover, the numerical efficiency of such procedures is further enhanced if the free-energy functional is local and is expressed in terms of the electrostatic potential. Existing PB functionals of the electrostatic potential, while possessing the local structure, are not free-energy functionals. We present a variational formulation with a local free-energy functional of the potential. In addition, we also construct a nonlocal free-energy functional of the electrostatic potential. These functionals are suited for employment in simulation schemes based on the ideas of dynamical optimization.

We study mode-I fracture in lattices using atomistic simulations with randomly distributed bond lengths. By using a small parameter that measures the variation of the bond length between the atoms in perfect lattices and using a three-body force law, simulations reproduce the qualitative behavior of the beyond-steady-state cracks in the high-velocity regime, including reasonable microbranching. In particular, the effect of the lattice structure on the crack appears minimal, even though in terms of the physical properties such as the structure factor $g\left(r\right)$ and the radial or angular distributions, these lattices share the physical properties of perfect lattices rather than those of an amorphous material (e.g., the continuous random network model). A clear transition can be seen between steady-state cracks, where a single crack propagates in the midline of the sample, and the regime of unstable cracks, where microbranches start to appear near the main crack, in line with previous experimental results. This is seen in both a honeycomb lattice and a fully hexagonal lattice. This model reproduces the main physical features of propagating cracks in brittle materials, including the total length of microbranches as a function of driving displacement and the increasing amplitude of oscillations of the electrical resistance. In addition, preliminary indications of power-law behavior of the microbranch shapes can be seen, potentially reproducing one of the most intriguing experimental results of brittle fracture. There was found to exist a critical degree of disorder, i.e., a sharp threshold between the cleaving behavior characterizing perfect lattices and the microbranching behavior that characterizes amorphous materials.

Here we report the chemical induction of the twist-bend nematic phase in a nematic mixture of ether-linked liquid crystal dimers by the addition of a dimer with methylene links; all dimers have an odd number of groups in the spacer connecting the two mesogenic groups. The twist-bend phase has been identified from its optical texture and x-ray scattering pattern as well as NMR spectroscopy, which demonstrates the phase chirality. Theory predicts that the key macroscopic property required for the stability of this chiral phase formed from achiral molecules is for the bend elastic constant to tend to be negative; in addition the twist elastic constant should be smaller than half the splay elastic constant. To test these important aspects of the prediction we have measured the bend and splay elastic constants in the nematic phase preceding the twist-bend nematic using the classic Frederiks methodology and all three elastic constants employing the dynamic light scattering approach. Our results show that, unlike the splay, the bend elastic constant is small and decreases significantly as the transition to the induced twist-bend nematic phase is approached, but then exhibits unexpected behavior prior to the phase transition.

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation, or segregation over a range of length scales, and quantifies spatial structures such as the shape, size, and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

We use the wormlike chain model to study supercoiling of DNA under tension and torque. The model reproduces experimental data for a broad range of forces, salt concentrations, and contour lengths. We find a plane of first-order phase transitions ending in a smeared-out line of critical points, the multiplectoneme phase, which is characterized by a fast twist-mediated diffusion of plectonemes and a torque that rises after plectoneme formation with increasing linking number. The discovery of this phase at the same time resolves the discrepancies between existing models and experiment.

The analysis of shape fluctuations of giant nearly spherical lipid vesicles observed via optical microscopy is one of the widely used methods for the determination of the bending elasticity of lipid membranes. Although the method has been used already for three decades, the values of this material constant, obtained by different groups for membranes of the same composition, in identical conditions, differ significantly. The aim of the present work is the development of the method, enabling us to avoid the influence of artifacts on the value of the measured bending modulus. This is achieved by rejection of some images of the vesicle or the whole vesicle when they do not satisfy the requirements (selection criteria) of the applied theory. The bending modulus of 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocholine lipid membranes is determined via the advanced method described here. The results are compared with the values in the literature and their difference is discussed.

Many biological regulatory systems respond with a physiological delay when processing signals. A simple model of regulation which respects these features shows how the ability of a delayed output to transmit information is limited: at short times by the time scale of the dynamic input, at long times by that of the dynamic output. We find that topologies of maximally informative networks correspond to commonly occurring biological circuits linked to stress response and that circuits functioning out of steady state may exploit absorbing states to transmit information optimally.

We consider an array of Josephson junctions with a common LCR load. Application of the Watanabe-Strogatz approach [Physica D 74, 197 (1994)] allows us to formulate the dynamics of the array via the global variables only. For identical junctions this is a finite set of equations, analysis of which reveals the regions of bistability of the synchronous and asynchronous states. For disordered arrays with distributed parameters of the junctions, the problem is formulated as an integro-differential equation for the global variables; here stability of the asynchronous states and the properties of the transition synchrony-asynchrony are established numerically.

We derive exact expressions for the autocorrelation and cross-correlation functions of wave forms generated by two exactly solvable chaotic systems. For each system, an analytic expression exists for chaotic solutions, which we use to evaluate correlation integrals explicitly. For some specific parameter values, we calculate the mean and variance of the correlation functions averaged over all possible solutions. The mean autocorrelation is shown to decay at a rate equal to the Kolmogorov-Sinai entropy. All derived results are shown to agree with numerical calculations of the corresponding quantities.

We study nonlinear phenomena of bistability and chaos at a level of few quanta. For this purpose, we consider a single-mode dissipative oscillator with strong Kerr nonlinearity with respect to the dissipation rate driven by a monochromatic force as well as by a train of Gaussian pulses. The quantum effects and decoherence in the oscillatory mode are investigated in the framework of the purity of states and the Wigner functions calculated from the master equation. We demonstrate the quantum chaotic regime by means of a comparison between the contour plots of the Wigner functions and the strange attractors on the classical Poincaré section. Considering bistability at a low limit of quanta, we analyze the minimal level of excitation numbers at which the bistable regime of the system is displayed. We also discuss the formation of an oscillatory chaotic regime by varying oscillatory excitation numbers at ranges of a few quanta. We demonstrate quantum-interference phenomena that are assisted hysteresis-cycle behavior and quantum chaos for the oscillator driven by a train of Gaussian pulses. We establish the border of quantum-classical correspondence for chaotic regimes in the case of strong nonlinearities.

In ordinal symbolic dynamics, transcripts describe the algebraic relationship between ordinal patterns. Using the concept of transcript, we exploit the mathematical structure of the group of permutations to derive properties and relations among information measures of the symbolic representations of time series. These theoretical results are then applied for the assessment of coupling directionality in dynamical systems, where suitable coupling directionality measures are introduced depending only on transcripts. These measures improve the reliability of the information flow estimates and reduce to well-established coupling directionality quantifiers when some general conditions are satisfied. Furthermore, by generalizing the definition of transcript to ordinal patterns of different lengths, several of the commonly used information directionality measures can be encompassed within the same framework.

We report the observation of spontaneous localization of energy in two spatial dimensions in the context of nonlinear electrical lattices. Both stationary and moving self-localized modes were generated experimentally and theoretically in a family of two-dimensional square as well as honeycomb lattices composed of 6 $\times$ 6 elements. Specifically, we find regions in driver voltage and frequency where stationary discrete breathers, also known as intrinsic localized modes (ILMs), exist and are stable due to the interplay of damping and spatially homogeneous driving. By introducing additional capacitors into the unit cell, these lattices can controllably induce mobile discrete breathers. When more than one such ILMs are experimentally generated in the lattice, the interplay of nonlinearity, discreteness, and wave interactions generates a complex dynamics wherein the ILMs attempt to maintain a minimum distance between one another. Numerical simulations show good agreement with experimental results and confirm that these phenomena qualitatively carry over to larger lattice sizes.

Using the lattice Boltzmann equation, we numerically studied the dynamics of a physical model system, the Poiseuille flow-induced vibrations (PFIV). At a moderate Reynolds number, for flows past a cylinder that is free to move in the cross-flow direction while being fixed in the streamwise direction, between two parallel walls, a variety of distinct vibration regimes involving symmetrical periodic vibration, deflective quasiperiodic vibration, and deflective periodic vibration with corresponding wake states were observed. The data analysis shows that the distribution of the lift coefficient depending on the blockage ratio plays an important role in such a system. A further study of the case of two side-by-side identical cylinders demonstrates the existence of two distinct cooperative vibrations of the cylinders, e.g., in-phase-synchronized vibration (IPSV) and anti-phase-synchronized vibration (APSV). The result reveals that there is a critical blockage ratio, beyond which a phase transition between IPSV and APSV occurs. For the phenomena observed here, PFIV can be considered a new type of vortex-induced vibration, and such a system is expected to find applications in fluid mixing.

Natural convection of air between two infinite vertical differentially heated plates is studied analytically in two dimensions (2D) and numerically in two and three dimensions (3D) for Rayleigh numbers $\mathrm{Ra}$ up to 3 times the critical value ${\mathrm{Ra}}_c=5708$. The first instability is a supercritical circle pitchfork bifurcation leading to steady 2D corotating rolls. A Ginzburg-Landau equation is derived analytically for the flow around this first bifurcation and compared with results from direct numerical simulation (DNS). In two dimensions, DNS shows that the rolls become unstable via a Hopf bifurcation. As $\mathrm{Ra}$ is further increased, the flow becomes quasiperiodic, and then temporally chaotic for a limited range of Rayleigh numbers, beyond which the flow returns to a steady state through a spatial modulation instability. In three dimensions, the rolls instead undergo another pitchfork bifurcation to 3D structures, which consist of transverse rolls connected by counter-rotating vorticity braids. The flow then becomes time dependent through a Hopf bifurcation, as exchanges of energy occur between the rolls and the braids. Chaotic behavior subsequently occurs through two competing mechanisms: a sequence of period-doubling bifurcations leading to intermittency or a spatial pattern modulation reminiscent of the Eckhaus instability.

In a granular porous medium the packing configuration and the shape of the grains influence how fluid flows through it. This is directly related to the porosity and tortuosity of the pore space. In this paper we present an analytical function relating the porosity $\varphi$ and the tortuosity $\tau$ of a granular pore medium by means of a packing parameter $B$. A general expression to estimate $B$ for different representative elementary volumes and grain shapes is presented; in particular, for polyhedral packings. Exploring the packing parameter properties, we discuss the nonuniqueness of the packing-shape combination in relation to $B$ and the porosity behavior for the special cases $0<B<1$, $B=1$, and $B>1$.

In this work, we introduce some basic principles of $\mathcal{PT}$-symmetric Klein-Gordon nonlinear field theories. By formulating a particular antisymmetric gain and loss profile, we illustrate that the stationary states of the model do not change. However, the stability critically depends on the gain and loss profile. For a symmetrically placed solitary wave (in either the continuum model or a discrete analog of the nonlinear Klein-Gordon type), there is no effect on the steady state spectrum. However, for asymmetrically placed solutions, there exists a measurable effect of which a perturbative mathematical characterization is offered. It is generally found that asymmetry towards the lossy side leads towards stability, while towards the gain side produces instability. Furthermore, a host of finite size effects, which disappear in the infinite domain limit, are illustrated in connection to the continuous spectrum of the problem.