In a previous work [Dillon and Nakanishi, Eur. Phys. J. B 87, 286 (2014)], we numerically calculated the transmission coefficient of the two-dimensional quantum percolation problem and mapped out in detail the three regimes of localization, i.e., exponentially localized, power-law localized, and delocalized, which had been proposed earlier [Islam and Nakanishi, Phys. Rev. E 77, 061109 (2008)]. We now consider a variation on quantum percolation in which the hopping integral $\left(w\right)$ associated with bonds that connect to at least one diluted site is not zero, but rather a fraction of the hopping integral $\left(V=1\right)$ between nondiluted sites. We study the latter model by calculating quantities such as the transmission coefficient and the inverse participation ratio and find the original quantum percolation results to be stable for $w>0$ over a wide range of energy. In particular, except in the immediate neighborhood of the band center (where increasing $w$ to just $0.02V\mathrm{appears}$ to eliminate localization effects), increasing $w$ only shifts the boundaries between the three regimes but does not eliminate them until $w$ reaches 10%–40% of $V$.

We consider an open billiard with two holes, connected by a handle. The central billiard is chosen so that its closed form's islands of stability occupy a significant part of the phase space. Holes destroy these islands, which leads to almost all trajectories of the system being interleaved. We also study the unbalanced flow of billiard particles through the handle, which appears only after a small border site of nonspecular reflection is added to the system. With this site our system is rather a ratchet of a different type, since the site does not produce an explicitly acting force or violate the reversibility of trajectories.

Birhythmicity arises in several physical, biological, and chemical systems. Although many control schemes have been proposed for various forms of multistability, only a few exist for controlling birhythmicity. In this paper we investigate the control of birhythmic oscillation by introducing a self-feedback mechanism that incorporates the variable to be controlled and its canonical conjugate. Using a detailed analytical treatment, bifurcation analysis, and experimental demonstrations, we establish that the proposed technique is capable of eliminating birhythmicity and generates monorhythmic oscillation. Further, the detailed parameter space study reveals that, apart from monorhythmicity, the system shows a transition between birhythmicity and other dynamical forms of bistability. This study may have practical applications in controlling birhythmic behavior of several systems, in particular in biochemical and mechanical processes.

While the interplay between neuronal excitability properties and global properties of network topology is known to affect network propensity for synchronization, it is not clear how detailed characteristics of these properties affect spatiotemporal pattern formation. Here we study mixed networks, composed of neurons having type I and/or type II phase response curves, with varying distributions of local and random connections and show that not only average network properties, but also the connectivity distribution statistics, significantly affect network synchrony. Namely, we study networks with fixed networkwide properties, but vary the number of random connections that nodes project. We show that varying node excitability (type I vs type II) influences network synchrony most dramatically for systems with long-tailed distributions of the number of random connections per node. This indicates that a cluster of even a few highly rewired cells with a high propensity for synchronization can alter the degree of synchrony in the network as a whole. We show this effect generally on a network of coupled Kuramoto oscillators and investigate the impact of this effect more thoroughly in pulse-coupled networks of biophysical neurons.

Self-consistent field theory (SCFT) is used to study the mean potential near a charged plate inside a $m\text{:}-n$ electrolyte. A perturbation series is developed in terms of $g=4\pi \kappa b$, where $band1/\kappa$ are Bjerrum length and bare Debye length, respectively. To the zeroth order, we obtain the nonlinear Poisson-Boltzmann theory. For asymmetric electrolytes $\left(m\ne n\right)$, the first order (one-loop) correction to mean potential contains a secular term, which indicates the breakdown of the regular perturbation method. Using a renormalizaton group transformation, we remove the secular term and obtain a globally well-behaved one-loop approximation with a renormalized Debye length and a renormalized surface charge density. Furthermore, we find that if the counterions are multivalent, the surface charge density is renormalized substantially downwards and may undergo a change of sign, if the bare surface charge density is sufficiently large. Our results agrees with large MC simulation even when the density of electrolytes is relatively high.

This paper extends to two and three dimensions the recently proposed renormalized multicanonical sampling procedure [D. Yevick, Int. J. Mod. Phys. C 27, 1650033 (2016)], which generates the density of states of a system from that of a smaller system. The accuracy and efficiency of the method is additionally enhanced through a transition matrix Monte Carlo method that incorporates multicanonical sampling. The performance of the resulting procedure is investigated through calculations of the specific heat of the standard Ising model for square lattices with up to ${128}^2$ spins and for cubic lattices with up to ${24}^3$ spins. A comparison of the scaling properties to those of other algorithms based on the transition matrix Monte Carlo method demonstrates that the relative advantage of the renormalized procedure increases rapidly with system size.

Many real systems composed of a large number of interacting components, as, for instance, neural networks, may exhibit collective periodic behavior even though single components have no natural tendency to behave periodically. Macroscopic oscillations are indeed one of the most common self-organized behavior observed in living systems. In the present paper we study some dynamical features of a two-population generalization of the mean-field Ising model with the scope of investigating simple mechanisms capable to generate rhythms in large groups of interacting individuals. We show that the system may undergo a transition from a disordered phase, where the magnetization of each population fluctuates closely around zero, to a phase in which they both display a macroscopic regular rhythm. In particular, there exists a region in the parameter space where having two groups of spins with inter- and intrapopulation interactions of different strengths suffices for the emergence of a robust periodic behavior.

Thermodynamic behaviors in a quantum Brownian motion coupled to a classical heat bath is studied. We then define a heat operator by generalizing the stochastic energetics and show the energy balance (first law) and the upper bound of the expectation value of the heat operator (second law). We further find that this upper bound depends on the memory effect induced by quantum fluctuations and hence the maximum extractable work can be qualitatively modified in quantum thermodynamics.

Effects of spatial diffusion in a Kauffman-like model for prebiotic evolution previously studied in a “well-mixed” limit are reported. The previous model was parametrized by a parameter $p$ defined as the probability that a possible reaction in a network of reactions characterizing the artificial chemistry actually appears in the chemical network. In the model reported here, we numerically study a grid of such well-mixed reactors on a two-dimensional spatial lattice in which the model chemical constituents can hop between neighboring reactors at a rate controlled by a second parameter $\eta$. We report the frequency of appearance of three distinct types of nonequilibrium steady states, characterized as “diffusively alive locally dead” (DALD), “diffusively dead locally alive” (DDLA) and “diffusively alive locally alive” (DALA). The types are defined according to whether they are chemically equilibrated at each site, diffusively equilibrated between sites, or neither, respectively. With our parametrization of the definitions of these nonequilibrium states, many of the DALA states are growing rapidly in population due to the explosive population growth of a few sites, while their entropy remains well below its equilibrium value. Sharp temporal transitions occur as exploding sites appear. DALD states occur less commonly than the other types and also usually harbor a few explosively growing sites but transitions are less sharp than in DALA systems.

Ultradian cycles are frequently observed in biological systems. They serve important roles in regulating, for example, cell fate and the development of the organism. Many mathematical models have been developed to analyze their behavior. Generally, these models can be classified into two classes: Deterministic models that generate oscillatory behavior by incorporating time delays or Hopf bifurcations, and stochastic models that generate oscillatory behavior by noise driven resonance. However, it is still unclear which of these two mechanisms applies to cellular oscillations. In this paper, we show through theoretical analysis and numerical simulation that we can distinguish which of these two mechanisms govern cellular oscillations, by measuring statistics of oscillation amplitudes for cells of different sizes. We found that, for oscillations driven deterministically, the normalized average amplitude is constant with respect to cell size, while the coefficient of variation of the amplitude scales with cell size with an exponent of $-0.5$. On the other hand, for oscillations driven stochastically, the coefficient of variation of the amplitude is constant with respect to cell size, while the normalized average amplitude scales with cell size with an exponent of $-0.5$. Our results provide a theoretical basis to discern whether a particular oscillatory behavior is governed by a deterministic or stochastic mechanism.

Within the continuum approach we study the equilibrium configurations of a cholesteric liquid crystal confined between two parallel plates, when a magnetic field is applied perpendicularly to the plates. We analyze the role of soft anchoring boundary conditions on magnetic-field-induced cholesteric-nematic transitions in a finite thickness cholesteric cell, treated to induce soft planar alignment. We study the stepwise behavior of cholesteric pitch as a function of the anchoring energy, the thickness of a layer, and the field strength. We analyze some kinds of soft anchoring potentials, including the case of degeneration of the easy axes. We show that the variation of the thickness or intrinsic pitch induces the the stepwise behavior of a pitch of the planar cholesteric structure, and the stepwise variations of the average tensor of diamagnetic susceptibility. The values of these jumps are determined by the anchoring energy. We find the values of critical parameters for the transitions between planar and confocal cholesteric states, and homeotropic nematic state. We show that the variation of the anchoring energy leads to change of the phase transition character; the conditions for hysteresis behavior are obtained. We show that for rather soft anchoring the confocal state is metastable, and the increase of a magnetic field leads to the direct transition between the planar cholesteric and homeotropic nematic phases. We also give a detailed derivation of the threshold and saturation properties of planar cholesteric to homeotropic nematic transition.

We derive an analytic expression for the height correlation function of a homogeneous, isotropic rough surface based on the inverse wave scattering method of Kirchhoff theory. The expression directly relates the height correlation function to diffuse scattered intensity along a linear path at fixed polar angle. We test the solution by measuring the angular distribution of light scattered from rough silicon surfaces and comparing extracted height correlation functions to those derived from atomic force microscopy (AFM). The results agree closely with AFM over a wider range of roughness parameters than previous formulations of the inverse scattering problem, while relying less on large-angle scatter data. Our expression thus provides an accurate analytical equation for the height correlation function of a wide range of surfaces based on measurements using a simple, fast experimental procedure.

Various spatial density profiles can develop in partially miscible stratifications when a phase $A$ dissolves with a finite solubility into a host phase containing a dissolved reactant $B$. We investigate theoretically the impact of an $A+B\to C$ reaction on such density profiles in the host phase and classify them in a parameter space spanned by the ratios of relative contributions to density and diffusion coefficients of the chemical species. While the density profile is either monotonically increasing or decreasing in the nonreactive case, reactions combined with differential diffusivity can create eight different types of density profiles featuring up to two extrema in density, at the reaction front or below it. We use this framework to predict various possible hydrodynamic instability scenarios inducing buoyancy-driven convection around such reaction fronts when they propagate parallel to the gravity field.

Adaptive molecular resolution approaches in molecular dynamics are becoming relevant tools for the analysis of molecular liquids characterized by the interplay of different physical scales. The essential difference among these methods is in the way the change of molecular resolution is made in a buffer (transition) region. In particular a central question concerns the possibility of the existence of a global Hamiltonian which, by describing the change of resolution, is at the same time physically consistent, mathematically well defined, and numerically accurate. In this paper we present an asymptotic analysis of the adaptive process complemented by numerical results and show that under certain mathematical conditions a Hamiltonian, which is physically consistent and numerically accurate, may exist. Such conditions show that molecular simulations in the current computational implementation require systems of large size, and thus a Hamiltonian approach such as the one proposed, at this stage, would not be practical from the numerical point of view. However, the Hamiltonian proposed provides the basis for a simplification and generalization of the numerical implementation of adaptive resolution algorithms to other molecular dynamics codes.

A kinetic equation for a dilute gas of hard spheres confined between two parallel plates separated a distance smaller than two particle diameters is derived. It is a Boltzmann-like equation, which incorporates the effect of the confinement on the particle collisions. A function $S\left(t\right)$ is constructed by adding to the Boltzmann expression a confinement contribution. Then it is shown that for the solutions of the kinetic equation, $S\left(t\right)$ increases monotonically in time, until the system reaches a stationary inhomogeneous state, when $S$ becomes the equilibrium entropy of the confined system as derived from equilibrium statistical mechanics. From the entropy, other equilibrium properties are obtained, and molecular dynamics simulations are used to verify some of the theoretical predictions.

Reconstructing the structural connectivity between interacting units from observed activity is a challenge across many different disciplines. The fundamental first step is to establish whether or to what extent the interactions between the units can be considered pairwise and, thus, can be modeled as an interaction network with simple links corresponding to pairwise interactions. In principle, this can be determined by comparing the maximum entropy given the bivariate probability distributions to the true joint entropy. In many practical cases, this is not an option since the bivariate distributions needed may not be reliably estimated or the optimization is too computationally expensive. Here we present an approach that allows one to use mutual informations as a proxy for the bivariate probability distributions. This has the advantage of being less computationally expensive and easier to estimate. We achieve this by introducing a novel entropy maximization scheme that is based on conditioning on entropies and mutual informations. This renders our approach typically superior to other methods based on linear approximations. The advantages of the proposed method are documented using oscillator networks and a resting-state human brain network as generic relevant examples.

Conserved directed percolation (C-DP) and the depinning transition of a disordered elastic interface belong to the same universality class, as has been proven very recently by Le Doussal and Wiese [Phys. Rev. Lett. 114, 110601 (2015)] through a mapping of the field theory for C-DP onto that of the quenched Edwards-Wilkinson model. Here, we present an alternative derivation of the C-DP field theoretic functional, starting with the coherent-state path integral formulation of the C-DP and then applying the Grassberger transformation, which avoids the disadvantages of the so-called Doi shift. We revisit the aforementioned mapping with focus on a specific term in the field theoretic functional that has been problematic in the past when it came to assessing its relevance. We show that this term is redundant in the sense of the renormalization group.