We consider strongly confined, stably stratified shear flows generated as a lock exchange in a tube inclined at an angle of $\theta ={45}^{\circ }$. This paper focuses on a transitional regime, in which the flow alternates between two distinct states: laminar, parallel shear flow and intense transverse motion characteristic of turbulence. Laminar-turbulent cycles were captured at Atwood numbers $\text{At}\equiv ({\rho }_2-{\rho }_1)/({\rho }_1+{\rho }_2)$ ranging from $2.45\times {10}^{-3}$ to $4.0\times {10}^{-3}$, where $({\rho }_1,{\rho }_2)$ are the initial densities of the two fluids, with multiple cycles observed at $\text{At}=2.55\times {10}^{-3}$. The evolution of the density and velocity fields in these flows was measured simultaneously using laser-induced fluorescence and particle image velocimetry. During each laminar-turbulent cycle, the axial velocity exhibits a distinctive ramp-cliff pattern, indicating that the flow accelerates as it relaminarizes, then decelerates rapidly as the Kelvin-Helmholtz billows break down. Within the range of experimental conditions, transverse stratification does not directly determine the onset of instability. Instead, the data suggest that a necessary criterion for the onset of instability is for the local Reynolds number to exceed 2200, with only a weak dependence on the Richardson number.

Because liquids cannot resist shear except over very short distances comparable to the atomic spacing, shear sound waves (i.e., transverse phonons) propagate only for very short wavelengths. A measure of this limit is the cutoff wave number $k_c$, which is sometimes called the critical wave number. Previously $k_c$ was determined in molecular dynamics (MD) simulations by obtaining the dispersion relation. Another approach is developed in this paper by identifying the wave number at the onset of a negative peak in the transverse current correlation function. This method is demonstrated using a three-dimensional MD simulation of a Yukawa fluid, which mimics dusty plasmas. In general, $k_c$ is an indicator of conditions where elastic and dissipative effects are approximately balanced. Additionally, the crossover frequency for the real and imaginary terms of the complex viscosity of a dusty plasma is obtained; this crossover frequency corresponds to the Maxwell relaxation time.

We study experimentally, numerically, and theoretically the elastic response of mechanical resonators along which the temperature is not uniform, as a consequence of the onset of steady-state thermal gradients. Two experimental setups and designs are employed, both using low-loss materials. In both cases, we monitor the resonance frequencies of specific modes of vibration, as they vary along with variations of temperatures and of temperature differences. In one case, we consider the first longitudinal mode of vibration of an aluminum alloy resonator; in the other case, we consider the antisymmetric torsion modes of a silicon resonator. By defining the average temperature as the volume-weighted mean of the temperatures of the respective elastic sections, we find out that the elastic response of an object depends solely on it, regardless of whether a thermal gradient exists and, up to 10$\%$ imbalance, regardless of its magnitude. The numerical model employs a chain of anharmonic oscillators, with first- and second-neighbor interactions and temperature profiles satisfying Fourier's Law to a good degree. Its analysis confirms, for the most part, the experimental findings and it is explained theoretically from a statistical mechanics perspective with a loose notion of local equilibrium.

A method for free-energy calculation based on mean-force dynamics (fictitious dynamics on a potential of mean force) is presented. The method utilizes a logarithmic form of free energy to enhance crossing barriers on a free-energy landscape, which results in efficient sampling of “rare” events. Invoking a conserved quantity in mean-force dynamics, free energy can be estimated on-the-fly without postprocessing. This means that an estimate of the free-energy profile can be locally made in contrast to the other methods based on mean-force dynamics such as metadynamics. The method is benchmarked against conventional methods and its high efficiency is demonstrated in the free-energy calculation for a glycine dipeptide molecule.

Simulating the static and dynamic properties of semidilute polymer solutions with Brownian dynamics (BD) requires the computation of a large system of polymer chains coupled to one another through excluded-volume and hydrodynamic interactions. In the presence of periodic boundary conditions, long-ranged hydrodynamic interactions are frequently summed with the Ewald summation technique. By performing detailed simulations that shed light on the influence of several tuning parameters involved both in the Ewald summation method, and in the efficient treatment of Brownian forces, we develop a BD algorithm in which the computational cost scales as $O\left(N^{1.8}\right)$, where $N$ is the number of monomers in the simulation box. We show that Beenakker's original implementation of the Ewald sum, which is only valid for systems without bead overlap, can be modified so that $\theta$ solutions can be simulated by switching off excluded-volume interactions. A comparison of the predictions of the radius of gyration, the end-to-end vector, and the self-diffusion coefficient by BD, at a range of concentrations, with the hybrid lattice Boltzmann–molecular dynamics (LB-MD) method shows excellent agreement between the two methods. In contrast to the situation for dilute solutions, the LB-MD method is shown to be significantly more computationally efficient than the current implementation of BD for simulating semidilute solutions. We argue, however, that further optimizations should be possible.

The entropy production in classical irreversible thermodynamics is expressed as a bilinear form of generalized (driving) forces and conjugated (driven) fluxes, which suffers from the arbitrary decomposition of the forces and the fluxes, and the possible negative entropy production in non-Fourier heat conduction problems (heat waves). This paper presents a general form of the entropy production for heat conduction based on the thermomass model, which is the product of the friction force and the drift velocity of the thermomass divided by the temperature; it holds true for both Fourier and non-Fourier heat conduction. Then a generalization of the entropy production is given for other kinds of linear and nonlinear transport processes. The general expression for entropy production is consistent with that given by extended irreversible thermodynamics, where the system entropy depends not only on the classical variables, but also on the dissipative fluxes, for example, the heat flux in heat conduction problems.

In this paper we study the ordered packing of wires in a sphere. We propose an analytical model and compare the model predictions with the results of our experiments and simulations for the maximum packing fraction, the number of formed coils, the fractal dimension, and bending energy. We show that the relative system size [i.e., the ratio of the wire radius to the sphere radius ($a/R$)] is the most important control parameter for the maximum packing fraction. We find that the number of coils obeys a power-law relation of the form $N\sim {(R/a)}^{1.5}$ and the fractal dimension of the structures is 2.5, independent of the system size. Our theoretical results are in good agreement with the experimental data and the predictions of the numerical simulations.

In this work, we present a supersymmetric extension of the quantum spherical model, both in components and also in the superspace formalisms. We find the solution for short- and long-range interactions through the imaginary time formalism path integral approach. The existence of critical points (classical and quantum) is analyzed and the corresponding critical dimensions are determined.

Using finite-size scaling, we have investigated the percolation phase transitions of evolving random networks under a generalized Achlioptas process (GAP). During this GAP, the edge with a minimum product of two connecting cluster sizes is taken with a probability $p$ from two randomly chosen edges. This model becomes the Erdös-Rényi network at $p=0.5$ and the random network under the Achlioptas process at $p=1$. Using both the fixed point of the size ratio $s_2/s_1$ and the straight line of $\ln s_1$, where $s_1$ and $s_2$ are the reduced sizes of the largest and the second-largest cluster, we demonstrate that the phase transitions of this model are continuous for $0.5⩽p⩽1$. From the slopes of $\ln s_1$ and $\ln {(s_2/s_1)}^{\prime }$ at the critical point, we get critical exponents $\beta$ and $\nu$ of the phase transitions. At $0.5⩽p⩽0.8$, it is found that $\beta$, $\nu$, and $s_2/s_1$ at critical point are unchanged and the phase transitions belong to the same universality class. When $p⩾0.9$, $\beta$, $\nu$, and $s_2/s_1$ at critical point vary with $p$ and the universality class of phase transitions depends on $p$.

A planar bistable liquid crystal device, reported in Tsakonas et al. [Appl. Phys. Lett. 90, 111913 (2007)], is modeled within the Landau-de Gennes theory for nematic liquid crystals. This planar device consists of an array of square micrometer-sized wells. We obtain six different classes of equilibrium profiles and these profiles are classified as diagonal or rotated solutions. In the strong anchoring case, we propose a Dirichlet boundary condition that mimics the experimentally imposed tangent boundary conditions. In the weak anchoring case, we present a suitable surface energy and study the multiplicity of solutions as a function of the anchoring strength. We find that diagonal solutions exist for all values of the anchoring strength $W⩾0$, while rotated solutions only exist for $W⩾W_c>0$, where $W_c$ is a critical anchoring strength that has been computed numerically. We propose a dynamic model for the switching mechanisms based on only dielectric effects. For sufficiently strong external electric fields, we numerically demonstrate diagonal-to-rotated and rotated-to-diagonal switching by allowing for variable anchoring strength across the domain boundary.

The influence of triplet levels on Förster resonance energy transfer via singlet levels in donor-acceptor ($D$-$A$) pairs is studied. Four types of $D$-$A$ pair are considered: (i) two-level donor and two-level acceptor, (ii) three-level donor and two-level acceptor, (iii) two-level donor and three-level acceptor, and (iv) three-level donor and three-level acceptor. If singlet-triplet transitions in a three-level acceptor molecule are ineffective, the energy transfer efficiency $E=I_A/(I_A+I_D)$, where $I_D$ and $I_A$ are the average intensities of donor and acceptor fluorescence, can be described by the simple theoretical equation $E\left(F\right)=F{T}_D/(1+F{T}_D)$. Here $F$ is the rate of energy transfer, and $T_D$ is the donor fluorescence lifetime. In accordance with the last equation, 100$\%$ of the donor electronic energy can be transferred to an acceptor molecule at $F{T}_D\gg 1$. However, if singlet-triplet transitions in a three-level acceptor molecule are effective, the energy transfer efficiency is described by another theoretical equation, $E\left(F\right)=\overline{F}\left(F\right)T_D/\left[1+\overline{F}\left(F\right)T_D\right]$. Here $\overline{F}\left(F\right)$ is a function of $F$ depending on singlet-triplet transitions in both donor and acceptor molecules. Expressions for the functions $\overline{F}\left(F\right)$ are derived. In this case the energy transfer efficiency will be far from 100$\%$ even at $F{T}_D\gg 1$. The character of the intensity fluctuations of donor and acceptor fluorescence indicates which of the two equations for $E\left(F\right)$ should be used to find the value of the rate $F$. Therefore, random time instants of photon emission in both donor and acceptor fluorescence are calculated by the Monte Carlo method for all four types of $D$-$A$ pair. Theoretical expressions for start-stop correlators (waiting time distributions) in donor and acceptor fluorescence are derived. The probabilities $w_N^D\left(t\right)$ and $w_N^A\left(t\right)$ of finding $N$ photons of donor and acceptor fluorescence in the time interval $t$ are calculated for various values of the energy transfer rate $F$ and for all four types of $D$-$A$ pair. Comparison of the calculated $D$ and $A$ fluorescence trajectories with those measured by Weiss and co-workers proves the important role of triplet levels in energy transfer via singlet levels.

Spatial data sets, generated from a wide range of physical systems can be analyzed by counting the number of objects in a set of bins. Previous work has been limited to equal-sized bins, which are inappropriate for some domains (e.g., circular). We consider a nonequal size bin configuration whereby overlapping or nonoverlapping bins cover the domain. A generalized index, defined in terms of a variance between bin counts, is developed to indicate whether or not a spatial data set, generated from exclusion or nonexclusion processes, is at the complete spatial randomness (CSR) state. Limiting values of the index are determined. Using examples, we investigate trends in the generalized index as a function of density and compare the results with those using equal size bins. The smallest bin size must be much larger than the mean size of the objects. We can determine whether a spatial data set is at the CSR state or not by comparing the values of a generalized index for different bin configurations—the values will be approximately the same if the data is at the CSR state, while the values will differ if the data set is not at the CSR state. In general, the generalized index is lower than the limiting value of the index, since objects do not have access to the entire region due to blocking by other objects. These methods are applied to two applications: (i) spatial data sets generated from a cellular automata model of cell aggregation in the enteric nervous system and (ii) a known plant data distribution.

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

We study two measures of the complexity of heterogeneous extended systems, taking random Boolean networks as prototypical cases. A measure defined by Shalizi et al. for cellular automata, based on a criterion for optimal statistical prediction [Shalizi et al., Phys. Rev. Lett. 93, 118701 (2004)], does not distinguish between the spatial inhomogeneity of the ordered phase and the dynamical inhomogeneity of the disordered phase. A modification in which complexities of individual nodes are calculated yields vanishing complexity values for networks in the ordered and critical regimes and for highly disordered networks, peaking somewhere in the disordered regime. Individual nodes with high complexity are the ones that pass the most information from the past to the future, a quantity that depends in a nontrivial way on both the Boolean function of a given node and its location within the network.

We identify an important correlation between skewness and kurtosis for a broad class of complex dynamic systems and present a specific analysis of earthquake and financial time series. Two regimes of non-Gaussianity can be identified: a parabolic one, which is common in various fields of physics, and a power law one, with exponent $4/3$, which at the moment appears to be specific of earthquakes and financial markets. For this property we propose a model and an interpretation in terms of very rare events dominating the statistics independently on the nature of the events considered. The predicted scaling relation between skewness and kurtosis matches very well the experimental pattern of the second regime. Regarding price fluctuations, this situation characterizes a universal stylized fact.

Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems, epidemics occur simultaneously across the entire system at a critical infection strength ${\beta }_c$, below which the disease does not spread. In contrast, in weakly coupled network systems, a mixed phase exists below ${\beta }_c$ of the coupled network system, where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.

Many complex networks from the World Wide Web to biological networks grow taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document such as personal page, thematic website, news, blog, search engine, social network, etc., or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an “effective fitness” for each class of nodes, determining the rate at which nodes acquire new links. The degree distribution exhibits a multiscaling behavior analogous to the the fitness model. This property is robust with respect to variations in the model, as long as links are assigned through effective preferential attachment. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show that it disappears for large network size, a property shared with the Barabási-Albert model. Negative degree correlations are also present in this class of models, along with nontrivial mixing patterns among features. We therefore conclude that both small clustering coefficients and disassortative mixing are outcomes of the preferential attachment mechanism in general growing networks.

The onset of double-diffusive natural convection in under-ice melt ponds is investigated through a linear stability analysis. The three-layer configuration is composed by a fluid layer (melt pond) overlying a saturated porous medium (ice matrix), which in turn overlies another fluid layer (under-ice melt pond). Water density inversion is taken into account by adopting a density profile with a quadratic temperature dependence and a linear concentration dependence. We show that the key parameter affecting stability is the depth of the ice matrix, while the depths of the upper and lower fluid layers play a marginal role. A Hopf bifurcation is observed in the whole range of parameters studied, and the size of the convection cells depends on ice permeability. The influence of the external temperature gradient is investigated by means of the definition of an extra thermal parameter accounting for the relative position of the density maximum. It is shown that convection is favored by larger temperature gradients, which occur during Arctic summer.

A numerical investigation of the collapse of granular columns has been conducted. In particular, we address the effect of the grain shape on the properties of the collapse. We show that the final runout and height of the deposits scale as a power law of the initial aspect ratio of the column, $a$, independently of the elongation of the grains used. We describe this process in terms of an energy balance, and construct an “inertial number” that can be used to describe the flow in terms of a recently proposed granular rheology. We argue that an effective friction that results from this dimensionless quantity explains why the shape of the grains is irrelevant for the final properties of the collapse.

Generic glass formers exhibit at least two characteristic changes in their relaxation behavior, first to an Arrhenius-type relaxation at some characteristic temperature and then at a lower characteristic temperature to a super-Arrhenius (fragile) behavior. We address these transitions by studying the statistics of free energy barriers for different systems at different temperatures and space dimensions. We present a clear evidence for changes in the dynamical behavior at the transition to Arrhenius and then to a super-Arrhenius behavior. A simple model is presented, based on the idea of competition between single-particle and cooperative dynamics. We argue that Arrhenius behavior can take place as long as there is enough free volume for the completion of a simple $T1$ relaxation process. Once free volume is absent one needs a cooperative mechanism to “collect” enough free volume. We show that this model captures all the qualitative behavior observed in simulations throughout the considered temperature range.