We consider random walks on random graphs, focusing on return probabilities and hitting times for sparse Erdös-Rényi graphs. Using the tree approach, which is expected to be exact in the large graph limit, we show how to solve for the distribution of these quantities and we find that these distributions exhibit a form of self-similarity.

Particles interacting by a combination of isotropic short-range attraction and long-range repulsion have been shown to form complex phases despite the apparent simplicity of the interparticle potential. Using computer simulations we study the behavior of two-dimensional systems of colloids with such an interaction, focusing on how area fraction and repulsion range at fixed repulsion gradient may be used to tune the resulting kinetics and nonequilibrium structure. While the short-range attraction leads to aggregation, the long-range repulsion encourages growth of chains of particles due to repulsive intercluster interactions. Depending on area fraction/repulsion range we observe chain labyrinths, chain-compact aggregate coexistence, and connected networks of chains. The kinetics of cluster growth displays a sequence of connected networks and disconnected cluster or chain systems with increasing repulsion range, indicating the competing roles of connectivity of growing chains and repulsion-driven breakup of chains into compact aggregates. Chain-dominated systems show approximately logarithmic coarsening at late time that we interpret as the result of chains performing random walks in the randomly fluctuating potential landscape created by their neighbors, a situation reminiscent of glassy systems.

Microtubules are highly regulated dynamic elements of the cytoskeleton of eukaryotic cells. One of the regulation mechanisms observed in living cells is the severing by the proteins katanin and spastin. We introduce a model for the dynamics of microtubules in the presence of randomly occurring severing events. Under the biologically motivated assumption that the newly created plus end undergoes a catastrophe, we investigate the steady-state length distribution. We show that the presence of severing does not affect the number of microtubules, regardless of the distribution of severing events. In the special case in which the microtubules cannot recover from the depolymerizing state (no rescue events) we derive an analytical expression for the length distribution. In the general case we transform the problem into a single ordinary differential equation that is solved numerically.

Hubbell’s neutral model provides a rich theoretical framework to study ecological communities. By incorporating both ecological and evolutionary time scales, it allows us to investigate how communities are shaped by speciation processes. The speciation model in the basic neutral model is particularly simple, describing speciation as a point-mutation event in a birth of a single individual. The stationary species abundance distribution of the basic model, which can be solved exactly, fits empirical data of distributions of species’ abundances surprisingly well. More realistic speciation models have been proposed such as the random-fission model in which new species appear by splitting up existing species. However, no analytical solution is available for these models, impeding quantitative comparison with data. Here, we present a self-consistent approximation method for neutral community models with various speciation modes, including random fission. We derive explicit formulas for the stationary species abundance distribution, which agree very well with simulations. We expect that our approximation method will be useful to study other speciation processes in neutral community models as well.

The behavior of a conductive membrane in a static (dc) electric field is investigated theoretically. An effective zero-thickness model is constructed based on a Robin-type boundary condition for the electric potential at the membrane, originally developed for electrochemical systems. Within such a framework, corrections to the elastic moduli of the membrane are obtained, which arise from charge accumulation in the Debye layers due to capacitive effects and electric currents through the membrane and can lead to an undulation instability of the membrane. The fluid flow surrounding the membrane is also calculated, which clarifies issues regarding these flows sharing many similarities with flows produced by induced charge electro-osmosis (ICEO). Nonequilibrium steady states of the membrane and of the fluid can be effectively described by this method. It is both simpler, due to the zero thickness approximation which is widely used in the literature on fluid membranes, and more general than previous approaches. The predictions of this model are compared to recent experiments on supported membranes in an electric field.

We analyze the class of networks characterized by modular structure where a sequence of $\ell$ Erdös-Renyi random networks of size $N⪢\ell$ with random average degrees is joined by links whose structure must remain immaterial. We find that traceroutes spanning the entire macronetwork exhibit scaling degree distributions $P\left(k\right)\sim k^{-\gamma }$, where $\gamma$ depends on how the degrees of the joined clusters are distributed. We thus suggest that yet another mechanism for the dynamic origin of arbitrary power-law degree distributions observed in natural and artificial networks, many of which belong to the range $2\le \gamma \le 3$, may be found in random processes on modular networks.

In a world without inertia, Purcell’s scallop theorem states that in a Newtonian fluid a time-reversible motion cannot produce any net force or net flow. Here we consider the extent to which the nonlinear rheological behavior of viscoelastic fluids can be exploited to break the constraints of the scallop theorem in the context of fluid pumping. By building on previous work focusing on force generation, we consider a simple, biologically inspired geometrical example of a flapper in a polymeric (Oldroyd-B) fluid, and calculate asymptotically the time-average net fluid flow produced by the reciprocal flapping motion. The net flow occurs at fourth order in the flapping amplitude, and suggests the possibility of transporting polymeric fluids using reciprocal motion in simple geometries even in the absence of inertia. The induced flow field and pumping performance are characterized and optimized analytically. Our results may be useful in the design of micropumps handling complex fluids.

This paper studies a simple two-dimensional model of a swimmer at low-Reynolds-number near a no-slip wall by utilizing methods of complex analysis. The swimmer is propelled by purely tangential surface deformations and is modeled by moving point singularities. The nonlinear dynamics of the swimmer is formulated explicitly, and its motion near the wall is fully characterized. The results show qualitative agreement with predictions of three-dimensional models and with motion experiments on a robotic swimmer. The success and simplicity of the model suggest that it will provide a simple way to study the dynamics of low-Reynolds-number swimmers in more complicated geometries.

For a classical particle undergoing nonlinear interaction with a wave in dielectric medium, a perturbation theory is developed, showing that the particle motion can be described in terms of an effective parallel mass which can become negative. A relativistic particle interacting with a circularly polarized wave and a static magnetic field is studied as an example. For the three stationary orbits corresponding to the same velocity parallel to the magnetic field, the conditions are found under which all these equilibria are centerlike, or neutrally stable. It is shown that a negative parallel mass is realized in the vicinity of the intermediate-energy equilibrium and can lead to a plasma collective instability.

Experimental measurements of proton acceleration with high intensity and high-contrast short laser pulses have been carried out over an order of magnitude range in target thickness and laser pulse duration. The dependence of the maximum proton energy with these parameters is qualitatively supported by two-dimensional particle-in-cell simulations. They evidence that two regimes of proton acceleration can take place, depending on the ratio between the density gradient and the hot electron Debye length at the rear target surface. As this ratio can be affected by the target thickness, a complex interplay between pulse duration and target thickness is observed. Measurements and simulations support unexpected variations in the laser absorption and hot electron temperature with the pulse duration and laser intensity, for which density profile modification at the target front surface is the controlling parameter.

Protein-protein interactions comprise both transport and reaction steps. During the transport step, anisotropy of proteins and their complexes is important both for hydrodynamic diffusion and accessibility of the binding site. Using a Brownian dynamics approach and extensive computer simulations, we quantify the effect of anisotropy on the encounter rate of ellipsoidal particles covered with spherical encounter patches. We show that the encounter rate $k$ depends on the aspect ratios $\xi$ mainly through steric effects, while anisotropic diffusion has only a little effect. Calculating analytically the crossover times from anisotropic to isotropic diffusion in three dimensions, we find that they are much smaller than typical protein encounter times, in agreement with our numerical results.

We investigate the stationary state of a model system evolving according to a modified focusing truncated nonlinear Schrödinger equation used to describe the envelope of Langmuir waves in a plasma. We restrict the system to have a finite number of normal modes each of which is in contact with a Langevin heat bath at temperature $T$. Arbitrarily large realizations of the field are prevented by restricting each mode to a maximum amplitude. We consider a simple modeling of wave breaking in which each mode is set equal to zero when it reaches its maximum amplitude. Without wave breaking the stationary state is given by a Gibbs measure. With wave breaking the system attains a nonequilibrium stationary state which is the unique invariant measure of the time evolution. A mean-field analysis shows that the system exhibits a transition from a regime of low-field values at small $\left|\lambda \right|$, to a regime of higher-field values at large $\left|\lambda \right|$, where $\lambda <0$ specifies the strength of the nonlinearity in the focusing case. Field values at large $\left|\lambda \right|$ are significantly smaller with wave breaking than without wave breaking.

The effects of size and charge asymmetry on the gas-liquid critical parameters of a primitive model (PM) of ionic fluids are studied within the framework of the statistical field theory based on the collective variables method. Recently, this approach has enabled us to obtain the correct trends of the both critical parameters of the equisize charge-asymmetric PM without assuming ionic association. In this paper, we focus on the general case of an asymmetric PM characterized by the two parameters: hard-sphere diameter, $\lambda ={\sigma }_{+}/{\sigma }_{-}$, and charge, $z=q_{+}/\left|q_{-}\right|$, ratios of the two ionic species. We derive an explicit expression for the chemical potential conjugate to the order parameter which includes the effects of correlations up to the third order. Based on this expression we consider the three versions of PM: a monovalent size-asymmetric PM $\left(\lambda \ne 1,z=1\right)$, an equisize charge-asymmetric PM $\left(\lambda =1,z\ne 1\right)$ and a size- and charge-asymmetric PM $\left(\lambda \ne 1,z=2\right)$. Similar to simulations, our theory predicts that the critical temperature and the critical density decrease with the increase in size asymmetry. Regarding the effects of charge asymmetry, we obtain the correct trend of the critical temperature with $z$, while the trend of the critical density obtained in this approximation is inconsistent with simulations, as well as with our previous results found in the higher-order approximation. We expect that the consideration of the higher-order correlations will lead to the correct trend of the critical density with charge asymmetry.

The rapid and efficient exchange of ions between porous electrodes and aqueous solutions is important in many applications, such as electrical energy storage by supercapacitors, water desalination and purification by capacitive deionization, and capacitive extraction of renewable energy from a salinity difference. Here, we present a unified mean-field theory for capacitive charging and desalination by ideally polarizable porous electrodes (without Faradaic reactions or specific adsorption of ions) valid in the limit of thin double layers (compared to typical pore dimensions). We illustrate the theory for the case of a dilute, symmetric, binary electrolyte using the Gouy-Chapman-Stern (GCS) model of the double layer, for which simple formulae are available for salt adsorption and capacitive charging of the diffuse part of the double layer. We solve the full GCS mean-field theory numerically for realistic parameters in capacitive deionization, and we derive reduced models for two limiting regimes with different time scales: (i) in the “supercapacitor regime” of small voltages and/or early times, the porous electrode acts like a transmission line, governed by a linear diffusion equation for the electrostatic potential, scaled to the RC time of a single pore, and (ii) in the “desalination regime” of large voltages and long times, the porous electrode slowly absorbs counterions, governed by coupled, nonlinear diffusion equations for the pore-averaged potential and salt concentration.

Assembly of the $T=3$ bacteriophage MS2 is initiated by the binding of a 19 nucleotide RNA stem loop from within the phage genome to a symmetric coat protein dimer. This binding event effects a folding of the FG loop in one of the protein subunits of the dimer and results in the formation of an asymmetric dimer. Since both the symmetric and asymmetric forms of the dimer are needed for the assembly of the protein container, this allosteric switch plays an important role in the life cycle of the phage. We provide here details of an all-atom normal-mode analysis of this allosteric effect. The results suggest that asymmetric contacts between the $A$-duplex RNA phosphodiester backbone of the stem loop with the EF loop in one coat protein subunit results in an increased dynamic behavior of its FG loop. The four lowest-frequency modes, which encompass motions predominantly on the FG loops, account for over 90% of the increased dynamic behavior due to a localization of the vibrational pattern on a single FG loop. Finally, we show that an analysis of the allosteric effect using an elastic network model fails to predict this localization effect, highlighting the importance of using an all-atom full force field method for this problem.

In recent studies a number of research groups have determined that human electroencephalograms (EEG) have scaling properties. In particular, a crossover between two regions with different scaling exponents has been reported. Herein we study the time evolution of diffusion entropy to elucidate the scaling of EEG time series. For a cohort of 20 awake healthy volunteers with closed eyes, we find that the diffusion entropy of EEG increments (obtained from EEG waveforms by differencing) exhibits three features: short-time growth, an alpha wave related oscillation whose amplitude gradually decays in time, and asymptotic saturation which is achieved after approximately 1 s. This analysis suggests a linear, stochastic Ornstein-Uhlenbeck Langevin equation with a quasiperiodic forcing (whose frequency and/or amplitude may vary in time) as the model for the underlying dynamics. This model captures the salient properties of EEG dynamics. In particular, both the experimental and simulated EEG time series exhibit short-time scaling which is broken by a strong periodic component, such as alpha waves. The saturation of EEG diffusion entropy precludes the existence of asymptotic scaling. We find that the crossover between two scaling regions seen in detrended fluctuation analysis (DFA) of EEG increments does not originate from the underlying dynamics but is merely an artifact of the algorithm. This artifact is rooted in the failure of the “trend plus signal” paradigm of DFA.

For a general class of diffusion processes with multiplicative noise, describing a variety of physical as well as financial phenomena, mostly typical of complex systems, we obtain the analytical solution for the moments at all times. We allow for a nontrivial time dependence of the microscopic dynamics and we analytically characterize the process evolution, possibly toward a stationary state, and the direct relationship existing between the drift and diffusion coefficients and the time scaling of the moments.

We test four fast mean-field-type algorithms on Hopfield networks as an inverse Ising problem. The equilibrium behavior of Hopfield networks is simulated through Glauber dynamics. In the low-temperature regime, the simulated annealing technique is adopted. Although performances of these network reconstruction algorithms on the simulated network of spiking neurons are extensively studied recently, the analysis of Hopfield networks is lacking so far. For the Hopfield network, we found that, in the retrieval phase favored when the network wants to memory one of stored patterns, all the reconstruction algorithms fail to extract interactions within a desired accuracy, and the same failure occurs in the spin-glass phase where spurious minima show up, while in the paramagnetic phase, albeit unfavored during the retrieval dynamics, the algorithms work well to reconstruct the network itself. This implies that, as an inverse problem, the paramagnetic phase is conversely useful for reconstructing the network while the retrieval phase loses all the information about interactions in the network except for the case where only one pattern is stored. The performances of algorithms are studied with respect to the system size, memory load, and temperature; sample-to-sample fluctuations are also considered.

Taming turbulence in the complex Ginzburg-Landau equation (CGLE) by using a global feedback control method and choosing traveling-wave solutions as our target state is investigated. The problem of optimal control for the smallest driving strength is studied by systematically comparing the stabilities of all traveling waves. Within the Benjamin-Feir-Newell unstable parameter region $\left(c_2<-c_1^{-1}\right)$, a critical control curve is determined, which is located at $c_2=\alpha c_1^{\beta }$, with $\alpha \approx -4.0$ and $\beta \approx -0.87$. It characterizes the transition of chosen traveling-wave target state from long wavelength to short one. This finding is of great significance for taming turbulence in the CGLE and some other spatiotemporal systems as well.