The utility of an enhanced chromodynamic, color gradient or phase-field multicomponent lattice Boltzmann (MCLB) equation for immiscible fluids with a density difference was demonstrated by Wen et al. [Phys. Rev. E 100, 023301 (2019)] and Ba et al. [Phys. Rev. E 94, 023310 (2016)], who advanced earlier work by Liu et al. [Phys. Rev. E 85, 046309 (2012)] by removing certain error terms in the momentum equations. But while these models' collision scheme has been carefully enhanced by degrees, there is, currently, no quantitative consideration in the macroscopic dynamics of the segregation scheme which is common to all. Here, by analysis of the kinetic-scale segregation rule (previously neglected when considering the continuum behavior) we derive, bound, and test the emergent kinematics of the continuum fluids' interface for this class of MCLB, concurrently demonstrating the circular relationship with—and competition between—the models' dynamics and kinematics. The analytical and numerical results we present in Sec. V confirm that, at the kinetic scale, for a range of density contrast, color is a material invariant. That is, within numerical error, the emergent interface structure is isotropic (i.e., without orientation dependence) and Galilean-invariant (i.e., without dependence on direction of motion). Numerical data further suggest that reported restrictions on the achievable density contrast in rapid flow, using chromodynamic MCLB, originate in the effect on the model's kinematics of the terms deriving from our term $F_{1i}$ in the evolution equation, which correct its dynamics for large density differences. Taken with Ba's applications and validations, this result significantly enhances the theoretical foundation of this MCLB variant, bringing it somewhat belatedly further into line with the schemes of Inamuro et al. [J. Comput. Phys. 198, 628 (2004)] and the free-energy scheme [see, e.g., Phys. Rev. E. 76, 045702(R) (2007), and references therein] which, in contradistinction to the present scheme and perhaps wisely, postulate appropriate kinematics a priori.

Parallel tempering Monte Carlo has proven to be an efficient method in optimization and sampling applications. Having an optimized temperature set enhances the efficiency of the algorithm through more-frequent replica visits to the temperature limits. The approaches for finding an optimal temperature set can be divided into two main categories. The methods of the first category distribute the replicas such that the swapping ratio between neighboring replicas is constant and independent of the temperature values. The second-category techniques including the feedback-optimized method, on the other hand, aim for a temperature distribution that has higher density at simulation bottlenecks, resulting in temperature-dependent replica-exchange probabilities. In this paper, we compare the performance of various temperature setting methods on both sparse and fully connected spin-glass problems as well as fully connected Wishart problems that have planted solutions. These include two classes of problems that have either continuous or discontinuous phase transitions in the order parameter. Our results demonstrate that there is no performance advantage for the methods that promote nonuniform swapping probabilities on spin-glass problems where the order parameter has a smooth transition between phases at the critical temperature. However, on Wishart problems that have a first-order phase transition at low temperatures, the feedback-optimized method exhibits a time-to-solution speedup of at least a factor of two over the other approaches.

A large class of mesoscopic or macroscopic flocking theories are coarse-grained from microscopic models that feature binary interactions as the chief aligning mechanism. However, while such theories seemingly predict the existence of polar order with just binary interactions, actomyosin motility assay experiments show that binary interactions are insufficient to obtain polar order, especially at high densities. To resolve this paradox, here we introduce a solvable one-dimensional flocking model and derive its stochastic hydrodynamics. We show that two-body interactions are insufficient to generate polar order unless the noise is non-Gaussian. We show that noisy three-body interactions in the microscopic theory allow us to capture all essential dynamical features of the flocking transition, in systems that achieve orientational order above a critical density.

Relaxation in a two-dimensional suspensions containing rods was studied by using dynamic Monte Carlo simulations. An off-lattice model with continuous positional and orientational degrees of freedom was considered. The initial state was produced by using a random sequential adsorption model. During the relaxation, the rods underwent translational and rotational Brownian motions. The simulations were run at different values of number density $\rho$ (the number of rods per unit area) and of the initial orientation order parameter $S_i$. The rods were assumed to have core-shell structures. The evolutions of both the connectivity and the order parameter have revealed different relaxation behavior.

In biological systems, polymeric materials block the movement of some macromolecules while allowing the selective passage of others. In some cases, binding enables selective transport, while in others the most inert particles appear to transit most rapidly. To study the general principles of filtering, we develop a model motivated by features of the nuclear pore complex (NPC) which are highly conserved and could potentially be applied to other biological systems. The NPC allows selective transport of proteins called transport factors, which transiently bind to disordered flexible proteins called phenylalanine-glycine–nucleoporins. While the NPC is tuned for transport factors and their cargo, we show that a single feature is sufficient for selective transport: the bound-state motion resulting from transient binding to flexible filaments. Interchain transfer without unbinding can further improve selectivity, especially for cross-linked chains. We generalize this observation to model nanoparticle transport through mucus and show that bound-state motion accelerates transport of transient nanoparticle application, even with clearance by mucus flow. Our model provides a framework to control binding-induced selective transport in biopolymeric materials.

We report a peculiar head-on collision network between two vibrating boundaries in experiments performed during a parabolic flight and in a laboratory using horizontal vibration. This structure is a new ordering, which is due to an orientation correlation between the relative position and velocity of any particle pair. It weakens the collision frequency and produces a long-range boundary effect. Moreover, we find the molecular chaos assumption is violated in a larger portion of the phase space. Using an anisotropic distribution model, we modify angular integration results and compare them to the results of the kinetic theory.

In this paper we develop a kernel density estimation (KDE) approach to modeling and forecasting recurrent trajectories on a suitable manifold. For the purposes of this paper, a trajectory is a sequence of coordinates in a phase space defined by an underlying hidden dynamical system. Our work is inspired by earlier work on the use of KDE to detect shipping anomalies using high-density, high-quality automated information system data as well as our own earlier work in trajectory modeling. We focus specifically on the sparse, noisy trajectory reconstruction problem in which the data are (i) sparsely sampled and (ii) subject to an imperfect observer that introduces noise. Under certain regularity assumptions, we show that the constructed estimator minimizes a specific energy function defined over the trajectory as the number of samples obtained grows.

Multivariate singular spectrum analysis (M-SSA), with a structured varimax rotation, is a method that allows a deep characterization of phase synchronization (PS) phenomena in an almost automatic fashion. It has been increasingly used in the study of PS in networks of nonlinear, real-world, and numeric systems. This paper investigates the impact of the other recently developed structured orthomax rotations on the M-SSA ability to characterize PS. The results show that by using the structured quartimax rotation, a very faint and intermittent PS regime can be detected, in contrast with the structured varimax (which demands a stronger, more consolidated PS regime). This is due to the fact that the different rotations do not have the same efficiency in achieving a simple structure of the M-SSA eigenvectors. Nevertheless, for well-established PS regimes, the same robustness of the original M-SSA approach against high levels of additive Gaussian noise was found for the structured quartimax and biquartimax rotations. However, for all approaches we found an overshoot of the qualitative range for the PS onset due to noise.

The use of Darcy's law to describe steady-state multiphase flow in porous media has been justified by the assumption that the fluids flow in continuously connected pathways. However, a range of complex interface dynamics have been observed during macroscopically steady-state flow, including intermittent pathway flow where flow pathways periodically disconnect and reconnect. The physical mechanisms controlling this behavior have remained unclear, leading to uncertainty concerning the occurrence of the different flow regimes. We observe that the fraction of intermittent flow pathways is dependent on the capillary number and viscosity ratio. We propose a phase diagram within this parameter space to quantify the degree of intermittent flow.

Employing the optimal fluctuation method, we study the large deviation function of long-time averages $(1/T){\int }_{-T/2}^{T/2}{x}^n\left(t\right)dt,n=1,2,\cdots$, of centered stationary Gaussian processes. These processes are correlated and, in general, non-Markovian. We show that the anomalous scaling with time of the large-deviation function, recently observed for $n>2$ for the particular case of the Ornstein-Uhlenbeck process, holds for a whole class of stationary Gaussian processes.

Non-Gaussian diffusion has been intensively studied in recent years, which reflects the dynamic heterogeneity in the disordered media. The recent study on the non-Gaussian diffusion in a static disordered landscape suggests novel phenomena due to the quenched disorder. In this paper, we further investigate the random walk on this landscape under various effective temperatures $\mu$, which continuously modulate the dynamic heterogeneity. We show in the long-time limit, the trap dynamics on the landscape is equivalent to the quenched trap model in which subdiffusion appears for $\mu <1$. The non-Gaussian distribution of displacement has been analytically estimated for short $t$ of which the stretched exponential tail is expected for $\mu \ne 1$. Due to the localization in the ensemble of trajectory segments, an additional peak arises in $P(x,t)$ around $x=0$ even for $\mu >1$. Evolving in different timescales, the peak and the tail of $P(x,t)$ are well split for a wide range of $t$. This theoretical paper reveals the connections among the subdiffusion, non-Gaussian diffusion, and the dynamic heterogeneity in the static disordered medium. It also offers an insight on how the cell would benefit from the quasistatic disordered structures.

Opinion formation is a process with strong implications for public policy. In controversial debates with large consequences, the public opinion is often trapped in a fifty-fifty stalemate, jeopardizing broadly accepted political decisions. Emergent effects from millions of private discussions make it hard to understand or influence this kind of opinion dynamics. Here we demonstrate that repulsion from opinions favors fifty-fifty stalemates. We study a voter model where agents can have two opinions or an undecided state in between, and where we allow for repulsion of opinions and for doubt: in pairwise discussions, undecided agents can be not only convinced, but also repelled from the opinion expressed by another agent, and decided agents may return to the undecided state. As a result, we observe that, if an agent is repelled instead of being convinced in at least one out of four interactions, as in controversial debates, the frequencies of both opinions equalize. This voter model attractor reproduces the phenomenology of repeated Brexit poll data well and provides a mechanism solely based on local interactions between agents that may explain stalemate polarization in controversial opinion formation.

Determination of optimal arrangements of $N$ particles on a sphere is a well-known problem in physics. A famous example of such is the Thomson problem of finding equilibrium configurations of electrical charges on a sphere. More recently, however, similar problems involving other potentials and nonspherical domains have arisen in biophysical systems. Many optimal configurations have previously been computed, especially for the Thomson problem; however, few results exist for potentials that correspond to more applied problems. Here we numerically compute optimal configurations corresponding to the narrow escape and narrow capture problems in biophysics. We provide comprehensive tables of global energy minima for $N\le 120$ and local energy minima for $N\le 65$, and we exclude all saddle points. Local minima up to $N=120$ are available online.

In nature and experiments, a large variety of rupture speeds and front modes along frictional interfaces are observed. Here, we introduce a minimal model for the rupture of homogeneously loaded interfaces with velocity strengthening dynamic friction, containing only two dimensionless parameters; $\overline{\tau }$, which governs the prestress, and $\overline{\alpha }$, which is set by the interfacial viscosity. This model contains a large variety of front types, including slow fronts, sub-Rayleigh fronts, supershear fronts, slip pulses, cracks, arresting fronts, and fronts that alternate between arresting and propagating phases. Our results indicate that this wide range of front types is an inherent property of frictional systems with velocity strengthening branches.

We study theoretically the influence of viscoelasticity on the steady cone-jet mode of electrospray for small stress relaxation times. For this purpose, we numerically integrate the leaky-dielectric model together with the Oldroyd-B constitutive relationship and calculate both the base flow and linear eigenmodes characterizing its stability as a function of the governing parameters. We describe the effect of the polymeric stresses on both the cone-jet mode and the minimum flow rate stability limit. There are considerable differences between the Newtonian and viscoelastic electrospray realizations even for relatively small stress relaxation times due to the intense extensional deformation suffered by the fluid particles in the cone-jet transition region The axial polymeric stress shrinks the liquid meniscus and stabilizes it by pushing the fluid particle in the cone-to-jet transition region.

We consider the dynamics of a one-dimensional system evolving according to a deterministic drift and randomly forced by two types of jump processes, one representing an external, uncontrolled forcing and the other one a control that instantaneously resets the system according to specified protocols (either deterministic or stochastic). We develop a general theory, which includes a different formulation of the master equation using antecedent and posterior jump states, and obtain an analytical solution for steady state. The relevance of the theory is illustrated with reference to stochastic irrigation to assess crop-failure risk, a problem of interest for environmental geophysics.

We investigate the phase diagram and critical behavior of three-dimensional multicomponent Abelian-Higgs models, in which an $N$-component complex field $z_{\mathit{x}}^a$ of unit length and charge is coupled to compact quantum electrodynamics in the usual Wilson lattice formulation. We determine the phase diagram and study the nature of the transition line for $N=2$ and $N=4$. Two phases are identified, specified by the behavior of the gauge-invariant local composite operator $Q_{\mathit{x}}^{ab}={\overline{z}}_{\mathit{x}}^a{z}_{\mathit{x}}^b-{\delta }^{ab}/N$, which plays the role of order parameter. In one phase, we have $\langle Q_{\mathit{x}}^{ab}\rangle =0$, while in the other $Q_{\mathit{x}}^{ab}$ condenses. Gauge correlations are never critical: gauge excitations are massive for any finite coupling. The two phases are separated by a transition line. Our numerical data are consistent with the simple scenario in which the nature of the transition is independent of the gauge coupling. Therefore, for any finite positive value of the gauge coupling, we predict a continuous transition in the Heisenberg universality class for $N=2$ and a first-order transition for $N=4$. However, notable crossover phenomena emerge for large gauge couplings, when gauge fluctuations are suppressed. Such crossover phenomena are related to the unstable $\mathrm{O}\left(2N\right)$ fixed point, describing the behavior of the model in the infinite gauge-coupling limit.

We present a simple extension in which a single parameter tunes the dynamics of cellular automata (CA) by consequently expanding their discrete state space into a Cantor set. Such an implementation serves as a potent platform for further investigation of several emergent phenomena, including deterministic phase transitions, pattern formation, autocatalysis, and self-organization. We first apply this approach to Conway's Game of Life and observe sudden changes in the asymptotic dynamics of the system accompanied by the emergence of complex propagators. Incorporation of the new state space with system features is used to explain the transitions and formulate the tuning parameter range where the propagators adaptively survive by investigating their autocatalytic local interactions. Similar behavior is present when the same recipe is applied to Rule 90, an outer totalistic elementary one-dimensional cellular automaton. In addition, the latter case shows that deterministic transitions between classes of CA can be achieved by tuning a single parameter continuously.