In a granular gas experiment of magnetized particles confined in a thin layer, the rate of dissipative collisions is tuned by adjusting the amplitude of an external magnetic field. The velocity statistics are analyzed using the dynamic and static structure factors of transverse velocity modes. Using the fluctuating hydrodynamics theory, we measure the deviation from kinetic energy equipartition in this out-of-equilibrium system as a function of the dissipative collision rate. When the collision rate is decreased, the distance to equipartition becomes smaller, meaning that the dynamical properties of this granular gas approach by analogy those of a molecular gas in thermal equilibrium.

We characterize the phase space of all helical Miura origami. These structures are obtained by taking a partially folded Miura parallelogram as the unit cell, applying a generic helical or rod group to the cell, and characterizing all the parameters that lead to a globally compatible origami structure. When such compatibility is achieved, the result is cylindrical-type origami that can be manufactured from a suitably designed flat tessellation and “rolled up” by a rigidly foldable motion into a cylinder. We find that the closed helical Miura origami are generically rigid to deformations that preserve cylindrical symmetry but are multistable. We are inspired by the ways atomic structures deform to develop two broad strategies for reconfigurability: motion by slip, which involves relaxing the closure condition, and motion by phase transformation, which exploits multistability. Taken together, these results provide a comprehensive description of the phase space of cylindrical origami, as well as quantitative design guidance for their use as actuators or metamaterials that exploit twist, axial extension, radial expansion, and symmetry.

We show that a commonly accepted transparency threshold for a thin foil in a strong circularly polarized normally incident laser pulse needs a refinement. We present an analytical model that correctly accounts for laser absorption. The refined threshold is determined not solely by the laser amplitude, but by other parameters that are equally or even more important. Our predictions are in perfect agreement with particle-in-cell simulations. The refined criterion is crucial for configuring laser plasma experiments in the high-field domain. In addition, an opaque foil steepens the pulse front, which can be important for numerous applications.

The Minkowski functionals, as the full set of additive morphological measures in three dimensions (3D) consisting of volume, surface area, mean curvature, and total curvature, can be calculated directly by evaluating the local contributions of vertices of a discrete structure. They are sensitive measures of microstructure, and for microstructures generated by a Boolean process, relate to their physical properties. In this work we introduce fast numerical techniques based on the additivity of the Minkowski functionals to derive fields of regional Minkowski measures over large regional support for large 3D data sets as generated, e.g., from x-ray tomography techniques. We demonstrate the application of these 3D feature fields to microstructure classification for a set of heterogeneous microstructures using a multivariate Gaussian mixture model and a thin-bedded sandstone. It is shown that for the case of a spatially heterogeneous Boolean process the internal boundaries of the generating process are recovered with high accuracy, while for the thin-bedded sandstone, compact partitions with clear layering are extracted.

Higher-order lattice Boltzmann (LB) pseudopotential models have great potential for solving complex fluid dynamics in various areas of modern science. The discreteness of the lattice discretization makes these models an attractive choice due to their flexibility, capacity to capture hydrodynamic details, and inherent adaptability to parallel computations. Despite those advantages, the discreteness makes high-order LB models difficult to apply due to the larger lattice structure, for which basic fundamental properties, namely diffusion coefficient and contact angle, remain unknown. This work addresses this by providing general continuum solutions for those two basic properties and demonstrating these solutions to compare favorably against known theory. Various high-order LB models are shown to reproduce the sinusoidal decay of a binary miscible mixture accurately and consistently. Furthermore, these models are shown to reproduce neutral, hydrophobic, and hydrophilic contact angles. Discrete differences are shown to exist, which are captured at the discrete level and confirmed through droplet shape analysis. This work provides practical tools that allow for high-order LB pseudopotential models to be used to simulate multicomponent flows.

Although the nonequilibrium-relaxation (NER) method has been widely used in Monte Carlo studies on phase transitions in classical spin systems, such studies have been quite limited in quantum phase transitions. The reason is that the relaxation process based on cluster-update quantum Monte Carlo (QMC) algorithms, which are now standards in Monte Carlo studies on quantum systems, has been considered “too fast” for such analyses. Recently, the present authors revealed that the NER process in classical spin systems based on cluster-update algorithms is characterized by stretched-exponential critical relaxation, rather than conventional power-law relaxation in local-update algorithms. In the present article, we show that this is also the case in quantum phase transitions analyzed with the cluster-update QMC. As the simplest example of isotropic quantum spin models that exhibit quantum phase transitions, we investigate the Néel-dimer quantum phase transition in the two-dimensional $S=1/2$ columnar-dimerized antiferromagnetic Heisenberg model with the continuous-time loop algorithm, and we confirm stretched-exponential critical relaxation consistent with the three-dimensional classical Heisenberg model in the Swendsen-Wang algorithm.

We show that a mesoscopic coarse-grained dynamics model which incorporates the transient potential can be formally derived from an underlying microscopic dynamics model. As a microscopic dynamics model, we employ the overdamped Langevin equation. By utilizing the path probability and the Onsager-Machlup type action, we calculate the path probability for the coarse-grained mesoscopic degrees of freedom. The action for the mesoscopic degrees of freedom can be simplified by incorporating the transient potential. Then the dynamic equation for the mesoscopic degrees of freedom can be simply described by the Langevin equation with the transient potential (LETP). As a simple and analytically tractable approximation, we introduce additional degrees of freedom which express the state of the transient potential. Then we approximately express the dynamics of the system as the the combination of the LETP and the dynamics model for the transient potential. The resulting dynamics model has the same dynamical structure as the responsive particle dynamics type models [W. J. Briels, Soft Matter 5, 4401 (2009)] and the multichain slip-spring type models [T. Uneyama and Y. Masubuchi, J. Chem. Phys. 137, 154902 (2012)]. As a demonstration, we apply our coarse-graining method with the LETP to a single particle dynamics in a supercooled liquid, and compare the results of the LETP with the molecular dynamics simulations and other coarse-graining models.

Maximum likelihood estimation (MLE) is fundamental to system inference for stochastic systems. In some generality, MLE will converge to the correct model in the infinite data limit. In the context of physical approaches to system inference, such as Boltzmann machines, MLE requires the arduous computation of partition functions summing over all configurations, both observed and unobserved. We present a conceptually transparent data-driven inference computation based on a reweighting of observed configuration frequencies that allows us to recast the inference problem as a simpler calculation. Modeling our approach on the high-temperature limit of statistical physics, we reweight the frequencies of observed configurations by multiplying with reciprocals of Boltzmann weights and update the Boltzmann weights iteratively to make these products close to the high-temperature limit of the Boltzmann weights. This converts the required partition function computation in the reweighted MLE to a tractable leading-order high-temperature term. We show that this is a convex optimization at each step. Then, for systems with a large number of degrees of freedom where other approaches are intractable, we demonstrate that this data-driven algorithm gives accurate inference with both synthetic data and two real-world examples.

The focusing nonlinear Schrödinger (NLS) equation is the simplest universal model describing the modulation instability of quasimonochromatic waves in weakly nonlinear media, the main physical mechanism for the appearance of anomalous (rogue) waves (AWs) in nature. In this paper, concentrating on the simplest case of a single unstable mode, we study the special Cauchy problem for the NLS equation perturbed by a linear loss or gain term, corresponding to periodic initial perturbations of the unstable background solution of the NLS. Using the finite gap method and the theory of perturbations of soliton partial differential equations, we construct the proper analytic model describing quantitatively how the solution evolves after a suitable transient into slowly varying lower dimensional patterns (attractors) on the $(x,t)$ plane, characterized by $\mathrm{\Delta }X=L/2$ in the case of loss and by $\mathrm{\Delta }X=0$ in the case of gain, where $\mathrm{\Delta }X$ is the $x$ shift of the position of the AW during the recurrence, and $L$ is the period. This process is described, to leading order, in terms of elementary functions of the initial data. Since dissipation can hardly be avoided in all natural phenomena involving AWs, and since a small dissipation induces $O\left(1\right)$ effects on the periodic AW dynamics, generating the slowly varying loss or gain attractors analytically described in this paper, we expect that these attractors together with their generalizations corresponding to more unstable modes will play a basic role in the theory of periodic AWs in nature.

The process of range expansion (colonization) is one of the basic types of biological dynamics, whereby a species grows and spreads outwards, occupying new territories. Spatial modeling of this process is naturally implemented as a stochastic cellular automaton, with individuals occupying nodes on a rectangular grid, births and deaths occurring probabilistically, and individuals only reproducing onto unoccupied neighboring spots. In this paper we derive several approximations that allow prediction of the expected range expansion dynamics, based on the reproduction and death rates. We derive several approximations, where the cellular automaton is described by a system of ordinary differential equations that preserves correlations among neighboring spots (up to a distance). This methodology allows us to develop accurate approximations of the population size and the expected spatial shape, at a fraction of the computational time required to simulate the original stochastic system. In addition, we provide simple formulas for the steady-state population densities for von Neumann and Moore neighborhoods. Finally, we derive concise approximations for the speed of range expansion in terms of the reproduction and death rates, for both types of neighborhoods. The methodology is generalizable to more complex scenarios, such as different interaction ranges and multiple-species systems.

We were motivated to perform this research by the investigation of Brownian motors in excited granular materials converting the chaotic motion of granules into the oriented motion of motors. We conducted experimental studies to explore the horizontal motion of granules in vertically vibrated annular granular systems, including mixed and pure granular systems with an asymmetrical periodic structure on the bottom. The variations of the horizontal granular flow caused by the height, vibrating parameters, and mixing ratio were described in detail. Our results revealed considerable changes in the horizontal flow of different granular systems. Most importantly, resonance was induced in the horizontal granular flow by the vertical vibration; that is, the horizontal flow reached its maximum at specific vibrating parameters. A collisional model of rigid objects was constructed to probe the flowing resonances in these granular systems and provided a qualitative agreement with the experimental results obtained. We conclude that when a flowing resonance occurs, the granular system oscillates horizontally with a natural frequency under periodic external excitation. The frequency matching between the external excitation and the horizontal oscillation is responsible for the flowing resonance. Our results could improve the current understanding of the dynamic properties of granular systems under external excitation.

We show that the Wang-Landau algorithm can be formulated as a stochastic gradient descent algorithm minimizing a smooth and convex objective function, of which the gradient is estimated using Markov chain Monte Carlo iterations. The optimization formulation provides us another way to establish the convergence rate of the Wang-Landau algorithm, by exploiting the fact that almost surely the density estimates (on the logarithmic scale) remain in a compact set, upon which the objective function is strongly convex. The optimization viewpoint motivates us to improve the efficiency of the Wang-Landau algorithm using popular tools including the momentum method and the adaptive learning rate method. We demonstrate the accelerated Wang-Landau algorithm on a two-dimensional Ising model and a two-dimensional ten-state Potts model.

The authors of the paper “Shallow-water soliton dynamics beyond the Korteweg—de Vries equation” [1] write that they derived a new nonlinear equation describing shallow water gravity waves for an uneven bottom in the form of the higher (fifth)-order Korteweg—de Vries equation for surface elevation. The equation has been obtained by applying a perturbation method [2] for specific relations between the orders of the three small parameters of the problem $\alpha =O\left(\beta \right)$ and $\delta =O\left(\beta \right)$ up to the second order in $\beta$. In this comment, it is shown that the derivation presented in [1] is inconsistent because of an oversight concerning the orders of terms in equations of the Boussinesq system. Therefore the results, in particular, the new evolution equation and the dynamics that it describes, bear no relation to the problem under consideration. A consistent derivation is presented, and also results of applying the perturbation procedure with some other orderings between the small parameters are given to provide a broader view of the problem. Several new nonlinear evolution equations governing small amplitude shallow water waves for an uneven bottom have been derived.

We agree with the objection raised by Burde that the wave equation in our previous paper [Phys. Rev. E 90, 012907 (2014)] was not derived in a consistent way. However, our paper contains an important result on the existence of soliton solutions to the extended Korteweg–de Vries equation.

We apply the homotopy analysis method to the motion of noninteracting active Brownian particles (ABPs) under a general situation such as in the presence of external fields, external torques, or even moving on non-Euclidean geometries. Within this framework, a general expression as a series solution in time for the probability density function (PDF) satisfying the Fokker-Planck (FP) equation is elucidated. Using the latter PDF, their respective mean values (first and second moments) are also found in general. Applications of the present technique are offered by solving classic ABP situations, namely free noninteracting ABPs, ABPs under a Poiseuille flow, and even ABPs confined to move on any Riemannian manifold. To improve the convergence of the obtained series solution for each situation, Padé approximants are incorporated. It is worth mentioning that the offered methodology may exactly be applied to other fields such as chemistry, biology, or econophysics where a FP equation governs the system.

Phase transitions, compensation phenomenon, and magnetization of a ferroferrimagnetic ternary alloy ${AB}_{\rho }{C}_{1-\rho }$ composed of three different kinds of magnetic ions $A$, $B$, and $C$ with the spin magnitudes 1/2, 1, and 3/2 are examined within the framework of a mixed-spin Ising model on a honeycomb lattice with a selective annealed site disorder on one of its two sublattices. It is supposed that the first sublattice of a bipartite honeycomb lattice is formed by the spin-1/2 magnetic ions, while the sites of the second sublattice are randomly occupied either by the spin-1 magnetic ions with a probability $\rho$ or the spin-3/2 magnetic ions with a probability $1-\rho$, both being subject to a uniaxial single-ion anisotropy. The model under investigation can be exactly mapped into an effective spin-1/2 Ising model on a triangular lattice through the generalized star-triangle transformation. For a specific concentration of the spin-1 (spin-3/2) magnetic ions, it is shown that the ferroferrimagnetic version of the studied model may display a compensation temperature at which the total magnetization vanishes below a critical temperature. The critical temperature strikingly may also become independent of the concentration of the randomly mixed spin-1 and spin-3/2 magnetic ions for a specific value of a uniaxial single-ion anisotropy. The spontaneous magnetic order may be notably restored at finite temperatures through the order-by-disorder mechanism above a disordered ground state, which results in an anomalous temperature dependence of the total magnetization with double reentrant phase transitions.

In the framework of a nonassociative geometry, we introduce an effective model that extends the statistical treatment of complex networks with hidden geometry. The small-world property of the network is controlled by nonlocal curvature in our model. We use this approach to study the Internet as a complex network embedded in a hyperbolic space. The model yields a remarkable agreement with available empirical data and explains features of Internet connectance data that other models cannot. Our approach offers a new avenue for the study of a wide class of complex networks, such as air transport, social networks, biological networks, and so on.

Relativistic electron temperatures were measured from kilojoule, subrelativistic laser-plasma interactions. Experiments show an order of magnitude higher temperatures than expected from a ponderomotive scaling, where temperatures of up to 2.2 MeV were generated using an intensity of $1\times {10}^{18}\mathrm{W}/{\mathrm{cm}}^2$. Two-dimensional particle-in-cell simulations suggest that electrons gain superponderomotive energies by stochastic acceleration as they sample a large area of rapidly changing laser phase. We demonstrate that such high temperatures are possible from subrelativistic intensities by using lasers with long pulse durations and large spatial scales.

We numerically estimate the leading asymptotic behavior of the length $L_n$ of the longest increasing subsequence of random walks with step increments following Student's $t$-distribution with parameters in the range $1/2\le \nu \le 5$. We find that the expected value $\mathbb{E}\left(L_n\right)\sim n^{\theta }lnn$, with $\theta$ decreasing from $\theta (\nu =1/2)\approx 0.70$ to $\theta (\nu \ge 5/2)\approx 0.50$. For random walks with a distribution of step increments of finite variance ($\nu >2$), this confirms previous observation of $\mathbb{E}\left(L_n\right)\sim \sqrt{n}lnn$ to leading order. We note that this asymptotic behavior (including the subleading term) resembles that of the largest part of random integer partitions under the uniform measure and that, curiously, both random variables seem to follow Gumbel statistics. We also provide more refined estimates for the asymptotic behavior of $\mathbb{E}\left(L_n\right)$ for random walks with step increments of finite variance.