A partially miscible binary liquid mixture, composed of $A$ and $B$ particles, is considered theoretically under conditions for which a stable $A$-rich liquid phase is in thermal equilibrium with the vapor phase. The $B$-rich liquid is metastable. The liquids and the thermodynamic conditions are chosen such that the interface between the $A$-rich liquid and the vapor contains an intervening wetting film of the $B$-rich phase. In order to obtain information about the large-scale fluid structure around a colloidal particle, which is trapped at such a composite liquid-vapor interface, three related and linked wetting phenomena at planar liquid-vapor, wall-liquid, and wall-vapor interfaces are studied analytically, using classical density functional theory in conjunction with the sharp-kink approximation for the number density profiles of the $A$ and $B$ particles. If in accordance with the so-called mixing rule the strength of the $A\text{−}B$ interaction is given by the geometric mean of the strengths of the $A\text{−}A$ and the $B\text{−}B$ interactions, and similarly the ratio between the wall-$A$ and the wall-$B$ interaction, the scenario, in which the colloid is enclosed by a film of the $B$-rich liquid, can be excluded. Up to six distinct wetting scenarios are possible, if the above mixing rules for the fluid-wall and for the fluid-fluid interactions are relaxed. The way the space of system parameters is divided into domains corresponding to the six scenarios, and which of the domains actually appear, depends on the signs of the deviations from the mixing rule prescriptions. Relevant domains, corresponding, e.g., to the scenario in which the colloid is enclosed by a film of the $B$-rich liquid, emerge, if the ratio between the strengths of the wall-$A$ and the wall-$B$ interactions is reduced as compared to the mixing rule prescription, or if the strength of the $A\text{−}B$ interaction is increased to values above the one from the mixing rule prescription. The range, within which the contact angle may vary inside the various domains, is also studied.

In this paper, an improved thermal multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is proposed for simulating liquid-vapor phase change. A temperature equation is first derived for liquid-vapor phase change, where the latent heat of vaporization is decoupled with the equation of state. Therefore, the latent heat of vaporization can be arbitrarily specified in practice, which significantly improves the flexibility of the present LB model for liquid-vapor phase change. The Laplacian term of temperature is avoided in the proposed temperature equation and the gradient term of temperature is calculated through a local scheme. To solve the temperature equation accurately and efficiently, an improved MRT LB equation with nondiagonal relaxation matrix is developed. The implicit calculation of the temperature, caused by the source term and encountered in previous works, is avoided by approximating the source term with its value at the previous time step. As demonstrated by numerical tests, the results by the present LB model agree well with analytical results, experimental results, or the results by the finite difference method where the fourth-order Runge-Kutta method is employed to implement the discretization of time.

Dark solitons are some of the most interesting nonlinear excitations and are considered to be the one-dimensional topological analogs of vortices. However, in contrast to their two-dimensional vortex counterparts, the topological characteristics of a dark soliton are far from fully understood because the topological charge defined according to the phase jump cannot reflect its essential property. Here, similar to the complex extension used in the exploration of the partition-function zeros to depict thermodynamic states, we extend the complex coordinate space to explore the density zeros of dark solitons. Surprisingly we find that these zeros constitute some pointlike magnetic fields, each of which has a quantized magnetic flux of elementary $\pi$. The corresponding vector potential fields demonstrate the topology of the Wess-Zumino term and can depict the essential characteristics of dark solitons. Then we classify the dark solitons according to the Euler characteristic of the topological manifold of the vector potential fields. Our study not only reveals the topological features of dark solitons but can also be applied to explore and identify new dark solitons with high topological complexity.

Direct-coupling analysis is a statistical learning method for protein contact prediction based on sequence information alone. The maximum entropy principle leads to an effective inverse Potts model. Predictions on contacts are based on fitted local fields and couplings from an empirical multiple sequence alignment. Typically, the $l_2$ norm of the resulting two-body couplings is used for contact prediction. However, this procedure discards important information. In this paper we show that the usage of the full fields and coupling information improves prediction accuracy.

We present the results of experiments on the aneutronic fusion of proton-boron (pB) in a single miniature device with electrodynamic (oscillatory) plasma confinement. The device is based on a low energy $(\sim 1–2 \mathrm{J})$ nanosecond vacuum discharge with a virtual cathode, the field of which accelerates protons and boron ions to the energies required for pB synthesis $(\sim 100–300 \mathrm{keV})$ under oscillating ions' head-on collisions. The yields of $\alpha$ particles registered for different conditions of the experiment are presented and discussed in detail. The experiment was preceded by particle-in-cell modeling of main processes accompanying pB reaction within the framework of the full electromagnetic code karat. The summary yield of $\alpha$ particles of about $5\times {10}^4/4\pi$ was obtained during the pulse-periodic operation of the generator within total $4\mu \mathrm{s}$ of the high voltage applied, which is $\sim 10\alpha$ particles/ns.

There has been active development of numerical pore-network simulation of two-phase immiscible flows in porous media in recent years. These models allow for generation of capillary pressure and relative permeability curves. However, percolation models provide an efficient alternative, with reduced reliance on numerical techniques. Implementation of effective medium or critical path theory along with the percolation model allows for evaluation of the relative permeability curves. Both approximations failed to match the irreducible water saturation for water relative permeability. While the effective medium approximation poorly matches the pore network simulator, the critical path approximation is shown to match the result of the oil relative permeability. Despite the difference in end points, there is qualitative agreement between critical path approximation and the pore network simulator. Moreover, observed differences are not necessarily a drawback due to important boundary effects as discussed in the paper. Our results indicate that percolation-theory based predictions have the potential to become an efficient tool for upscaling by computing two-phase flow properties for numerous porosity subdomains.

We present a method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled synthetic video (or, more generally, for discovering and modeling predictable features in time-series data). We first train an autoencoder that maps each video frame into a low-dimensional latent space where the laws of motion are as simple as possible, by minimizing a combination of nonlinearity, acceleration, and prediction error. Differential equations describing the motion are then discovered using Pareto-optimal symbolic regression. We find that our pre-regression (“pregression”) step is able to rediscover Cartesian coordinates of unlabeled moving objects even when the video is distorted by a generalized lens. Using intuition from multidimensional knot theory, we find that the pregression step is facilitated by first adding extra latent space dimensions to avoid topological problems during training and then removing these extra dimensions via principal component analysis. An inertial frame is autodiscovered by minimizing the combined equation complexity for multiple experiments.

The model of a medium made of oscillators can describe various materials, including artificial ones made of meta-atoms. Here the transformation of an electromagnetic wave in such a medium with rapidly growing oscillator density is studied. The initial polariton is shown to be transformed not only into new polariton modes but also into natural oscillations of the existing and created oscillators. The oscillations produce zero net polarization but consume significant amount of the initial polariton energy. Although the boundary conditions at the temporal jump are sufficient to find the new polaritons, the description of the polarization oscillations requires integrating the material equations because the oscillations are uncoupled from the fields. Under some conditions, the spatial dependence of the amplitude of the oscillations can provide a snapshot of the electromagnetic field distribution at the moment of rapid density growth. Some subtle issues related to the continuity conditions at the density jump are also discussed.

We consider the problem of the absence of backscattering in the transport of Manakov solitons on a line. The concept of transparent boundary conditions is used for modeling the reflectionless propagation of Manakov vector solitons in a one-dimensional domain. Artificial boundary conditions that ensure the absence of backscattering are derived and their numerical implementation is demonstrated.

The trigger time of light-driven wrinkling is very critical for accurate active control in photo-powered machines. In this paper, the wrinkling of liquid-crystal elastomer disks caused by light-driven dynamic contraction is theoretically studied, and the critical times for appearance and disappearance of the wrinkles are numerically calculated. The light-driven prebuckling stress can be significantly adjusted by changing the contraction coefficient, while controlled within a certain limit by tuning the light intensity and illumination time. There exists a critical contraction coefficient for triggering the wrinkling of the disk, and the second-order mode of wrinkling is the most unstable mode, which is most easily induced for the illumination radius ratio 0.69. The critical times for the appearance and disappearance of wrinkling can be significantly changed by the contraction coefficient, while regulated only within a certain range by the light intensity and the illumination radius ratio. These results have potential applications for accurate active control in the fields of soft robotics, active microlens, smart windows, and tunable surface patterns.

We determine the asymptotic behavior of the entropy of full coverings of a $L\times M$ square lattice by rods of size $k\times 1$ and $1\times k$, in the limit of large $k$. We show that full coverage is possible only if at least one of $L$ and $M$ is a multiple of $k$, and that all allowed configurations can be reached from a standard configuration of all rods being parallel, using only basic flip moves that replace a $k\times k$ square of parallel horizontal rods by vertical rods, and vice versa. In the limit of large $k$, we show that the entropy per site $S_2\left(k\right)$ tends to $A{k}^{-2}lnk$, with $A=1$. We conjecture, based on a perturbative series expansion, that this large-$k$ behavior of entropy per site is superuniversal and continues to hold on all $d$-dimensional hypercubic lattices, with $d\ge 2$.

We consider a particle transport process in a one-dimensional system with a thin membrane, described by the normal diffusion equation. We consider two boundary conditions at the membrane that are linear combinations of integral operators, with time-dependent kernels, which act on the functions and their spatial derivatives defined on both membrane surfaces. We show how boundary conditions at the membrane change the temporal evolution of the first and second moments of particle position distribution (the Green's function) which is a solution to the normal diffusion equation. As these moments define the kind of diffusion, an appropriate choice of boundary conditions generates the moments characteristic for subdiffusion. The interpretation of the process is based on a particle random walk model in which the subdiffusion effect is caused by anomalously long stays of the particle in the membrane.

Spectral properties of Hermitian Toeplitz, Hankel, and Toeplitz-plus-Hankel random matrices with independent identically distributed entries are investigated. Combining numerical and analytic arguments it is demonstrated that spectral statistics of all these low-complexity random matrices is of the intermediate type, characterized by: (i) level repulsion at short distances, (ii) an exponential decrease in the nearest-neighbor distributions at long distances, (iii) a nontrivial value of the spectral compressibility, and (iv) the existence of nontrivial fractal dimensions of eigenvectors in Fourier space. Our findings show that intermediate-type statistics is more ubiquitous and universal than was considered so far and open a new direction in random matrix theory.

Establishing formal mathematical analogies between disparate physical systems can be a powerful tool, allowing for the well studied behavior of one system to be directly translated into predictions about the behavior of another that may be harder to probe. In this paper we lay the foundation for such an analogy between the macroscale electrodynamics of simple magnetic circuits and the microscale chemical kinetics of transcriptional regulation in cells. By artificially allowing the inductor coils of the former to elastically expand under the action of their Lorentz pressure, we introduce nonlinearities into the system that we interpret through the lens of our analogy as a schematic model for the impact of crosstalk on the rates of gene expression near steady state. Synthetic plasmids introduced into a cell must compete for a finite pool of metabolic and enzymatic resources against a maelstrom of crisscrossing biological processes, and our theory makes sensible predictions about how this noisy background might impact the expression profiles of synthetic constructs without explicitly modeling the kinetics of numerous interconnected regulatory interactions. We conclude the paper with a discussion of how our theory might be expanded to a broader class of plasmid circuits and how our predictions might be tested experimentally.

We propose a granular architecture as a potential impact protector and signal filter. The system consists of monodispersed granular chains decorated with side beads fixed (welded) on sidewalls. Numerical results from usual monodispersed chains and simple tapered chains are employed as reference. An appropriate material combination and an optimal radii ratio between the side and axial granules show that more than $90\%$ of the momentum amplitude of solitary pulses can be attenuated using a small and scalable system composed of five axial granules. Considering sinusoidal signals, the findings suggest that regular chains (monodispersed and tapered) are low-pass filters with cutoff frequencies as functions of the driven amplitude, restitutional losses, and tapering. The granular chain with fixed decoration filters all the input signals.

Reduction of collective dynamics of large heterogeneous populations to low-dimensional mean-field models is an important task of modern theoretical neuroscience. Such models can be derived from microscopic equations, for example with the help of Ott-Antonsen theory. An often used assumption of the Lorentzian distribution of the unit parameters makes the reduction especially efficient. However, the Lorentzian distribution is often implausible as having undefined moments, and the collective behavior of populations with other distributions needs to be studied. In the present Letter we propose a method which allows efficient reduction for an arbitrary distribution and show how it performs for the Gaussian distribution. We show that a reduced system for several macroscopic complex variables provides an accurate description of a population of thousands of neurons. Using this reduction technique we demonstrate that the population dynamics depends significantly on the form of its parameter distribution. In particular, the dynamics of populations with Lorentzian and Gaussian distributions with the same center and width differ drastically.

It is conjectured that the four classes of elementary cellular automata classified by Wolfram are related to phase transitions; however, the structure of the phase diagram is yet to be clarified. Hence, we propose two parameters that are calculated using the $s$-step transition function of elementary cellular automata. We calculate these two quantities based on a second-order approximation of the transition function. The phase diagram of these two parameters can separate the rules into four Wolfram classes. Based on this phase diagram, it is clear that the rules of class 4 are located on the phase boundary between the regions of classes 2 and 3.

To investigate the influence of geometric frustration on the properties of low-energy configurations of systems of ferromagnetic nanoislands located on the edges of the Cairo lattice, the model of interacting Ising-like magnetic dipoles is used. By the method of complete enumeration, the densities of states of the Cairo pentagonal lattices of a finite number of Ising-like point dipoles are calculated. The calculated ground and low-energy states for systems with a small number of dipoles can be used to solve the problem of searching for the ground states in a system with a relatively large number of dipoles. It is shown that the ground-state energy of the Cairo pentagonal lattices exhibits nonmonotonic behavior on one of the lattice parameters. The lattice parameters can be used to control the degree of geometric frustration. For the studied lattices of a finite number of Ising dipoles on the Cairo lattice in the ground-state configurations, a number of closed pentagons is observed, which are different from the obtained maximum closed pentagons. The magnetic order in the ground-state configurations obeys the ice rule and the quasi-ice rules.

We present experimental and theoretical results for the fluctuation properties in the incomplete spectra of quantum systems with symplectic symmetry and a chaotic dynamics in the classical limit. To obtain theoretical predictions, we extend the random-matrix theory (RMT) approach introduced in Bohigas and Pato [O. Bohigas and M. P. Pato, Phys. Rev. E 74, 036212 (2006)] for incomplete spectra of quantum systems with orthogonal symmetry. We validate these RMT predictions by randomly extracting a fraction of levels from complete sequences obtained numerically for quantum graphs and experimentally for microwave networks with symplectic symmetry and then apply them to incomplete experimental spectra to demonstrate their applicability. Independently of their symmetry class, quantum graphs exhibit nongeneric features which originate from nonuniversal contributions. Part of the associated eigenfrequencies can be identified in the level dynamics of parameter-dependent quantum graphs and extracted, thereby yielding spectra with systematically missing eigenfrequencies. We demonstrate that, even though the RMT approach relies on the assumption that levels are missing at random, it is possible to determine the fraction of missing levels and assign the appropriate symmetry class by comparison of their fluctuation properties with the RMT predictions.