The global linear stability of a water drop on hot nonwetting surfaces is studied. The droplet is assumed to have a static shape and the surface tension gradient is neglected. First, the nonlinear steady Boussinesq equation is solved to obtain the axisymmetric toroidal base flow. Then, the linear stability analysis is conducted for different contact angles $\beta ={110}^{\circ }$ (hydrophobic) and $\beta ={160}^{\circ }$ (superhydrophobic) which correspond to the experimental study of Dash et al. [Phys. Rev. E 90, 062407 (2014)]. The droplet with $\beta ={110}^{\circ }$ is stable while the one with $\beta ={160}^{\circ }$ is unstable to the azimuthal wave number $m=1$ mode. This suggests that the experimental observation for a droplet with $\beta ={110}^{\circ }$ corresponds to the steady toroidal base flow, while for $\beta ={160}^{\circ }$, the $m=1$ instability promotes the rigid body rotation motion. A marginal stability analysis for different $\beta$ shows that a $3\text{−}\mu \mathrm{L}$ water droplet is unstable to the $m=1$ mode when the contact angle $\beta$ is larger than ${130}^{\circ }$. A marginal stability analysis for different volumes is also conducted for the two contact angles $\beta ={110}^{\circ }$ and ${160}^{\circ }$. The droplet with $\beta ={110}^{\circ }$ becomes unstable when the volume is larger than $3.5\mu \mathrm{L}$ while the one with $\beta ={160}^{\circ }$ is always unstable to $m=1$ mode for the considered volume range ($2–5\mu \mathrm{L}$). In contrast to classical buoyancy driven (Rayleigh-Bénard) problems whose instability is controlled independently by the geometrical aspect ratio and the Rayleigh number, in this problem, these parameters are all linked together with the volume and contact angles.

Gyrokinetic simulations of turbulence are fundamental to understanding and predicting particle and energy loss in magnetic fusion devices. Previous works have used model collision operators with approximate field-particle terms of unknown accuracy and/or have neglected collisional finite Larmor radius effects. This work moves beyond models to demonstrate important corrections using a gyrokinetic Fokker-Planck collision operator with the exact field-particle terms, in realistic simulations of turbulence in magnetically confined fusion plasmas. The exact operator shows significant corrections for temperature-gradient-driven trapped electron mode turbulence and zonal flow damping, and for microtearing modes in a Joint European Torus pedestal under ITER-like wall conditions. Analysis of the corrections using parameter scans motivates an accurate model which closely reproduces the exact results while reducing computational demands.

The effects of bound electron screening in warm and hot dense matter are investigated analytically and a theoretical description of screened short-range repulsion is given meanwhile. An empirical ion-ion potential including the classic charge screening and chemical bond attraction at various temperatures and densities is proposed. By solving hypernetted chain equations and comparing the obtained radial distribution function (RDF) with ab initio simulations, the proposed ion-ion potential is found to be promising over a wide range of temperatures and densities for warm dense aluminum and iron. The elastic scattering amplitude and the x-ray absorption near the edge structure of warm dense aluminum calculated from the obtained RDF are in good agreement with experiment results.

Evaluating expectations on an Ising model (or Boltzmann machine) is essential for various applications, including statistical machine learning. However, in general, the evaluation is computationally difficult because it involves intractable multiple summations or integrations; therefore, it requires approximation. Monte Carlo integration (MCI) is a well-known approximation method; a more effective MCI-like approximation method was proposed recently, called spatial Monte Carlo integration (SMCI). However, the estimations obtained using SMCI (and MCI) exhibit a low accuracy in Ising models under a low temperature owing to degradation of the sampling quality. Annealed importance sampling (AIS) is a type of importance sampling based on Markov chain Monte Carlo methods that can suppress performance degradation in low-temperature regions with the force of importance weights. In this study, a method is proposed to evaluate the expectations on Ising models combining AIS and SMCI. The proposed method performs efficiently in both high- and low-temperature regions, which is demonstrated theoretically and numerically.

While averages and typical fluctuations often play a major role in understanding the behavior of a nonequilibrium system, this nonetheless is not always true. Rare events and large fluctuations are also pivotal when a thorough analysis of the system is being done. In this context, the statistics of extreme fluctuations in contrast to the average plays an important role, as has been discussed in fields ranging from statistical and mathematical physics to climate, finance, and ecology. Herein, we study extreme value statistics (EVS) of stochastic resetting systems, which have recently gained significant interest due to its ubiquitous and enriching applications in physics, chemistry, queuing theory, search processes, and computer science. We present a detailed analysis for the finite and large time statistics of extremals (maximum and arg-maximum, i.e., the time when the maximum is reached) of the spatial displacement in such system. In particular, we derive an exact renewal formula that relates the joint distribution of maximum and arg-maximum of the reset process to the statistical measures of the underlying process. Benchmarking our results for the maximum of a reset trajectory that pertain to the Gumbel class for large sample size, we show that the arg-maximum density attains a uniform distribution independent of the underlying process at a large observation time. This emerges as a manifestation of the renewal property of the resetting mechanism. The results are augmented with a wide spectrum of Markov and non-Markov stochastic processes under resetting, namely, simple diffusion, diffusion with drift, Ornstein-Uhlenbeck process, and random acceleration process in one dimension. Rigorous results are presented for the first two setups, while the latter two are supported with heuristic and numerical analysis.

In this paper we investigate the existence of Anderson localization induced by one specific component of a binary Bose-Einstein condensate (BEC). We use a mean-field approach, in which each type of particle of the BEC is considered as a specific field, and we consider that only one kind of particle is subject to a quasiperiodic potential, which induces a localization in the partner field. We assume the system is under a Rabi coupling, i.e., a linear coupling mixing the two-field component, and we investigate the conditions associated with the parameter values of the system for observing the localization. Numerical simulations are performed, confirming the existence of Anderson localization in the partner field.

We study a quantum-dots (QDs) dispersed bent-core nematic liquid crystalline system in planar geometry and present experimental measurements of the birefringence ($\mathrm{\Delta }n$), order parameter ($S$), dielectric dispersion, absorption spectra, and optical textures with attention to variations with temperature. A bent-core liquid crystal (LC) $14\text{−}2\mathrm{M}\text{−}{\mathrm{CH}}_3$ is used as the host material and CdSe/ZnS core-shell type QDs are used as the dopant. The nematic ($N$) phase of the pristine (undoped) LC $14\text{−}2\mathrm{M}\text{−}{\mathrm{CH}}_3$ contains cybotactic clusters, which are retained by its QDs incorporated LC nanocomposite. Our experimental findings support: (i) reduced orientational order parameter of the QDs dispersed LC system compared to its pristine counterpart at fixed temperatures, (ii) reduced cybotactic cluster sizes due to the incorporation of QDs, and (iii) increased activation energies related to reduced cluster sizes. We complement the experiments with a novel Landau–de Gennes-type free energy for a doped bent-core LC system that qualitatively captures the doping-induced reduced order parameter and its dependence on the properties of the QDs and its variation with temperature.

Clustering of plumes in turbulent Rayleigh-Bénard convection has been numerically observed in low-Prandtl-number fluids. In this framework, turbulent plumes undergo a phase-separation process leading to large-scale clusters and circulations, sometimes called plume superstructures and reminiscent of solar granulation and supergranulation. On the other hand, the possible presence of large-scale plume aggregates has not been explored in the case of large values of the Prandtl number, Pr, relevant to geological settings such as convection in planetary interiors. Here we address this problem and numerically explore the behavior of plume ensembles in turbulent convection at very high Prandtl number values, including the case $\text{Pr}\to \infty$. The results indicate the presence of plume clustering, albeit at smaller scale, also for large Pr number fluids, suggesting interesting consequences for mantle convection processes.

The combined influence of rarefaction and compressibility on classical Kelvin-Helmholtz instability is investigated with numerical simulations employing the unified gas kinetic scheme. Five different regimes in the Reynolds-Mach-Knudsen number parameter space are identified. The flow features in various Mach and Knudsen number regimes are examined. Stabilizing action of compressibility leads to suppression of perturbation kinetic energy and vorticity and/or momentum thickness. The suppression due to rarefaction exhibits a different behavior. At high enough Knudsen numbers, even as the perturbation kinetic energy is suppressed, the vorticity and/or momentum thickness grows. The flow physics underlying the contrasting mechanisms of compressibility and rarefaction is highlighted.

Using a modified version of the pseudoatom molecular-dynamics approach, the silicon and oxygen equations of state were generated and then employed to construct the equation of state of silicon dioxide. The results are supported by the close agreement with ab initio simulations of the silicon pressure and experimental shock Hugoniot of silicon dioxide. Ion thermal contributions to thermodynamic functions provided by the PAMD simulations are compared to their counterparts obtained with the one-component plasma and charged-hard-sphere approximations.

We report on the increase in the accelerated electron number and energy using compound parabolic concentrator (CPC) targets from a short-pulse ($\sim 150$ fs), high-intensity ($>{10}^{18}$ W/${\mathrm{cm}}^2$), and high-contrast ($\sim {10}^8$) laser-solid interaction. We report on experimental measurements using CPC targets where the hot-electron temperature is enhanced up to $\sim 9$ times when compared to planar targets. The temperature measured from the CPC target is $〈T_e〉=4.4\pm 1.3$ MeV. Using hydrodynamic and particle in cell simulations, we identify the primary source of this temperature enhancement is the intensity increase caused by the CPC geometry that focuses the laser, reducing the focal spot and therefore increasing the intensity of the laser-solid interaction, which is also consistent with analytic expectations for the geometrical focusing.

In existing linear response theories for adiabatically driven cyclic heat engines, Onsager symmetry is identified only phenomenologically, and a relation between global and local Onsager coefficients, defined over one cycle and at any instant of a cycle, respectively, is not derived. To address this limitation, we develop a linear response theory for the speed of adiabatically changing parameters and temperature differences in generic Gaussian heat engines obeying Fokker-Planck dynamics. We establish a hierarchical relationship between the global linear response relations, defined over one cycle of the heat engines, and the local ones, defined at any instant of the cycle. This yields a detailed expression for the global Onsager coefficients in terms of the local Onsager coefficients. Moreover, we derive an efficiency bound, which is tighter than the Carnot bound, for adiabatically driven linear irreversible heat engines based on the detailed global Onsager coefficients. Finally, we demonstrate the application of the theory using the simplest stochastic Brownian heat engine model.

Size dependence of energy transport and the effects of reduced dimensionality on transport coefficients are of key importance for understanding nonequilibrium properties of matter on the nanoscale. Here, we perform nonequilibrium and equilibrium simulations of heat conduction in a three-dimensional (3D) fluid with the multiparticle collision dynamics, interacting with two thermal walls. We find that the bulk 3D momentum-conserving fluid has a finite nondiverging thermal conductivity. However, for large aspect ratios of the simulation box, a crossover from 3D to one-dimensional (1D) abnormal behavior of the thermal conductivity occurs. In this case, we demonstrate a transition from normal to abnormal transport by a suitable decomposition of the energy current. These results not only provide a direct verification of Fourier's law, but also further confirm the validity of existing theories for 3D fluids. Moreover, they indicate that abnormal heat transport persists also for almost 1D fluids over a large range of sizes.

The conventional (Zwanzig-Mountain) expressions for instantaneous elastic moduli of simple fluids predict their divergence as the limit of hard-sphere (HS) interaction is approached. However, elastic moduli of a true HS fluid are finite. Here we demonstrate that this paradox reveals the soft-to-hard-sphere crossover in fluid excitations and thermodynamics. With extensive in silico study of fluids with repulsive power-law interactions ($\propto r^{-n}$), we locate the crossover at $n\simeq 10$–20 and develop a simple and accurate model for the HS regime. The results open prospects to deal with the elasticity and related phenomena in various systems, from simple fluids to melts and glasses.

We present an in-depth study of the universal correlations of scattering-matrix entries required in the framework of nonstationary many-body scattering of noninteracting indistinguishable particles where the incoming states are localized wave packets. Contrary to the stationary case, the emergence of universal signatures of chaotic dynamics in dynamical observables manifests itself in the emergence of universal correlations of the scattering matrix at different energies. We use a semiclassical theory based on interfering paths, numerical wave function based simulations, and numerical averaging over random-matrix ensembles to calculate such correlations and compare with experimental measurements in microwave graphs, finding excellent agreement. Our calculations show that the universality of the correlators survives the extreme limit of few open channels relevant for electron quantum optics, albeit at the price of dealing with large-cancellation effects requiring the computation of a large class of semiclassical diagrams.

Models of complex networks often incorporate node-intrinsic properties abstracted as hidden variables. The probability of connections in the network is then a function of these variables. Real-world networks evolve over time and many exhibit dynamics of node characteristics as well as of linking structure. Here we introduce and study natural temporal extensions of static hidden-variable network models with stochastic dynamics of hidden variables and links. The dynamics is controlled by two parameters: one that tunes the rate of change of hidden variables and another that tunes the rate at which node pairs reevaluate their connections given the current values of hidden variables. Snapshots of networks in the dynamic models are equivalent to networks generated by the static models only if the link reevaluation rate is sufficiently larger than the rate of hidden-variable dynamics or if an additional mechanism is added whereby links actively respond to changes in hidden variables. Otherwise, links are out of equilibrium with respect to hidden variables and network snapshots exhibit structural deviations from the static models. We examine the level of structural persistence in the considered models and quantify deviations from staticlike behavior. We explore temporal versions of popular static models with community structure, latent geometry, and degree heterogeneity. While we do not attempt to directly model real networks, we comment on interesting qualitative resemblances to real systems. In particular, we speculate that links in some real networks are out of equilibrium with respect to hidden variables, partially explaining the presence of long-ranged links in geometrically embedded systems and intergroup connectivity in modular systems. We also discuss possible extensions, generalizations, and applications of the introduced class of dynamic network models.

An experimental study of the magnetic field distribution in gas-puff $Z$ pinches with and without a preembedded axial magnetic field ($B_{z0}$) is presented. Spatially resolved, time-gated spectroscopic measurements were made at the Weizmann Institute of Science on a 300 kA, 1.6 μs rise time pulsed-power driver. The radial distribution of the azimuthal magnetic field, $B_{\theta }$, during the implosion, with and without a preembedded axial magnetic field of $B_{z0}=0.26\mathrm{T}$, was measured using Zeeman polarization spectroscopy. The spectroscopic measurements of $B_{\theta }$ were consistent with the corresponding values of $B_{\theta }$ inferred from current measurements made with a B-dot probe. One-dimensional magnetohydrodynamic simulations, performed with the code trac-ii, showed agreement with the experimentally measured implosion trajectory, and qualitatively reproduced the experimentally measured radial $B_{\theta }$ profiles during the implosion when $B_{z0}=0.26\mathrm{T}$ was applied. Simulation results of the radial profile of $B_{\theta }$ without a preembedded axial magnetic field did not qualitatively match experimental results due to magneto-Rayleigh-Taylor (MRT) instabilities. Our analysis emphasizes the importance of MRT instability mitigation when studying the magnetic field and current distributions in $Z$ pinches. Discrepancies of the simulation results with experiment are discussed.

Microscopic organisms, such as bacteria, have the ability of colonizing surfaces and developing biofilms that can determine diseases and infections. Most bacteria secrete a significant amount of extracellular polymer substances that are relevant for biofilm stabilization and growth. In this work, we apply computer simulation and perform experiments to investigate the impact of polymer size and concentration on early biofilm formation and growth. We observe as bacterial cells formed loose, disorganized clusters whenever the effect of diffusion exceeded that of cell growth and division. Addition of model polymeric molecules induced particle self-assembly and aggregation to form compact clusters in a polymer size- and concentration-dependent fashion. We also find that large polymer size or concentration lead to the development of intriguing stripe-like and dendritic colonies. The results obtained by Brownian dynamic simulation closely resemble the morphologies that we experimentally observe in biofilms of a Pseudomonas Putida strain with added polymers. The analysis of the Brownian dynamic simulation results suggests the existence of a threshold polymer concentration that distinguishes between two growth regimes. Below this threshold, the main force driving polymer-induced compaction is the hindrance of bacterial cell diffusion, while collective effects play a minor role. Above this threshold, especially for large polymers, polymer-induced compaction is a collective phenomenon driven by depletion forces. Well above this concentration threshold, severely limited diffusion drives the formation of filaments and dendritic colonies.

We present a minimal one-dimensional continuum model for the transition from cracklike to pulselike propagation of frictional rupture. In its nondimensional form, the model depends on only two free parameters: the nondimensional prestress and an elasticity ratio that accounts for the finite height of the system. The model predicts stable slip pulse solutions for slip boundary conditions, and unstable slip pulse solutions for stress boundary conditions. The results demonstrate that a mechanism based solely on elastic relaxation and redistribution of initial prestress can cause pulselike rupture, without any particular rate or slip dependences of dynamic friction. This means that pulselike propagation along frictional interfaces is likely a generic feature that can occur in systems of finite thickness over a wide range of friction constitutive laws.