An electron heating mechanism based on a resonance between the cyclotron motion of electrons and the radio frequency sheath oscillations is reported in weakly magnetized capacitively coupled plasmas at low pressure. If half of the electron cyclotron period coincides with the radio frequency period, then electrons will coherently collide with the expanding sheath and gain substantial energy, which enhances the plasma density. A relation between the magnetic field and the driving frequency is found to characterize this resonance effect and the kinetics of electrons are revealed at resonance conditions for various driving frequencies.

Intracellular transport in living cells is often spatially inhomogeneous with an accelerated effective diffusion close to the cell membrane and a ballistic motion away from the centrosome due to active transport along actin filaments and microtubules, respectively. Recently it was reported that the mean first passage time (MFPT) for transport to a specific area on the cell membrane is minimal for an optimal actin cortex width. In this paper, we ask whether this optimization in a two-compartment domain can also be achieved by passive Brownian particles. We consider a Brownian motion with different diffusion constants in the two shells and a potential barrier between the two, and we investigate the narrow escape problem by calculating the MFPT for Brownian particles to reach a small window on the external boundary. In two and three dimensions, we derive asymptotic expressions for the MFPT in the thin cortex and small escape region limits confirmed by numerical calculations of the MFPT using the finite-element method and stochastic simulations. From this analytical and numeric analysis, we finally extract the dependence of the MFPT on the ratio of diffusion constants, the potential barrier height, and the width of the outer shell. The first two are monotonous, whereas the last one may have a minimum for a sufficiently attractive cortex, for which we propose an analytical expression of the potential barrier height matching very well the numerical predictions.

We investigate experimentally as well as theoretically the dynamic magnetic phase diagram and its associated order parameter $Q$ upon the application of a non-antisymmetric magnetic field sequence composed of a fundamental harmonic component $H_0$, a constant bias field $H_b$, and a second-harmonic component $H_2$. The broken time antisymmetry introduced by the second-harmonic field component $H_2$ leads to an effective bias effect that is superimposed onto the influence of the static bias $H_b$. Despite this interference, we can demonstrate the existence of a generalized conjugate field $H^{*}$ for the dynamic order parameter $Q$, to which both the static bias field and the second-harmonic Fourier amplitude of the field sequence contribute. Hereby, we observed that especially the conventional paramagnetic dynamic phase is very susceptible to the impact of the second-harmonic field component $H_2$, whereas this additional field component leads to only very minor phase-space modifications in the ferromagnetic and anomalous paramagnetic regions. In contrast to prior studies, we also observe that the critical point of the phase transition is shifted upon introducing a second-harmonic field component $H_2$, illustrating that the overall dynamic behavior of such magnetic systems is being driven by the total effective amplitude of the field sequence.

In this paper, we consider the one-dimensional dynamical evolution of a particle traveling at constant speed and performing, at a given rate, random reversals of the velocity direction. The particle is subject to stochastic resetting, meaning that at random times it is forced to return to the starting point. Here we consider a return mechanism governed by a deterministic law of motion, so that the time cost required to return is correlated to the position occupied at the time of the reset. We show that in such conditions the process reaches a stationary state which, for some kinds of deterministic return dynamics, is independent of the return phase. Furthermore, we investigate the first-passage properties of the system and provide explicit formulas for the mean first-hitting time. Our findings are supported by numerical simulations.

The diffusion type is determined not only by microscopic dynamics but also by the environment properties. For example, the environment's fractal structure is responsible for the emergence of subdiffusive scaling of the mean square displacement in Markovian systems because the presence of nontrivially placed obstacles puts constraints on possible displacements. We investigate how the additional action of drift changes properties of the diffusion in the crowded environment. It is shown that the action of a constant drift increases chances of trapping, which suppresses the persistent ballistic motion. Such a diffusion becomes anisotropic because the drift introduces a preferred direction of motion which is further altered by interactions with obstacles. Moreover, individual trajectories display a high level of variability, which is responsible for the macroscopic properties of the diffusing front. Overall, the interplay among drift, diffusion, and a crowded environment, as measured by the time-averaged mean square displacement, is responsible for the emergence of superdiffusive and subdiffusive patterns in the very same system. Importantly, in contrast to free motion, the constant drift can enhance signatures of subdiffusive motion as it increases trapping chances.

The relationship between excess entropy and diffusion is revisited by means of large-scale computer simulation combined to supervised learning approach to determine the excess entropy for the Lennard-Jones potential. Results reveal a strong correlation with the properties of the potential energy landscape (PEL). In particular the exponential law holding in the liquid is seen to be linked with the landscape-influenced regime of the PEL whereas the fluidlike power-law corresponds to the free diffusion regime.

Individuals of modern societies share ideas and participate in collective processes within a pervasive, variable, and mostly hidden ecosystem of content filtering technologies that determine what information we see online. Despite the impact of these algorithms on daily life and society, little is known about their effect on information transfer and opinion formation. It is thus unclear to what extent algorithmic bias has a harmful influence on collective decision-making, such as a tendency to polarize debate. Here we introduce a general theoretical framework to systematically link models of opinion dynamics, social network structure, and content filtering. We showcase the flexibility of our framework by exploring a family of binary-state opinion dynamics models where information exchange lies in a spectrum from pairwise to group interactions. All models show an opinion polarization regime driven by algorithmic bias and modular network structure. The role of content filtering is, however, surprisingly nuanced; for pairwise interactions it leads to polarization, while for group interactions it promotes coexistence of opinions. This allows us to pinpoint which social interactions are robust against algorithmic bias, and which ones are susceptible to bias-enhanced opinion polarization. Our framework gives theoretical ground for the development of heuristics to tackle harmful effects of online bias, such as information bottlenecks, echo chambers, and opinion radicalization.

Subgraphs such as cliques, loops, and stars play a crucial role in real-world networks. Random graph models can provide estimates for how often certain subgraphs appear, which can be tested against real-world networks. These estimated subgraph counts, however, crucially depend on the assumed degree distribution. Fitting a degree distribution to network data is challenging, in particular, for scale-free networks with power-law degrees. Therefore, in this paper we develop robust subgraph counts that do not depend on the entire degree distribution but only on its mean and mean absolute deviation (MAD), summary statistics that are easy to obtain for most real-world networks. By solving an optimization problem, we provide tight (the sharpest possible) bounds for the subgraph counts, for all possible subgraphs, and for all networks with degree distributions that share the same mean and MAD. We identify the extremal random graph that attains these tight bounds as the graph with a specific three-point degree distribution. We leverage the bounds on the maximal subgraph counts to obtain robust scaling laws for how the number of subgraphs grows as a function of the network size. The scaling laws indicate that sparse power-law networks are not the most extreme networks in terms of subgraph counts but dense power-law networks are. The robust bounds are also shown to hold for several real-world data sets.

Topological defects in liquid crystals under confined geometries have attracted extensive research interests. Here, we perform molecular dynamics simulations to investigate the formation and transition of defect patterns in two-dimensional smectic Gay-Berne liquid crystals with a simple rectangular confinement boundary. Two typical types of defect patterns, bridge and diagonal defect patterns, are observed, which can be transformable continuously between each other over time. The transition usually starts from the line or point defect regions, and the competition between neighboring and opposite boundary effects induces the continuous realignments of the smectic layers to connect the neighboring or opposite walls. The relative stability of these two defect patterns can be controlled by changing the confinement conditions. These results deepen our understanding of transition kinetics of defect patterns in confined liquid crystals.

Silo discharge has been extensively studied for decades although questions remain regarding the nature of the velocity field, particularly for submerged systems. In this work, fluid-driven granular drainage was performed in a quasi-two-dimensional silo with grains submerged in fluid. While the observed Gaussian velocity profiles were generally consistent with current diffusion models, the diffusion length was found to significantly decrease with height in contrast to the increases previously seen in dry silos. We propose a phenomenological anomalous diffusion model for the spreading of the flow upwards in the cell, with the fluid-driven flows we study here falling in the category of subdiffusive behavior. As the viscous characteristics of the system were amplified, the diffusion length increased and the shape of the flowing zone in the silo changed, deviating further from the parabolic form predicted by traditional normal diffusion models, in effect becoming more subdiffusive as quantified by a decreasing diffusion exponent.

Viscous fingering in radial Hele-Shaw cells is markedly characterized by the occurrence of fingertip splitting, where growing fingered structures bifurcate at their tips, via a tip-doubling process. A much less studied pattern-forming phenomenon, which is also detected in experiments, is the development of fingertip tripling, where a finger divides into three. We investigate the problem theoretically, and employ a third-order perturbative mode-coupling scheme seeking to detect the onset of tip-tripling instabilities. Contrary to most existing theoretical studies of the viscous fingering instability, our theoretical description accounts for the effects of viscous normal stresses at the fluid-fluid interface. We show that accounting for such stresses allows one to capture the emergence of tip-tripling events at weakly nonlinear stages of the flow. Sensitivity of fingertip-tripling events to changes in the capillary number and in the viscosity contrast is also examined.

A combined approach to study cold rarefied matter is introduced that includes a semianalytical method based on the free-energy minimization and ab initio calculations based on the finite-temperature density-functional theory. The approach is used to calculate the ionization state of hydrocarbon (CH) under the shock-release conditions in inertial confinement fusion. The dielectric constant of CH is calculated using the Kubo-Greenwood formulation and contribution from atomic polarizabilities is found to be as important as the free-electron contribution. Using the ionization state and dielectric constant, the electron density profile in the rarefaction wave of the shock-release plasma is obtained.

We have performed measurements of the ir absorption of ${\text{SiO}}_2$ nanoparticles confined in an argon radiofrequency plasma discharge using a Fourier transform infrared spectrometer. By varying the gas pressure of the discharge and duty cycle of the applied radiofrequency voltage, we observed a shift of the absorption peak of ${\text{SiO}}_2$. We attributed this shift to charge-dependent absorption features of ${\text{SiO}}_2$. The charge-dependent shift has been calculated for ${\text{SiO}}_2$ particles, and from comparisons with the experiment the particle charge has been retrieved using our infrared phonon resonance shift method. With the two different approaches of changing the gas pressure and altering the duty cycle, we are able to deduce a relative change of the particle charge with pressure variations and an absolute estimate of the charge with the duty cycle.

Understanding the connections between information and thermodynamics has been among the most visible applications of stochastic thermodynamics. While recent theoretical advances have established that the second law of thermodynamics sets limits on information-to-energy conversion, it is currently unclear to what extent real systems can achieve the predicted theoretical limits. Using a simple model of an information engine that has recently been experimentally implemented, we explore the limits of information-to-energy conversion when an information engine's benefit is limited to output energy that can be stored. We find that restricting the engine's output in this way can limit its ability to convert information to energy. Nevertheless, a feedback control that inputs work can allow the engine to store energy at the highest achievable rate. These results sharpen our theoretical understanding of the limits of real systems that convert information to energy.

We use large-scale Monte Carlo simulations to obtain comprehensive results for domain growth and aging in the random field XY model in dimensions $d=2,3$. After a deep quench from the paramagnetic phase, the system orders locally via annihilation of topological defects, i.e., vortices and antivortices. The evolution morphology of the system is characterized by the correlation function and the structure factor of the magnetization field. We find that these quantities obey dynamical scaling, and their scaling function is independent of the disorder strength $\mathrm{\Delta }$. However, the scaling form of the autocorrelation function is found to be dependent on $\mathrm{\Delta }$, i.e., superuniversality is violated. The large-$t$ behavior of the autocorrelation function is explored by studying aging and autocorrelation exponents. We also investigate the characteristic growth law $L(t,\mathrm{\Delta })$ in $d=2,3$, which shows an asymptotic logarithmic behavior: $L(t,\mathrm{\Delta })\sim {\mathrm{\Delta }}^{-\phi }{(lnt)}^{1/\psi }$, with exponents $\phi ,\psi >0$.

In this paper, we apply Lagrangian descriptors to study the invariant manifolds that emerge from the top of two barriers existing in the $\mathrm{LiCN}\rightleftharpoons \mathrm{LiNC}$ isomerization reaction. We demonstrate that the integration times must be large enough compared with the characteristic stability exponents of the periodic orbit under study. The invariant manifolds manifest as singularities in the Lagrangian descriptors. Furthermore, we develop an equivalent potential energy surface with 2 degrees of freedom, which reproduces with a great accuracy previous results [F. Revuelta, R. M. Benito, and F. Borondo, Phys. Rev. E 99, 032221 (2019)]. This surface allows the use of an adiabatic approximation to develop a more simplified potential energy with solely 1 degree of freedom. The reduced dimensional model is still able to qualitatively describe the results observed with the original 2-degrees-of-freedom potential energy landscape. Likewise, it is also used to study in a more simple manner the influence on the Lagrangian descriptors of a bifurcation, where some of the previous invariant manifolds emerge, even before it takes place.

Based on a local greedy numerical algorithm, we compute the topology of weighted, directed, and unlimited extension networks of nonidentical Kuramoto oscillators which simultaneously satisfy two criteria: (i) global frequency synchronization and (ii) minimum total mass of the connection weights. This problem has been the subject of many previous interesting studies; in the present paper, no a priori constraint is imposed, either on the form or on the dynamics of the connections. The results are surprising: the optimal networks turn out to be strongly symmetric, to be very economical, and to display a strong rich club structure, and in addition to the already reported strong correlation between natural frequencies and the weight of incoming connections we also observe a correlation, even more marked, between these same natural frequencies and the weight of outgoing connections. The latter result is at odds with theoretical predictions.

Sensor-to-actuator delay is inevitable in any complex control system, be it one for a free-flying insect or a mimicking insectlike robotic flyer. In this work, we analyze the effects of control delay (latency) on the hovering performance of a model insect flyer, as exemplified by the hummingbird hawkmoth $\mathrm{Re}\sim 3000$, and determine how control coefficients or gains may be modified to ameliorate the adverse effects of latency. The analyses are based on a simplified or reduced dynamic model of the hovering flyer. The longitudinal dynamics of the hovering flyer comprises the coupled forward (backward) and vertical translations and pitch rotation of the flyer, with kinematical wing actions being governed by proportional-differential (PD) closed-loop control. Keeping to the same PD control coefficients as a stable reference zero-delay case, the flight system becomes overly responsive at a small control delay, eventually diverging when delay approaches around one wing cycle. Stable hovering may be regained for control delay of up to several wingbeats by suitably reducing or softening the PD control coefficients. The results of the analyses are validated by a series of time-based simulations using the simplified dynamic model and a high-fidelity three-dimensional computational fluid dynamics with fluid structure–body interaction model of the hovering flyer. The simulations also show that noncyclic asymptotic oscillations about the mean equilibrium hovering state are enhanced with larger control delay. The analyses and simulations have helped us to gain a better understanding of the effects of control latency in insect free flight, which may be relevant for the design of mimetic insect flyers.

Harmonic cell models (HCMs) are shown to predict the melting line of the Lennard-Jones (LJ) but not the sublimation line. In addition, even for the melting line, the HCMs are found to be physically unrealistic for inverse power potential systems near the hard-sphere limit, and for the Weeks-Chandler-Andersen system at extremely low temperatures. Despite this, the HCM accurately predicts the LJ mean-square displacement (MSD) from molecular-dynamics (MD) simulations along both lines after simple scaling corrections, to include the effects of anharmonicity and correlated dynamics of the atoms, are applied. Single caged atom molecular dynamics and Monte Carlo simulations provide further quantitative characterization of these additional effects, which go beyond harmonicity. The melting indicator and a modification of the cell model in a similar form are shown to be approximately constant along the melting line, which indicates an isomorph. The less well studied LJ sublimation line is shown not to be an isomorph, yet it still can be represented analytically very accurately by the relationship $k_{B}T=a{\rho }^4+b{\rho }^2$, where $a$ and $b$ are constants ($k_B$ is Boltzmann's constant, $T$ is the temperature, and $\rho$ is the number density). This relationship has been found previously for the melting line, but the two constants have opposite signs for the sublimation and melting lines. This simple formula is also predicted using a nonharmonic static lattice expression for the pressure. The probability distribution function of the melting factor indicates departures from harmonic or Gaussian behavior in the lower wing. Nevertheless, the mean melting factor is shown to follow a simple MSD Debye-Waller factor dependence along both the melting and sublimation lines. This work combining HCM and MD simulations provides a comparison of the melting and sublimation lines of the LJ system, which could provide the foundations for a more unified statistical mechanical description of these two solid boundary lines.