This work presents a theoretical analysis of the motion of a tracer colloid driven by a time-dependent force through a viscoelastic fluid. The recoil of the colloid after application of a strong force is determined. It provides insights into the elastic forces stored locally in the fluid and their weakening by plastic processes. We generalize the mode-coupling theory of microrheology to include time-dependent forces. After deriving the equations of motion for the tracer correlator and simplifying to a schematic model, we apply the theory to a switch-off force protocol that features the recoiling of the tracer after cessation of the driving. We also include Langevin dynamics simulations to compare to the results of the theory. A nonmonotonic trend of the recoil amplitude is found in the theory and confirmed in the simulations. The linear-response approximation is also verified in the small-force regime. While the overall agreement between simulation and theory is good, simulation shows that the theory predicts a too strong nonmonotonous dependence of the recoil distance on the applied force.

Pair correlations for a polar liquid-crystal (LC) system have been theoretically investigated by means of integral equation approach. Using the dipolar Gay-Berne (GB) interactions between the molecules that composed the LC system, calculations of the nearest-neighbor (NN) and next-NN (NNN) correlators as well as the order parameters and the static dielectric coefficients were performed. It is shown that for a simple cubic packing, NN dipoles tend to be mutually antiparallel with respect to the central dipole, while the opposite trend was observed for NNN dipoles. Our calculations also show that the anisotropy of the nematic phase is not imposed by the symmetry of the system, but rather is a consequence of the dipolar GB potential.

We study the effects of disorder on the exciton spectra in quantum well (QW) semiconductor structures. We model the disorder by introducing the fractional Laplacian into the Schrödinger equations, which describe the exciton spectra of the above QW structures. We calculate the exciton binding energies in its ground state and a few low-lying excited states as a function of the GaAs QW size. Our main finding is that disorder significantly increases the exciton binding energy in QWs, sometimes by a factor of 10. For disordered case, the interplay between strength of disorder (characterized by Lévy index $\alpha$ in our approach) and nonzero exciton angular momentum in its excited states causes the system to perceive QW finite physical barrier heights as infinite, which also influences the exciton binding energy. Our results can be applied for heterostructures like GaAs/AlGaAs, GaN/AlGaN, as well as to any of the II–VI and III–V heterostructures, which may be used in many optoelectronic and spintronic applications.

A novel quantum Otto heat engine that operates within a finite-time framework by incorporating measurement procedures is proposed. Departing from conventional quantum Otto heat engines, our model replaces the heat absorption process from a high-temperature source with invasive measurement. Moreover, we consider finite-time thermodynamic manipulation in each step. Our model focuses on exploring the effects of the angles of the measurement basis on the Bloch sphere and the timings of time-dependent evolutions on thermodynamic properties, with a specific emphasis on the trade-off between the power output and the efficiency. Our findings demonstrate that by carefully selecting specific parameters, the efficiency and overall performance of this heat engine can be significantly enhanced.

Intermittent switchings between weakly chaotic (laminar) and strongly chaotic (bursty) states are often observed in systems with high-dimensional chaotic attractors, such as fluid turbulence. They differ from the intermittency of a low-dimensional system accompanied by the stability change of a fixed point or a periodic orbit in that the intermittency of a high-dimensional system tends to appear in a wide range of parameters. This paper considers a case where the skeleton of a laminar state $L$ exists as a proper chaotic subset $S$ of a chaotic attractor $X$, that is, $S⊊X$. We characterize such a laminar state $L$ by a chaotic saddle $S$, which is densely filled with periodic orbits of different numbers of unstable directions. This study demonstrates the presence of chaotic saddles underlying intermittency in fluid turbulence and phase synchronization. Furthermore, we confirm that chaotic saddles persist for a wide range of parameters. Also, a kind of phase synchronization turns out to occur in the turbulent model.

We explore how the interplay of finite availability, carrying capacity of particles at different parts of a spatially extended system, and particle diffusion between them control the steady-state currents and density profiles in a one-dimensional current-carrying channel connecting the different parts of the system. To study this, we construct a minimal model consisting of two particle reservoirs of finite carrying capacities connected by a totally asymmetric simple exclusion process (TASEP). In addition to particle transport via TASEP between the reservoirs, the latter can also directly exchange particles via Langmuir kinetics-like processes, modeling particle diffusion between them that can maintain a steady current in the system. We calculate the steady-state density profiles and the associated particle currents in the TASEP lane. The resulting phases and the phase diagrams are quite different from an open TASEP, and are characterized by the model parameters defining particle exchanges between the TASEP and the reservoirs, direct particle exchanges between the reservoirs, and the filling fraction of the particles that determines the total resources available. These parameters can be tuned to make the density on the TASEP lane globally uniform or piecewise continuous, and can make the two reservoirs preferentially populated or depopulated.

The problem of estimating the constant parameters of the Kuramoto-Sivashinsky (KS) equation from observed data has received attention from researchers in physics, applied mathematics, and statistics. This is motivated by the various physical applications of the equation and also because it often serves as a test model for the study of space-time pattern formation. Remarkably, most existing inference techniques rely on statistical tools, which are computationally very costly yet do not exploit the dynamical features of the system. In this paper, we introduce a simple, online parameter estimation method that relies on the synchronization properties of the KS equation. In particular, we describe a master-slave setup where the slave model is driven by observations from the master system. The slave dynamics are data-driven and designed to continuously adapt the model parameters until identical synchronization with the master system is achieved. We provide a simple analysis that supports the proposed approach and also present and discuss the results of an extensive set of computer simulations. Our numerical study shows that the proposed method is computationally fast and also robust to initialization errors, observational noise, and variations in the spatial resolution of the numerical scheme used to integrate the KS equation.

Buckling instabilities driven by tissue growth underpin key developmental events such as the folding of the brain. Tissue growth is disordered due to cell-to-cell variability, but the effects of this variability on buckling are unknown. Here, we analyze what is perhaps the simplest setup of this problem: the buckling of an elastic rod with fixed ends driven by spatially varying, yet highly symmetric growth. Combining analytical calculations for simple growth fields and numerical sampling of random growth fields, we show that variability can increase as well as decrease the growth threshold for buckling, even when growth variability does not cause any residual stresses. For random growth, we find numerically that the shift of the buckling threshold correlates with spatial moments of the growth field. Our results imply that biological systems can either trigger or avoid buckling by exploiting the spatial arrangement of growth variability.

We investigate the influence of the network topology on the asymptotic dynamical patterns, attractors, in a general model of excitable dynamics on signed directed graphs. In this framework, network topology manifests itself as an interplay of positive and negative feedback loops. A small change in a feedback loop, by addition or removal of edges in the graph, can drastically change the dynamical patterns in the network, characterized by the appearance and disappearance of attractors from the attractor space of the network. We identify the determinants of such events via a systematic set of numerical experiments. As application examples, we discuss the basal ganglia network that is relevant in the context of Parkinson's disease and the two-compartment cortico-thalamic network thought to be related to generating epileptic seizures, showing that a given attractor in the attractor space of a network can be induced or destroyed via a specific set of topological manipulations. Thus, we propose a systematic way to alter the dynamical landscape of the system via changes in its topology and hence for perturbation therapies like deep brain stimulation.

In this work, we shall study the role of threefold and fivefold coordination defects in the structure and dynamics of the hydrogen bond network of liquid water, with special emphasis on the glassy regime. A significant defect clusterization propensity will be made evident, with a prevalence of mixed pairs, that is, threefold- and fivefold-coordinated defects being first neighbors of each other. This structural analysis will enable us to determine the existence of defective and nondefective regions compatible with the high local density and low local density molecular states of liquid water, respectively. Hydrogen bond coordination defects will also be shown to promote water's structural relaxation, with the undercoordinated ones playing a main role in driving glassy relaxation dynamics. Moreover, we shall show that the three-foldcoordinated molecules together with their first neighbors present at the initial configuration act as markers of the dynamical heterogeneities that would emerge at later times commensurate with the structural relaxation of the supercooled system.

A common intuition in thermodynamics is that bubbles can spontaneously grow in unstable liquids, which will be detrimental to a variety of physical and chemical processes, such as evaporation-induced self-assembly and electrocatalysis. Here, we show that this common intuition can be significantly reversed by demonstrating a suppression of bubbles in unstable active liquids induced by fast evaporation, which is in contrast to the bubble growth in passive liquids. Such anomalous bubble suppression can be attributed to an activity-induced inversion of pressure difference between bubbles and their surrounding liquid. Moreover, this pressure flip depends on the activity as well as the thermodynamics of passive liquids, and it can generate different kinetic pathways that allow controlling the bubble dynamics in unstable liquids. Our results establish a foundation for promoting applications of unstable active liquids in various physical and chemical processes.

We develop convergence acceleration procedures that enable a gradient descent-type iteration method to efficiently simulate Hartree-Fock equations for many particles interacting both with each other and with an external potential. Our development focuses on three aspects: (i) optimization of a parameter in the preconditioning operator; (ii) adoption of a technique that eliminates the slowest-decaying mode to the case of many equations (describing many particles); and (iii) a novel extension of the above technique that allows one to eliminate multiple modes simultaneously. We illustrate performance of the numerical method for the two-dimensional model of the first layer of helium atoms above a graphene sheet. We demonstrate that incorporation of aspects (i) and (ii) above into the “plain” gradient descent method accelerates it by at least two orders of magnitude, and often by much more. Aspect (iii)—the multiple-mode elimination—may bring further improvement to the convergence rate compared to aspect (ii), the single-mode elimination. Both single- and multiple-mode elimination techniques are shown to significantly outperform the well-known Anderson Acceleration. We believe that our acceleration techniques can also be employed by other iterative methods, especially those handling hard-core-type interaction of many particles.

The shear viscosity is a fundamental transport property of matter. Here we derive a general theory of the viscosity of gases based on the relativistic Langevin equation (deduced from a relativistic Lagrangian) and nonaffine linear response theory. The proposed relativistic theory is able to recover the viscosity of nonrelativistic classical gases, with all its key dependencies on mass, temperature, particle diameter, and Boltzmann constant, in the limit of Lorentz factor $\gamma =1$. It also unveils the relativistic enhancement mechanism of viscosity. In the limit of ultrarelativistic fluids, the theory provides an analytical formula which reproduces the cubic increase of viscosity with temperature in agreement with various estimates for hot dense matter and the quark-gluon-plasma-type fluid.

Isoenergetic thermalization amongst $n$ bodies is a well-known irreversible process, bringing the bodies to a common temperature $T_F$ and leading to a rise in the total entropy of the bodies. We express this change in entropy using the Clausius formula over a reversible path connecting $T_F$ with $T_f$, which corresponds to the entropy-preserving temperature of the initial nonequilibrium state. Under the assumption of positive heat capacities of the bodies, the second law inequality simply follows from the fact that $T_F>T_f$. We extend this approach to the continuum case of an unequally heated rod, illustrating with the special case of the rod with constant heat capacity and a linear temperature profile. An interpolating profile between the discrete and the continuum models is studied whereby $T_f$, given by the geometric mean temperature over $n$ elements, is shown to approach the identric mean of the lowest and the highest temperatures as $n$ becomes large. We also discuss the case of negative heat capacity in a two-body set up where isoenergetic thermalization may be forbidden by the second law. However, the alternate scheme in which first work is performed reversibly on the system and then an equivalent amount of energy is extracted in the form of heat, brings the system to an energy-preserving common temperature.

We study a simple model of swarmalators subject to periodic forcing and confined to moving around a one-dimensional ring. This is a toy model for physical systems with a mix of sync, swarming, and forcing, such as colloidal micromotors. We find rich behavior: pinned states where the swarmalators are locked to the driving, sync states where their phases are either identical or have fixed differences, and unsteady states, such as swarmalator chimera where the population splits into two sync dots enclosed by a "train" of swarmalators that run around a peanut-shaped loop. We derive the stability thresholds for most of these states which give us a good approximation of the model's phase diagram.

The bacterial flagellar motor is both chemo- and mechanosensitive. It is sensitive to the intracellular concentration of the chemotaxis response regulator CheY-P and to external load conditions. The motor's dose-response curve, which represents the probability of the motor rotating clockwise (CW bias) as a function of CheY-P concentration, characterizes its chemical sensitivity. However, it remains unclear how this dose-response curve depends on the load conditions. Here, we measured the dose-response curves of the motor under various load conditions. Surprisingly, we found that the dose-response curve exhibited minimal changes with load at low CW biases, but shifted leftward with higher sensitivity to CheY-P concentration at high CW biases when the load increased. This observation contradicts previous model predictions that incorporated the effect of stator-rotor interaction on motor switching. Through the development of an Ising-type model for the coupled chemo- and mechanosensitivity of the flagellar switch, we revealed that the mechanism underlying the mechanosensitive dose response is the synergistic interplay between the adaptive remodeling of the motor switch complex and the nonequilibrium effect of the stator-rotor interaction.

Robert May famously used random matrix theory to predict that large, complex systems cannot admit stable fixed points. However, this general conclusion is not always supported by empirical observation: from cells to biomes, biological systems are large, complex, and often stable. In this paper, we revisit May's argument in light of recent developments in both ecology and random matrix theory. We focus on competitive systems, and, using a nonlinear generalization of the competitive Lotka-Volterra model, we show that there are, in fact, two kinds of complexity-stability relationships in disordered dynamical systems: if self-interactions grow faster with density than cross-interactions, complexity is destabilizing; but if cross-interactions grow faster than self-interactions, complexity is stabilizing.

We investigate the effects of quenched elastic disorder on the nature of the crumpling-to-flat transition of $D$-dimensional polymerized membranes using a two-loop computation near the upper critical dimension $D_c=4$. While the pure system undergoes fluctuation-induced first-order transitions below $D_c$ and for an embedding dimension $d<d_{c,\mathrm{pure}}\simeq 218.2$, one observes, in the presence of disorder, the emergence of various regions of second order governed by a disordered stable fixed point for $d<d_{c1}\sim d_{c,\mathrm{pure}}$. This opens the possibility of a new universality class associated with the crumpling-to-flat transition of disordered membranes in $d=3$.

This study investigates the Rayleigh-Taylor instability in the magnetic field applied parallel to the interface. The motion of the interface is described using a current-vortex-sheet model. The growth rate of the interface is obtained from a linear stability analysis of the model. The interface of a single mode $k=1$ is linearly stable for $R_A\le 1$, where $R_A$ denotes the Alfvén number. Further, we conduct numerical computations for the evolution of the interface from the model for both regimes of $R_A\le 1$ and $R_A>1$. For $R_A\le 1$, the interface oscillates vertically but does not intrude into the opposite phase. The amplitude of the interface and the oscillation period decrease with decrease in $R_A$. For $1<R_A\lesssim 1.5$, the interface undergoes some growth at early times and then decreases. This oscillation is repeated, and no roll-ups are observed at the interface. Therefore, the nonlinear growth of the Rayleigh-Taylor instability is stabilized by a sufficiently strong magnetic field. For $R_A\gtrsim 3$ the interface is unstable and the pattern of the interface evolution differs from the density ratio. In addition, the magnetic field is greatly amplified as $R_A$ increases.