A composite subdiffusion equation with fractional Caputo time derivative with respect to another function $g$ is used to describe a process of a continuous transition from subdiffusion with parameters $\alpha$ and $D_{\alpha }$ to subdiffusion with parameters $\beta$ and $D_{\beta }$. The parameters are defined by the time evolution of the mean square displacement of diffusing particle ${\sigma }^2\left(t\right)=2D_i{t}^i/\mathrm{\Gamma }(1+i)$, $i=\alpha ,\beta$. The function $g$ controls the process at intermediate times. The composite subdiffusion equation is more general than the ordinary fractional subdiffusion equation with constant parameters; it has potentially wide application in modeling diffusion processes with changing parameters.

In the present work, we focus on two dynamical timescales in the Arnold Hamiltonian model: the Lyapunov time and the diffusion time when the system is confined to the stochastic layer of its dominant resonance (guiding resonance). Following Chirikov's formulation, the model is revisited, and a discussion about the main assumptions behind the analytical estimates for the diffusion rate is given. On the other hand, and in line with Chirikov's ideas, theoretical estimations of the Lyapunov time are derived. Later on, three series of numerical experiments are presented for various sets of values of the model parameters, where both timescales are computed. Comparisons between the analytical estimates and the numerical determinations are provided whenever the parameters are not too large, and those cases are in fact in agreement. In particular, the case in which both parameters are equal is numerically investigated. Relationships between the diffusion time and the Lyapunov time are established, like an exponential law or a power law in the case of large values of the parameters.

With quenched disorder, we introduce two-dimensional active nematics suspended in an incompressible fluid. We write the coarse-grained hydrodynamic equations of motion for slow variables, viz. density, orientation, and flow fields. The quenched disorder is introduced such that it interacts with the local orientation at every point with some strength. Disorder strength is tuned from zero to large values. We numerically study the defect dynamics and system kinetics and find that the finite disorder slows the ordering. The presence of fluid induces large fluctuation in the orientation field, further disturbing the ordering. The large fluctuation in the orientation field due to the fluid is so dominant that it reduces the effect of the quenched disorder. We have also found that the disorder effect is almost the same for both the contractile and extensile nature of active stresses in the system. This study can help to understand the impact of quenched disorder on the ordering kinetics of active gels with nematic interaction among the constituent objects.

The mechanism responsible for the damping of the large-scale, azimuthally directed jets observed at Jupiter's surface is not well known, but electromagnetic forces are suspected to play a role as the planet's electrical conductivity increases radially with depth. To isolate the jet damping process, we carry out a suite of direct numerical simulations of quasi-two-dimensional, horizontally periodic Rayleigh-Bénard convection with stress-free boundary conditions in the presence of an external, vertical magnetic field. Jets, punctuated by intermittent convective bursts, develop at Rayleigh numbers ($\mathrm{Ra}$, ratio of buoyancy to diffusion) beyond ${10}^5$ when the magnetic field is relatively weak. Five primary flow regimes are found by varying ${10}^3\le \mathrm{Ra}\le {10}^{10}$ and the Chandrasekhar number ($\mathrm{Ch}$, ratio of Lorentz to viscosity) $0\le \mathrm{Ch}\le {10}^6$: (i) steady convection rolls, (ii) steady magneto-columns, (iii) unsteady to turbulent magneto-plumes, (iv) horizontally drifting magneto-plumes, and (v) jets with intermittent turbulent convective bursts. We parse the parameter space using transitions derived from the interaction parameter ($N$, ratio of Lorentz to inertia). The transition to the regime dominated by jets has the most immediate applications to the magnetic damping of Jovian jet flows, where the separation between jets and a magnetically constrained system occurs at a jet-based interaction parameter value of $N_J\approx 1$. We approximate the value of the Jovian interaction parameter as a function of depth, and find that the jets may brake at $\approx 6000$ km below the surface, which is deeper than recent estimates from NASA's Juno mission. This suggests that mechanisms in addition to electromagnetic forces are likely required to fully truncate the jets.

Universal fault-tolerant quantum computers require millions of qubits with low error rates. Since this technology is years ahead, noisy intermediate-scale quantum (NISQ) computation is receiving tremendous interest. In this setup, quantum reservoir computing is a relevant machine learning algorithm. Its simplicity of training and implementation allows to perform challenging computations on today's available machines. In this Letter, we provide a criterion to select optimal quantum reservoirs, requiring few and simple gates. Our findings demonstrate that they render better results than other commonly used models with significantly less gates and also provide insight on the theoretical gap between quantum reservoir computing and the theory of quantum states' complexity.

The magnetic properties and thermodynamical description of the Fe-Mn-Al ternary alloy are studied using the spin 1 antiferromagnetic Blume-Capel (BC) model by the pair approximation based on the Gibbs-Feymann-Bogoliubov inequality for the free energy. The values of the spin operator are $+1$ for ferromagnetic interaction (Fe-Fe), $-1$ for the antiferromagnetic one (Mn-Mn, Mn-Fe), and 0 for the magnetic diluter (corresponding to Al). The BC model with antiferromagnetic (AF) next-nearest-neighbor coupling better accurately fit the mean hyperfine field experimental data obtained by Mössbauer spectroscopy. Considering the crystalline field, the predicted temperature as a function of the Al concentration phase diagram, for the fcc lattice, from the numerical solution is remarkably good and significantly improves the traditional Ising and random-site Ising models.

Numerical simulations are used to examine the dynamics of the dc-driven Frenkel-Kontorova model with an oscillation substrate subjected to lateral periodic excitations in overdamped and underdamped cases, respectively. The results reveal that the system exhibits frequency locking and chaotic behaviors due to the fact that the lateral vibration of the substrate potential introduces an additional frequency and degree of freedom into the system. In the overdamped case, we show that the appearance of subharmonic Shapiro steps can be attributed to the deformation of the substrate potential or inertia. The characteristics of the steps are significantly affected by the amplitude and frequency of the lateral vibration. When the vibration frequency is relatively high, the change of the width of the first harmonic Shapiro step with increasing amplitude exhibits a Bessel-type oscillation, but the oscillation deviates from the Bessel curve at lower frequencies. In the amplitude dependence, although the oscillatory behavior of the critical depinning force at the high frequency is anomalous, local maxima (minima) of the first step width correspond to local minima (maxima) of the critical depinning force, and the largest Lyapunov exponent obtained in the pinned state represents a mirror relationship of the critical depinning force. In contrast to the overdamped system, the underdamped one exhibits both subharmonic Shapiro steps and chaotic behaviors. We show the increased inertia of the latter system plays an important role in suppressing the emergence of subharmonic steps, which is opposite to the result of the former. When the dc force changes, chaos appears not only between adjacent subharmonic Shapiro steps but also on some specific steps where chaos should be avoided. The variation regularity of the first step width and the critical depinning force is thus annihilated in vibration amplitude and frequency dependence. However, superlubricity can be achieved by careful adjustment of vibration amplitude and frequency. The findings can serve as a theoretical guideline for technological applications such as device building and voltage standards.

Single-stranded RNA (ssRNA) viruses self-assemble spontaneously in solutions that contain the viral RNA genome molecules and viral capsid proteins. The self-assembly of empty capsids can be understood on the basis of free energy minimization. However, during the self-assembly of complete viral particles in the cytoplasm of an infected cell, the viral genome molecules must be selected from a large pool of very similar host messenger RNA molecules and it is not known whether this also can be understood by free energy minimization. We address this question using a simple mathematical model, the spanning tree model, that was recently proposed for the assembly of small ssRNA viruses. We present a statistical physics analysis of the properties of this model. RNA selection takes place via a kinetic mechanism that operates during the formation of the nucleation complex and that is related to Hopfield kinetic proofreading.

Transcriptional pausing is highly regulated by the template DNA and nascent transcript sequences. Here, we propose a thermodynamic model of transcriptional pausing, based on the thermal energy of transcription bubbles and nascent RNA structures, to describe the kinetics of the reaction pathways between active translocation, elemental, backtracked, and hairpin-stabilized pauses. The model readily predicts experimentally detected pauses in high-resolution optical-tweezer measurements of transcription. Unlike other models, it also predicts the effect of tension and the GreA transcription factor on pausing.

Collagen fibrils, when subjected to cyclic loading, are known to exhibit hysteretic behavior with energy dissipation that is partially recovered on relaxation. In this paper, we develop a kinetic model for a collagen fibril incorporating presence of hidden loops and stochastic fragmentation as well as reformation of sacrificial bonds. We show that the model reproduces well the characteristic features of reported experimental data on cyclic response of collagen fibrils, such as moving hysteresis loops, time evolution of residual strains and energy dissipation, recovery on relaxation, etc. We show that the approach to the steady state is controlled by a characteristic cycle number for both residual strain as well as energy dissipation and is in good agreement with reported existing experimental data.

The drift wave in the presence of impurity ions was investigated numerically in reversed-field pinch plasmas, using the gyrokinetic integral eigenmode equation. By comparing the results of regular and hollow plasma density profiles, it was found that the ion temperature gradient mode for the hollow density profile case is much harder to excite. For the impurity effects, when the impurity density gradient is opposite to the electrons, namely when $L_{ez}$ ($L_{ez}=L_{ne}/L_{nz}$ with $1/L_n$ being the density gradient scale length, and the subscript “$e$” and “$z$” indicates electrons and impurity ions, respectively) is negative, the impurities can enhance the instability. On the contrary, when $L_{ez}$ is positive, the instability is stabilized. Regarding the trapped electron mode (TEM), the growth rate for plasmas with a hollow density profile remains smaller than that of the standard density gradient. There exists a threshold in $L_{ez}$. When $L_{ez}$ is less than this value, the impurities destabilize the TEMs, while when $L_{ez}$ is greater than this value, the impurities stabilize the TEMs. In addition, the influence of the collisionality on the TEMs was also studied.

We study the nonequilibrium dynamics of two particles confined in two spatially separated harmonic potentials and linearly coupled to the same thermally fluctuating scalar field, a cartoon for optically trapped colloids in contact with a medium close to a continuous phase transition. When an external periodic driving is applied to one of these particles, a nonequilibrium periodic state is eventually reached in which their motion synchronizes thanks to the field-mediated effective interaction, a phenomenon already observed in experiments. We fully characterize the nonlinear response of the second particle as a function of the driving frequency, in particular far from the adiabatic regime in which the field can be assumed to relax instantaneously. We compare the perturbative, analytic solution to its adiabatic approximation, thus determining the limits of validity of the latter, and we qualitatively test our predictions against numerical simulations.

We address the problem of random search for a target in an environment with a space-dependent diffusion coefficient $D\left(x\right)$. Considering a general form of the diffusion differential operator that includes Itô, Stratonovich, and Hänggi-Klimontovich interpretations of the associated stochastic process, we obtain and analyze the first-passage-time distribution and use it to compute the search efficiency $\mathcal{E}=\langle 1/t\rangle$. For the paradigmatic power-law diffusion coefficient $D\left(x\right)=D_0{\left|x\right|}^{\alpha }$, where $x$ is the distance from the target and $\alpha <2$, we show the impact of the different interpretations. For the Stratonovich framework, we obtain a closed-form expression for $\mathcal{E}$, valid for arbitrary diffusion coefficient $D\left(x\right)$. This result depends only on the distribution of diffusivity values and not on its spatial organization. Furthermore, the analytical expression predicts that a heterogeneous diffusivity profile leads to a lower efficiency than the homogeneous one with the same average level within the space between the target and the searcher initial position, but this efficiency can be exceeded for other interpretations.

Nonlinear metamaterials have great potential in heat management, which has aroused intensive research interest in both theory and application, especially for their response to surroundings. However, most existing works focus on geometrically isotropic (circular) structures, limiting the potential versatile functionalities. On the other hand, anisotropy in architecture promisingly offers an additional degree of freedom in modulating directional heat transfer. Here, we investigate nonlinear composition effects in geometrically anisotropic (confocal elliptical) thermal medium under the framework of effective medium approximation, and deduce a series of general formulas for quantitatively predicting nonlinearity enhancement. Enhancement coefficients are analytically derived by the Taylor expansion method in different nonlinearity cases. In particular, we find that some coupling conditions can greatly promote the nonlinear modulation coefficients, introducing stronger enhancement beyond isotropic construction. Our theoretical predictions are verified by finite-element simulation, and feasible experimental suggestions are also given. For extending these results to practical scenes, two intelligent thermal metadevices are designed in proof of concept and demonstrated by numerical simulation. Our works provide a unified theory for anisotropic nonlinear thermal metamaterial design and may benefit flexible applications in self-adaptive thermal management, such as switchable cloaks, concentrators, or macroscopic thermal diodes.

We investigate the effects of adiabatic, quasistatic, and finite-rate types of driving on the evolution of disordered three-dimensional ferromagnetic systems, studied within the frame of the nonequilibrium athermal random field Ising model. The effects were examined in all three domains of disorder (low, high, and transitional) for all types of driving, and in a wide range of driving rates for quasistatic and finite-rate driving, providing an extensive overview and comparison of the joint effects that the disorder, type of driving, and rate regime have on the system's behavior.

Markov media provide a prototype class of stochastic geometries that are widely used in order to model several complex and disordered systems encompassing, e.g., turbulent fluids and plasma, atmospheric layers, or biological tissues, especially in relation to particle transport problems. In several key applications, the statistical properties of random media may display spatial gradients due to material stratification, which means that the typical spatial scale and the probability of finding a given material phase at a spatial location become nonhomogeneous. In this paper we investigate the main features of spatially heterogeneous Markov media, using Poisson hyperplane tessellations and Arak polygonal fields. We show that both models can generate geometry realizations sharing Markov-like properties, and discuss their distinct advantages and drawbacks in terms of flexibility and ease of use. The impact of these models on the observables related to particle transport will be assessed using Monte Carlo simulations.

We derive expressions for classical isothermal and adiabatic elastic constants for periodic systems with the boundary contributions included explicitly. The potential-dependent part of these expressions is written in terms of potential energies of atomic groups that make up the total potential energy. It is shown that in the thermodynamic limit, the Born term, which depends on the second derivatives of potential energy, can be expressed exactly in terms of equilibrium averages that involve two types of atomic-group virials. As a result, the new form of the Born term involves only first derivatives of either atomic-group or total potential energies. The derived elastic constant expressions involving the two forms of the Born terms are tested and compared using molecular-dynamics simulations of crystalline argon and silicon. For both materials, the elastic constants obtained using the two forms of the Born term are in good agreement. In particular, the new form of the Born term converges to the same value as the original Born term but at a slower rate. The results for silicon also agree well with the results from the previous molecular-dynamics studies.

We consider the relaxation (noise-free) statistics of the one-point height $H=h(x=0,t)$, where $h(x,t)$ is the evolving height of a one-dimensional Kardar-Parisi-Zhang (KPZ) interface, starting from a Brownian (random) initial condition. We find that, at short times, the distribution of $H$ takes the same scaling form $-ln\mathcal{P}(H,t)=S\left(H\right)/\sqrt{t}$ as the distribution of $H$ for the KPZ interface driven by noise, and we find the exact large-deviation function $S\left(H\right)$ analytically. At a critical value $H=H_c$, the second derivative of $S\left(H\right)$ jumps, signaling a dynamical phase transition (DPT). Furthermore, we calculate exactly the most likely history of the interface that leads to a given $H$, and show that the DPT is associated with spontaneous breaking of the mirror symmetry $x\leftrightarrow -x$ of the interface. In turn, we find that this symmetry breaking is a consequence of the nonconvexity of a large-deviation function that is closely related to $S\left(H\right)$, and describes a similar problem but in half space. Moreover, the critical point $H_c$ is related to the inflection point of the large-deviation function of the half-space problem.