We propose a method to reconstruct the phase dynamics in rhythmical interacting systems from macroscopic responses to weak inputs by developing linear and nonlinear response theories, which predict the responses in a given system. By solving an inverse problem, the method infers an unknown system: the natural frequency distribution, the coupling function, and the time delay which is inevitable in real systems. In contrast to previous methods, our method requires neither strong invasiveness nor microscopic observations. We demonstrate that the method reconstructs two phase systems from observed responses accurately. The qualitative methodological advantages demonstrated by our quantitative numerical examinations suggest its broad applicability in various fields, including brain systems, which are often observed through macroscopic signals such as electroencephalograms and functional magnetic response imaging.

Using two-dimensional porous structures made up of homogeneously arranged solid obstacles, we examine the effects of rarefaction on the hydraulic tortuosity in the slip and early transition flow regimes via extended lattice Boltzmann method. We observed that modification in either the obstacle's arrangement or the porosity led to a power-law relation between the porosity-tortuosity. Along with this, we also found that in the slip-flow regime, the exponent of this relation contains the effect of finite Knudsen number (Kn). In addition, we observed that on properly scaling Kn with porosity and hydraulic tortuosity, a generalized correlation can be obtained for apparent permeability.

The quality of the proton beam produced by target normal sheath acceleration (TNSA) with high-power lasers can be significantly improved with the use of helical coils. While they showed promising results in terms of focusing, their performances in terms of the of cut-off energy and bunching stay limited due to the dispersive nature of helical coils. A new scheme of helical coil with a tube surrounding the helix is introduced, and the first numerical simulations and an analytical model show a possibility of a drastic reduction of the current pulse dispersion for the parameters of high-power-laser facilities. The helical coils with tube strongly increase bunching, creating two collimated narrow-band proton beams from a broad and divergent TNSA distribution. The analytical model provides scaling of proton parameters as a function of laser facility features.

We determine bifurcations from gradual to explosive synchronization in coupled oscillator networks with higher-order coupling using self-consistency analysis. We obtain analytic bifurcation values for generic symmetric natural frequency distributions. We show that nonsynchronized, drifting, oscillators are non-negligible and play a crucial role in bifurcation. As such, the entire natural frequency distribution must be accounted for, rather than just the shape at the center. We verify our results for Lorentzian- and Gaussian-distributed natural frequencies.

We address the gas, liquid, and crystal phase behaviors of active Brownian particles in three dimensions. The nonequilibrium force balance at coexistence leads to equality of state functions for which we use power functional approximations. Motility-induced phase separation starts at a critical point and quickly becomes metastable against active freezing for Péclet numbers above a nonequilibrium triple point. The mean swim speed acts as a state variable, similar to the density of depletion agents in colloidal demixing. We obtain agreement with recent simulation results and correctly predict the strength of particle number fluctuations in active fluids.

We characterize collective diffusion of hardcore run-and-tumble particles (RTPs) by explicitly calculating the bulk-diffusion coefficient $D(\rho ,\gamma )$ for arbitrary density $\rho$ and tumbling rate $\gamma$, in systems on a $d$-dimensional periodic lattice. We study two minimal models of RTPs: Model I is the standard version of hardcore RTPs introduced in [Phys. Rev. E 89, 012706 (2014)], whereas model II is a long-ranged lattice gas (LLG) with hardcore exclusion, an analytically tractable variant of model I. We calculate the bulk-diffusion coefficient analytically for model II and numerically for model I through an efficient Monte Carlo algorithm; notably, both models have qualitatively similar features. In the strong-persistence limit $\gamma \to 0$ (i.e., dimensionless ratio $r_0\gamma /v\to 0$), with $v$ and $r_0$ being the self-propulsion speed and particle diameter, respectively, the fascinating interplay between persistence and interaction is quantified in terms of two length scales: (i) persistence length $l_p=v/\gamma$ and (ii) a “mean free path,” being a measure of the average empty stretch or gap size in the hopping direction. We find that the bulk-diffusion coefficient varies as a power law in a wide range of density: $D\propto {\rho }^{-\alpha }$, with exponent $\alpha$ gradually crossing over from $\alpha =2$ at high densities to $\alpha =0$ at low densities. As a result, the density relaxation is governed by a nonlinear diffusion equation with anomalous spatiotemporal scaling. In the thermodynamic limit, we show that the bulk-diffusion coefficient—for $\rho ,\gamma \to 0$ with $\rho /\gamma$ fixed—has a scaling form $D(\rho ,\gamma )=D^{\left(0\right)}\mathcal{F}(\rho av/\gamma )$, where $a\sim r_0^{d-1}$ is particle cross section and $D^{\left(0\right)}$ is proportional to the diffusion coefficient of noninteracting particles; the scaling function $\mathcal{F}\left(\psi \right)$ is calculated analytically for model II (LLG) and numerically for model I. Our arguments are independent of dimensions and microscopic details.

The richness of the mean-field solution of simple glasses leaves many of its features challenging to interpret. A minimal model that illuminates glass physics in the same way that the random energy model clarifies spin glass behavior would therefore be beneficial. Here we propose such a real-space model that is amenable to infinite-dimensional $d\to \infty$ analysis and is exactly solvable in finite $d$ in some regimes. By joining analysis with numerical simulations, we uncover geometrical signatures of the dynamical and jamming transitions and obtain insight into the origin of activated processes. Translating these findings into the context of standard glass formers further reveals the role played by nonconvexity in the emergence of Gardner and jamming physics.

We investigate the existence of self-trapped nonlinear waves with multiple phase singularities. Working with the cubic-quintic nonlinear Schrödinger equation, we focus on configurations with an antivortex surrounded by a triangular arrangement of vortices within a hosting soliton. We find stationary patterns that can be interpreted as stable self-trapped vortex crystals, constituting the first example of a configuration of this sort with space-independent potentials. Their stability is linked to their norm, transitioning from unstable to stable as their size increases, with an intermediate region where the structure is marginally unstable, undergoing a remarkable and puzzling self-reconstruction during its evolution.

We consider a discrete-time random walk on a one-dimensional lattice with space- and time-dependent random jump probabilities, known as the beta random walk. We are interested in the probability that, for a given realization of the jump probabilities (a sample), a walker starting at the origin at time $t=0$ is at position beyond $\xi \sqrt{T/2}$ at time $T$. This probability fluctuates from sample to sample and we study the large-deviation rate function, which characterizes the tails of its distribution at large time $T\gg 1$. It is argued that, up to a simple rescaling, this rate function is identical to the one recently obtained exactly by two of the authors for the continuum version of the model. That continuum model also appears in the macroscopic fluctuation theory of a class of lattice gases, e.g., in the so-called KMP model of heat transfer. An extensive numerical simulation of the beta random walk, based on an importance sampling algorithm, is found in good agreement with the detailed analytical predictions. A first-order transition in the tilted measure, predicted to occur in the continuum model, is also observed in the numerics.

We consider mixtures of oppositely driven particles, showing that their nonequilibrium steady states form lanes parallel to the drive, which coexist with transient jammed clusters where particles are temporarily immobilized. We analyze the interplay between these two types of nonequilibrium pattern formation, including their implications for macroscopic demixing perpendicular to the drive. Finite-size scaling analysis indicates that there is no critical driving force associated with demixing, which appears as a crossover in finite systems. We attribute this effect to the disruption of long-ranged order by the transient jammed clusters.

Turing bifurcation and Hopf bifurcation are two important kinds of transitions giving birth to inhomogeneous solutions, in spatial or temporal ways. On a disk, these two bifurcations may lead to equivariant Turing-Hopf bifurcations whose normal forms are given in three different cases in this paper. In addition, we analyzed the possible solutions for each normal form, which can guide us to find solutions with physical significance in real-world systems, and the breathing, standing wave-like, and rotating wave-like patterns are found in a delayed mussel-algae model.

A path integration (PI) approach that is progressive for studying the stochastic response driven by Lévy white noise is presented. First, a probability mapping is constructed, which decouples the domain of interest for the system state and the probability space derived from the randomness of Lévy white noise within a short time interval. Then, solving the probability mapping yields the short-time response of the system. Finally, the stochastic evolution of the system can be grasped in a stepwise manner based on the fundamental concept of the PI method. The applicability and effectiveness of our approach in addressing the transient and stationary responses under Lévy white noises are verified by Monte Carlo simulation results. Moreover, the advances in utilization of this method are that it eliminates the restriction of the previous PI method on the controlling parameter of Lévy white noises, and it is highly efficient for solving responses of systems under Lévy white noises.

This article reveals a specific category of solutions for the $1+1$ variable order (VO) nonlinear fractional Fokker-Planck equations. These solutions are formulated using VO $q$-Gaussian functions, granting them significant versatility in their application to various real-world systems, such as financial economy areas spanning from conventional stock markets to cryptocurrencies. The VO $q$-Gaussian functions provide a more robust expression for the distribution function of price returns in real-world systems. Additionally, we analyzed the temporal evolution of the anomalous characteristic exponents derived from our study, which are associated with the long-term (power-law) memory in time series data and autocorrelation patterns.

Interacting many-body physical systems ranging from neural networks in the brain to folding proteins to self-modifying electrical circuits can learn to perform diverse tasks. This learning, both in nature and in engineered systems, can occur through evolutionary selection or through dynamical rules that drive active learning from experience. Here, we show that learning in linear physical networks with weak input signals leaves architectural imprints on the Hessian of a physical system. Compared to a generic organization of the system components, (a) the effective physical dimension of the response to inputs decreases, (b) the response of physical degrees of freedom to random perturbations (or system “susceptibility”) increases, and (c) the low-eigenvalue eigenvectors of the Hessian align with the task. Overall, these effects embody the typical scenario for learning processes in physical systems in the weak input regime, suggesting ways of discovering whether a physical network may have been trained.

Electrohydrodynamic ion transport has been studied in nanotubes, nanoslits, and nanopores to mimic the advanced functionalities of biological ion channels. However, probing how the intricate interplay between the electrical and mechanical interactions affects ion conduction in asymmetric nanoconduits presents further obstacles. Here, ion transport across a conical nanopore embedded in a polarizable membrane under an electric field and pressure is analyzed by numerically solving a continuum model based on the Poisson, Nernst-Planck, and Navier-Stokes equations. We report an anomalous ionic current depletion, of up to 75%, and an unexpected rise in current rectification when pressure is exerted along the external electric field. Membrane polarization is revealed as the prerequisite to obtain this previously undetected electrohydrodynamic coupling. The electric field induces large surface charges at the pore tip due to its conical shape, creating nonuniform electrical double layers (EDL) with a massive accumulation of electrolyte ions near the orifice. Once applied, the pressure distorts the quasiequilibrium distribution of the EDL ions to influence the nanopore conductivity. Our fundamental approach to inspect the effect of pressure on the channel EDL (and thus ionic conductance) in contrast to its effect on the current arising from the hydrodynamic streaming of ions further explains the pressure-sensitive ion transport in different nanochannels and physical regimes manifested in past experiments, including the hitherto inexplicit mechanism behind the mechanically activated ion transport in carbon nanotubes. This enhances our broad understanding of nanoscale electrohydrodynamic ion transport, yielding a platform to build nanofluidic devices and ionic circuits with more robust and tunable responses to electrical and mechanical stimuli.

A generalized one-dimensional telegrapher equation associated with an intermittent change of sign in the velocity of a Kac's flight has been proposed. To solve this random differential equation, we used the enlarged master equation approach to obtain the exact differential equation for the evolution of a normalized positive distribution. This distribution is associated with a generalized finite-velocity diffusionlike process. We studied the robustness of the ballistic regime, the cutoff of its domain, and the time-dependent Gaussian convergence. The second moment for the evolution of the profile has been studied as a function of non-Poisson statistics (possibly intermittent) for the time intervals ${\mathrm{\Delta }}_{ij}$ in the Kac's flight. Numerical results for the evolution of sharp and wide initial profiles have also been presented. In addition, for comparison with a non-Gaussian process at all times, we have revisited the non-Markov Poisson's flight with exponential pulses. A theory for generalized random flights with intermittent stochastic velocity and in the presence of a force is also presented, and the stationary distribution for two classes of potential has been obtained.

We study the average and the standard deviation of the entanglement entropy of highly excited eigenstates of the integrable interacting spin-$\frac{1}{2} XYZ$ chain away from and at special lines with $\text{U}\left(1\right)$ symmetry and supersymmetry. We universally find that the average eigenstate entanglement entropy exhibits a volume-law coefficient that is smaller than that of quantum-chaotic interacting models. At the supersymmetric point, we resolve the effect that degeneracies have on the computed averages. We further find that the normalized standard deviation of the eigenstate entanglement entropy decays polynomially with increasing system size, which we contrast with the exponential decay in quantum-chaotic interacting models. Our results provide state-of-the art numerical evidence that integrability in spin-$\frac{1}{2}$ chains reduces the average and increases the standard deviation of the entanglement entropy of highly excited energy eigenstates when compared with those in quantum-chaotic interacting models.

The supercritical region is often described as uniform with no definite transitions. The distinct behaviors of the matter therein, e.g., as liquidlike and gaslike, however, suggest “supercritical boundaries.” Here we provide a mathematical description of these phenomena by revisiting the Yang-Lee theory and introducing a complex phase diagram, specifically a four-dimensional (4D) one with complex $T$ and $p$. While the traditional 2D phase diagram with real temperature $T$ and pressure $p$ values (the physical plane) lacks Lee-Yang (LY) zeros beyond the critical point, preventing the occurrence of criticality, the off-plane zeros in this 4D scenario still induce critical anomalies in various physical properties. This relationship is evidenced by the correlation between the Widom line and LY edges in van der Waals, 2D Ising model, and water. The diverged supercritical boundaries manifest the high-dimensional feature of the phase diagram: e.g., when LY zeros of complex $T$ or $p$ are projected onto the physical plane, boundaries defined by isobaric heat capacity $C_p$ or isothermal compression coefficient $K_T$ emanates. These results demonstrate the incipient phase transition nature of the supercritical matter.