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We show that the Gross-Pitaevskii equation coupled with the wave equation for a wire (GP-W) provides a natural theoretical framework for understanding recent experiments employing a nanowire to detect a single quantum vortex in superfluid $^4 {\rm He}$. We uncover the complete spatiotemporal evolution of such wire-based vortex detection via direct numerical simulations of the GP-W system. Furthermore, by computing the spatiotemporal spectrum, we obtain the vortex-capture-induced change in the oscillation frequency of the wire. We quantify this frequency shift by plotting the wire's oscillation frequency versus time and obtain results that closely match experimental observations. In addition, we provide analytical support for our numerical results by deriving the dispersion relation for the oscillating wire, with and without a trapped vortex., Comment: 7 pages, 3 figures

Liquid-droplet coalescence and the mergers of liquid lenses are problems of great practical and theoretical interest in fluid dynamics and the statistical mechanics of multi-phase flows. During such mergers, there is an interesting and intricate interplay between the shapes of the interfaces, separating two phases, and the background flow field. In experiments, it is easier to visualize concentration fields than to obtain the flow field. We demonstrate that two-dimensional (2D) encoder-decoder CNNs, 2D U-Nets, and three-dimensional (3D) U-Nets can be used to obtain flow fields from concentration fields here. To train these networks, we use concentration and flow fields, which we obtain from extensive direct numerical simulations (DNSs) of (a) the coalescence of two circular droplets in the two-component 2D Cahn-Hilliard-Navier-Stokes (CHNS) partial differential equations (PDEs), (b) liquid-lens mergers in the three-component 2D CHNS PDEs, and (c) spherical-droplet coalescence in the two-component 3D CHNS PDEs. We then show that, given test images of concentration fields, our trained models accurately predict the flow fields at both high and low Ohnesorge numbers $Oh$ (a dimensionless ratio of viscous stresses to the inertial and surface-tension forces). Using autoencoders and fully connected neural networks, we also investigate the mapping between the concentration and vorticity fields via low-dimensional latent variables for droplet mergers in the 2D CHNS system. We compare the accuracies of flow-field reconstruction based on the two approaches we employ. Finally, we use data from recent experiments on droplet coalescence to show how our method can be used to obtain the flow field from measurements of the concentration field.

Recent results suggest that highly active, chaotic, non-equilibrium states of living fluids might share much in common with high Reynolds number, inertial turbulence. We now show, by using a hydrodynamical model, the onset of intermittency and the consequent multiscaling of Eulerian and Lagrangian structure functions as a function of the bacterial activity. Our results bridge the worlds of low and high Reynolds number flows as well as open up intriguing possibilities of what makes flows intermittent.

We demonstrate the existence of interface-induced turbulence, an emergent nonequilibrium statistically steady state (NESS) with spatiotemporal chaos, which is induced by interfacial fluctuations in low-Reynolds-number binary-fluid mixtures. We uncover the properties of this NESS via direct numerical simulations (DNSs) of cellular flows in the Cahn-Hilliard-Navier-Stokes (CHNS) equations for binary fluids. We show that, in this NESS, the shell-averaged energy spectrum $E(k)$ is spread over several decades in the wavenumber $k$ and it exhibits a power-law region, indicative of turbulence but without a conventional inertial cascade. To characterize the statistical properties of this turbulence, we compute, in addition to $E(k)$, the time series $e(t)$ of the kinetic energy and its power spectrum, scale-by-scale energy transfer as a function of $k$, and the energy dissipation resulting from interfacial stresses. Furthermore, we analyze the mixing properties of this low-Reynolds-number turbulence via the mean-square displacement (MSD) of Lagrangian tracer particles, for which we demonstrate diffusive behavior at long times, a hallmark of strong mixing in turbulent flows., Comment: 9 pages, 6 figures

We investigate the complex-time analytic structure of solutions of the 3D-axisymmetric, wall-bounded, incompressible Euler equations, by starting with the initial data proposed in Luo and Hou (2014), to study a possible finite-time singularity. We use our pseudospectral Fourier-Chebyshev method, with quadruple-precision arithmetic, to compute the time-Taylor series coefficients of the flow fields, up to a high order. We show that the resulting approximations display early-time resonances; the initial spatial location of these structures is different from that for the tygers, which we have obtained in Kolluru et al. (2022). We then perform asymptotic analysis of the Taylor-series coefficients, by using generalised ratio methods, to extract the location and nature of the convergence-limiting singularities and demonstrate that these singularities are distributed around the origin, in the complex-t2 plane, along two curves that resemble the shape of an eye. We obtain similar results for the 1D wall-approximation (of the full 3D-axisymmetric Euler equation) called the 1D HL model, for which we use Fourier-pseudospectral methods to compute the time-Taylor series coefficients of the flow fields. Our work examines the link between tygers, in Galerkin-truncated pseudospectral studies, and early-time resonances, in truncated time-Taylor expansions of solutions of PDEs, such as those we consider., Comment: 17 pages, 11 figures

We develop a theoretical framework that allows us to explore the coupled motion of neutron-superfluid vortices and proton-superconductor flux tubes in a gravitationally collapsed condensate, which describe neutron stars that form pulsars. Our framework uses the 3D Gross-Pitaevskii-Poisson-Equation (GPPE) for neutron Cooper pairs, the Real-Time-Ginzburg-Landau equation (RTGLE) for proton Cooper pairs, the Maxwell equations for the vector potential ${\bf A}$, and Newtonian gravity and interactions, both direct and induced by the Poisson equation, between the neutron and proton subsystems. For a pulsar we include a crust potential, characterized by an angle $\theta$, and frictional drag. By carrying out extensive direct numerical simulations, we obtain a variety of interesting results. We show that a rotating proton superconductor generates a uniform London magnetic field, which changes the field distribution inside flux tubes. In the absence of any direct interaction between the two species, they interact through the gravitational Poisson equation. The presence of attractive (repulsive) density-density interaction leads to the attraction (repulsion) between neutron vortices and proton flux tubes. The inclusion of the current-current interaction and the complete Maxwell equations allows us to quantify the entrainment effect that leads to induced magnetization of neutron vortices. We show that, with a strong external magnetic field ${\bf B}_{\rm ext}$, proton flux tubes are anchored to the crust, whereas neutron vortices leave the condensate and lead to abrupt changes of the crust angular momentum ${\rm J}_c$. The frictional term in the dynamical equation for $\theta$ yields stick-slip dynamics that leads, in turn, to glitches in the time series of ${\rm J}_c$. By calculating various statistical properties of this time series, we demonstrate that they display self-organised criticality(SOC)., Comment: 18 pages, 13 figures

We investigate the role of interfaces as transport barriers in binary-fluid turbulence by employing Lagrangian tracer particles. The Cahn-Hilliard-Navier-Stokes (CHNS) system of partial differential equations provides a natural theoretical framework for our investigations. For specificity, we utilize the two-dimensional (2D) CHNS system. We capture efficiently interfaces and their fluctuations in 2D binary-fluid turbulence by using extensive pseudospectral direct numerical simulations (DNSs) of the 2D CHNS equations. We begin with $n$ tracers within a droplet of one phase and examine their dispersal into the second phase. The tracers remain within the droplet for a long time before emerging from it, so interfaces act as transport barriers in binary-fluid turbulence. We show that the fraction of the number of particles inside the droplet decays exponentially and is characterized by a decay time $\tau_{\xi}\sim R_0^{3/2}$ that increases with $R_0$, the radius of the initially circular droplet. Furthermore, we demonstrate that the average first-passage time $\langle \tau \rangle$ for tracers inside a droplet is orders of magnitude larger than it is for transport out of a hypothetical circle with the same radius as the initially circular droplet. We examine the roles of the Okubo-Weiss parameter $\Lambda$, the fluctuations of the droplet perimeter, and the probability distribution function of $\cos(\theta)$, with $\theta$ the angle between the fluid velocity and the normal to a droplet interface, in trapping tracers inside droplets. We mention possible generalisations of our study., Comment: 9 pages, 5 figures

Energy cascades lie at the heart of the dynamics of turbulent flows. In a recent study of turbulence in fluids with odd-viscosity [de Wit \textit{et al.}, Nature \textbf{627}, 515 (2024)], the two-dimensionalization of the flow at small scales leads to the arrest of the energy cascade and selection of an intermediate scale, between the forcing and the viscous scales. To investigate the generality of this phenomenon, we study a shell model that is carefully constructed to have three-dimensional turbulent dynamics at small wavenumbers and two-dimensional turbulent dynamics at large wavenumbers. The large scale separation that we can achieve in our shell model allows us to examine clearly the interplay between these dynamics, which leads to an arrest of the energy cascade at a transitional wavenumber and an associated accumulation of energy at the same scale. Such pile-up of energy around the transitional wavenumber is reminiscent of the formation of condensates in two-dimensional turbulence, \textit{but, in contrast, it occurs at intermediate wavenumbers instead of the smallest wavenumber, Comment: Typos corrected

We introduce a novel model, comprising self-avoiding surfaces and incorporating edges and tubules, that is designed to characterize the structural morphologies and transitions observed within the endoplasmic reticulum (ER). By employing discretized models, we model smooth membranes with triangulated surfaces, and we utilize numerical variational methods to minimize energies associated with periodic morphologies. Our study obtains phases, their morphologies, and their transitions and examines their dependence on the membrane chemical potential, the line tensions, and the positive Gaussian curvature stiffness. By starting with diverse topological structures, we explore shape variations by using Surface Evolver, while maintaining fixed topology. Notably, we identify the region of parameter space where the model displays lamellae, with a lattice of helical edges connecting the layers; this resembles structures that have been observed in the rough ER. Furthermore, our investigation reveals an intricate phase diagram with periodic structures, including flat lamellar sheets, sponge phases, and configurations comprising tubules with junctions, which are akin to the morphology of the smooth ER. An estimation of lattice parameters is achieved through fluctuation analysis. Significantly, our model predicts a transition between homotopically equivalent lamellae, with helical edges and configurations featuring tubules with junctions., Comment: 15 pages, 15 figures

Spectral methods yield numerical solutions of the Galerkin-truncated versions of nonlinear partial differential equations involved especially in fluid dynamics. In the presence of discontinuities, such as shocks, spectral approximations develop Gibbs oscillations near the discontinuity. This causes the numerical solution to deviate quickly from the true solution. For spectral approximations of the 1D inviscid Burgers equation, nonlinear wave resonances lead to the formation of tygers in well-resolved areas of the flow, far from the shock. Recently, Besse(to be published) has proposed novel spectral relaxation (SR) and spectral purging (SP) schemes for the removal of tygers and Gibbs oscillations in spectral approximations of nonlinear conservation laws. For the 1D inviscid Burgers equation, it is shown that the novel SR and SP approximations of the solution converge strongly in L2 norm to the entropic weak solution, under an appropriate choice of kernels and related parameters. In this work, we carry out a detailed numerical investigation of SR and SP schemes when applied to the 1D inviscid Burgers equation and report the efficiency of shock capture and the removal of tygers. We then extend our study to systems of nonlinear hyperbolic conservation laws - such as the 2x2 system of the shallow water equations and the standard 3x3 system of 1D compressible Euler equations. For the latter, we generalise the implementation of SR methods to non-periodic problems using Chebyshev polynomials. We then turn to singular flow in the 1D wall approximation of the 3D-axisymmetric wall-bounded incompressible Euler equation. Here, in order to determine the blowup time of the solution, we compare the decay of the width of the analyticity strip, obtained from the pure pseudospectral method, with the improved estimate obtained using the novel spectral relaxation scheme.

We uncover a new type of turbulence -- activity-induced homogeneous and isotropic turbulence in a model that has been employed to investigate motility-induced phase separation (MIPS) in a system of microswimmers. The active Cahn-Hilliard-Navier-Stokes equations (CHNS), also called active model H, provides a natural theoretical framework for our study. In this CHNS model, a single scalar order parameter $\phi$, positive (negative) in regions of high (low) microswimmer density, is coupled with the velocity field $\bm u$. The activity of the microswimmers is governed by an activity parameter $\zeta$ that is positive for \textit{extensile} swimmers and negative for \textit{contractile} swimmers. With extensile swimmers, this system undergoes complete phase separation, which is similar to that in binary-fluid mixtures. By carrying out pseudospectral direct numerical simulations (DNSs), we show, for the first time, that this model (a) develops an emergent nonequilibrium, but statistically steady, state (NESS) of active turbulence, for the case of contractile swimmers, if $\zeta$ is sufficiently large and negative and (b) this turbulence arrests the phase separation. We quantify this suppression by showing how the coarsening-arrest length scale does not grow indefinitely, with time $t$, but saturates at a finite value at large times. We characterise the statistical properties of this active-scalar turbulence by employing energy spectra and fluxes and the spectrum of $\phi$. For sufficiently high Reynolds numbers, the energy spectrum $\mathcal E(k)$ displays an inertial range, with a power-law dependence on the wavenumber $k$. We demonstrate that, in this range, the flux $\Pi(k)$ assumes a nearly constant, negative value, which indicates that the system shows an inverse cascade of energy, even though energy injection occurs over a wide range of wavenumbers in our active-CHNS model., Comment: 8 pages, 5 figures

Lagrangian pair dispersion provides insights into mixing in turbulent flows. By direct numerical simulations (DNS) we show that the statistics of pair dispersion in the randomly forced two-dimensional Burgers equation, which is a typical model of shock-dominated turbulence, is very different from its incompressible counterpart because Lagrangian particles get trapped in shocks. We develop a heuristic theoretical framework that accounts for this -- a generalization of the multifractal model -- whose prediction of the scaling of Lagrangian exit times agrees well with our DNS.

We show how to use the cubic-quintic Gross-Pitaevskii-Poisson equation (cq-GPPE) and the cubic-quintic Stochastic Ginzburg-Landau-Poisson equation (cq-SGLPE) to investigate the gravitational collapse of a tenuous axionic gas into a collapsed axionic condensate for both zero and finite temperature $T$. At $T=0$, we use a Gaussian Ansatz for a spherically symmetric density to obtain parameter regimes in which we might expect to find compact axionic condensates. We then go beyond this Ansatz, by using the cq-SGLPE to investigate the dependence of the axionic condensate on the gravitational strength $G$ at $T = 0$. We demonstrate that, as $G$ increases, the equilibrium configuration goes from a tenuous axionic gas, to flat sheets or $\textit{Zeldovich pancakes}$, cylindrical structures, and finally a spherical axionic condensate. By varying $G$, we show that there are first-order phase transitions, as the system goes from one of these structures to the next one; we find hysteresis loops that are associated with these transitions. We examine these states and the transitions between these states via the Fourier truncated cq-GPPE; and we also obtain the thermalized $T > 0$ states from the cq-SGLPE; the transitions between these states yield thermally driven first-order phase transitions and their associated hysteresis loops. Finally, we discuss how our cq-GPPE approach can be used to follow the spatiotemporal evolution of a rotating axionic condensate and also a rotating binary-axionic-condensate system; in particular, we demonstrate, in the former, the emergence of vortices at large angular speeds $\Omega$ and, in the latter, the rich dynamics of the mergers of the components of this binary system, which can yield vortices in the process of merging., Comment: 13 pages, 8 figures

We demonstrate that the three-phase Cahn-Hilliard-Navier-Stokes (CHNS3) system provides a natural theoretical framework for studying liquid-lens coalescence, which has been investigated in recent experiments. Our extensive direct numerical simulations (DNSs) of lens coalescence, in the two and three dimensional (2D and 3D) CHNS3, uncover the rich spatiotemporal evolution of the fluid velocity $\bf u$ and vorticity $\omega$, the concentration fields $c_1, \, c_2,$ and $c_3$ of the three liquids, and a generalized Laplace pressure $P^G_\mathcal{L}$, which we define in terms of these concentrations via a Poisson equation. We find, in agreement with experiments, that as the lenses coalesce, their neck height $h(t) \sim t^{\alpha_v}$, with $\alpha_v \simeq 1$ in the viscous regime, and $h(t) \sim t^{\alpha_i}$, with $\alpha_i \simeq 2/3$ in the inertial regime. We obtain the crossover from the viscous to the inertial regimes as a function of the Ohnesorge number $Oh$, a dimensionless combination of viscous stresses and inertial and surface tension forces. We show that a vortex quadrupole, which straddles the neck of the merging lenses, and $P^G_\mathcal{L}$ play crucial roles in distinguishing between the viscous- and inertial-regime growths of the merging lenses. In the inertial regime we find signatures of turbulence, which we quantify via kinetic-energy and concentration spectra. Finally, we examine the merger of asymmetric lenses, in which the initial stages of coalescence occur along the circular parts of the lens interfaces; in this case, we obtain power-law forms for the $h(t)$ with inertial-regime exponents that lie between their droplet-coalescence and lens-merger counterparts., Comment: 9 pages, 8 figures

Focal arrhythmias, which arise from delayed afterdepolarizations (DADs), are observed in various pathophysiological heart conditions; these can lead to sudden cardiac death. A clear understanding of the electrophysiological factors of cardiac myocytes, which lead to DADs, can suggest pharmacological targets that can eliminate DAD-induced arrhythmias. Therefore, we carry out multiscale investigations of two mathematical models for human-ventricular myocytes, namely, the ten Tusscher-Panfilov and the HuVEC15 model, at the levels of single myocytes, one- and two-dimensional (1D and 2D) tissue, and anatomically realistic bi-ventricular domains. By using continuation analysis, we uncover steady- to oscillatory-state transitions in the Ca\textsuperscript{2+} concentrations and show that they lead to DADs. We demonstrate that the Sarco/endoplasmic reticulum Ca\textsuperscript{2+}-ATPase (SERCA) pump uptake rate and the Ca\textsuperscript{2+} leak through the ryanodine-receptor (RyR) channel impact this transition significantly. We show that the frequencies and amplitudes of the DADs are key features that can be used to classify them into three types. By carrying out detailed parameter-sensitivity analyses, we identify the electrophysiological parameters, in the myocyte models, that most affect these key features. We then obtain stability (or phase) diagrams for different types of DADs. We demonstrate that the Na\textsuperscript{+}/Ca\textsuperscript{2+} exchanger plays a protective role by suppressing DADs in the TP06 model. We present tissue simulations to illustrate how arrhythmogenic premature ventricular complexes (PVCs) emerge from patches of DAD cells when we pace the tissue. We discuss the implications of our results for some DAD-induced ventricular arrhythmias, which we examine in detail in the companion Paper II., Comment: The draft contains 27 pages, 23 figures and 73 citations

Disturbances in calcium homeostasis in a cardiac myocyte can lead to calcium-overload conditions and abnormal calcium releases, which occur primarily in the following two phases of the action potential (AP): (a) triggered or late calcium release (LCR) during the plateau phase; (b) spontaneous calcium release (SCR) during the diastolic interval (DI). Experimental and numerical studies of LCRs and SCRs have suggested that these abnormal calcium releases can lead to triggered excitations and, thence to life-threatening ventricular arrhythmias. We explore this suggestion in detail by building on our work in the previous accompanying Paper I, where we have studied abnormal calcium releases and delayed afterdepolarizations (DADs) in two state-of-the-art mathematical models for human ventricular myocytes. Here, we carry out a detailed \textit{in-silico} study of one of these models, namely, the ten Tusscher-Panfilov TP06~\cite{ten2006alternans} model. We increase the L-type Ca-channel current $I_{\rm{CaL}}$ to trigger LCRs, and calcium leak through the ryanodine receptor (RyR) to trigger SCRs, in the myocyte. We then perform multiscale simulations of coupled TP06-model myocytes in tissue in one-, two-, and three-dimensional (1D, 2D, and 3D) domains, with clumps of DAD-capable myocytes, to demonstrate how these clumps precipitate premature ventricular complexes (PVCs) that lead, in turn, to fibrillatory excitations like spiral and scroll waves. We examine possible pharmacological implications of our study for the class of ventricular arrhythmias that result from Ca\textsuperscript{2+} overload., Comment: This manuscript contains 17 pages, 14 figures and 79 citations

We develop a minimal hydrodynamic model, without an orientational order parameter, for assemblies of contractile swimmers encapsulated in a droplet of a binary-fluid emulsion. Our model uses two coupled scalar order parameters, $\phi$ and $\psi$, which capture, respectively, the droplet interface and the activity of the contractile swimmers inside this droplet. These order parameters are also coupled to the velocity field $\bm u$. At low activity, our model yields a self-propelling droplet whose center of mass $(CM)$ displays rectilinear motion, powered by the spatiotemporal evolution of the field $\psi$, which leads to a time-dependent vortex dipole at one end of the droplet. As we increase the activity, this $CM$ shows chaotic super-diffusive motion, which we characterize by its mean-square displacement; and the droplet interface exhibits multifractal fluctuations, whose spectrum of exponents we calculate. We explore the implications of our results for experiments on active droplets of contractile swimmers., Comment: 5 figures, 9 pages

The incompressible Toner-Tu (ITT) partial differential equations (PDEs) are an important example of a set of active-fluid PDEs. While they share certain properties with the Navier-Stokes equations (NSEs), such as the same scaling invariance, there are also important differences. The NSEs are usually considered in either the decaying or the additively forced cases, whereas the ITT equations have no additive forcing. Instead, they include a linear, activity term $\alpha \bu$ ($\bu$ is the velocity field) which pumps energy into the system, but also a negative $\bu|\bu|^{2}$-term which provides a platform for either frozen or statistically steady states. Taken together, these differences make the ITT equations an intriguing candidate for study using a combination of PDE analysis and pseudo-spectral direct numerical simulations (DNSs). In the $d=2$ case, we have established global regularity of solutions, but we have also shown the existence of bounded hierarchies of weighted, time-averaged norms of both higher derivatives and higher moments of the velocity field. Similar bounded hierarchies for Leray-type weak solutions have also been established in the $d=3$ case. We present results for these norms from our DNSs in both $d=2$ and $d=3$, and contrast them with their Navier-Stokes counterparts.

We carry out a detailed study of dynamic multiscaling in the turbulent nonequilibrium, but statistically steady, state of the stochastically forced one-dimensional Burgers equation. We introduce the concept of $\textit{interval collapse times}$ $\tau_{\rm col}$, the time taken for an interval of length $\ell$, demarcated by a pair of Lagrangian tracers, to collapse at a shock. By calculating the dynamic scaling exponent of the order-$p$ moment of $\tau_{\rm col}$, we show that (a) there is $\textit{not one but an infinity of characteristic time scales}$ and (b) the probability distribution function of $\tau_{\rm col}$ is non-Gaussian and has a power-law tail. Our study is based on (a) a theoretical framework that allows us to obtain dynamic-multiscaling exponents analytically, (b) extensive direct numerical simulations, and (c) a careful comparison of the results of (a) and (b). We discuss possible generalizations of our work to dimensions $d >1 $, for the stochastically forced Burgers equation, and to other compressible flows that exhibit turbulence with shocks.

We use the mean-bacterial-velocity model to investigate the \textit{irreversibility} of two-dimensional (2D) \textit{bacterial turbulence} and to compare it with its 2D fluid-turbulence counterpart. We carry out extensive direct numerical simulations of Lagrangian tracer particles that are advected by the velocity field in this model. Our work uncovers an important, qualitative way in which irreversibility in bacterial turbulence is different from its fluid-turbulence counterpart: For large positive (or large but negative) values of the \textit{friction} (or \textit{activity}) parameter, the probability distribution functions of energy increments, along tracer trajectories, or the power are \textit{positively} skewed; so irreversibility in bacterial turbulence can lead, on average, to \textit{particles gaining energy faster than they lose it}, which is the exact opposite of what is observed for tracers in 2D fluid turbulence.

Spiral waves are ubiquitous spatiotemporal patterns that occur in various excitable systems. In cardiac tissue, the formation of these spiral waves is associated with life-threatening arrhythmias, and, therefore, it is important to study the dynamics of these waves. Tracking the trajectory of a spiral-wave tip can reveal important dynamical features of a spiral wave, such as its periodicity, and its vulnerability to instabilities. We show how to employ the data-driven spectral-decomposition method, called dynamic mode decomposition (DMD), to detect a spiral tip trajectory (TT) in three settings: (1) a homogeneous medium; (2) a heterogeneous medium; and (3) with external noise. We demonstrate that the performance of DMD-based TT (DMDTT) is either comparable to or better than the conventional tip-tracking method called the isopotential-intersection method (IIM) in the cases (1)-(3): (1) Both IIM and DMDTT capture TT patterns at small values of the image-sampling interval $\tau$; however, IIM is more sensitive than DMDTT to the changes in $\tau$. (2) In a heterogeneous medium, IIM yields TT patterns, but with a background of scattered noisy points, which is suppresed in DMDTT. (3) DMDTT is more robust to external noise than IIM. We show, finally, that DMD can be used to reconstruct, and hence predict, the spatiotemporal evolution of spiral waves in the models we study.

We present the first experimental evidence for the multifractality of a transport property at a topological phase transition. In particular, we show that conductance fluctuations display multifractality at the integer-quantum-Hall $\nu=1 \longleftrightarrow \nu=2$ plateau-to-plateau transition in a high-mobility mesoscopic graphene device. We establish that to observe this multifractality, it is crucial to work with very high-mobility devices with a well-defined critical point. This multifractality gets rapidly suppressed as the chemical potential moves away from these critical points. Our combination of multifractal analysis with state-of-the-art transport measurements at a topological phase transition provides a novel method for probing such phase transitions in mesoscopic devices., Comment: 10 pages, 4 figures

We use pseudospectral direct numerical simulations (DNSs) to solve the three-dimensional (3D) Hall-Vinen-Bekharevich-Khalatnikov (HVBK) model of superfluid Helium. We then explore the statistical properties of inertial particles, in both coflow and counterflow superfluid turbulence (ST) in the 3D HVBK system; particle motion is governed by a generalization of the Maxey-Riley-Gatignol equations. We first characterize the anisotropy of counterflow ST by showing that there exist large vortical columns. The light particles show confined motion as they are attracted towards these columns and they form large clusters; by contrast, heavy particles are expelled from these vortical regions. We characterise the statistics of such inertial particles in 3D HVBK ST: (1) The mean angle $\Theta(\tau)$, between particle positions, separated by the time lag $\tau$, exhibits two different scaling regions in (a) dissipation and (b) inertial ranges, for different values of the parameters in our model; in particular, the value of $\Theta(\tau)$, at large $\tau$, depends on the magnitude of ${\bf U}_{ns}$. (2) The irreversibility of 3D HVBK turbulence is quantified by computing the statistics of energy increments for inertial particles. (3) The probability distribution function (PDF) of energy increments is of direct relevance to recent experimental studies of irreversibility in superfluid turbulence; we find, in agreement with these experiments, that, for counterflow ST, the skewness of this PDF is less pronounced than its counterparts for coflow ST or for classical-fluid turbulence., Comment: 15 pages, 13 figures

Spiral waves of excitation in cardiac tissue are associated with life-threatening cardiac arrhythmias. It is, therefore, important to study the electrophysiological factors that affect the dynamics of these spiral waves. By using an electrophysiologically detailed mathematical model of a myocyte (cardiac cell), we study the effects of cellular parameters, such as membrane-ion-channel conductances, on the properties of the action-potential (AP) of a myocyte. We then investigate how changes in these properties, specifically the upstroke velocity and the AP duration (APD), affect the frequency $\omega$ of a spiral wave in the mathematical model that we use for human-ventricular tissue. We find that an increase (decrease) in this upstroke-velocity or a decrease (increase) in the AP duration increases (decreases) $\omega$. We also study how other intercellular factors, such as the fibroblast-myocyte coupling, diffusive coupling strength, and the effective number of neighboring myocytes, modulate $\omega$. Finally, we demonstrate how a spiral wave can drift to a region with a high density of fibroblasts. Our results provide a natural explanation for the anchoring of spiral waves in highly fibrotic regions in fibrotic hearts.

The three-dimensional (3D) Hall magnetohydrodynamics (HMHD) equations are often used to study turbulence in the solar wind. Some earlier studies have investigated the statistical properties of 3D HMHD turbulence by using simple shell models or pseudospectral direct numerical simulations (DNSs) of the 3D HMHD equations; these DNSs have been restricted to modest spatial resolutions and have covered a limited parameter range. To explore the dependence of 3D HMHD turbulence on the Reynolds number $Re$ and the ion-inertial scale $d_{i}$, we have carried out detailed pseudospectral DNSs of the 3D HMHD equations and their counterparts for 3D MHD ($d_{i} = 0$). We present several statistical properties of 3D HMHD turbulence, which we compare with 3D MHD turbulence by calculating (a) the temporal evolution of the energy-dissipation rates and the energy, (b) the wave-number dependence of fluid and magnetic spectra, (c) the probability distribution functions (PDFs) of the cosines of the angles between various pairs of vectors, such as the velocity and the magnetic field, and (d) various measures of the intermittency in 3D HMHD and 3D MHD turbulence.

Infarction- or ischaemia-induced cardiac fibrosis can be arrythmogenic. We use mathematcal models for diffuse fibrosis ($\mathcal{DF}$), interstitial fibrosis ($\mathcal{IF}$), patchy fibrosis ($\mathcal{PF}$), and compact fibrosis ($\mathcal{CF}$) to study patterns of fibrotic cardiac tissue that have been generated by new mathematical algorithms. We show that the fractal dimension $\mathbb{D}$, the lacunarity $\mathcal{L}$, and the Betti numbers $\beta_0$ and $\beta_1$ of such patterns are \textit{fibrotic-tissue markers} that can be used to characterise the arrhythmogenicity of different types of cardiac fibrosis. We hypothesize, and then demonstrate by extensive \textit{in silico} studies of detailed mathematical models for cardiac tissue, that the arrhytmogenicity of fibrotic tissue is high when $\beta_0$ is large and the lacunarity parameter $b$ is small., Comment: Manuscript: 6 pages 7 figures Supplemental Material: 4 pages 6 figures

Antibubbles, which consist of a shell of a low-density fluid inside a high-density fluid, have several promising applications. We show, via extensive direct numerical simulations (DNSs), in both two and three dimensions (2D and 3D), that the spatiotemporal evolution of antibubbles can be described naturally by the coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations for a binary fluid. Our DNSs capture elegantly the gravity-induced thinning and breakup of an antibubble via the time evolution of the Cahn-Hilliard scalar order parameter field $\phi$, which varies continuously across interfaces, so we do not have to enforce complicated boundary conditions at the moving antibubble interfaces. To ensure that our results are robust, we supplement our CHNS simulations with sharp-interface Volume-of-Fluid (VoF) DNSs. We track the thickness of the antibubble and calculate the dependence of the lifetime of an antibubble on several parameters; we show that our DNS results agree with various experimental results; in particular, the velocity with which the arms of the antibubble retract after breakup scales as $\sigma^{1/2}$, where $\sigma$ is the surface tension., Comment: Ancillary folder contains movies and supplementary material -->

We develop a Fourier-Chebyshev pseudospectral direct numerical simulation (DNS) to examine a potentially singular solution of the radially bounded, three-dimensional (3D), axisymmetric Euler equations [G. Luo and T.Y. Hou, Proc. Natl. Acad. Sci. USA, 111.36 (2014)]. We demonstrate that: (a) the time of singularity is preceded, in any spectrally truncated DNS, by the formation of oscillatory structures called tygers, first investigated in the one-dimensional (1D) Burgers and two-dimensional (2D) Euler equations; (b) the analyticity-strip method can be generalized to obtain an estimate for the (potential) singularity time., Comment: 17 pages. 13 figures

We present pseudospectral direct-numerical-simulation (DNS) studies of the three-dimensional magnetohydrodynamic (MHD) equations (3DRFMHD) with a stochastic force that has zero mean and a variance $\sim k^{-3}$, where $k$ is the wavenumber, because 3DRFMHD is used in field-theoretic studies of the scaling of energy spectra in MHD turbulence. We obtain velocity and magnetic-field spectra and structure functions and, from these, the multiscaling exponent ratios $\zeta_p/\zeta_3$, by using the extended self similarity (ESS) procedure. These exponent ratios lie within error bars of their counterparts for conventional three-dimensional MHD turbulence (3DMHD). We then carry out a systematic comparison of the statistical properties of 3DMHD and 3DRFMHD turbulence by examining various probability distribution functions (PDFs), joint PDFs, and isosurfaces of of, e.g., the moduli of the vorticity and the current density for three magnetic Prandtl numbers ${\rm Pr_M} = 0.1,~1$, and $10$., Comment: 30 pages, 34 figures. arXiv admin note: text overlap with arXiv:1006.5585

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are lethal rhythm disorders, which are associated with the occurrence of abnormal electrical scroll waves in the heart. Given the technical limitations of imaging and probing, the in situ visualization of these waves inside cardiac tissue remains a challenge. Therefore, we must, perforce, rely on in-silico simulations of scroll waves in mathematical models for cardiac tissue to develop an understanding of the dynamics of these waves in mammalian hearts. We use direct numerical simulations of the Hund-Rudy-Dynamic (HRD) model, for canine ventricular tissue, to examine the interplay between electrical scroll-waves and conduction and ionic inhomogeneities, in anatomically realistic canine ventricular geometries with muscle-fiber architecture. We find that millimeter-sized, distributed, conduction inhomogeneities cause a substantial decrease in the scroll wavelength, thereby increasing the probability for wave breaks; by contrast, single, localized, medium-sized ($\simeq $ cm) conduction inhomogeneities, exhibit the potential to suppress wave breaks or enable the self-organization of wave fragments into stable, intact scrolls. We show that ionic inhomogeneities, both distributed or localised, suppress scroll-wave break up. The dynamics of a stable rotating wave is not affected significantly by such inhomogeneities, except at high concentrations of distributed inhomogeneities, which can cause a partial break up of scroll waves. Our results indicate that inhomogeneities in the canine ventricular tissue are less arrhythmogenic than inhomogeneities in porcine ventricular tissue, for which an earlier in silico study has shown that the inhomogeneity-induced suppression of scroll waves is a rare occurrence.

We conduct a systematic,direct-numerical-simulation study,in mathematical models for ventricular tissue,of the dependence of spiral-and scroll-wave dynamics on $G_{Kr}$, the maximal conductance of the delayed rectifier Potassium current($I_{Kr}$) channel,and the parameter $\gamma_{Cao}$,which determines the magnitude and shape of the current $I_{CaL}$ for the L-type calcium-current channel,in both square and anatomically realistic,whole-ventricle simulation domains using canine and human models. We use ventricular geometry with fiber-orientation details and employ a physiologically realistic model for a canine ventricular myocyte. We restrict ourselves to an HRD-model parameter regime, which does not produce spiral- and scroll-wave instabilities because of other,well-studied causes like a very sharp action-potential-duration-restitution (APDR) curve or early after depolarizations(EADs) at the single-cell level. We find that spiral- or scroll-wave dynamics are affected predominantly by a simultaneous change in $I_{CaL}$ and $I_{Kr}$,rather than by a change in any one of these currents;other currents do not have such a large effect on these wave dynamics in this parameter regime of the HRD model.We obtain stability diagrams in the $G_{Kr} -\gamma_{Cao}$ plane.In the 3D domain,the geometry of the domain supports the confinement of the scroll waves and makes them more stable compared to their spiral-wave counterparts in 2D domain. We have also carried out a comparison of our HRD results with their counterparts for the human-ventricular TP06 model and have found important differences. In both these models,to make a transition,(from broken-wave to stable-scroll states or vice versa) we must simultaneously increase $I_{Kr}$ and decrease $I_{CaL}$;a modification of only one of these currents is not enough to effect this transition.

Anisotropy and multifractality in velocity and temperature time series sampled at multiple heights in the roughness sublayer (RSL) over a boreal mixed-coniferous forest are reported. In particular, a turbulent-stress invariant analysis along with a scalewise version of it are conducted to elucidate the nature of relaxation of large-scale anisotropy to quasi-isotropic states at small scales. As the return to isotropy is linked to nonlinear interactions and correlations between different fluctuating velocity components across scales, we study the velocity and temperature time series by using multifractal detrended fluctuation analysis and multiscale multifractal analysis to assess the effects of thermal stratification and surface roughness on turbulence in the RSL. The findings are compared so as to quantify the anisotropy and multifractality ubiquitous to RSL turbulent flow. As we go up in the RSL, (a) the length scale at which return to isotropy commences increases because of the weakening of the surface effects and (b) the largest scales become increasingly anisotropic. The anisotropy in multifractal exponents for the velocity fluctuations is diminished when we use the extended-self-similarity procedure to extract the multifractal-exponent ratios., Comment: 17 pages, 15 figures

We develop a minimal model for \textit{pulsar glitches} by introducing a solid-crust potential in the three-dimensional (3D) Gross-Pitaevskii-Poisson equation (GPPE), which we have used earlier to study gravitationally bound Bose-Einstein Condensates (BECs), i.e., bosonic stars. In the absence of the crust potential, we show that, if we rotate such a bosonic star, it is threaded by vortices. We then show, via extensive direct numerical simulations (DNSs), that the interaction of these vortices with the crust potential yields (a) stick-slip dynamics and (b) dynamical glitches. We demonstrate that, if enough momentum is transferred to the crust from the bosonic star, then the vortices are expelled from the star and the crust's angular momentum $J_c$ exhibits features that can be interpreted naturally as glitches. From the time series of $J_c$, we compute the cumulative probability distribution functions (CPDFs) of event sizes, event durations, and waiting times. We show that these CPDFs have signatures of self-organized criticality (SOC), which have been seen in observations on pulsar glitches.

We study the spreading of viruses, such as SARS-CoV-2, by airborne aerosols, via a new first-passage-time problem for Lagrangian tracers that are advected by a turbulent flow: By direct numerical simulations of the three-dimensional (3D) incompressible, Navier-Stokes equation, we obtain the time $t_R$ at which a tracer, initially at the origin of a sphere of radius $R$, crosses the surface of the sphere \textit{for the first time}. We obtain the probability distribution function $\mathcal{P}(R,t_R)$ and show that it displays two qualitatively different behaviors: (a) for $R \ll L_{\rm I}$, $\mathcal{P}(R,t_R)$ has a power-law tail $\sim t_R^{-\alpha}$, with the exponent $\alpha = 4$ and $L_{\rm I}$ the integral scale of the turbulent flow; (b) for $l_{\rm I} \lesssim R $, the tail of $\mathcal{P}(R,t_R)$ decays exponentially. We develop models that allow us to obtain these asymptotic behaviors analytically. We show how to use $\mathcal{P}(R,t_R)$ to develop social-distancing guidelines for the mitigation of the spreading of airborne aerosols with viruses such as SARS-CoV-2.

We study self-gravitating bosonic systems, candidates for dark-matter halos, by carrying out a suite of direct numerical simulations (DNSs) designed to investigate the formation of finitetemperature, compact objects in the three-dimensional (3D) Fourier-truncated Gross-Pitaevskii-Poisson equation (GPPE). This truncation allows us to explore the collapse and fluctuations of compact objects, which form at both zero temperature and finite temperature. We show that the statistically steady state of the GPPE, in the large-time limit and for the system sizes we study, can also be obtained efficiently by tuning the temperature in an auxiliary stochastic Ginzburg-Landau-Poisson equation (SGLPE). We show that, over a wide range of model parameters, this system undergoes a thermally driven first-order transition from a collapsed, compact, Bose-Einstein condensate (BEC) to a tenuous Bose gas without condensation. By a suitable choice of initial conditions in the GPPE, we also obtain a binary condensate that comprises a pair of collapsed objects rotating around their center of mass.

We develop an adversarial-reinforcement learning scheme for microswimmers in statistically homogeneous and isotropic turbulent fluid flows, in both two (2D) and three dimensions (3D). We show that this scheme allows microswimmers to find non-trivial paths, which enable them to reach a target on average in less time than a naive microswimmer, which tries, at any instant of time and at a given position in space, to swim in the direction of the target. We use pseudospectral direct numerical simulations (DNSs) of the 2D and 3D (incompressible) Navier-Stokes equations to obtain the turbulent flows. We then introduce passive microswimmers that try to swim along a given direction in these flows; the microswimmers do not affect the flow, but they are advected by it., Comment: 8 pages, 10 figures

Tracy-Widom and Baik-Rains distributions appear as universal limit distributions for height fluctuations in the one-dimensional Kardar-Parisi-Zhang (KPZ) \textit{stochastic} partial differential equation (PDE). We obtain the same universal distributions in the spatiotemporally chaotic, nonequilibrium, but statistically steady state (NESS) of the one-dimensional Kuramoto-Sivashinsky (KS) \textit{deterministic} PDE, by carrying out extensive pseudospectral direct numerical simulations to obtain the spatiotemporal evolution of the KS height profile $h(x,t)$ for different initial conditions. We establish, therefore, that the statistical properties of the 1D KS PDE in this state are in the 1D KPZ universality class.

Unbroken and broken spiral waves, in partial-differential-equation (PDE) models for cardiac tissue, are the mathematical analogs of life-threatening cardiac arrhythmias, namely, ventricular tachycardia (VT) and ventricular-fibrillation (VF). We develop a (a) deep-learning method for the detection of unbroken and broken spiral waves and (b) the elimination of such waves, e.g., by the application of low-amplitude control currents in the cardiac-tissue context. Our method is based on a convolutional neural network (CNN) that we train to distinguish between patterns with spiral waves S and without spiral waves NS. We obtain these patterns by carrying out extensive direct numerical simulations (DNS) of PDE models for cardiac tissue in which the transmembrane potential V, when portrayed via pseudocolor plots, displays patterns of electrical activation of types S and NS. We then utilize our trained CNN to obtain, for a given pseudocolor image of V, a heat map that has high intensity in the regions where this image shows the cores of spiral waves. Given this heat map, we show how to apply low-amplitude Gaussian current pulses to eliminate spiral waves efficiently. Our in silico results are of direct relevance to the detection and elimination of these arrhythmias because our elimination of unbroken or broken spiral waves is the mathematical analog of low-amplitude defibrillation.

We obtain the von K\'arm\'an-Howarth relation for the stochastically forced three-dimensional Hall-Vinen-Bekharvich-Khalatnikov (3D HVBK) model of superfluid turbulence in Helium ($^4$He) by using the generating-functional approach. We combine direct numerical simulations (DNSs) and analyitcal studies to show that, in the statistically steady state of homogeneous and isotropic superfluid turbulence, in the 3D HVBK model, the probability distribution function (PDF) $P(\gamma)$, of the ratio $\gamma$ of the magnitude of the normal fluid velocity and superfluid velocity, has power-law tails that scale as $P(\gamma) \sim \gamma^3$, for $\gamma \ll 1$, and $P(\gamma) \sim \gamma^{-3}$, for $\gamma \gg 1$. Furthermore, we show that the PDF $P(\theta)$, of the angle $\theta$ between the normal-fluid velocity and superfluid velocity exhibits the following power-law behaviors: $P(\theta)\sim \theta$ for $\theta \ll \theta_*$ and $P(\theta)\sim \theta^{-4}$ for $\theta_* \ll \theta \ll 1$, where $\theta_*$ is a crossover angle that we estimate. From our DNSs we obtain energy, energy-flux, and mutual-friction-transfer spectra, and the longitudinal-structure-function exponents for the normal fluid and the superfluid, as a function of the temperature $T$, by using the experimentally determined mutual-friction coefficients for superfluid Helium $^4$He, so our results are of direct relevance to superfluid turbulence in this system., Comment: 13 pages, 3 figures

Two-dimensional magnetohydrodynamics (2D MHD), forced at (a) large length scales or (b) small length scales, displays turbulent, but statistically steady, states with widely different statistical properties. We present a systematic, comparative study of these two cases (a) and (b) by using direct numerical simulations (DNSs). We find that, in case (a), there is energy equipartition between the magnetic and velocity fields, whereas, in case (b), such equipartition does not exist. By computing various probability distribution functions (PDFs), we show that case (a) displays extreme events that are much less common in case (b).

We compare and contrast spiral- and scroll-wave dynamics in five different mathematical models for cardiac tissue. The first is the TP06 model, due to ten Tusscher and Panfilov, which is based on the Hodgkin-Huxley formalism; the remaining four are Markov-state models, MM1 WT and MM2 WT, for the wild-type (WT) Na channel, and MM1 MUT and MM2 MUT, for the mutant Na channel. Our results are based on extensive direct numerical simulations of waves of electrical activation in these models, in two- and three-dimensional (2D and 3D) homogeneous simulation domains and also in domains with localised heterogeneities, either obstacles with randomly distributed inexcitable regions or mutant cells in a wild-type background. Our study brings out the sensitive dependence of spiral- and scroll-wave dynamics on these five models and the parameters that define them. We also explore the control of spiral-wave turbulence in these models., Comment: 26 pages, 12 figures and 2 Tables