We study the Brownian motion of ellipsoidal particles lying on an agitated granular bath composed of magnetic particles. We quantify the mobility of different floating ellipsoidal particles using the mean-square displacement and the mean-square angular displacement, and relate the diffusion coefficients to the bath particle motion. In terms of the particle major radius $R$, we find the translational diffusion coefficient scales roughly as $1/R^2$ and the rotational diffusion coefficient scales as roughly $1/R^4$; this is consistent with the assumption that diffusion arises from random kicks of the bath particles underneath the floating particle. By varying the magnetic forcing, the bath particles' diffusivity changes by a factor of ten; over this range, the translational and rotational diffusion of the floating particles change by a factor of 50. However, the ratio of the two diffusion constants for the floating particles is forcing-independent. Unusual aspects of the floating particle motion include non-Gaussian statistics for their displacements.

Blood flowing through microvascular bifurcations has been an active research topic for many decades, while the partitioning pattern of nanoscale solutes in the blood remains relatively unexplored. Here we demonstrate a multiscale computational framework for direct numerical simulation of the nanoparticle (NP) partitioning through physiologically relevant vascular bifurcations in the presence of red blood cells (RBCs). The computational framework is established by embedding a particulate suspension inflow-outflow boundary condition into a multiscale blood flow solver. The computational framework is verified by recovering a tubular blood flow without a bifurcation and validated against the experimental measurement of an intravital bifurcation flow. The classic Zweifach-Fung (ZF) effect is shown to be well captured by the method. Moreover, we observe that NPs exhibit a ZF-like heterogeneous partition in response to the heterogeneous partition of the RBC phase. The NP partitioning prioritizes the high-flow-rate daughter branch except for extreme (large or small) suspension flow partition ratios under which the complete phase separation tends to occur. By analyzing the flow field and the particle trajectories, we show that the ZF-like heterogeneity in the NP partition can be explained by the RBC-entrainment effect caused by the deviation of the flow separatrix preceded by the tank treading of RBCs near the bifurcation junction. The recovery of homogeneity in the NP partition under extreme flow partition ratios is due to the plasma skimming of NPs in the cell-free layer. These findings, based on the multiscale computational framework, provide biophysical insights to the heterogeneous distribution of NPs in microvascular beds that are observed pathophysiologically.

It is well known that Brownian ratchets can exhibit current reversals, wherein the sign of the current switches as a function of the driving frequency. We introduce a spatial discretization of such a two-dimensional Brownian ratchet to enable spectral methods that efficiently compute those currents. These discrete-space models provide a convenient way to study the Markovian dynamics conditioned upon generating particular values of the currents. By studying such conditioned processes, we demonstrate that low-frequency negative values of current arise from typical events and high-frequency positive values of current arises from rare events. We demonstrate how these observations can inform the sculpting of time-dependent potential landscapes with a specific frequency response.

Cell division is central for embryonic development, tissue morphogenesis, and tumor growth. Experiments have evidenced that mitotic cell division is manipulated by the intercellular cues such as cell-cell junctions. However, it still remains unclear how these cortical-associated cues mechanically affect the mitotic spindle machinery, which determines the position and orientation of the cell division. In this paper, a mesoscopic dynamic cell division model is established to explore the integrated regulations of cortical polarity, microtubule pulling forces, cell deformability, and internal osmotic pressure. We show that the distributed pulling forces of astral microtubules play a key role in encoding the instructive cortical cues to orient and position the spindle of a dividing cell. The present model can not only predict the spindle orientation and position, but also capture the morphological evolution of cell rounding. The theoretical results agree well with relevant experiments both qualitatively and quantitatively. This work sheds light on the mechanical linkage between cell cortex and mitotic spindle, and holds potential in regulating cell division and sculpting tissue morphology.

Finding the source of an odor dispersed by a turbulent flow is a vital task for many organisms. When many individuals concurrently perform the same olfactory search task, sharing information about other members' decisions can potentially boost the performance. But how much of this information is actually exploitable for the collective task? Here we show, in a model of a swarm of agents inspired by moth behavior, that there is an optimal way to blend the private information about odor and wind detections with the public information about other agents' heading direction. Our results suggest an efficient multiagent olfactory search algorithm that could prove useful in robotics, e.g., in the identification of sources of harmful volatile compounds.

Collisionless shocks are multiscale objects. Energetic ion distributions are gyrotropic at sufficiently large distances upstream and downstream of the shock transition while at the transition itself the ion dynamics is significantly gyrophase dependent. Magnetic-moment conservation of an ion is widely used as a viable approximation during the shock crossing. It is shown that this approximation is inconsistent with the required entropy increase due to the loss of the gyrophase information.

Bacteria communicate by secreting and detecting diffusible small molecule signals or pheromones. Using the local concentrations of these signals to regulate gene expression, individual cells can synchronize changes in phenotype population-wide, a behavior known as quorum sensing (QS). In unstirred media, the interplay between diffusion of signals, bacterial growth, and regulatory feedback can generate complex spatial and temporal patterns of expression of QS-controlled genes. Here we identify the parameters that allow a local signal to trigger a self-sustaining, traveling activation of QS behavior. Using the natural bioluminescence of wild-type Vibrio fischeri as a readout of its lux QS system, we measure the induction of a spreading QS response by a localized triggering stimulus in unstirred media. Our data show that a QS response propagates outward, sustained by positive feedback in synthesis of the diffusible signal, and that this response occurs only if the triggering stimulus exceeds a critical threshold. We also test how the autonomous or untriggered activation of the V. fischeri QS pathway changes at very low initial population densities. At the lowest population densities, clusters of cells do not transition to a self-sensing behavior, but rather remain in communication via signal diffusion until they reach sufficiently large size that their own growth slows. Our data, which are reproduced by simple growth and diffusion simulations, indicate that in part owing to bacterial growth behavior, natural QS systems can be characterized by long distance communication through signal diffusion even in very heterogeneous and spatially dispersed populations.

Granular packings of nonconvex or elongated particles can form freestanding structures like walls or arches. For some particle shapes, such as staples, the rigidity arises from interlocking of pairs of particles, but the origins of rigidity for noninterlocking particles remains unclear. We report on experiments and numerical simulations of sheared columns of “hexapods,” particles consisting of three mutually orthogonal sphero-cylinders whose centers coincide. We vary the length-to-diameter aspect ratio, $\alpha$, of the sphero-cylinders and subject the packings to quasistatic direct shear. For small $\alpha$, we observe a finite yield stress. For large $\alpha$, however, the column becomes rigid when sheared, supporting stresses that increase sharply with increasing strain. Analysis of x-ray microcomputed tomography (micro-CT) data collected during the shear reveals that the stiffening is associated with a tilted, oblate cluster of hexapods near the nominal shear plane in which particle deformation and average contact number both increase. Simulation results show that the particles are collectively under tension along one direction, even though they do not interlock pairwise. These tensions comes from contact forces carrying large torques, and they are perpendicular to the compressive stresses in the packing. They counteract the tendency to dilate, thus stabilizing the particle cluster.

We present an approach to derive the connectivity properties of pairwise interacting $n$-body systems in thermal equilibrium. We formulate an integral equation that relates the pair connectedness to the distribution of nearest neighbors. For one-dimensional systems with nearest-neighbor interactions, the nearest-neighbor distribution is in turn related to the pair-correlation function $g$ through a simple integral equation. As a consequence, for those systems, we arrive at an integral equation relating $g$ to the pair connectedness, which is readily solved even analytically if $g$ is specified analytically. We demonstrate the procedure for a variety of pair potentials including fully penetrable spheres as well as impenetrable spheres, the only two systems for which analytical results for the pair connectedness exist. However, the approach is not limited to nearest-neighbor interactions in one dimension. Hence, we also outline the treatment of external fields and long-range interactions and we illustrate how the formalism can applied to higher-dimensional systems using the three-dimensional ideal gas as an example.

In this work, we use the finite differences in time domain (FDTD) numerical method to compute and assess the validity of Hopf solutions, or hopfions, for the electromagnetic field equations. In these solutions, field lines form closed loops characterized by different knot topologies which are preserved during their time evolution. Hopfions have been studied extensively in the past from an analytical perspective but never, to the best of our knowledge, from a numerical approach. The implementation and validation of this technique eases the study of more complex cases of this phenomena; e.g., how these fields could interact with materials (e.g., anisotropic or nonlinear), their coupling with other physical systems (e.g., plasmas), and also opens the path on their artificial generation by different means (e.g., antenna arrays or lasers).

Recent experiments have reported a novel splay nematic phase, which has alternating domains of positive and negative splay. To model this phase, previous studies have considered a one-dimensional (1D) splay modulation of the director field, accompanied by a 1D modulation of polar order. When the flexoelectric coupling between splay and polar order becomes sufficiently strong, the uniform nematic state becomes unstable to the formation of a modulated phase. Here we reexamine this theory in terms of a recent approach to liquid crystal elasticity, which shows that pure splay deformation is double splay rather than planar single splay. Following that reasoning, we propose a structure with a two-dimensional (2D) splay modulation of the director field, accompanied by a 2D modulation of polar order, and show that the 2D structure generally has a lower free energy than the 1D structure.

We numerically explore the behavior of repelling and aligning self-propelled polar particles (boids) in two dimensions enclosed by a damped flexible and elastic loop-shaped boundary. We observe disordered, polar ordered, jammed, and circulating states. The latter produce a rich variety of boundary shapes, including circles, ovals, irregulars, ruffles, or sprockets, depending upon the bending moment of the boundary and the boundary to particle mass ratio. With the exception of the circulating states with nonround boundaries, states resemble those exhibited by attracting self-propelled particles, but here the confining boundary acts in place of a cohesive force. We attribute the formation of ruffles to instability mediated by pressure on the boundary when the speed of waves on the boundary approximately matches the self-propelled particle's swim speed.

We investigate experimentally and numerically the response of hinged shallow arches subjected to a transverse midpoint displacement. We find that this simple system supports a rich set of responses, which, to date, have received relatively little attention. We observe not only the snapping of the arches to their inverted equilibrium configuration, but also an earlier dynamic transition from a symmetric to an asymmetric shape that results in a sudden strength loss. Moreover, we find that the response of plastically deformed arches is nonreciprocal with respect to the loading direction. Finally, we discover that, while elastically deformed arches always snap to the inverted stable configuration, for plastically deformed ones there is a critical rise below which the structures are monostable.

At equilibrium, the structure and response of ordered phases are typically determined by the spontaneous breaking of spatial symmetries. Out of equilibrium, spatial order itself can become a dynamically emergent concept. In this article, we show that spatially anisotropic viscous coefficients and stresses can be designed in a far-from-equilibrium fluid by applying to its constituents a time-modulated drive. If the drive induces a rotation whose rate is slowed down when the constituents point along specific directions, then anisotropic structures and mechanical responses arise at long timescales. We demonstrate that the viscous response of such two-dimensional anisotropic driven fluids can acquire a tensorial, dissipationless component called anisotropic odd (or Hall) viscosity. Classical fluids with internal torques can display additional components of the odd viscosity neglected in previous studies of quantum Hall fluids that assumed angular momentum conservation. We show that, unlike their isotropic counterparts, these anisotropic and angular momentum-violating odd-viscosity coefficients can change even the bulk flow of an incompressible fluid by acting as a source of vorticity. In addition, shear distortions in the shape of an inclusion result in torques. We derive how the odd-viscous coefficients depend on the nonlinear, dissipative response of a fluid of rotating rods, i.e., odd viscosity is not simply given by angular momentum density.

Slender elastic objects such as a column tend to buckle under loads. While static buckling is well understood as a bifurcation problem, the evolution of shapes during dynamic buckling is much harder to study. Elastic rings under normal pressure have emerged as a theoretical and experimental paradigm for the study of dynamic buckling with controlled loads. Experimentally, an elastic ring is placed within a soap film. When the film outside the ring is removed, surface tension pulls the ring inward, mimicking an external pressurization. Here we present a theoretical analysis of this process by performing a postbifurcation analysis of an elastic ring under pressure. This analysis allows us to understand how inertia, material properties, and loading affect the observed shape. In particular, we combine direct numerical solutions with a postbifurcation asymptotic analysis to show that inertia drives the system towards higher modes that cannot be selected in static buckling. Our theoretical results explain experimental observations that cannot be captured by a standard linear stability analysis.

We study a one-dimensional disordered Bose fluid using bosonization, the replica method, and a nonperturbative functional renormalization-group approach. We find that the Bose-glass phase is described by a fully attractive strong-disorder fixed point characterized by a singular disorder correlator whose functional dependence assumes a cuspy form that is related to the existence of metastable states. At nonzero momentum scale $k$, quantum tunneling between the ground state and low-lying metastable states leads to a rounding of the cusp singularity into a quantum boundary layer (QBL). The width of the QBL depends on an effective Luttinger parameter $K_k\sim k^{\theta }$ that vanishes with an exponent $\theta =z-1$ related to the dynamical critical exponent $z$. The QBL encodes the existence of rare “superfluid” regions, controls the low-energy dynamics, and yields a (dissipative) conductivity vanishing as ${\omega }^2$ in the low-frequency limit. These results reveal the glassy properties (pinning, “shocks,” or static avalanches) of the Bose-glass phase and can be understood within the “droplet” picture put forward for the description of glassy (classical) systems.

Using population data of high spatial resolution for a region in the south of Europe, we define cities by aggregating individuals to form connected clusters. The resulting cluster-population distributions show a smooth decreasing behavior covering six orders of magnitude. We perform a detailed study of the distributions, using state-of-the-art statistical tools. By means of scaling analysis we rule out the existence of a power-law regime in the low-population range. The logarithmic-coefficient-of-variation test allows us to establish that the power-law tail for high population, characteristic of Zipf's law, has a rather limited range of applicability. Instead, lognormal fits describe the population distributions in a range covering from a few dozen individuals to more than $1\times {10}^6$ (which corresponds to the population of the largest cluster).

Entropy production characterizes the thermodynamic irreversibility and reflects the amount of heat dissipated into the environment and free energy lost in nonequilibrium systems. According to the thermodynamic uncertainty relation, we propose a deterministic method to estimate the entropy production from a single trajectory of system states. We explicitly and approximately compute an optimal current that yields the tightest lower bound using predetermined basis currents. Notably, the obtained tightest lower bound is intimately related to the multidimensional thermodynamic uncertainty relation. By proving the saturation of the thermodynamic uncertainty relation in the short-time limit, the exact estimate of the entropy production can be obtained for overdamped Langevin systems, irrespective of the underlying dynamics. For Markov jump processes, because the attainability of the thermodynamic uncertainty relation is not theoretically ensured, the proposed method provides the tightest lower bound for the entropy production. When entropy production is the optimal current, a more accurate estimate can be further obtained using the integral fluctuation theorem. We illustrate the proposed method using three systems: a four-state Markov chain, a periodically driven particle, and a multiple bead-spring model. The estimated results in all examples empirically verify the effectiveness and efficiency of the proposed method.

We show that a collection of independent Ising spins evolving stochastically can display surprisingly large fluctuations toward ordered behavior, as quantified by certain types of time-integrated plaquette observables, despite the underlying dynamics being noninteracting. In the large-deviation (LD) regime of long times and large system size, this can give rise to a phase transition in trajectory space. As a noninteracting system we consider a collection of spins undergoing single spin-flip dynamics at infinite temperature. For the dynamical observables we study, the associated tilted generators have an exact and explicit spin-plaquette duality. Such setup suggests the existence of a transition (in the large size limit) at the self-dual point of the tilted generator. The nature of the LD transition depends on the observable. We consider explicitly two situations: (i) for a pairwise bond observable the LD transition is continuous and equivalent to that of the transverse field Ising model and (ii) for a higher-order plaquette observable, in contrast, the LD transition is first order. Case (i) is easy to prove analytically, while we confirm case (ii) numerically via an efficient trajectory sampling scheme that exploits the noninteracting nature of the original dynamics.

Multibody interactions can reveal higher-order dynamical effects that are not captured by traditional two-body network models. In this work, we derive and analyze models for consensus dynamics on hypergraphs, where nodes interact in groups rather than in pairs. Our work reveals that multibody dynamical effects that go beyond rescaled pairwise interactions can appear only if the interaction function is nonlinear, regardless of the underlying multibody structure. As a practical application, we introduce a specific nonlinear function to model three-body consensus, which incorporates reinforcing group effects such as peer pressure. Unlike consensus processes on networks, we find that the resulting dynamics can cause shifts away from the average system state. The nature of these shifts depends on a complex interplay between the distribution of the initial states, the underlying structure, and the form of the interaction function. By considering modular hypergraphs, we discover state-dependent, asymmetric dynamics between polarized clusters where multibody interactions make one cluster dominate the other.