Living cells presumably employ optimized information transfer methods, enabling efficient communication even in noisy environments. The efficiency of chemical communication between cells depends on the properties of the molecular messenger. Evidence suggests that proteins within narrow molecular mass ranges have been naturally selected to mediate cellular communication, yet the underlying communication design principles remain poorly understood. Using a simple physical model that accounts for the cost of chemical synthesis, diffusion, molecular binding, and degradation, we show that optimal masses exist to ensure efficient communication of various types of signals. Our findings provide insights into the design principles of biological communication and may inform the engineering of biomimetic systems with chemical signaling capabilities.

High-field terahertz (THz) pulse generation is investigated through the interaction of an intense single-color ${\mathrm{CO}}_2$ laser pulse with helium (He) gas targets. Employing particle-in-cell (PIC) simulations, this study reveals a substantial enhancement in THz generation efficiency, even with a single-color laser pulse interacting with gas targets in the self-modulated-laser-wakefield (SMLWF) regime. Our study demonstrates that in the presence of photoionization, a synergistic interplay of laser self-modulation, self-focusing, and local pump depletion leads to the generation of robust THz pulses polarized parallel to the laser electric field. The dependence of THz generation efficiency on target density, laser intensity, and laser pulse duration has been investigated. Our study identifies a favorable parametric regime for producing THz fields with amplitudes reaching hundreds of GV/m, surpassing those reported in previous studies.

In the percolation model, specific preprocessing of configuration data enables identifying phase transitions with unsupervised learning methods such as principal component analysis (PCA). However, the limitations of using original percolation configuration data and the role of preprocessing remain incompletely understood. Here, we study how PCA works in percolation. Firstly, we theoretically derive the PCA results. For the original configurations, PCA shows no insights into the percolation phase transition. The theoretical results of PCA reveal the relation between principal components and the indicators of phase transitions, i.e., order parameters and structure factors based on the preprocessing of removing unpercolating clusters. In addition, we investigate the PCA based on auxiliary Ising mapping, and the relation is also derived and validated. Secondly, we examine the intrinsic properties of the original percolation configurations and the operational principles of PCA and then reveal the challenge of PCA in percolation. The statistical independence among sites results in the absence of necessary lattice structure information, and further, the negligible threshold number of occupied (unoccupied) sites required for forming (destructing) percolating cluster results in the invisibility of the phase transition to the cluster analysis or statistical approaches. Both removing unpercolating clusters and auxiliary Ising mapping can remove this invisibility. Our work suggests that yielding discernible differences between percolating state and unpercolating state, or further introducing percolation statistical correlation among sites, gives effective data preprocessing methods.

We present four classes of highly symmetric defect patterns on a spherical surface tiled with triangular and square tiles. These patterns accommodate both stretched triangular and square lattices and are analyzed in terms of their symmetries. Both spherical and corresponding polyhedron views are considered, with emphasis on three-dimensional point-group symmetries. In addition to the original patterns, alternative defect configurations are explored, including those generated by the kaleidoscopic operation, originally suggested by Caspar and Klug for triangular tiling, as well as the cut-and-rotate operation applied through a great circle on the sphere. While these alternatives can lower the space-group symmetries, they provide a broader understanding of the system's possible configurations. For a fixed square surface area fraction, we also examine a scenario that identifies the likely ground state among the four primary classes and their alternatives.

Swimming micro-objects exist in viscoelastic fluids. Elucidating the effect of viscoelasticity on the motion of these objects is important for understanding their behavior. Since the mechanical response of viscoelastic fluids depends on the temporal deformation rate exerted by a moving object, it is necessary to control their speed over a wide range to examine the effect of viscoelasticity. In this study, we examined the motion of Janus particles self-propelled by induced charge electrophoresis over a wide range of speeds in semidilute polymer solutions. In our system, the motion of Janus particles changed from active Brownian motion to stationary rotation as the speed increased. The torque for stationary rotation originates from the difference between the direction of self-propulsion and that of the time-delayed restoring force from the polymer solution, which has been reported in another self-propelled particle system. The switch from active Brownian motion to stationary rotation at different polymer concentrations can be explained by the Weisenberg number, which is defined as the ratio of the relaxation time of the polymer network to the travel time of the Janus particle to its size. The results of this study will lead to a better understanding of the motion of self-propelled micro-objects in viscoelastic fluids.

Chiral nematic or cholesteric liquid crystals (LCs) are fluid mesophases with long-ranged orientational order featuring a quasilayered periodicity imparted by a helical director configuration but lacking long-range positional order. Doping molecular cholesteric LCs with strongly anisotropic uniaxial colloidal particles adds another level of complexity because of the interplay between weak surface-anchoring boundary conditions and bulk-based elastic distortions near the particle-LC interface. Using cylindrical colloidal disks and rods with different geometric shapes and surface conditions, we demonstrate that these colloidal inclusions generically exhibit biaxial orientational probability distributions which may impart anomalously strong local biaxiality onto the hybrid cholesteric LC structure. Unlike nonchiral hybrid molecular-colloidal LCs, where biaxial order emerges only at critical colloid volume fractions exceeding some uniaxial-biaxial transition value, the orientational probability of the colloidal inclusions immersed in chiral nematic hosts is unambiguously biaxial even at infinite dilution. We demonstrate that the colloids induce local biaxial perturbations within the molecular orientational order of the LC host medium which strongly enhances the weak but native biaxial order of chiral nematic LC induced by the chiral symmetry breaking of the director field. With the help of analytical modeling and computer simulations based on the Landau–de Gennes free energy of the host LC around the colloids, we rationalize the observed multilevel biaxial order and conclude that it is not only unavoidable but also strongly enhanced compared to both achiral hybrid LCs and purely molecular cholesteric LCs.

A symmetrically buckled arch whose boundaries are clamped at an angle has two stable equilibria: an inverted and a natural state. When the distance between the clamps is increased (i.e., the confinement is decreased), the system snaps from the inverted to the natural state. Depending on the rate at which the confinement is decreased (“unloading”), the symmetry of the system during snap through may change: slow unloading results in snap-through occurring asymmetrically, while fast unloading results in a symmetric snap-through. It has recently been shown [Wang et al., Phys. Rev. Lett. 132, 267201 (2024)] that the transient asymmetry observed at slow unloading rates is the result of the amplification of small asymmetric precursor oscillations (shape perturbations) introduced dynamically to the system, even when the system itself is perfectly symmetric. In reality, however, imperfections, such as small asymmetries in the boundary conditions, are present too. Using numerical simulations and a simple toy model, we discuss the relative importance of imperfections in the boundary conditions and initial asymmetric shape perturbations in determining the transient asymmetry that is observed. We show that for small initial shape perturbations, the magnitude of the asymmetry grows in proportion to the size of the imperfection, but that when initial shape perturbations are large, imperfections are unimportant—the asymmetry of the system is dominated by the transient amplification of the initial asymmetric shape perturbations. We also show that the dominant origin of asymmetry changes the way that asymmetry grows dynamically. Our results may guide the engineering and design of snapping beams used to control insect-sized jumping robots.

We study numerically the kinetic roughening properties of the precursor fronts of nonvolatile liquid droplets spreading on solid substrates, for the case of circular droplets, more frequently addressed in experiments. To this end, we perform kinetic Monte Carlo (kMC) simulations of a lattice gas model whose kinetic roughening behavior has been recently assessed in a band geometry [J. M. Marcos et al., Phys. Rev. E 105, 054801 (2022)]. We compare the scaling behaviors of the spreading fronts obtained for the two geometries, in view of the occurrence of, for example, different universality subclasses for different growth geometries for the related important Kardar-Parisi-Zhang (KPZ) universality class. For circular droplets, we obtain that the average front position increases (sub)diffusively as $R\sim t^{\delta }$, where $\delta \lesssim 1/2$ shows a stronger dependence on the conditions considered for temperature and substrate wettability than in band geometry. In spite of this, front fluctuations for circular droplets behave qualitatively similar to those seen for band geometries, with kinetic roughening exponent values which similarly depend on temperature $T$ but become $T$-independent for sufficiently high $T$. Circular droplets also display intrinsic anomalous scaling with different values of the roughness exponent at short and large length scales, and fluctuations statistics which are close to the Tracy-Widom probability distribution function that applies in the corresponding KPZ universality subclass, now the one expected for interfaces with an overall circular symmetry.

It is well established that the ferromagnetic phase remains stable under random magnetic fields in three and higher dimensions for the ferromagnetic Ising model and the Edwards-Anderson model of spin glasses without correlation in the disorder variables. In this study, we investigate an Ising spin glass with correlated disorder and demonstrate that the ferromagnetic phase becomes unstable under random fields in any dimension, provided that magnetic field chaos exists in the Edwards-Anderson model on the same lattice. Additionally, we show that this instability can also be attributed to disorder (bond) chaos. We further argue that the model with correlated disorder remains in the ferromagnetic phase even in the presence of symmetry-breaking fields, as long as the Edwards-Anderson model on the same lattice exhibits a spin glass phase under a magnetic field. These results underscore the profound impact of spatial correlations in the disorder.

Numerical simulations and finite-size scaling analysis have been carried out to study the percolation behavior of square tiles of side $k$ ($k$-tiles) on two-dimensional square lattices. The $k$-tiles, containing $k\times k$ identical units (each one occupying a lattice site), were reversibly adsorbed on the lattice. The process was monitored by following the probability $R_{L,k}\left(\theta \right)$ that a lattice composed of $L\times L$ sites percolates at a concentration $\theta$ of sites occupied by particles of side $k$. The classical percolation problem is recovered for $k=1$ giving the well-known site percolation threshold ${\theta }_{c,k=1}=0.592746\cdots$. A slight decrease is observed at the percolation threshold when $k$ goes from 1 to 2, with ${\theta }_{c,k=2}=0.58483\left(9\right)$. For $k\ge 2$, the percolation threshold ${\theta }_{c,k}$ monotonically increases with $k$ and asymptotically converges toward a definite value for large $k$-tiles ${\theta }_{c,k\to \infty }\approx 0.963$. Accordingly, the model presents a percolation transition for the whole range of $k$. This behavior is completely different from that observed for the percolation problem of $k\times k$ square tiles irreversibly deposited on square lattices, where the percolation threshold is an increasing function of $k$ in the range of $1\le k\le 3$. For $k\ge 4$, the percolation phase transition disappears. This stark contrast between the behaviors of reversible and irreversible adsorption models is a significant outcome of this research. Our findings could guide future studies exploring possible formation mechanisms in conductivity experiments of composite materials. Finally, the accurate determination of the critical exponents $\alpha , \beta$, and $\gamma$, along with the measurement of the fractal dimension of the percolating cluster and the shortest-path exponent, indicates that although the deposition mechanism drastically affects the behavior of the percolation threshold with $k$, it does not alter the nature of the percolation transition occurring in the system. Accordingly, the universality class of the reversible adsorption model was found to be the same as for the random percolation model.

Stars orbiting a supermassive black hole in the center of galaxies undergo very efficient diffusion in their orbital orientations: this is “Vector Resonant Relaxation.” Such a dynamics is intrinsically nonlinear, stochastic, and correlated, hence bearing deep similarities with turbulence in fluid mechanics or plasma physics. In that context, we show how generic methods stemming from statistical closure theory, namely, the celebrated “Martin-Siggia-Rose formalism,” can be used to characterize the correlations describing the redistribution of orbital orientations. In particular, limiting ourselves to the leading order truncation in this closure scheme, the so-called “direct interaction approximation,” and placing ourselves in the limit of an isotropic distribution of orientations, we explicitly compare the associated prediction for the two-point correlation function with measures from numerical simulations. We discuss the successes and limitations of this approach and present possible future venues.

We investigate the steady-state transport characteristics of a quantum dot system consisting of a single energy level embedded between two reservoirs under the influence of both the temperature gradient and bias voltage. Within tailored parameter regimes, the system can exhibit three counterintuitive transport phenomena of anomalous thermodiffusion, absolute negative mobility, and reverse heat transport respectively. These counterintuitive phenomena do not violate the second law of thermodynamics. Moreover, absolute negative mobility and reverse heat transport can be identified by a reversible energy level. These anomalous transports are different from thermoelectric transports and provide different perspectives for a more comprehensive understanding of the transport characteristics of quantum systems.

Network science has presented community detection as a valuable tool for revealing functional modules in complex systems rooted in the wiring architectures of complex networks. The varying procedures of community detection can produce, however, divisions of a network into communities that vary considerably in structure but are deemed to be of similar merit. This is especially problematic when the network is constructed on uncertain data, since small changes to the network's configuration can cause radically different structures to be detected. To reconcile with the ambiguity in interpreting degenerate network partitions as representations of the underlying system function, we introduce a recursive significance clustering scheme that identifies the subsets of nodes having stable joint community assignments under network perturbation. These robust node groups are referred to here as cores, and represent well-supported features of network structure as distinct from the nodes with unstable community assignments. We show that cores characterize the variability inherent to nonoverlapping community structure in networks and are cohesive under temporal evolution of the network.

In this paper, we provide a theoretical framework for understanding the friction of water flowing in carbon nanotubes with diameters of the order of a nanometer. Molecular dynamics simulations show that under such circumstances, water forms one-dimensional water wires or hollowed cylindrical periodic structures. Since these structures are likely incommensurate with the nanotube, they exhibit very low friction, analogous to “superlubricity” in solids. We calculate the sliding friction arising from phonon excitation in nanotubes and in water structures, and show that it scales linearly with the sliding velocity, and the interfacial friction coefficient is consistent with the results of the molecular simulations. Next, we consider the existence of defects in the water structures and show that they give rise to a nonviscous friction. Using a Langevin equation, we show how our model can account for the water flow measured in experiments for extremely narrow carbon nanotubes.

A simple nonempirical approximation is proposed to calculate the ionic thermal contribution to the average-atom equations of state. The approximation represents the main regularities of temperature and mass-density dependences of the ionic thermodynamic-function components revealed from the pseudoatom molecular dynamics calculations. It is shown that the employment of our approximation instead of commonly used ideal-gas or one-component-plasma approximations significantly improves the accuracy of the equations-of-state calculations done with the Liberman average-atom model.

During quasistatic dynamics of granular systems, the stress and structure self-organize, but there is currently no quantitative measure or understanding of this phenomenon. Such an understanding is essential because local structural properties of the settled material are then correlated with the local stress, which calls into question existing linear theories of stress transmission in granular media. A method to quantify the local stress-structure correlations is necessary for addressing this issue and we present here such a method for planar systems. We then use it to analyze numerically several different systems, compressed quasistatically by two different procedures. We define cells, cell orders, cell orientations, and cell stresses and report the following results. (i) Cells orient along the local stress major principal axes. (ii) The mean ratio of cell principal stresses decreases with cell order and increases with friction. (iii) The ratio distributions collapse onto a single curve under a simple scaling, for all packing protocols and friction coefficients. (iv) A constructed model explains the correlations between the local cell and stress principal axis orientations. (v) The collapse of the stress ratios onto a Weibull distribution is modeled theoretically. Our results quantify the cooperative stress-structure self-organization and provide a way to relate quantitatively the stress-structure coupling to different process parameters and particle characteristics. Significantly, the strong stress-structure correlation, driven by structural reorganization upon application of external stress, suggests that current stress theories of granular matter need to be revisited.

The transport behavior of an inertial deformable particle in a two-dimensional steady laminar flow is numerically analyzed under the influence of a constant force and a periodic potential. By systematically adjusting parameters such as phase difference, target area, potential height, constant force, shape parameter, diffusion coefficient, and Stokes time, we analyze the effects on particle motion and the emergence of absolute negative mobility (ANM). Our results reveal that smaller target areas and moderate potential heights maximize ANM, while increased external force and extreme diffusion or inertia reduce it. We identify an optimal parameter range where negative mobility is most prominent, providing insights relevant to applications in fields like microfluidics and soft robotics.

We study the dynamics of solitons under the action of one-dimensional quasiperiodic lattice potentials, fractional diffraction, and nonlinearity. The formation and stability of the solitons are investigated in the framework of the fractional nonlinear Schrödinger equation. By means of variational and numerical methods, we identify conditions under which stable solitons emerge, stressing the effect of fractional diffraction on soliton properties. The reported findings contribute to understanding the soliton behavior in complex media, with implications for topological photonics and matter-wave dynamics in lattice potentials.