At zero temperature, spring networks with connectivity below Maxwell's isostatic threshold undergo a mechanical phase transition from a floppy state at small strains to a rigid state for applied shear strain above a critical strain threshold. Disordered networks in the floppy mechanical regime can be stabilized by entropic effects at finite temperature. We develop a scaling theory for this mechanical phase transition at finite temperature, yielding relationships between various scaling exponents. Using Monte Carlo simulations, we verify these scaling relations and identify anomalous entropic elasticity with sublinear $T$ dependence in the linear elastic regime. While our results are consistent with prior studies of phase behavior near the isostatic point, the present work also makes predictions relevant to the broad class of disordered thermal semiflexible polymer networks for which the connectivity generally lies far below the isostatic threshold.

We investigate the thermodynamics of general nonequilibrium processes stopped at stochastic times. We propose a systematic strategy for constructing fluctuation-theorem-like martingales for each thermodynamic functional, yielding a family of stopping-time fluctuation theorems. We derive second-law-like thermodynamic inequalities for the mean thermodynamic functional at stochastic stopping times, the bounds of which are even stronger than the thermodynamic inequalities resulting from the traditional fluctuation theorems when the stopping time is reduced to a deterministic one. Numerical verification is carried out for three well-known thermodynamic functionals, namely, entropy production, free energy dissipation, and dissipative work. These universal equalities and inequalities are valid for arbitrary stopping strategies, and thus provide a comprehensive framework with insights into the fundamental principles governing nonequilibrium systems.

We present a staged hot-electron acceleration mechanism of the two-plasmon decay (TPD) instability in the transverse magnetic field under the parameters relevant to inertial confinement fusion experiments. After being accelerated by the forward electron plasma wave (FEPW) of TPD, the hot-electrons can be anomalously accelerated again by the backward electron plasma wave (BEPW) of TPD and then obtain higher energy. Moreover, the surfatron acceleration mechanism of TPD in the magnetic field is also confirmed, the electrons trapped by the TPD daughter EPWs are accelerated in the direction along the wave front. Interestingly, the velocity of electrons accelerated by surfing from the FEPW is quite easily close to the BEPW phase velocity, which markedly enhances the efficiency of the staged acceleration. The coexistence of these two acceleration mechanisms leads to a significant increase of energetic electrons generated by TPD in the magnetic field. Meanwhile the EPWs are dissipated, TPD instability is effectively suppressed, and the laser transmission increases.

We obtain an explicit formula to enumerate closed random walks on a cubic lattice with a specified length and algebraic area. The algebraic area of a closed cubic lattice walk is defined as the sum of the algebraic areas obtained from the walk's projection onto the three Cartesian planes. This enumeration formula can be mapped onto the cluster coefficients of three types of particles that obey quantum exclusion statistics with statistical parameters $g=1, g=1$, and $g=2$, respectively, subject to the constraint that the numbers of $g=1$ (fermions) exclusion particles of two types are equal.

Normal life activities between cells rely crucially on the homeostasis of the cellular microenvironment, but aging and cancer will upset this balance. In this paper we introduce the microenvironmental feedback mechanism to the growth dynamics of multicellular organisms, which changes the cellular competitive ability and thereby regulates the growth of multicellular organisms. We show that the presence of microenvironmental feedback can effectively delay aging, but cancer cells may grow uncontrollably due to the emergence of the tumor microenvironment (TME). We study the effect of the fraction of cancer cells relative to that of senescent cells on the feedback rate of the microenvironment on the lifespan of multicellular organisms and find that the average lifespan shortened is close to the data for non-Hodgkin's lymphoma in Canada from 1980 to 2015. We also investigate how the competitive ability of cancer cells affects the lifespan of multicellular organisms and reveal that there is an optimal value of the competitive ability of cancer cells allowing the organism to survive longest. Interestingly, the proposed microenvironmental feedback mechanism can give rise to the phenomenon of Parrondo's paradox: When the competitive ability of cancer cells switches between a too-high and a too-low value, multicellular organisms are able to live longer than in each case individually. Our results may provide helpful clues for targeted therapies aimed at the TME.

We give a comprehensive mean-field analysis of the partisan voter model (PVM) and report analytical results for exit probabilities, fixation times, and the quasistationary distribution. In addition, and similarly to the noisy voter model, we introduce a noisy version of the PVM, named the noisy partisan voter model (NPVM), which accounts for the preferences of each agent for the two possible states, as well as for idiosyncratic spontaneous changes of state. We find that the finite-size noise-induced transition of the noisy voter model is modified in the NPVM leading to the emergence of intermediate phases that were absent in the standard version of the noisy voter model, as well as to both continuous and discontinuous transitions.

We revisit the approach to the lower critical dimension $d_{\mathrm{lc}}$ in the Ising-like ${\phi }^4$ theory within the functional renormalization group by studying the lowest approximation levels in the derivative expansion of the effective average action. Our goal is to assess how the latter, which provides a generic approximation scheme valid across dimensions and found to be accurate in $d\ge 2$, is able to capture the long-distance physics associated with the expected proliferation of localized excitations near $d_{\mathrm{lc}}$. We show that the convergence of the fixed-point effective potential is nonuniform in the field when $d\to d_{\mathrm{lc}}$ with the emergence of a boundary layer around the minimum of the potential. This allows us to make analytical predictions for the value of the lower critical dimension $d_{\mathrm{lc}}$ and for the behavior of the critical temperature as $d\to d_{\mathrm{lc}}$, which are both found in fair agreement with the known results. This confirms the versatility of the theoretical approach.

We consider globally coupled networks of identical oscillators, located on the surface of a sphere with interaction time delays, and show that the distance-dependent time delays play a key role for the spiral chimeras to occur as a generic state in different systems of coupled oscillators. For the phase oscillator system, we analyze the existence and stability of stationary solutions along the Ott-Antonsen invariant manifold to find the bifurcation structure of the spiral chimera state. We demonstrate via an extensive numerical experiment that the time-delay-induced spiral chimeras are also present for coupled networks of the Stuart-Landau and Van der Pol oscillators in the same parameter regime as that of phase oscillators, with a series of evenly spaced band-type regions. It is found that the spiral chimera state occurs as a consequence of a resonant-type interplay between the intrinsic period of an individual oscillator and the interaction time delay as a topological structure property.

We consider propagation of solitons along large-scale background waves in the generalized Korteweg–de Vries (gKdV) equation theory when the width of the soliton is much smaller than the characteristic size of the background wave. Due to this difference in scales, the soliton's motion does not affect the dispersionless evolution of the background wave. We obtained the Hamilton equations for soliton's motion and derived simple relationships which express the soliton's velocity in terms of a local value of the background wave. Solitons' paths obtained by integration of these relationships agree very well with the exact numerical solutions of the gKdV equation.

We explore Fermi acceleration in a stochastic oval billiard which shows unlimited to limited diffusion in energy when passing from the free to the dissipative case. We provide evidence for a transition from limited to unlimited energy growth taking place while detuning the corresponding restitution coefficient responsible for the degree of dissipation. A corresponding order parameter is suggested, and its susceptibility is shown to diverge at the critical point. We show that this order parameter is also be applicable to the periodically driven oval billiard and discuss the elementary excitation of the controlled diffusion process.

A central role in shaping the experience of users online is played by recommendation algorithms. On the one hand they help retrieving content that best suits users taste, but on the other hand they may give rise to the so-called “filter bubble” effect, favoring the rise of polarization. In the present paper we study how a user-user collaborative-filtering algorithm affects the behavior of a group of agents repeatedly exposed to it. By means of analytical and numerical techniques we show how the system stationary state depends on the strength of the similarity and popularity biases, quantifying respectively the weight given to the most similar users and to the best rated items. In particular, we derive a phase diagram of the model, where we observe three distinct phases: disorder, consensus, and polarization. In the last users spontaneously split into different groups, each focused on a single item. We identify, at the boundary between the disorder and polarization phases, a region where recommendations are nontrivially personalized without leading to filter bubbles. Finally, we show that our model well reproduces the behavior of users on the online music platform last.fm. This analysis paves the way to a systematic analysis of recommendation algorithms by means of statistical physics methods and opens the possibility of devising less polarizing recommendation algorithms.

Infectious diseases that spread silently through asymptomatic or pre-symptomatic infections represent a challenge for policy makers. A traditional way of achieving isolation of silent infectors from the community is through forward contact tracing, aimed at identifying individuals that might have been infected by a known infected person. In this work we investigate how efficient this measure is in preventing a disease from becoming endemic. We introduce an SIS-based compartmental model where symptomatic individuals may self-isolate and trigger a contact tracing process aimed at quarantining asymptomatic infected individuals. Imperfect adherence and delays affect both measures. We derive the epidemic threshold analytically and find that contact tracing alone can only lead to a very limited increase of the threshold. We quantify the effect of imperfect adherence and the impact of incentivizing asymptomatic and symptomatic populations to adhere to isolation. Our analytical results are confirmed by simulations on complex networks and by the numerical analysis of a much more complex model incorporating more realistic in-host disease progression.

Ant foraging is one of the most fascinating examples of cooperative behavior observed in nature. It is well studied from an entomology viewpoint, but there is currently a lack of mathematical synthesis of this phenomenon. We address this by constructing an ant foraging model that incorporates simple behavioral rules within three task groups of the ant colony during foraging (foragers, transporters, and followers), pheromone trails, and memory effects. The motion of an ant is modeled as a discrete correlated random walk, with a characteristic zigzag path that is congruent with experimental data. We simulate the foraging cycle, which consists of ants searching for food, transporting food, and depositing chemical trails to recruit and orient more ants (en masse) to the food source. This allows us to gain insights into the basic mechanism of the cooperative interactions between ants and the dynamical division of labor within an ant colony during foraging to achieve optimal efficiency. We observe a disorder-order phase transition from the start to the end of a foraging process, signaling collective motion at the population level. Finally, we present a set of time delay ODEs that corroborates with numerical simulations.

Granular flows occur in various contexts, including laboratory experiments, industrial processes, and natural geophysical flows. To investigate their dynamics, different kinds of physically based models have been developed. These models can be characterized by the length scale at which dynamic processes are described. Discrete models use a microscopic scale to individually model each grain, Navier-Stokes models use a mesoscopic scale to consider elementary volumes of grains, and thin-layer models use a macroscopic scale to model the dynamics of elementary columns of fluids. In each case, the derivation of the associated equations is well-known. However, few studies focus on the extent to which these modeling solutions yield mutually coherent results. In this article, we compare the simulations of a granular dam break on a horizontal or inclined planes for the discrete model convex optimization contact dynamics (COCD), the Navier-Stokes model Basilisk, and the thin-layer depth-averaged model SHALTOP. We show that, although all three models allow reproducing the temporal evolution of the free surface in the horizontal case (except for SHALTOP at the initiation), the modeled flow dynamics are significantly different, and, in particular, during the stopping phase. The stresses measured at the flow's bottom, reflecting the flow dynamics, are in relatively good agreement, but significant variations are obtained with the COCD model due to complex and fast-varying granular lattices. Similar conclusions are drawn using the same rheological parameters to model a granular dam break on an inclined plane. This comparison exercise is essential for assessing the limits and uncertainties of granular flow modeling.

Two-dimensional numerical simulations for the Rayleigh-Taylor instability in an elastic-plastic medium are presented. Recent predictions of the theory regarding the asymmetric growth of peaks and valleys during the linear phase of the instability evolution are confirmed. Extension to the nonlinear regime reveals singular features, such as the long delay in achieving the nonlinear saturation and an intermediate phase with growth rate larger than the classical one.

We study chemical pattern formation in a fluid between two flat plates and the effect of such patterns on the formation of convective cells. This patterning is made possible by assuming the plates are chemically reactive or release reagents into the fluid, both of which we model as chemical fluxes. We consider this as a specific example of boundary-bound reactions. In the absence of coupling with fluid flow, we show that the two-reagent system with nonlinear reactions admits chemical instabilities equivalent to diffusion-driven Turing instabilities. In the other extreme, when chemical fluxes at the two bounding plates are constant, diffusion-driven instabilities do not occur but hydrodynamic phenomena analogous to Rayleigh–Bénard convection are possible. Assuming we can influence the chemical fluxes along the domain and select suitable reaction systems, this presents a mechanism for the control of chemical and hydrodynamic instabilities and pattern formation. We study a generic class of models and find necessary conditions for a bifurcation to pattern formation. Afterwards, we present two examples derived from the Schnakenberg–Selkov reaction. Unlike the classical Rayleigh–Bénard instability, which requires a sufficiently large unstable density gradient, a chemohydrodynamic instability based on Turing-style pattern formation can emerge from a state that is uniform in density. We also find parameter combinations that result in the formation of convective cells whether gravity acts upwards or downwards relative to the reactive plate. The wave number of the cells and the direction of the flow at regions of high/low concentration depend on the orientation, hence, different patterns can be elicited by simply inverting the device. More generally, our results suggest methods for controlling pattern formation and convection by tuning reaction parameters. As a consequence, we can drive and alter fluid flow in a chamber without mechanical pumps by influencing the chemical instabilities.

Volume plasma density gratings receive increasing interest since, compared to solid-state optical media, they posses significantly higher damage thresholds. The gratings are produced by counterpropagating laser pulses in underdense plasma. When analyzing their optical properties, usually they are assumed to be homogeneous in space. The latter assumption, however, breaks down, especially when the gratings are produced by short high-power laser pump pulses. Then, generically the plasma grating posses an inhomogeneous envelope which results from the superposition of the pump pulses envelopes. The present paper discusses the effect of grating inhomogeneity on reflection and transmission of probe pulses. A Gaussian plasma density grating becomes an apodized grating which offers significant improvement over homogeneous gratings due to side-lobe suppression while maintaining reflectivity and a narrow bandwidth. On the other hand, the reflected probe pulses receive a chirp which depends on the spatial scale. For a Gaussian grating a cubic spectral phase appears. Numerical particle-in-cell simulations are supported by theoretical analysis based on coupled mode equations as well as an effective medium approach.

We investigate the classical ground state of a large number of charges confined inside a disk and interacting via the Coulomb potential. By realizing the important role that the peripheral charges play in determining the lowest energy solutions, we have successfully implemented an algorithm that allows us to work with configurations with a desired number of border charges. This feature brings a consistent reduction in the computational complexity of the problem, thus simplifying the search of global minima of the energy. Additionally, we have implemented a divide and conquer approach which has allowed us to study configurations of size never reached before (the largest one corresponding to $N=40886$ charges). These last configurations, in particular, are seen to display an increasingly rich structure of topological defects as $N$ gets larger.

We investigate bounds on speed, nonadiabatic entropy production, and the trade-off relation between them for classical stochastic processes with time-independent transition rates. Our results show that the time required to evolve from an initial to a desired target state is bounded from below by the information-theoretical $\infty$-Rényi divergence between these states, divided by the total rate. Furthermore, we conjecture and provide extensive numerical evidence for an information-theoretical bound on the nonadiabatic entropy production and a dissipation-time trade-off relation that outperforms previous bounds in some cases..

We present a microscopic derivation of the nonlinear fluctuating hydrodynamic equation for a homogeneous crystalline solid from the Hamiltonian description of a many-particle system. We propose a microscopic expression of the displacement field that correctly generates the nonlinear elastic properties of the solid and find the nonlinear mode-coupling terms in reversible currents that are consistent with the phenomenological equation. The derivation relies on the projection onto the coarse-grained fields including the displacement field, the long-wavelength expansion, and the stationarity condition of the Fokker–Planck equation.