arXiv subjects

Ruben Zakine

Publications and source records attributed to Ruben Zakine.

15 recordsLinked to original sources

arXiv2025

Hydrodynamics of Cooperation and Self-Interest in a Two-Population Occupation Model

We study the hydrodynamics of a system of agents who optimize either their individual utility (self-interest) or the collective welfare (cooperation). When agents act selfishly, their interactions are non-reciprocal, driving the system out of equilibrium; by contrast, purely altruistic dynamics restore reciprocity and yield an equilibrium-like description. We investigate how mixtures of these two behaviors shape the macroscopic properties of the liquid of agents. For highly rational agents, we find that introducing a small fraction of altruists can suppress the sub-optimal clustering induced by selfish dynamics. This phenomenon can be attributed to altruists localizing at interfaces and acting as effective surfactants, shedding a new light on earlier findings in fixed neighborhood-based models [Phys. Rev. Lett. \textbf{120}, 208301 (2018)]. When agents are boundedly rational, we introduce a well-mixed approximation that reduces the two-population model to a single effective scalar field theory. This allows us to leverage state-of-the-art tools from active matter to analytically characterize how altruism modifies surface tension and nucleation dynamics.

cond-mat.stat-mech↗

arXiv2025

Patterns robust to Disorder in spatially-interacting Generalized Lotka-Volterra Ecosystems

How do interactions between species influence their spatial distribution in an ecosystem? To answer this question, we introduce a spatially-extended ecosystem of Generalized Lotka-Volterra type, where species can diffuse and interactions are nonlocal. We compute the criterion for the loss of stability of the spatially homogeneous ecosystem, and we show that the stability of the uniform state crucially depends on the most abundant species, and on the interplay between space exploration during one species generation and the interaction range. Focusing on the spectrum of the interaction matrix weighted by the species abundances, we identify a Baik-Ben Arous-Péché transition that translates into a transition in the final patterns of the species repartition. Finally assuming that the disorder is small, we exhibit an explicit solution of the dynamical mean-field equation for the species density, obtained as the fixed point of a nonlocal Fisher-Kolmogorov-Petrovski-Piskounov equation. Our work paves the way of future combined approaches at the frontier of active matter and disordered systems, with the hope of better understanding complex ecosystems like bacterial communities.

cond-mat.stat-mech↗

arXiv2024

Socioeconomic agents as active matter in nonequilibrium Sakoda-Schelling models

How robust are socioeconomic agent-based models with respect to the details of the agents' decision rule? We tackle this question by considering an occupation model in the spirit of the Sakoda-Schelling model, historically introduced to shed light on segregation dynamics among human groups. For a large class of utility functions and decision rules, we pinpoint the nonequilibrium nature of the agent dynamics, while recovering the equilibrium-like phase separation phenomenology. Within the mean field approximation we show how the model can be mapped, to some extent, onto an active matter field description. Finally, we consider non-reciprocal interactions between two populations, and show how they can lead to non-steady macroscopic behavior. We believe our approach provides a unifying framework to further study geography-dependent agent-based models, notably paving the way for joint consideration of population and price dynamics within a field theoretic approach.

cond-mat.stat-mech↗

arXiv2024

Unveiling the Phase Diagram and Reaction Paths of the Active Model B with the Deep Minimum Action Method

Nonequilibrium phase transitions are notably difficult to analyze because their mechanisms depend on the system's dynamics in a complex way due to the lack of time-reversal symmetry. To complicate matters, the system's steady-state distribution is unknown in general. Here, the phase diagram of the active Model B is computed with a deep neural network implementation of the geometric minimum action method (gMAM). This approach unveils the unconventional reaction paths and nucleation mechanism in dimensions 1, 2 and 3, by which the system switches between the homogeneous and inhomogeneous phases in the binodal region. Our main findings are: (i) the mean time to escape the phase-separated state is (exponentially) extensive in the system size $L$, but it increases non-monotonically with $L$ in dimension 1; (ii) the mean time to escape the homogeneous state is always finite, in line with the recent work of Cates and Nardini~[Phys. Rev. Lett. 130, 098203]; (iii) at fixed $L$, the active term increases the stability of the homogeneous phase, eventually destroying the phase separation in the binodal for large but finite systems. Our results are particularly relevant for active matter systems in which the number of constituents hardly goes beyond $10^7$ and where finite-size effects matter.

cond-mat.stat-mech↗

arXiv2024

On the relative packing densities of pistachios and pistachio shells

Given an appetizer bowl full of $N$ pistachios, what is the optimal size of the container -- neither too small, nor too big -- needed for accommodating the resulting $2N$ non-edible pistachio shells? Performing a simple experiment we find that, provided the shells are densely packed, such container needs only be slightly more than half ($\approx 0.57$) that of the original pistachio bowl. If loosely packed this number increases to $\approx 0.73$. Our results are discussed in light of existing literature on packing ellipsoids and spherical caps.

cond-mat.soft↗

arXiv2024

Active Young-Dupré Equation: How Self-organized Currents Stabilize Partial Wetting

The Young-Dupré equation is a cornerstone of the equilibrium theory of capillary and wetting phenomena. In the biological world, interfacial phenomena are ubiquitous, from the spreading of bacterial colonies to tissue growth and flocking of birds, but the description of such active systems escapes the realm of equilibrium physics. Here we show how a microscopic, mechanical definition of surface tension allows us to build an Active Young-Dupré equation able to account for the partial wetting observed in simulations of active particles interacting via pairwise forces. Remarkably, the equation shows that the corresponding steady interfaces do not result from a simple balance between the surface tensions at play but instead emerge from a complex feedback mechanism. The interfaces are indeed stabilized by a drag force due to the emergence of steady currents, which are themselves a by-product of the symmetry breaking induced by the interfaces. These currents also lead to new physics by selecting the sizes and shapes of adsorbed droplets, breaking the equilibrium scale-free nature of the problem. Finally, we demonstrate a spectacular consequence of the negative value of the liquid-gas surface tensions in systems undergoing motility-induced phase separation: partially-immersed objects are expelled from the liquid phase, in stark contrast with what is observed in passive systems. All in all, our results lay the foundations for a theory of wetting in active systems.

cond-mat.soft↗

arXiv2024

Evolving motility of active droplets is captured by a self-repelling random walk model

Swimming droplets are a class of active particles whose motility changes as a function of time due to shrinkage and self-avoidance of their trail. Here we combine experiments and theory to show that our non-Markovian droplet (NMD) model, akin to a true self-avoiding walk [1], quantitatively captures droplet motion. We thus estimate the effective temperature arising from hydrodynamic flows and the coupling strength of the propulsion force as a function of fuel concentration. This framework explains a broad range of phenomena, including memory effects, solute-mediated interactions, droplet hovering above the surface, and enhanced collective diffusion.

cond-mat.soft↗

arXiv2023

Interactions enhance dispersion in fluctuating channels via emergent flows

Understanding particle motion in narrow channels is essential to guide progress in numerous applications, from filtration to vascular transport. Thermal or active fluctuations of channel walls for fluid-filled channels can slow down or increase the dispersion of tracer particles. Entropic trapping in the wall bulges slows dispersion, and hydrodynamic flows induced by wall fluctuations enhance dispersion. Previous studies primarily concentrated on the case of a single Brownian tracer either embedded in an incompressible fluid or in the ideal case where the presence of fluid is ignored. Here we address the question of what happens when there is a large ensemble of interacting Brownian tracers -- a common situation in applications. Introducing repulsive interactions between the tracer particles, while ignoring the presence of a background fluid, leads to an effective flow field. This flow field enhances tracer dispersion, a phenomenon strongly reminiscent of that seen in incompressible background fluid. We characterise the dispersion by the long-time diffusion coefficient of a single tracer, numerically and analytically with a mean-field density functional analysis. We find a surprising effect where an increased particle density enhances the diffusion coefficient, challenging the notion that crowding effects tend to reduce diffusion. Here, inter-particle interactions push particles closer to the fluctuating channel walls. Then, interactions between the fluctuating wall and the now-nearby particles drive particle mixing. Our mechanism is sufficiently general that we expect it to apply to various systems. In addition, the perturbation theory we derive quantifies dispersion in generic advection-diffusion systems with arbitrary spatiotemporal drift.

cond-mat.soft↗

arXiv2022

Minimum Action Method for Nonequilibrium Phase Transitions

First-order nonequilibrium phase transitions observed in active matter, fluid dynamics, biology, climate science, and other systems with irreversible dynamics are challenging to analyze because they cannot be inferred from a simple free energy minimization principle. Rather the mechanism of these transitions depends crucially on the system's dynamics, which requires us to analyze them in trajectory space rather than in phase space. Here we consider situations where the path of these transitions can be characterized as the minimizer of an action, whose minimum value can be used in a nonequilibrium generalization of the Arrhenius law to calculate the system's phase diagram. We also develop efficient numerical tools for the minimization of this action. These tools are general enough to be transportable to many situations of interest, in particular when the fluctuations present in the microscopic system are non-Gaussian and its dynamics is not governed by the standard Langevin equation. As an illustration, first-order phase transitions in two spatially-extended nonequilibrium systems are analyzed: a modified Ginzburg-Landau equation with a chemical potential which is non-gradient, and a reaction-diffusion network based on the Schlögl model. The phase diagrams of both systems are calculated as a function of their control parameters, and the paths of the transitions, including their critical nuclei, are identified. These results clearly demonstrate the nonequilibrium nature of the transitions, with differing forward and backward paths.

cond-mat.stat-mech↗

arXiv2019

Spatial Organization of Active Particles with Field Mediated Interactions

We consider a system of independent point-like particles performing a Brownian motion while interacting with a Gaussian fluctuating background. These particles are in addition endowed with a discrete two-state internal degree of freedom that is subjected to a nonequilibrium source of noise, which affects their coupling with the background field. We explore the phase diagram of the system and pinpoint the role of the nonequilibrium drive in producing a nontrivial patterned spatial organization. We are able, by means of a weakly nonlinear analysis, to account for the parameter-dependence of the boundaries of the phase and pattern diagram in the stationary state.

cond-mat.soft↗

arXiv2019

Surface Tensions between Active Fluids and Solid Interfaces: bare vs dressed

We analyze the surface tension exerted at the interface between an active fluid and a solid boundary in terms of tangential forces. Focusing on active systems known to possess an equation of state for the pressure, we show that interfacial forces are of a more complex nature. Using a number of macroscopic setups, we show that the surface tension is a combination of an equation-of-state abiding part and of setup-dependent contributions. The latter arise from generic setup-dependent steady currents which "dress" the measurement of the "bare" surface tension. The former shares interesting properties with its equilibrium counterpart, and can be used to generalize the Young-Laplace law to active systems. We finally show how a suitably designed probe can directly access this bare surface tensions, which can also be computed using a generalized Virial formula.

cond-mat.soft↗

arXiv2019

Interaction and self-assembly of membrane-binding and membrane-excluding colloids embedded in lamellar phases

Within the framework of a discrete Gaussian model, we present analytical results for the interaction induced by a lamellar phase between small embedded colloids. We consider the two limits of particles strongly adherent to the adjacent membranes and of particles impenetrable to the membranes. Our approach takes into account the finite size of the colloids, the discrete nature of the layers, and includes the Casimir-like effect of fluctuations, which is very important for dilute phases. Monte Carlo simulations of the statistical behavior of the membrane-interacting colloids account semi-quantitatively, without any adjustable parameters, for the experimental data measured on silica nanospheres inserted within lyotropic smectics. We predict the existence of finite-size and densely packed particle aggregates originating from the competition between attractive interactions between colloids in the same layer and repulsion between colloids one layer apart.

cond-mat.soft↗

arXiv2018

Field-Embedded Particles Driven by Active Flips

Systems of independent active particles embedded into a fluctuating environment are relevant to many areas of soft-matter science. We use a minimal model of noninteracting spin-carrying Brownian particles in a Gaussian field and show that activity-driven spin dynamics leads to patterned order. We find that the competition between mediated interactions and active noise alone can yield such diverse behaviors as phase transitions and microphase separation, from lamellar up to hexagonal ordering of clusters of opposite magnetization. These rest on complex multibody interactions. We find regimes of stationary patterns, but also dynamical regimes of relentless birth and growth of lumps of magnetization opposite to the surrounding one. Our approach combines Monte-Carlo simulations with analytical methods based on dynamical density functional approaches.

cond-mat.soft↗

arXiv2017

Stochastic Stirling engine operating in contact with active baths

A Stirling engine made of a colloidal particle in contact with a nonequilibrium bath is considered and analyzed with the tools of stochastic energetics. We model the bath by non Gaussian persistent noise acting on the colloidal particle. Depending on the chosen definition of an isothermal transformation in this nonequilibrium setting, we find that either the energetics of the engine parallels that of its equilibrium counterpart or, in the simplest case, that it ends up being less efficient. Persistence, more than non Gaussian effects, are responsible for this result.

cond-mat.stat-mech↗

arXiv2017

The elusive synchrotron precursor of collisionless shocks

Most of the plasma microphysics which shapes the acceleration process of particles at collisionless shock waves takes place in the cosmic-ray precursor, through the interaction of accelerated particles with the unshocked plasma. Detecting directly or indirectly the synchrotron radiation of accelerated particles in this precursor would open a new window on the microphysics of acceleration and of collisionless shock waves. We provide analytical estimates of the spectrum and of the polarization fraction of the synchrotron precursor for both relativistic and non-relativistic collisionless shock fronts, accounting for the self-generation or amplification of magnetic turbulence. In relativistic sources, the spectrum of the precursor is harder than that of the shocked plasma, because the upstream residence time increases with particle energy, leading to an effectively hard spectrum of accelerated particles in the precursor volume. At high frequencies, typically in the optical to X-ray range, the contribution of the precursor becomes sizeable, but we find that in most cases studied, it remains dominated by the synchrotron or inverse Compton contribution of the shocked plasma; its contribution might be detectable only in trans-relativistic shock waves. Non-relativistic sources offer the possibility of spectral imaging of the precursor by viewing the shock front edge-on. We calculate this spectro-morphological contribution for various parameters. The synchrotron contribution is also sizeable at the highest frequencies (X-ray range). If the turbulence is tangled in the plane transverse to the shock front, the resulting synchrotron radiation should be nearly maximally linearly polarized; polarimetry thus arises as an interesting tool to reveal this precursor.[Abridged]

astro-ph.HE↗