arXiv subjects

Shradha Mishra

Publications and source records attributed to Shradha Mishra.

At least 19 recordsLinked to original sources

arXiv2026

Unconventional Growth Kinetics and Fractal Interfaces of Colloidal Phase Separation in Active Liquids

Phase separation driven by nonequilibrium fluctuations is a hallmark of both living and synthetic active matter. Unlike equilibrium systems, where ordered states arise from the minimization of free energy, active systems are fueled by a constant injection of energy at the microscopic scale. The emergence of ordered phases in such driven systems challenges our conventional views of domain growth and interfacial structure. In this study, we investigate the coarsening of colloidal clusters in active liquids containing E. coli. Our experiments reveal that uniform dispersions of colloids and swimmers are inherently unstable, resulting in spontaneous phase separation characterized by fractal interfaces and unconventional kinetics. The correlation function of the order parameter displays dynamical scaling, with the size of colloidal domains initially growing as $t^{1/z}$, where $z \sim 4$, in contrast to the well-known growth laws for thermal systems with a conserved order parameter. Furthermore, the structure factor exhibits non-Porod behavior, indicating domains with fractal interfaces. This non-Porod behavior also manifests itself as a cusp singularity in the correlation function. We elucidate our experimental findings using a scalar field theory in which the nonequilibrium fluctuations arising from swimmer activity are modeled as spatio-temporally correlated noise. It quantitatively reproduces the domain growth law and non-Porod structure factor resulting from fractal interfaces observed in experiments. In addition, it also reveals a fluctuating microphase separation, where the initial growth of the domain is eventually arrested, thus shedding new light on the microscopic origins of the unconventional phase separation of colloids in active liquids.

cond-mat.soft↗

arXiv2026

Data Driven Equation Discovery for Phase-Ordering Dynamics : From Allen Cahn to the Ising Model

Data-driven discovery of governing equations from spatiotemporal data offers a promising route to obtaining coarse-grained descriptions of complex dynamical systems. Here, we investigate the performance of PDE-SINDy for discovering phase-ordering dynamics using the Allen--Cahn equation as a benchmark and the Ising model with Glauber spin-flip dynamics as a microscopic system. We systematically analyze the effects of data availability, size of the candidate library, and noise on the efficiency of the equation discovery. We find that stability-selection PDE-SINDy can robustly identify the relevant terms in the governing dynamics even under limited or noisy data, while the recovered coefficient values are substantially more sensitive to these factors. We further show that enlarging the candidate library can strongly affect both term identification and coefficient recovery. Incorporating library bagging with stability selection reduces this sensitivity and improves the efficiency of equation discovery. For the Glauber spin flip Ising model dynamics, the resulting coarse-grained equation reproduces the characteristic phase-separation and coarsening dynamics of the underlying microscopic system. Overall, our results demonstrate the potential of PDE-SINDy for phase-ordering systems while highlighting the importance of carefully assessing the factors that influence the efficiency of equation discovery.

cond-mat.soft↗

arXiv2026

Statistical Language Competition Model with Dynamic Edge Weighting on a Random Network

This paper presents a computational study of language competition dynamics on Erdős--Rényi random networks, extending the foundational Abrams--Strogatz model through two novel contributions: (i) a dynamic edge-weighting mechanism that reinforces social ties between co-minority speakers by an additive increment $Δ$, and (ii) a probabilistic agent-based framework governing language switching via a weighted majority rule. Phase boundaries separating the dominance and coexistence regimes are identified across a two-dimensional parameter space $(p, Δ)$, where $p$ denotes the network connectivity probability. We further characterise anomalous persistence zones within predicted dominance regions, attributing them to the formation of isolated minority speaker clusters. Scaling study across network sizes $N \in \{50, 100, 250, 500, 1000\}$ reveal that average cluster size decreases with $N$ and that phase boundaries diffuse with increasing stochastic noise. Finally, we discuss extensions to a tripartite bilingual model and heterogeneous prestige/volatility to more faithfully capture real sociolinguistic contact scenarios.

cond-mat.stat-mech↗

arXiv2026

Shape Evolution and Dynamics of Deformable Ring

We numerically investigate the dynamics of a deformable closed ring filled with active particles. The ring is modeled as a flexible boundary made up of passive beads interacting with a harmonic spring force. The interior of the ring is filled with active Brownian particles (ABPs), and their activity is controlled through the rotational diffusion coefficient. We explore how, by systematically varying the activity of ABPs, packing fraction, and size of the ring, we can control the shape deformation and dynamics of the ring. At low packing fractions, low rotational diffusion coefficients, and smaller ring sizes, the ring exhibits highly irregular and strongly deformed shapes due to the uneven spatial arrangement of active particles along the boundary. Increasing the packing fraction, rotational diffusion coefficient, or ring size promotes a more even distribution of active particles within the ring, thereby suppressing shape deformations and fluctuations, driving the ring toward a more circular shape. We further analyze the mean-squared displacement (MSD) of the ring's center of mass and observe a crossover from ballistic to diffusive dynamics, which can be tuned by varying the system parameters. Our results demonstrate that, despite its internal complexity and deformability, the ring exhibits emergent behavior analogous to that of a single effective active particle. This study provides insight into the collective effects of confined active matter and the resulting macroscopic dynamics of deformable systems.

cond-mat.soft↗

arXiv2026

Emergent Rotation of Passive Clusters in a Chiral Active Bath

We investigate the dynamics of passive particles immersed in a bath of chiral active particles, focusing on the emergence of collective rotational motion. Using numerical simulations, we show that passive particles aggregate into clusters that can exhibit persistent rotation within a well-defined regime of size ratio and active particle packing fraction. This rotational state is characterized by the coexistence of internal structural order, enhanced shape fluctuations, and a coherent net torque generated by the surrounding active bath. Outside this regime, the dynamics remain predominantly diffusive, highlighting that sustained rotation is not ubiquitous but arises from a delicate interplay between geometry, activity, and chirality. Furthermore, we demonstrate that chirality heterogeneity disrupts rotational coherence, while a uniform chiral bath promotes strongly superdiffusive angular dynamics. These results provide new insights into the role of chirality and collective interactions in shaping the emergent behavior of active-passive mixtures.

cond-mat.soft↗

arXiv2026

Density-Induced Reentrant Coarsening in a Two-Temperature System

Understanding how nonequilibrium driving modifies phase-separation kinetics remains a fundamental challenge. Here we show that phase separation in a two-temperature system exhibits a striking density-induced reentrant coarsening behavior. Using Brownian dynamics simulations and a coarse-grained field-theoretic model, we find that the characteristic domain size grows as $L(t)\sim t^{1/z}$, displaying a reentrant sequence $(t^{1/3} \rightarrow t^{1/4}\rightarrow t^{1/3})$ with increasing density. While the low- and high-density regimes are governed by classical curvature-driven bulk diffusion, the intermediate-density regime exhibits anomalously slow growth. We show that this slowdown originates from a transport bottleneck arising from the interplay of particle diffusivity, particle availability, and attachment kinetics, which suppresses the effective mass flux between domains. Unlike equilibrium phase separation, where density primarily affects morphology and crossover scales, the two-temperature drive renders density a key control parameter for coarsening pathways. Our results uncover a nonequilibrium mechanism for anomalous domain growth in two-temperature systems.

cond-mat.soft↗

arXiv2026

Homing through Reinforcement Learning

Homing and navigation are fundamental behaviors in biological systems that enable agents to reliably reach a target under uncertainty. We present a Reinforcement Learning (RL) framework to model adaptive homing in continuous two-dimensional domain. In this framework, the agent's state is given by its angular deviation from home, actions correspond to alignment or stochastic reorientation, and learning is driven by a radial-distance-based cost that penalizes motion away from the target, where the cost also acts as an effective signal guiding the agent towards the home. For a single self-propelled agent moving with constant speed, we find that the mean homing time $\langle T_{\mathrm{home}} \rangle$ exhibits a non-monotonic dependence on the rotational diffusion strength $D_r$, with an optimal noise level $D_r^\ast$, revealing a subtle interplay between exploration and goal-directed correction. Extending to two agents with soft repulsion, one agent consistently reaches home faster than the other, while in multi-agents system, repulsion ensures separation and the fastest agent becomes progressively faster as group size increases. Finally, we have compared the homing time obtained from the RL agent with that of an Active Brownian Particle (ABP) with resetting and a pure ABP (without resetting) under identical conditions. The RL-based agent consistently achieves shorter homing times with trajectories that are less noisy and more directed than both cases, while the pure ABP typically continues wandering near the target without reliable localization. Our results show that cost-driven learning, stochastic reorientation, and inter-agent interactions enable efficient adaptive navigation, linking individual and collective homing. This RL framework captures key biological features such as feedback-based route learning, randomness to escape unfavorable orientations, and mutual coordination.

cond-mat.soft↗

arXiv2026

Analytical Theory of Chiral Active Particle Transport in a Fluctuating Density Field

We develop a closed-form analytical theory for the transport of a chiral active Brownian particle in three dimensions, moving through a fluctuating local density field that models steric and dynamical interactions in a dense active medium. The density field is modeled as an Ornstein--Uhlenbeck process with finite correlation time $τ$ and fluctuation strength $σ_ρ^2$, capturing both spatial fluctuations and temporal memory. Within this framework, we derive exact expressions for the mean-squared displacement and time-dependent diffusivity, revealing how chirality and density coupling jointly renormalise orientational persistence and generate nontrivial dynamical crossovers. The theory predicts: (i) anomalously high initial diffusivity for particles starting in locally denser regions, arising from a transient active drift driven by local swim-pressure gradients; (ii) a finite crossover time $t_c$ for homogenising density inhomogeneities, with a transient dependence of the dynamics on the initial local density environment which arises from the non-equilibrium evolution of density fluctuations and does not persist when averaging over stationary initial conditions ($ρ_0 = ρ_\infty$) ; (iii) a non-monotonic $t_c(Ω)$ with a global minimum at intermediate chirality, and a three-regime suppression of long-time diffusivity $D_\infty(Ω)$, consistent with micro-clustered phases observed in simulations; and (iv) a resonance-like peak in the early-time oscillatory strength of the mean-squared displacement at an optimal chirality $Ω^*$, set by the interplay of orientational diffusion, density-field decorrelation, and imposed rotation. The framework captures the qualitative dependence of $D_\infty$ on $Pe$ and $Ω$, {where Pe denotes the Péclet number}, while uncovering chirality-dependent transport features in active matter.

cond-mat.stat-mech↗

arXiv2026

Spatiotemporal Chaos and Defect Proliferation in Polar-Apolar Active Mixture

Chaotic transitions in inertial fluids typically proceed through a direct energy cascade from large to small scales. In contrast, active systems, composed of self propelled units, inject energy at microscopic scales and therefore exhibit an inverse cascade, giving rise to distinctly unconventional flow patterns. Here, we investigate an active mixture consisting of both apolar and polar self driven components, a setting expected to display richer behaviours than those found in living liquid crystal (LLC) systems, where the apolar constituent is passive. Using numerical solutions of the corresponding hydrodynamic equations, we uncover a variety of complex dynamical states. Our results reveal a non-monotonic response of the apolar species to changes in the density and activity of the polar component. In an intermediate regime, reminiscent of LLC-induced disorder, the system develops a dynamically disordered phase characterised by high-density, chaotically evolving band-like structures and by the continual creation and annihilation of half integer topological defects. We show that this regime exhibits spatiotemporal chaos, which we quantify through two complementary measures: the spectral properties of density fluctuations and the maximal Lyapunov exponent. Together, these findings broaden the understanding of complex transitions in active matter and suggest potential experimental realisations in bacterial suspensions or synthetic microswimmer assemblies.

cond-mat.soft↗

arXiv2025

Competing effect of disorder on phase separation in active systems

We investigate the impact of random pinned disorder on a collection of self propelled particles. To achieve this, we construct a continuum model by formulating the coupled hydrodynamic equations for slow variables, local density and momentum density of particles. The disorder in the system acts as pinning sites, effectively immobilizing the particles that come into contact with them. Our numerical results reveal that weak disorder leads to phase separation in the system at density and activity lower than the typical values for motility induced phase separation. We construct a phase diagram using numerical simulations as well as linearized approximation in the plane of activity and packing fraction of particles at weak disorder densities. On increasing disorder density the system shows the Micro phase separation, while at large disorder densities, the system becomes heterogeneous and eventually undergoes kinetic arrest. The structure factor tail deviates from the Porods law, indicating increased roughness at domain interfaces under strong disorder. Furthermore, we analyze the fractal dimension of the interface as a function of disorder density, highlighting the increasing irregularity of phase separated domains. We also found that disorder significantly suppresses number fluctuations in the system.

cond-mat.soft↗

arXiv2025

Phase separation kinetics of 2-TIPS at low density: Cluster growth by ballistic agglomeration

We study the kinetics of two-temperature induced phase separation (2-TIPS) in dilute binary mixtures of active ("hot") and passive ("cold") particles using molecular dynamics simulations and a coarse-grained hydrodynamic model. Following a temperature quench, cold particles nucleate into mobile clusters that move ballistically and merge through successive coalescence events. The resulting domain growth exhibits dynamic scaling with a growth exponent of approximately 0.7, markedly faster than diffusive coarsening. We identify this regime as ballistic agglomeration of cold clusters, demonstrating a distinct nonequilibrium growth mechanism in low-density scalar active systems.

cond-mat.soft↗

arXiv2025

From LRO to Disorder via QLRO in Spatially Inhomogeneous Polar Flock

We study the collective behavior of a polar flock in an inhomogeneous environment in two-dimensions. The inhomogeneity is modelled by introducing regions at random locations on the substrate with higher noise but accessible for the flock to move. Hence inside such regions the particles orientation get randomised. Such inhomogeneities are different from the physical disorder, which obstructs the space for the incoming particles. The study focuses on how the phase behavior of polar flock changes by tuning the packing fraction of inhomogeneity. As packing fraction increases, the system crosses over from long-range to quasi long range order and ultimately to a disordered phase, while the order disorder transition for flocking changes from discontinuous to continuous. The resultant phase behavior of polar flock patterns here is comparable to that exhibited in the presence of physical disorder.

cond-mat.soft↗

arXiv2025

From Flocking to Condensation: Collective Dynamics in Binary Chiral Active Matter

Many microswimmers are inherently chiral, and this chirality can introduce fascinating behaviors in a collection of microswimmers. The dynamics become even more intriguing when two types of microswimmers with distinct chirality are mixed. Our study examines a mixture of self-propelled particles with opposite chirality, investigating how the system's characteristics evolve as the magnitude of chirality is varied. In weakly chiral systems, the particles exhibit similar behavior, leading to a globally flocking phase where both types of particles are well-mixed. However, in an intermediate range of chirality, the condensates of different particles are formed as a result of a competition between chirality and self-propulsion. This competition results in interesting phases within the system. We explore the characteristics of these distinct phases in detail, focusing on the roles of self-propulsion speed and chirality.

cond-mat.soft↗

arXiv2025

Coarsening Kinetics in Active Model B+: Macroscale and Microscale Phase Separation

We perform a comprehensive numerical investigation of the coarsening kinetics of active Brownian particles modeled by the {\it Active Model B+} (AMB+). This model was introduced by Tjhung et al. [Phys. Rev. X {\bf 8}, 031080 (2018)] and is a generalization of Model B for a conserved order parameter, with two additional activity terms. These terms correspond to rotation-free current (of strength $λ$) and rotational current (of strength $ξ$). We find that the presence of rotational current $(ξ\neq 0)$ significantly affects growth kinetics. Depending on the parameter values, AMB+ exhibits either {\it macroscale phase separation} (MPS) or {\it microscale phase separation} ($μ$PS). We present detailed results for the kinetics of MPS and $μ$PS in AMB+ with critical composition.

cond-mat.soft↗

arXiv2025

Spatio-temporal patterns in Growing Bacterial Suspensions

The field of active matter explores the behaviors of self propelled agents out of equilibrium, with active suspensions, such as swimming bacteria in solutions, serving as impactful models. These systems exhibit spatio-temporal patterns akin to active turbulence, driven by internal energy injection. While bacterial turbulence in dense suspensions is well studied, the dynamics in growing bacterial suspensions are less understood. This work presents a phenomenological coarse-grained model for growing bacterial suspensions, incorporating hydrodynamic equations for bacterial density, orientation, and fluid velocity, with birth and death terms for colony growth. Starting with low density and random orientations, the model shows the development of local ordering as bacterial density increases. As density continues to rise, the model captures four distinct phases; dilute, clustered, turbulent, and trapped based on structural patterns and dynamics, with the turbulent phase characterized by spatio-temporal vortex structures, aligning with observations in dense bacterial suspensions.

cond-mat.soft↗

arXiv2025

Spontaneous Rotation of a Symmetric Inclusion in Chiral Active Bath

We study the dynamics of a circular passive inclusion, termed a torquer, in a bath of chiral active Brownian particles. Despite being geometrically symmetric and non-motile, the torquer exhibits persistent rotation due to spatially inhomogeneous torques arising from angularly biased collisions with active particles. This interaction-driven symmetry breaking does not rely on shape anisotropy or external forcing. Through simulations, we identify two distinct regimes of rotation: one dominated by density gradients at low chirality, and another by increased impact frequency at high chirality. Our results highlight how nonequilibrium interactions in chiral active media can induce motion in symmetric objects, offering a new perspective on symmetry breaking in active systems.

cond-mat.soft↗

arXiv2025

String Formation and Arrested Ordering Kinetics in Nematics Induced by Polar Particles

Our study explores the mixture of polar particles in apolar environment. We employ a coarse-grained approach to model the mixture, where polar particles are in minority. The interaction between polar and apolar components is incorporated via a coupling term in the free energy. Coupling generates local interaction in the system which results in the formation of string like structures connecting a pair of half integer topological defects. The increase in the coupling strength or the density of polar particles results in the: Sharper strings with larger probability of connecting the topological defects of same charge and the enhanced dynamics of topological defects. However, the ordering kinetics of the system shows the delayed coarsening for larger coupling or polar density. Our results can be used to develop controlled kinetics as well as to detect the impurities in liquid crystals.

cond-mat.soft↗

arXiv2025

Effective single particle theory for active particles using local density fluctuations

We characterize the dynamic non-equilibrium steady state behavior of active particles using density fluctuations in the system. We analyze the effective local density around a particle in the steady state and numerically calculate its mean, variance and autocorrelation. Thus, using local density and its statistical properties as a temporally correlated stochastic variable, we develop an effective single-particle theoretical model and analytically derive an expression for the particle's diffusivity as a function of the global packing density in the system. Our theory accurately predicts the transport properties of an active particle, validated against numerical simulations. Unlike mean-field theory, which fails at high packing densities due to significant density fluctuations from dynamic cluster formation, our model remains effective across all densities. It also captures the well-known phase transition beyond a critical packing density. The key novelty of our model lies in the introduction of a stochastic local density field, which encapsulates the effect of steric interactions on an active particle and helps predict single-particle behavior in a collection, a feature often absent in standard active matter models. This approach could be useful in experimental setups where fluctuations in local density around a tagged particle are measurable.

cond-mat.stat-mech↗