arXiv subjects

Shradha Mishra

Publications and source records attributed to Shradha Mishra.

At least 37 records · Page 2Linked to original sources

arXiv2025

Growth Laws and Universality in 2-TIPS: Microscopic and Coarse grained approach

Two temperature induced phase separation(2-TIPS) is a phenomenon observed in mixtures of active and passive particles modeled by scalar activity where the temperature of the particle is proportional to its activity. The binary mixture of 'hot' and 'cold' particles phase separate when the relative temperature difference between hot and cold particles defined as activity $χ$ exceeds a density dependent critical value. The study of kinetics in 2-TIPS, a non-equilibrium phase separation, is of fundamental importance in statistical physics. In this paper, we investigate 2-TIPS kinetics using molecular dynamics (MD) and coarse-grained (CG) modeling in 3D and 2D. The coarse-grained model couples two passive Model B equations for hot and cold particles, with coupling terms emulating the energy transfer between them by raising the temperature of cold particles and lowering that of hot particles, a key observation from the MD simulations. MD simulations reveal that at high densities, phase separation begins immediately after the quench, forming bi-continuous domains rich in hot or cold particles, similar to spinodal decomposition in passive systems. These interconnected domains are also observed in the coarse-grained model for the mixture's critical composition. Both MD and CG models show dynamic scaling of the correlation function, indicating self-similar domain growth. Regardless of dimensionality, both methods report algebraic growth in domain length with a growth exponent of $1/3$, known as the Lifshitz-Slyozov exponent, widely observed in passive systems. Our results demonstrate that the universality of phase separation kinetics observed in passive systems also extends to the non-equilibrium binary mixture undergoing 2-TIPS.

cond-mat.soft↗

arXiv2025

Run-and-tumble chemotaxis using reinforcement learning

Bacterial cells use run-and-tumble motion to climb up attractant concentration gradient in their environment. By extending the uphill runs and shortening the downhill runs the cells migrate towards the higher attractant zones. Motivated by this, we formulate a reinforcement learning (RL) algorithm where an agent moves in one dimension in the presence of an attractant gradient. The agent can perform two actions: either persistent motion in the same direction or reversal of direction. We assign costs for these actions based on the recent history of the agent's trajectory. We ask the question: which RL strategy works best in different types of attractant environment. We quantify efficiency of the RL strategy by the ability of the agent (a) to localize in the favorable zones after large times, and (b) to learn about its complete environment. Depending on the attractant profile and the initial condition, we find an optimum balance is needed between exploration and exploitation to ensure the most efficient performance.

q-bio.CB↗

arXiv2025

Polarised crowd in motion: insights into statistical and dynamical behavior

The collection of active agents often exhibits intriguing statistical and dynamical properties, particularly when considering human crowds. In this study, we have developed a computational model to simulate the recent experiment on real marathon races by Bain et al. Our primary goal is to investigate the impact of race staff on crowd dynamics. By comparing simulated races with and without the presence of race staff, our study reveals that the local velocity and density of participants display a wave pattern akin to real races for both the cases. The observed traveling wave in the crowd consistently propagates at a constant speed, regardless of the system size under consideration. The participants dynamics in the longitudinal direction primarily contribute to velocity fluctuations, while fluctuations in the transverse direction are suppressed. In the absence of race staff, density and velocity fluctuations weaken without significantly affecting other statistical and dynamic characteristics of the crowd. Through this research, we aim to deepen our understanding of crowd motion, providing insights that can inform the development of effective crowd management strategies and contribute to the successful control of such events.

cond-mat.stat-mech↗

arXiv2024

Adaptive dynamics of Ising spins in one dimension leveraging Reinforcement Learning

A one-dimensional flocking model using active Ising spins is studied, where the system evolves through the reinforcement learning approach \textit{via} defining state, action, and cost function for each spin. The orientation of spin with respect to its neighbouring spins defines its state. The state of spin is updated by altering its spin orientation in accordance with the $\varepsilon$-greedy algorithm (action) and selecting a finite step from a uniform distribution to update position. The $\varepsilon$ parameter is analogous to the thermal noise in the system. The cost function addresses cohesion among the spins. By exploring the system in the plane of the self-propulsion speed and $\varepsilon$ parameter, four distinct phases are found: disorder, flocking, flipping, and oscillatory. In the flipping phase, a condensed flock reverses its direction of motion stochastically. The mean reversal time $\langle T \rangle $ exponentially decays with $\varepsilon$. A new phase, an oscillatory phase, is also found, which is a chaotic phase with a positive Lyapunov exponent. The findings obtained from the reinforcement learning approach for the active Ising model system exhibit similarities with the outcomes of other conventional techniques, even without defining any explicit interaction among the spins.

cond-mat.soft↗

arXiv2024

Dynamics of phagocytosis through interplay of forces

Phagocytosis is the process by which cells, which are 5 to 10 times larger than the particle size, engulf particles, holding substantial importance in various biological contexts ranging from the nutrient uptake of unicellular organisms to immune system of humans, animals etc. While the previous studies focused primarily on the mechanism of phagocytosis, in this study we have a taken a different route by studying the dynamics of the phagocytes in a system consisting of many bacteria and a small number of phagocytes. We put forward a minimalist framework that models bacteria and phagocytes as active and passive circular disks, respectively. The interactions are governed by directional forces: phagocytes are attracted toward bacteria, while bacteria experience a repulsive force in proximity to phagocytes. Bacteria are capable of reproduction at a fixed rate, and the balance between bacterial reproduction and phagocytic engulfment is governed by the interplay of the two opposing forces. In attraction dominated regimes, bacterial populations decrease rapidly, while in repulsion dominated regimes, bacterial clusters grow and impede phagocytes, often resulting in phagocyte trapping. Conversely, in attraction-dominated scenarios, only a few bacteria remain at later times, rendering the motion of the phagocytes diffusive. Further, the transition between the two regimes occurs through a regime of bi-stability. Our study further describes the dynamics of both species using the tools of statistical analysis, offering insights into the internal dynamics of this system.

cond-mat.soft↗

arXiv2024

Dynamical Swirl Structures Powered by Microswimmers in Active Nematics

Active nematics, in their pure form, have demonstrated a plethora of dynamic and steady state behaviors, including large-scale dynamic structures, collective flows, and intricate multi-spatial temporal dynamics. This complexity further increases in the presence of external polar agents. We investigate active nematics interspersed with polar microswimmers, akin to active apolar cells infused with active impurities, microswimmers. Our comprehensive numerical study reveals that varying the microswimmers' motility induces a novel spatiotemporal state in the active nematics backdrop. This state is marked by macroscopic swirl-like structures and a reduction in the overall order of the active nematics. Interestingly, this state emerges at intermediate motility levels, where microswimmers form local clusters and exhibit coherent motion. However, at higher motility levels, the swirls become less coherent, and microswimmer clustering intensifies. We show that the effect of the polar microswimmers on active nematics can be interpreted as a spatiotemporally correlated colored noise on active nematics, which promotes bend instability in active nematics, leading to the observed swirling dynamics. Our findings indicate that the spatiotemporal states are highly sensitive to the microswimmers' motility, offering potential avenues for pathogen identification based on known motility characteristics

cond-mat.stat-mech↗

arXiv2024

Synchronous and Asynchronous Updates of Active Ising Spins in One Dimension

How do update rules affect the dynamical and steady state properties of a flock? In this study, we have explored the active Ising spins (s = +-1) in one dimension, where spin updates its orientation according to the Metropolis algorithm (based on the neighbors) via two different update rules. (i) Parallel, and (ii) Random-sequential. We explore the effect of Parallel and Random-sequential updates on the dynamical properties of flocks in one dimension. Due to the inherent asynchronous nature of the Random-sequential update, the directional switching of the flock is increased compared to the Parallel one. The nature of phase transition is affected by the difference in the updating mechanism: discontinuous for Parallel and continuous for Random-sequential updates.

cond-mat.soft↗

arXiv2024

Directional cues affect the collective behaviour of Self propelled particles in one dimension

This study explores the effect of quenched disorder on the characteristic of self-propelled particles in one-dimension. Here,particles interact with disorder which serve as directional cues. The study investigates how the density of the disorder influence the emergence of ordering and clustering in the collection of the self propelled particles. We introduce the microscopic model as well as corresponding coarse-grained equations of motion for the local density and the orientation of particle. Disorder affects the macroscopic ordering in the system, the size of the ordered clusters decays algebraically with disorder. Further, the disorder also affects the clustering of particles; in the presence of disorder, a big macroscopic cluster breaks into small clusters, leads to the localization of particles around it and results in high density around the disorder.

cond-mat.soft↗

arXiv2024

Ordering kinetics and steady states of XY-model with ferromagnetic and nematic interaction

Previous studies on the generalized XY model have concentrated on the equilibrium phase diagram and the equilibrium nature of distinct phases under varying parameter conditions. We direct our attention towards examining the systems evolution towards equilibrium states across different parameter values, specifically by varying the relative strengths of ferromagnetic and nematic interactions. We study the kinetics of the system, using the temporal annihilation of defects at varying temperatures and its impact on the coarsening behavior of the system. For both pure polar and pure nematic systems, we observe temperature-dependent decay of the exponent, leading to a decelerated growth of domains within the system. At parameter values where both ferromagnetic and nematic interactions are simultaneously present, we show a phase diagram highlighting three low-temperature phases : polar, nematic, and coexistence, alongside a high-temperature disordered phase. Our study provides valuable insights into the complex interplay of interactions, offering a comprehensive understanding of the systems behavior during its evolution towards equilibrium.

cond-mat.soft↗

arXiv2024

Domain growth kinetics of active model B with thermal fluctuations

We perform a comprehensive study on the role of thermal noise on the ordering kinetics of a collection of active Brownian particles modeled using coarse-grained conserved active model B (AMB). The ordering kinetics of the system is studied for the critical mixture when quenched from high to a low temperature. The structure of the growing domains changes from isolated droplet type for AMB without noise to bi-continuous type for active model B with noise (AMBN). Unlike the passive counterpart of the AMB, the noise is relevant for the growth kinetics of the AMB. We use extensive numerical study, as well as dynamic scaling hypothesis to characterize the kinetics of the system. We find that the asymptotic growth law for AMBN is diffusive Lifshitz-Slyozov (LS) type, whereas it was reported previously that the asymptotic growth law for the AMB without noise is slower, with a growth exponent 4. Moreover, the kinetics of the growing domains show a strong time dependent growth for AMBN. The growth law shows a crossover from early time 1/3 value to intermediate time 1/4 value, and it again traverses from 1/4 to 1/3 asymptotically. The two different scaling functions are found for intermediate time and late time with growth law 1/4 and 1/3 respectively.

cond-mat.stat-mech↗

arXiv2024

Synchronized Rotations of Active Particles on Chemical Substrates

Many microorganisms use chemical `signaling' - a quintessential self-organizing strategy in non-equilibrium - that can induce spontaneous aggregation and coordination in behavior. Using synthetic signaling as a design principle, we construct a minimal model of active Brownian particles (ABPs) having soft repulsive interactions on a chemically quenched patterned substrate. The interplay between chemo-phoretic interactions and activity is numerically investigated for a proposed variant of the Keller-Segel model for chemotaxis. Such competition not only results in a chemo-motility-induced phase-separated state but also a new cohesive clustering phase with synchronized rotations. Our results suggest that rotational order can emerge in systems by virtue of activity and repulsive interactions alone without an explicit alignment interaction. These rotations can also be exploited by designing mechanical devices that can generate reorienting torques using active particles.

cond-mat.soft↗

arXiv2023

Active Brownian particles can mimic the pattern of the substrate

Active Brownian particles (ABPs) are termed out to be a successful way of modeling the moving microorganism on the substrate. In recent studies, it is shown that such organisms can sense the characteristics of the substrate. Motivated by such work, we studied the dynamics and the steady state of ABP moving on a substrate with space-dependent activity. On the substrate, some regions are marked as high in activity, and other regions are such that particles behave as passive Brownian particles. The system is studied in two dimensions with step, sigmoid, Gaussian and cone shape distribution of activity profile on the substrate. The whole interface of the activity profile is symmetrically divided into two regions. This lead to the flow of particles from the active region to the passive region. The final steady state of particle density profile, polarisation and flux very much follows the structure of the inhomogeneous activity and the density in high activity region is lower, maximum at the interface and nearly constant with mean density in the passive region. Further, the steady state density profile for various shapes and designs on two-dimensional substrates. Hence the collection of ABPs on an inhomogeneous substrate can mimic the inhomogeneity of the substrate.

cond-mat.soft↗

arXiv2023

Ordering kinetics in active polar fluid

We model the active polar fluid as a collection of orientable objects supplied with active stresses and momentum damping coming from the viscosity of bulk fluid medium. The growth kinetics of local orientation field is studied. The effect of active fluid is contractile or extensile depending upon the sign of the active stress. We explore the growth kinetics for different activities. We observe that for both extensile and contractile cases the growth is altered by a prefactor when compared to the equilibrium Model A. We find that the extensile fluid enhances the domain growth whereas the contractile fluid supresses it. The asymptotic growth becomes pure algebraic for large magnitudes of activity. We also find that the domain morphology remains unchanged due to activity and system shows the good dynamic scaling for all activities. Our study provides the understanding of ordering kinetics in active polar gel.

cond-mat.soft↗

arXiv2023

Current reversal in polar flock at order-disorder interface

We studied a system of polar self-propelled particles (SPPs) on a thin rectangular channel designed into three regions of order-disorder-order. The division of the three regions is made on the basis of the noise SPPs experience in the respective regions. The noise in the two wide region is chosen lower than the critical noise of order-disorder transition and noise in the middle region or interface is higher than the critical noise. This make the geometry of the system analogous to the Josephson Junction (JJ) in solid state physics. Keeping all other parameters fixed, we study the properties of the moving SPPs in the bulk as well as along the interface for different widths of the junction. On increasing interface width, system shows a order-to-disorder transition from coherent moving SPPs in the whole system to the interrupted current for large interface width. Surprisingly, inside the interface we observed the current reversal for intermediate widths of the interface. Such current reversal is due to the strong randomness present inside the interface, that makes the wall of the interface reflecting. Hence Our study give a new interesting collective properties of SPPs at the interface which can be useful to design devices like switch using active agents.

cond-mat.soft↗

arXiv2022

Kinetics and steady state of polar flock with birth and death

We study a collection of polar self-propelled particles or polar flock on a two dimensional substrate with birth and death. Most of the previous studies of polar flock with birth and death have assumed the compressible flock, such that the local density of flock is completely ignored. Effect of birth and death of particles on the flock with moderate density is focus of our study. System is modeled using coarse-grained hydrodynamic equations of motion for local density and velocity of the flock and solved using numerical integration of the nonlinear coupled partial differential equations of motion and linearised hydrodynamics about the broken symmetry state. We studied the ordering kinetics as well as the steady state properties of the immortal flock and flock with finite birth and death rate. The ordering kinetics of the velocity field remains unaffected whereas the density field shows a crossover from asymptotic growth exponent $5/6$ for the immortal flock to diffusive limit $1/3$ for large birth and death rates. In the steady state, the presence of birth and death rate leads to the suppression of speed of sound wave and density fluctuations in the system.

cond-mat.soft↗

arXiv2022

Ordering through learning in two-dimensional Ising spins

We study two-dimensional Ising spins, evolving through reinforcement learning using their state, action, and reward. The state of a spin is defined as whether it is in the majority or minority with its nearest neighbours. The spin updates its state using an ε-greedy algorithm. The parameter ε plays the role equivalent to the temperature in the Ising model. We find a phase transition from long-ranged ordered to a disordered state as we tune ε from small to large values. In analogy with the phase transition in the Ising model, we calculate the critical ε and the three critical exponents β, γ, ν of magnetization, susceptibility, and correlation length, respectively. A hyper-scaling relation dν = 2β + γ is obtained between the three exponents. The system is studied for different learning rates. The exponents approach the exact values for two-dimensional Ising model for lower learning rates.

cond-mat.stat-mech↗

arXiv2022

Effect of polydispersity on the dynamics of active Brownian particles

We numerically study the dynamics and the phases of self-propelled disk-shaped particles of different sizes with soft repulsive potential in two dimensions. Size diversity is introduced by the polydispersity index (PDI) $ε$, which is the width of the uniform distribution of the particle's radius. The self-propulsion speed of the particles controls the activity $v$. We observe enhanced dynamics for large size diversity among the particles. We calculate the effective diffusion coefficient $D_{eff}$ in the steady-state. The system exhibits four distinct phases, jammed phase with small $D_{eff}$ for small activity and liquid phase with enhanced $D_{eff}$ for large activity. The number fluctuation is larger and smaller than the equilibrium limit in the liquid and jammed phase, respectively. Further, the jammed phase is of two types: solid-jammed and liquid jammed for small and large PDI. Whereas the liquid phase is called motility induced phase separation (MIPS)-liquid for small PDI and for large PDI, we find enhanced diffusivity and call it the {\em pure liquid} phase. The system is studied for three packing densities $ϕ$, and the response of the system for polydispersity is the same for all $ϕ$'s. Our study can help understand the behavior of cells of various sizes in a tissue, artificial self-driven granular particles, or living organisms of different sizes in a dense environment.

cond-mat.soft↗

arXiv2022

Active nematic gel with quenched disorder

With quenched disorder, we introduce two-dimensional active nematics suspended in an incompressible fluid. We write the coarse-grained hydrodynamic equations of motion for slow variables, viz. density, orientation and flow fields. The quenched disorder is introduced such that it interacts with the local orientation at every point with some strength. Disorder strength is tuned from zero to large values. We numerically study the defect dynamics and system's kinetics and find that the finite disorder slows the ordering. The presence of fluid induces large fluctuation in the orientation field, further disturbing the ordering. The large fluctuation in the orientation field due to the fluid is so dominant that it reduces the effect of the quenched disorder. We have also found that the disorder's effect is almost the same for both the contractile and extensile nature of active stresses in the system. This study can help {\color{black} to} understand the impact of quenched {\color{black} disorder} on the ordering kinetics of active gels with nematic interaction among the constituent objects.

cond-mat.soft↗