arXiv subjects

V Sasidevan

Publications and source records attributed to V Sasidevan.

3 recordsLinked to original sources

arXiv2025

Critical and quasicritical behavior in a three-species dynamical model of semi-directed percolation

We investigate a one-dimensional three-species dynamical model whose dynamics naturally generate the semi-directed percolation cluster in time and show a non-equilibrium absorbing state phase transition from an active to inactive state. The critical threshold and exponents associated with the dynamic process are determined using Monte Carlo simulations. Critical behavior observed shows that the model belongs to the directed percolation (DP) universality class. Further, we consider the effect of spontaneous activity generation in the dynamical model. While, as expected, this destroys the usual critical behaviour, we find that the dynamic susceptibility shows a maximum at a specific value of the control parameter, indicating a quasi-critical behaviour, similar to the findings in the case of DP models and DP-inspired models of neuronal activity with spontaneous activity generation. Interestingly, in the presence of spontaneous activity, we find that spatial and temporal correlations exhibit power-law decays at a value of the control parameter different from the pseudo-threshold corresponding to the peak of the dynamic susceptibility, indicating that there are two pseudo-thresholds in such a case, one where the response function is maximum and another where the spatial and temporal correlations show scale-free behaviour.

cond-mat.stat-mech↗

arXiv2024

Modelling competition for space: Emergent inefficiency and inequality due to spatial self-organization among a group of crowd-avoiding agents

Competition for a limited resource is the hallmark of many complex systems, and often, that resource turns out to be the physical space itself. In this work, we study a novel model designed to elucidate the dynamics and emergence in complex adaptive systems in which agents compete for some spatially spread resource. Specifically, in the model, the dynamics result from the agents trying to position themselves in the quest to avoid physical crowding experienced locally. We characterize in detail the dependence of the emergent behavior of the model on the population density of the system and the individual-level agent traits such as the extent of space an agent considers as her neighborhood, the limit of occupation density one tolerates within that neighborhood, and the information accessibility of the agents about neighborhood occupancy. We show that inefficiency in utilizing physical space shows transition at a specific density and peaks at another distinct density. Furthermore, we demonstrate that the variation of inefficiency relative to the information accessible to the agents exhibits contrasting behavior above and below this second density. We also look into the inequality of resource sharing in the model and show that although inefficiency can be a non-monotonic function of information depending upon the parameters of the model, inequality, in general, decreases with information. Our study sheds light on the role of competition, spatial constraints, and agent traits within complex adaptive systems, offering insights into their emergent behaviors.

physics.soc-ph↗

arXiv2022

Social adaptive behavior and oscillatory prevalence in an epidemic model on evolving random geometric graphs

Our recent experience with the COVID-19 pandemic amply shows that spatial effects like the mobility of agents and average interpersonal distance, together with the adaptation of agents, are very important in deciding the outcome of epidemic dynamics. Structural and dynamical aspects of random geometric graphs are widely employed in describing processes with a spatial dependence, such as the spread of an airborne disease. In this work, we investigate the interplay between spatial factors, such as agent mobility and average interpersonal distance, and the adaptive responses of individuals to an ongoing epidemic within the framework of random geometric graphs. We show that such spatial factors, together with the adaptive behavior of the agents in response to the prevailing level of global epidemic, can give rise to oscillatory prevalence even with the classical SIR framework. We characterize in detail the effects of social adaptation and mobility of agents on the disease dynamics and obtain the threshold values. We also study the effects of delayed adaptive response of agents on epidemic dynamics. We show that a delay in executing non-pharmaceutical spatial mitigation strategies can amplify oscillatory prevalence tendencies and can have non-linear effects on peak prevalence. This underscores the importance of early implementation of adaptive strategies coupled with the dissemination of real-time prevalence information to manage and control the epidemic effectively.

physics.soc-ph↗