arXiv subjects

Pintu Patra

Publications and source records attributed to Pintu Patra.

3 recordsLinked to original sources

arXiv2026

Thermodynamic and Statistical Signatures of Modality Changes in Concentration Distributions Driven by Stochastic Switching Between Two Activity States

Stochastic switching between gene expression states, coupled with production and degradation dynamics, governs the accumulation of mRNA and proteins in cells. The concentrations of these accumulated entities dictate the phenotypic distribution of genetically identical cells. The underlying accumulation dynamics are well-captured by a two-state promoter switching model, with statistical and thermodynamic properties quantified via the Fano factor and entropy production rates. However, how these measures correlate with concentration distributions and their shifts under varying kinetic parameters remains largely unexplored. To this end, we use chemical master equations to study a generalized model of mRNA accumulation dynamics in the presence of stochastic switching between two activity states and state-dependent production and degradation rates. We derive exact expressions for the steady-state probability distribution and analytically compute the mean concentration, Fano factor, and entropy production rate (EPR). Simplifying these expressions, we identify contributions arising from stochastic switching rates and relaxation dynamics toward equilibrium in each activity state. Next, using our theoretical results, we characterize the variation in the Fano factor and EPR as a function of mean expression during modality changes of the distributions mediated by the variation of switching rates. We also identify the conditions in kinetic parameters that achieve the highest Fano factor and entropy production rates. Our findings establish a generalized framework for examining stochastic accumulation dynamics, clarifying how kinetic parameters dictate molecular distributions, noise, and dissipation. These insights extend readily to broader contexts coupling stochastic switching with accumulation, including protein burst dynamics, phenotype-switching-mediated drug intake, and queuing theory.

q-bio.MN↗

arXiv2026

Spatially heterogeneous noise restructures flocking into geometry-locked and vortex states

Spatially heterogeneous environments continually challenge the ability of active matter to sustain coherent collective motion. Understanding how collective motion remains robust under changing environments is central to both the functioning of biological systems and the design of smart active matter. Here, we extend the Vicsek model to include a circular non-noisy region surrounded by a noisy environment - a configuration in which the noise difference sets up a contrast in local directional order between the two regions. We find that, as the surrounding noise is increased, the system passes through three distinct dynamical regimes: (i) conventional global flocking at low noise; (ii) geometry-locked motion, aligned with simulation boundaries, at intermediate noise; and (iii) vortical motion within the non-noisy region at high noise. Extending the environment to multiple non-noisy regions, we find that the geometry-locked regime can develop a directional coupling, while the vortex mode leads to antiferromagnetic order between the regions. Taken together, our results demonstrate that the spatial modulation of order and disorder offers a powerful and generic strategy for steering active matter, aligning with recent experimental observations of active particles in patterned landscapes.

cond-mat.soft↗

arXiv2026

On the role of higher-order interactions towards first synchronization time

This study investigates transient collective dynamics, with a focus on how higher-order interactions impact the time required to reach steady-state synchronization. Assuming a large ensemble of deterministic and globally coupled Kuramoto oscillators with Cauchy-distributed natural frequencies, an expression for the first synchronization time is derived using the Ott-Antonsen ansatz. Subsequent numerics reveal that (i) increasing the coupling strengths for a fixed interaction order accelerates the transition to synchronization and (ii) increasing the interaction order for fixed interaction strength produces non-monotonic behavior. In particular, the inclusion of triadic interactions generally accelerates synchronization, whereas further higher-order interactions progressively delay convergence to the steady state, in some regimes even falling below the pairwise level. Ultimately, for very large interaction orders, the dynamics revert to pairwise-like behavior. Simulations of the system equations for different parameter combinations support these observations, while the asymptotic case is interpreted through the nonlinear structure of the order-parameter dynamics.

nlin.AO↗