arXiv subjects

Syed Yunus Ali

Publications and source records attributed to Syed Yunus Ali.

4 recordsLinked to original sources

arXiv2025

Fluctuations in first passage times and utility of resetting protocol in biochemical systems with two-state toggling

Interesting theoretical problems of target search or threshold crossing, formally known as {\it first passage}, often arise in both diffusive transport problems as well as problems of chemical reaction kinetics. We study three systems following different chemical kinetics, and are special as they {\it toggle between two states}: (i) a population dynamics of cells with auto-catalytic birth and intermittent toxic chemical-induced forced death, (ii) a bond cluster model representing membrane adhesion to extracellular matrix under a fluctuating load, and (iii) a model of gene transcription with a regulated promoter switching between active and inactive states. Each of these systems has a target state to attain, which defines a first passage problem -- namely, population becoming extinct, complete membrane detachment, or mRNA count crossing a threshold. We study the fluctuations in first passage time and show that it is interestingly {\it non-monotonic} in all these cases, with increasing strength of bias towards the target. We also study suitable {\it stochastic resetting} protocols to expedite first passage for these systems, and show that there is a re-entrant transition of the efficacy of this protocol in all the three cases, as a function of the bias. The exact analytical condition for these transitions predicted in earlier literature is verified here through simulations.

cond-mat.stat-mech↗

arXiv2025

Geometric Brownian information engine with finite cycle time: Optimisation of output work, power and efficiency

We consider a Geometric Brownian Information Engine to explore the effects of finite cycle time $(τ)$ on the extractable work, power, and efficiency. We incorporate an error-free feedback controller that converts the information obtained about the state of overdamped Brownian particles, confined within a 2-D monolobal geometry, into extractable work. The performance of the information engine depends on the cycle period $(τ)$, measurement distance $(x_m)$, and feedback location $(x_f)$ of the controller. Upon increasing the feedback cycle time, the engine transitions from a high non-equilibrium steady state to a completely relaxed state. We set the measurement distance at an optimum position related to a fully relaxed state ($x_m^* \sim 0.6 σ$). When the cycle time is finite and short ($τ<τ_r$), the best information processing occurs with a shorter distance of the feedback site. While increasing the cycle time towards a fully relaxed state ($τ\gg τ_r$), the maximum extractable work that can be achieved with a feedback location is set to be twice that of $x_m^*$, as expected. When the cycle time ($τ$) is longer than the relaxation time ($τ_r$), the maximum power is achieved when the scaled feedback location is exactly double the optimum measurement distance ($x_f^{*}=2x_m^*$). In contrast, when $τ< τ_r$, the maximum power is achieved when the feedback site is set at a lower value. As the $τ$ increases, the maximum average power decreases. In the limit of a long $τ$, the highest efficiency as well extractable work is attained when $x_f$ is located at $2x_m$, regardless of the level of entropic control. As the dominance of entropic control increases, the extractable work and efficiency in the fully relaxed state decrease due to higher information loss during relaxation.

cond-mat.stat-mech↗

arXiv2024

Dynamics of Brownian particles in asymmetric confinement: Insights into Entropic Stochastic Resonance

We explore the effect of asymmetry in the thermodynamic response (work done) of an overdamped Brownian system driven by a time-periodic field when the particle is confined inside a bilobal irregular structure. The spatial irregularity of the asymmetric confinement results in an effective asymmetric entropic bistable potential along the direction of transport. We investigate how the frequency of the periodic field and the intensity of the noise impact the average work done, focusing on its potential as a key metric for examining Entropic Stochastic Resonance (ESR). The study highlights the impact of confinement asymmetry on reducing the average work done. Furthermore, we observe a transition of average work done from a state dominated by energy to one dominated by entropy, as we manipulate the magnitude of the transverse force. In addition, an alternative quantity called the mean free flight time ($T_{MFFT}$) is proposed to describe the ESR in the presence of asymmetry.

cond-mat.stat-mech↗

arXiv2022

Geometric Brownian Information Engine: Essentials for the best performance

We investigate a Geometric Brownian Information Engine (GBIE) in the presence of an error-free feedback controller that transforms the information gathered on the state of Brownian particles entrapped in monolobal geometric confinement into extractable work. Outcomes of the information engine depend on the reference measurement distance $x_m$, feedback site $x_f$ and the transverse force $G$. We determine the benchmarks for utilizing the available information in an output work and the optimum operating requisites for best work extraction. Transverse bias force ($G$) tunes the entropic contribution in the effective potential and hence the standard deviation ($σ$) of the equilibrium marginal probability distribution. We recognize that the amount of extracted work reaches a global maximum when $x_f = 2x_m$ with $x_m \sim 0.6σ$, irrespective of the extent of the entropic limitation. Because of the higher loss of information during the relaxation process, the best achievable work of a GBIE is lower in an entropic system. The feedback regulation also bears the unidirectional passage of particles. The average displacement increases with growing entropic control and is maximum when $x_m \sim 0.81σ$. Finally, we explore the efficacy of the information engine, a quantity that regulates the efficiency in utilizing the information acquired. With $x_f=2x_m$, the maximum efficacy reduces with increasing entropic control and shows a cross over from $2$ to $11/9$. We discover that the condition for the best efficacy depends only on the confinement length scale along the feedback direction. The broader marginal probability distribution accredits the increased average displacement in a cycle and the lower efficacy in an entropy-dominated system.

cond-mat.stat-mech↗