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Subhanker Howlader

Publications and source records attributed to Subhanker Howlader.

4 recordsLinked to original sources

Velocity Resetting of Inertial Run-and-Tumble Particles in Non-Newtonian Media: Velocity Distribution, Diffusion and First-Passage Time

We study the dynamics of an athermal inertial run-and-tumble particle moving through a non-Newtonian medium in $d=1$, where the particle's velocity $v$ is reset to zero at a constant rate $r$. The drag force from the non-Newtonian medium is represented by a nonlinear velocity-dependent function $g(v)$. The run-and-tumble dynamics is modeled by a symmetric dichotomous noise with strength $\Sigma$ and flipping rate $\lambda$. We begin with the Fokker-Planck (FP) equation for the velocity distribution $P(v,t)$ of the particle. In the presence of resetting, however, the FP equation does not yield a closed-form solution even in the steady state. We therefore compute the steady-state velocity distribution $P_s(v)$ directly from particle trajectories and compare it with the numerical solution of the FP equation, finding good agreement between the two approaches. For sufficiently large $r$, $P_s(v)$ shows a cusp-like singularity at $v=0$ and the particles display diffusive motion at long times. The effective diffusion coefficient $D_{\mathrm{eff}}$ decays as $r^{-2}$ in the large-$r$ regime. These results hold irrespective of the specific form of $g(v)$ and the values of $\lambda$ and $\Sigma$. However, the mean first-passage time exhibits a strong dependence on the nature of the medium as the resetting rate $r$ is varied. In shear-thickening media, there exists an optimal resetting rate that minimizes the time required to reach the target velocity $v_t$. In contrast, no such optimal resetting rate is observed in shear-thinning media.

cond-mat.soft

Velocity Distribution and Diffusion of an Athermal Inertial Run-and-Tumble Particle in a Shear-Thickening Medium

We study the dynamics of an athermal inertial run-and-tumble particle moving in a shear-thickening medium in $d=1$. The viscosity of the medium is represented by a nonlinear function $f(v)\sim\tan(v)$, while a symmetric dichotomous noise of strength $\Sigma$ and flipping rate $\lambda$ models the activity of the particle. Starting from the Fokker-Planck~(FP) equation for the time-dependent probability distribution $W_{\pm\Sigma}(v, t)$ of the particle's velocity $v$ at time $t$ and the active force is $\pm\Sigma$, we analytically derive the steady-state velocity distribution function $W_s(v)$ and a quadrature expression for the effective diffusion coefficient $D_{\rm eff}$. For a fixed $\Sigma$, $W_s(v)$ undergoes multiple transitions with varying $\lambda$, and we have identified the corresponding transition points. We then numerically compute $W_s(v)$, the mean-squared velocity $\langle v^2\rangle(t)$, and the diffusion coefficient $D_{\rm eff}$, all of which show excellent agreement with the analytical results in the steady-state. Finally, we test the robustness of the transitions in $W_s(v)$ by considering an alternative $f(v)$ function that also capture the shear-thickening behavior of the medium.

cond-mat.stat-mech

Ultraslow Growth of Domains in a Random-Field System With Correlated Disorder

We study domain growth kinetics in a random-field system in the presence of a spatially correlated disorder $h_{i}(\vec r)$ after an instantaneous quench at a finite temperature $T$ from a random initial state corresponding to $T=\infty$. The correlated disorder field $h_{i}(\vec r)$ arises due to the presence of magnetic impurities, decaying spatially in a power-law fashion. We use Glauber spin-flip dynamics to simulate the kinetics at the microscopic level. The system evolves via the formation of ordered magnetic domains. We characterize the morphology of domains using the equal-time correlation function $C(r,t)$ and structure factor $S(k,t)$. In the large-$k$ limit, $S(k, t)$ obeys Porod's law: $S(k, t)\sim k^{-(d+1)}$. The average domain size $L(t)$ asymptotically follows \textit{double logarithmic growth behavior}.

cond-mat.stat-mech

Virial Equation of State for a Granular System

The equation of state for an ideal gas is simple, which is $P=nk_{\rm B}T$. In the case of imperfect gases where mutual interactions among the constituents are important, pressure $P$ can be expressed as the series expansion of density $n$ with appropriate coefficients, known as virial coefficients $B_m$. In this paper, we have obtained the first four virial coefficients for a model interaction potential $\Phi(r)$ using multidimensional Monte-Carlo integration and importance sampling methods. Next, we perform molecular dynamics simulations with the same $\Phi(r)$ for a many-particle system to obtain $P$ as a function of $T$ and $n$. We compare our numerical data with the virial equation of state.

cond-mat.soft