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Apoorva Nagar

Publications and source records attributed to Apoorva Nagar.

14 recordsLinked to original sources

Ising Model with Power Law Resetting

We investigate the nonequilibrium dynamics of the nearest-neighbour Ising model subjected to stochastic resetting, where the system is intermittently returned to an initial configuration with magnetisation $m_0$, with the inter-reset times drawn from the power law distribution $\alpha \tau_0^\alpha / \tau^{\alpha+1}$. The heavy-tailed resets generate magnetisation distributions that differ significantly from both equilibrium dynamics and the previously studied Ising model with exponentially distributed reset times. In two dimensions, for $T > T_C$, we find a quasi-ferro state for all $\alpha$, marked by a double-peaked distribution that diverges at $m=0$ and $m=m_0$; no steady state exists for $\alpha < 1$, while a stationary state emerges for $\alpha > 1$. For $T < T_C$, power law resetting produces two distinct regimes separated by a crossover exponent $\alpha^* = 1-c$: a single-peak ferromagnetic phase localised at $m_{eq}$ for $\alpha < \alpha^*$, and a dual-peak ferromagnetic phase with divergences at $m_{eq}$ and $m_0$ for $\alpha > \alpha^*$. Analytic results in one and two dimensions, supported by simulations, yield a rich phase diagram in the $(T,\alpha)$ plane and reveal how heavy-tailed resetting generates nonequilibrium phases very different from those seen in the case of exponential resetting.

cond-mat.stat-mech

Stochastic resetting in interacting particle systems: A review

We review recent work on systems with multiple interacting-particles having the dynamical feature of stochastic resetting. The interplay of time scales related to inter-particle interactions and resetting leads to a rich behavior, both static and dynamic. The presence of multiple particles also opens up a new possibility for the resetting dynamics itself, namely, that of different particles resetting all together (global resetting) or independently (local resetting). We divide the review on the basis of specifics of reset dynamics (global versus local resetting), and further, on the basis of number (two versus a large number) of interacting particles. We will primarily be dealing with classical systems, and only briefly discuss resetting in quantum systems.

cond-mat.stat-mech

Diffusion with stochastic resetting at power-law times

What happens when a continuously evolving stochastic process is interrupted with large changes at random intervals $τ$ distributed as a power-law $\sim τ^{-(1+α)};α>0$? Modeling the stochastic process by diffusion and the large changes as abrupt resets to the initial condition, we obtain {\em exact} closed-form expressions for both static and dynamic quantities, while accounting for strong correlations implied by a power-law. Our results show that the resulting dynamics exhibits a spectrum of rich long-time behavior, from an ever-spreading spatial distribution for $α< 1$, to one that is time independent for $α> 1$. The dynamics has strong consequences on the time to reach a distant target for the first time; we specifically show that there exists an optimal $α$ that minimizes the mean time to reach the target, thereby offering a step towards a viable strategy to locate targets in a crowded environment.

cond-mat.stat-mech

Resetting of fluctuating interfaces at power-law times

What happens when the time evolution of a fluctuating interface is interrupted with resetting to a given initial configuration after random time intervals $τ$ distributed as a power-law $\sim τ^{-(1+α)};~α> 0$? For an interface of length $L$ in one dimension, and an initial flat configuration, we show that depending on $α$, the dynamics as $L \to \infty$ exhibits a rich long-time behavior. Without resetting, the interface width grows unbounded with time as $t^β$, where $β$ is the so-called growth exponent. We show that introducing resetting induces for $α>1$ and at long times fluctuations that are bounded in time. Corresponding to such a stationary state is a distribution of fluctuations that is strongly non-Gaussian, with tails decaying as a power-law. The distribution exhibits a cusp for small argument, implying that the stationary state is out of equilibrium. For $α<1$, resetting is unable to counter the otherwise unbounded growth of fluctuations in time, so that the distribution of fluctuations remains time dependent with an ever-increasing width even at long times. Although stationary for $α>1$, the width of the interface grows forever with time as a power-law for $1<α< α^{({\rm w})}$, and converges to a finite constant only for larger $α$, thereby exhibiting a crossover at $α^{({\rm w})}=1+2β$. The time-dependent distribution of fluctuations for $α<1$ exhibits for small argument another interesting crossover behavior, from cusp to divergence, across $α^{({\rm d})}=1-β$. We demonstrate these results by exact analytical results for the paradigmatic Edwards-Wilkinson (EW) dynamical evolution of the interface, and further corroborate our findings by extensive numerical simulations of interface models in the EW and the Kardar-Parisi-Zhang universality class.

cond-mat.stat-mech

Absence of jamming in ant trails: Feedback control of self propulsion and noise

We present a model of ant traffic considering individual ants as self-propelled particles undergoing single file motion on a one-dimensional trail. Recent experiments on unidirectional ant traffic in well-formed natural trails showed that the collective velocity of ants remains approximately unchanged, leading to absence of jamming even at very high densities [ John et. al., Phys. Rev. Lett. 102, 108001 (2009) ]. Assuming a feedback control mechanism of self-propulsion force generated by each ant using information about the distance from the ant in front, our model captures all the main features observed in the experiment. The distance headway distribution shows a maximum corresponding to separations within clusters. The position of this maximum remains independent of average number density. We find a non-equilibrium first order transition, with the formation of an infinite cluster at a threshold density where all the ants in the system suddenly become part of a single cluster.

physics.bio-ph

Fixation of mutators in asexual populations: the role of genetic drift and epistasis

We study the evolutionary dynamics of an asexual population of nonmutators and mutators on a class of epistatic fitness landscapes. We consider the situation in which all mutations are deleterious and mutators are produced from nonmutators continually at a constant rate. We find that in an infinitely large population, a minimum nonmutator-to-mutator conversion rate is required to fix the mutators but an arbitrarily small conversion rate results in the fixation of mutators in a finite population. We calculate analytical expressions for the mutator fraction at mutation-selection balance and fixation time for mutators in a finite population when mutational effects are weaker (regime I) and stronger (regime II) than the selective effects. Our main result is that in regime I, the mutator fraction and the fixation time are independent of epistasis but in regime II, mutators are rarer and take longer to fix when the decrease in fitness with the number of deleterious mutations occurs at an accelerating rate (synergistic epistasis) than at a diminishing rate (antagonistic epistasis). Our analytical results are compared with numerics and their implications are discussed.

q-bio.PE

Condensation transition in a model with attractive particles and non-local hops

We study a one dimensional nonequilibrium lattice model with competing features of particle attraction and non-local hops. The system is similar to a zero range process (ZRP) with attractive particles but the particles can make both local and non-local hops. The length of the non-local hop is dependent on the occupancy of the chosen site and its probability is given by the parameter $p$. Our numerical results show that the system undergoes a phase transition from a condensate phase to a homogeneous density phase as $p$ is increased beyond a critical value $p_c$. A mean-field approximation does not predict a phase transition and describes only the condensate phase. We provide heuristic arguments for understanding the numerical results.

cond-mat.stat-mech

Exact phase diagram of quasispecies model with mutation rate modifier

We consider an infinite asexual population with a mutator allele which can elevate mutation rates. With probability $f$, a transition from nonmutator to mutator state occurs but the reverse transition is forbidden. We find that at $f=0$, the population is in the state with minimum mutation rate and at $f=f_c$, a phase transition occurs between a mixed phase with both nonmutators and mutators and a pure mutator phase. We calculate the critical probability $f_c$ and the total mutator fraction $Q$ in the mixed phase exactly. Our predictions for $Q$ are in agreement with those seen in microbial populations in static environments.

q-bio.PE

Passive Sliders and Scaling: from Cusps to Divergences

The steady state reached by a system of particles sliding down a fluctuating surface has interesting properties. Particle clusters form and break rapidly, leading to a broad distribution of sizes and large fluctuations. The density-density correlation function is a singular scaling function of the separation and system size. A simple mapping is shown to take a configuration of sliding hard-core particles with mutual exclusion (a system which shows a cusp singularity) to a configuration with multiparticle occupancy. For the mapped system, a calculation of the correlation function shows that it is of the same scaling form again, but with a stronger singularity (a divergence) of the sort observed earlier for noninteracting passive particles.

cond-mat.stat-mech

Boundary-induced abrupt transition in the symmetric exclusion process

We investigate the role of the boundary in the symmetric simple exclusion process with competing nonlocal and local hopping events. With open boundaries, the system undergoes a first order phase transition from a finite density phase to an empty road phase as the nonlocal hopping rate increases. Using a cluster stability analysis, we determine the location of such an abrupt nonequilibrium phase transition, which agrees well with numerical results. Our cluster analysis provides a physical insight into the mechanism behind this transition. We also explain why the transition becomes discontinuous in contrast to the case with periodic boundary conditions, in which the continuous phase transition has been observed.

cond-mat.stat-mech

Strong clustering of non-interacting, passive sliders driven by a Kardar-Parisi-Zhang surface

We study the clustering of passive, non-interacting particles moving under the influence of a fluctuating field and random noise, in one dimension. The fluctuating field in our case is provided by a surface governed by the Kardar-Parisi-Zhang (KPZ) equation and the sliding particles follow the local surface slope. As the KPZ equation can be mapped to the noisy Burgers equation, the problem translates to that of passive scalars in a Burgers fluid. We study the case of particles moving in the same direction as the surface, equivalent to advection in fluid language. Monte-Carlo simulations on a discrete lattice model reveal extreme clustering of the passive particles. The resulting Strong Clustering State is defined using the scaling properties of the two point density-density correlation function. Our simulations show that the state is robust against changing the ratio of update speeds of the surface and particles. In the equilibrium limit of a stationary surface and finite noise, one obtains the Sinai model for random walkers on a random landscape. In this limit, we obtain analytic results which allow closed form expressions to be found for the quantities of interest. Surprisingly, these results for the equilibrium problem show good agreement with the results in the non-equilibrium regime.

cond-mat.stat-mech

Passive Sliders on Fluctuating Surfaces: Strong-Clustering States

We study the clustering properties of particles sliding downwards on a fluctuating surface evolving through the Kardar-Parisi-Zhang equation, a problem equivalent to passive scalars driven by a Burgers fluid. Monte Carlo simulations on a discrete version of the problem in one dimension reveal that particles cluster very strongly: the two point density correlation function scales with the system size with a scaling function which diverges at small argument. Analytic results are obtained for the Sinai problem of random walkers in a quenched random landscape. This equilibrium system too has a singular scaling function which agrees remarkably with that for advected particles.

cond-mat.stat-mech

Residence Time Distribution of Sand Grains in the 1-Dimensional Abelian Sandpile Model

We study the probability distribution of residence time, $T$, of the sand grains in the one dimensional abelian sandpile model on a lattice of $L$ sites, for $T< >L^2$. The distribution function decays as $\exp(-\frac{K_LT}{L^2})$. We numerically calculate the coefficient $K_L$ for the value of $L$ upto 150 . Interestingly the distribution function has a scaling form $\frac{1}{L^a}f(\frac{T}{L^b})$ with $a \neq b$ for large $L$.

cond-mat.stat-mech

Clustering of advected passive sliders on a fluctuating surface

We study the clustering properties of advected, non-interacting,passive scalar particles in a Burgers fluid with noise, a problem which maps to that of passive sliding particles moving under gravity on a surface evolving through the Kardar-Parisi-Zhang equation. Numerical simulations show that both the density-density correlation function and the single-site mass distribution scale with system size. The scaling functions diverge at small argument, indicating strong clustering of particles. We analytically evaluate the scaling functions for the two-point correlation and mass distribution of noninteracting particles in thermal equilibrium in a random landscape, and find that the results are remarkably similar to those for nonequilibrium advection.

cond-mat.stat-mech