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Parongama Sen

Publications and source records attributed to Parongama Sen.

At least 55 records · Page 3Linked to original sources

Zero temperature coarsening in Ising model with asymmetric second neighbour interaction in two dimensions

We consider the zero temperature coarsening in the Ising model in two dimensions where the spins interact within the Moore neighbourhood. The Hamiltonian is given by $H = - \sum_{ }{S_iS_j} - κ\sum_{ }{S_iS_{j'}}$ where the two terms are for the first neighbours and second neighbours respectively and $κ\geq 0$. The freezing phenomena, already noted in two dimensions for $κ=0$, is seen to be present for any $κ$. However, the frozen states show more complicated structure as $κ$ is increased; e.g. local anti-ferromagnetic motifs can exist for $κ>2$. Finite sized systems also show the existence of an iso-energetic active phase for $κ> 2$, which vanishes in the thermodynamic limit. The persistence probability shows universal behaviour for $κ>0$, however it is clearly different from the $κ=0$ results when non-homogeneous initial condition is considered. Exit probability shows universal behaviour for all $κ\geq 0$. The results are compared with other models in two dimensions having interactions beyond the first neighbour.

cond-mat.stat-mech↗

Interplay of interfacial noise and curvature driven dynamics in two dimensions

We explore the effect of interplay of interfacial noise and curvature driven dynamics in a binary spin system. An appropriate model is the generalised two dimensional voter model proposed earlier (J. Phys. A: Math. Gen. {\bf 26}, 2317 (1993)), where the flipping probability of a spin depends on the state of its neighbours and is given in terms of two parameters $x$ and $y$. $x = 0.5, y =1$ corresponds to the conventional voter model which is purely interfacial noise driven while $x = 1 $ and $y = 1$ corresponds to the Ising model, where coarsening is fully curvature driven. The coarsening phenomena for $0.5< x < 1$ keeping $y=1$ is studied in detail. The dynamical behaviour of the relevant quantities show characteristic differences from both $x=0.5$ and $1$. The most remarkable result is the existence of two time scales for $x\ge x_c$ where $x_c \approx 0.7$. On the other hand, we have studied the exit probability which shows Ising like behaviour with an universal exponent for any value of $x > 0.5$; the effect of $x$ appears in altering the value of the parameter occurring in the scaling function only.

cond-mat.stat-mech↗

An empirical analysis of the Ebola outbreak in West Africa

The data for the Ebola outbreak that occurred in 2014-2016 in three countries of West Africa are analysed within a common framework. The analysis is made using the results of an agent based Susceptible-Infected-Removed (SIR) model on a Euclidean network, where nodes at a distance $l$ are connected with probability $P(l) \propto l^{-δ}$, $δ$ determining the range of the interaction, in addition to nearest neighbors. The cumulative (total) density of infected population here has the form $R(t) = \frac{a\exp(t/T)}{1+c\exp(t/T)}$, where the parameters depend on $δ$ and the infection probability $q$. This form is seen to fit well with the data. Using the best fitting parameters, the time at which the peak is reached is estimated and is shown to be consistent with the data. We also show that in the Euclidean model, one can choose $δ$ and $q$ values which reproduce the data for the three countries qualitatively. These choices are correlated with population density, control schemes and other factors. Comparing the real data and the results from the model one can also estimate the size of the actual population susceptible to the disease. Rescaling the real data a reasonably good quantitative agreement with the simulation results is obtained.

physics.soc-ph↗

Minority spin dynamics in non-homogeneous Ising model: diverging timescales and exponents

We investigate the dynamical behaviour of the Ising model under a zero temperature quench with the initial fraction of up spins $0\leq x\leq 1$. In one dimension, the known results for persistence probability are verified; it shows algebraic decay for both up and down spins asymptotically with different exponents. It is found that the conventional finite size scaling is valid here. In two dimensions however, the persistence probabilities are no longer algebraic; in particular for $x\leq 0.5$, persistence for the up (minority) spins shows the behaviour $P_{min}(t) \sim t^{-γ}\exp(-(t/τ)^δ)$ with time $t$, while for the down (majority) spins, $P_{maj}(t)$ approaches a finite value. We find that the timescale $τ$ diverges as $(x_c-x)^{- λ}$, where $x_c=0.5$ and $λ\simeq2.31$. The exponent $γ$ varies as $θ_{2d}+c_0(x_c-x)^β$ where $θ_{2d}\simeq0.215$ is very close to the persistence exponent in two dimensions; $β\simeq1$. The results in two dimensions can be understood qualitatively by studying the exit probability, which for different system size is found to have the form $E(x) = f\big[(\frac{x-x_c}{x_c})L^{1/ν}\big]$, with $ν\approx 1.47$. This result suggests that $τ\sim L^{\tilde{z}}$, where $\tilde{z} = \fracλν = 1.57 \pm 0.11$ is an exponent not explored earlier.

cond-mat.stat-mech↗

Annual Journal citation indices: a comparative study

We study the statistics of citations made to the indexed Science journals in the Journal Citation Reports during the period 2004-2013 using different measures. We consider different measures which quantify the impact of the journals. To our surprise, we find that the apparently uncorrelated measures, even when defined in an arbitrary manner, show strong correlations. This is checked over all the years considered. Impact factor being one of these measures, the present work raises the question whether it is actually a nearly perfect index as claimed often. In addition we study the distributions of the different indices which also behave similarly.

cs.DL↗

Condensation transition in a conserved generalized interacting zero-range process

A conserved generalized zero range process is considered in which two sites interact such that particles hop from the more populated site to the other with a probability $p$. The steady state particle distribution function $P(n)$ is obtained using both analytical and numerical methods. The system goes through several phases as $p$ is varied. In particular, a condensate phase appears for $p_l < p < p_c$, where the bounding values depend on the range of interaction, with $p_c < 0.5$ in general. Analysis of $P(n)$ in the condensate phase using a known scaling form shows there is universal behaviour in the short range process while the infinite range process displays non-universality. In the non-condensate phase above $p_c$, two distinct regions are identified: $p_c < p \leq 0.5$ and $p> 0.5$; a scale emerges in the system in the latter and this feature is present for all ranges of interaction.

cond-mat.stat-mech↗

Frozen states and active-absorbing phase transitions of the Ising model on networks

A zero temperature quench of the Ising model is known to lead to a frozen steady state on random and small world networks. We study such quenches on random scale free networks (RSF) and compare the scenario with that in the Barabási-Albert network (BA) and the Watts Strogatz (WS) addition type network. While frozen states are present in all the cases, the RSF shows an order-disorder phase transition of mean field nature as in the WS model as well as the existence of two absorbing phases separated by an active phase. The WS network also shows an active-absorbing (A-A) phase transition occurring at the known order-disorder transition point. The comparison of the RSF and the BA network results show interesting difference in finite size dependence.

cond-mat.stat-mech↗

Continuous utility factor in segregation models

We consider the constrained Schelling model of social segregation in which the utility factor of agents strictly increases and non-local jumps of the agents are allowed. In the present study, the utility factor u is defined in a way such that it can take continuous values and depends on the tolerance threshold as well as the fraction of unlike neighbours. Two models are proposed: in model A the jump probability is determined by the sign of u only which makes it equivalent to the discrete model. In model B the actual values of u are considered. Model A and model B are shown to differ drastically as far as segregation behaviour and phase transitions are concerned. In model A, although segregation can be achieved, the cluster sizes are rather small. Also, a frozen state is obtained in which steady states comprise of many unsatisfied agents. In model B, segregated states with much larger cluster sizes are obtained. The correlation function is calculated to show quantitatively that larger clusters occur in model B. Moreover for model B, no frozen states exist even for very low dilution and small tolerance parameter. This is in contrast to the unconstrained discrete model considered earlier where agents can move even when utility remains same. In addition, we also consider a few other dynamical aspects which have not been studied in segregation models earlier.

physics.soc-ph↗

Maximizing the strength of fiber bundles under uniform loading

The collective strength of a system of fibers, each having a failure threshold drawn randomly from a distribution, indicates the maximum load carrying capacity of different disordered systems ranging from disordered solids, power-grid networks, to traffic in a parallel system of roads. In many of the cases where the redistribution of load following a local failure can be controlled, it is a natural requirement to find the most efficient redistribution scheme, i.e., following which system can carry the maximum load. We address the question here and find that the answer depends on the mode of loading. We analytically find the maximum strength and corresponding redistribution schemes for sudden and quasi static loading. The associated phase transition from partial to total failure by increasing the load has been studied. The universality class is found to be dependent on the redistribution mechanism.

cond-mat.stat-mech↗

Exit Probability in Generalised Kinetic Ising Model

In this paper we study generalised Ising Glauber models with inflow of informa- tion in one dimension and derive expressions for the exit probability using well established analytical methods. The analytical expressions agree very well with the results obtained from numerical simulation only when the interaction is restricted to the nearest neighbor. But as the range of interaction is increased the analytical results deviate from simulation results systematically. The reasons for the deviation as well as some related open questions are discussed.

cond-mat.stat-mech↗

Effect of randomness in logistic maps

We study a random logistic map $x_{t+1} = a_{t} x_{t}[1-x_{t}]$ where $a_t$ are bounded ($q_1 \leq a_t \leq q_2$), random variables independently drawn from a distribution. $x_t$ does not show any regular behaviour in time. We find that $x_t$ shows fully ergodic behaviour when the maximum allowed value of $a_t$ is $4$. However $< x_{t \to \infty}>$, averaged over different realisations reaches a fixed point. For $1\leq a_t \leq 4$ the system shows nonchaotic behaviour and the Lyapunov exponent is strongly dependent on the asymmetry of the distribution from which $a_t$ is drawn. Chaotic behaviour is seen to occur beyond a threshold value of $q_1$ ($q_2$) when $q_2$ ($q_1$) is varied. The most striking result is that the random map is chaotic even when $q_2$ is less than the threshold value $3.5699......$ at which chaos occurs in the non random map. We also employ a different method in which a different set of random variables are used for the evolution of two initially identical $x$ values, here the chaotic regime exists for all $q_1 \neq q_2 $ values.

cond-mat.stat-mech↗

Universal features of exit probability in opinion dynamics models with domain size dependent dynamics

We study the exit probability for several binary opinion dynamics models in one dimension in which the opinion state (represented by $\pm 1$) of an agent is determined by dynamical rules dependent on the size of its neighbouring domains. In all these models, we find the exit probability behaves like a step function in the thermodynamic limit. In a finite system of size $L$, the exit probability $E(x)$ as a function of the initial fraction $x$ of one type of opinion is given by $E(x) = f[(x-x_c)L^{1/ν}]$ with a universal value of $ν= 2.5 \pm 0.03$. The form of the scaling function is also universal: $f(y) = [\tanh(λy +c) +1]/2$, where $λ$ is found to be dependent on the particular dynamics. The variation of $λ$ against the parameters of the models is studied. $c$ is non-zero only when the dynamical rule distinguishes between $\pm 1$ states; comparison with theoretical estimates in this case shows very good agreement.

cond-mat.stat-mech↗

Agent based models for wealth distribution with preference in interaction

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of real economic system can be reproduced by the models.

physics.soc-ph↗

Exit probability in inflow dynamics: nonuniversality induced by range, asymmetry and fluctuation

Probing deeper into the existing issues regarding the exit probability (EP) in one dimensional dynamical models, we consider several models where the states are represented by Ising spins and the information flows inwards. At zero temperature, these systems evolve to either of two absorbing states. The exit probability $E(x)$, which is the probability that the system ends up with all spins up starting with $x$ fraction of up spins is found to have the general form $E(x) = x^α/\left[x^α+ (1-x)^α\right]$. The exit probability exponent $α$ strongly depends on $r$, the range of interaction, the symmetry of the model and the induced fluctuation. Even in a nearest neighbour model, nonlinear form of EP can be obtained by controlling the fluctuations and for the same range, different models give different results for $α$. Non-universal behaviour of the exit probability is thus clearly established and the results are compared to existing studies in models with outflow dynamics to distinguish the two dynamical scenarios.

cond-mat.stat-mech↗

On the evolution and utility of annual citation indices

We study the statistics of citations made to the top ranked indexed journals for Science and Social Science databases in the Journal Citation Reports using different measures. Total annual citation and impact factor, as well as a third measure called the annual citation rate are used to make the detailed analysis. We observe that the distribution of the annual citation rate has an universal feature - it shows a maximum at the rate scaled by half the average, irrespective of how the journals are ranked, and even across Science and Social Science journals, and fits well to log-Gumbel distribution. Correlations between different quantities are studied and a comparative analysis of the three measures is presented. The newly introduced annual citation rate factor helps in understanding the effect of scaling the number of citation by the total number of publications. The effect of the impact factor on authors contributing to the journals as well as on editorial policies is also discussed.

cs.DL↗

Damage spreading transition in an opinion dynamics model

We study the damage spreading phenomena in two different ways in a opinion dynamics model introduced recently. This kinetic exchange type model is characterized by a fraction $q$ of negative interactions and shows the presence of an order-disorder transition at $q_c$. In the traditional method, two replicas of the population are considered in which the opinion of all the agents are identical initially except for a single agent. The systems are then allowed to evolve identically. In the other method, the initial opinions are identical for all agents but the two replicas are evolved independently. In both cases, a damage spreading transition occurs at $q_d$ where $q_d \approx 0.18$ in the traditional method and $q_d =0$ for the other; the damage increases with $q$ above $q_d$ and attains a constant value for $q\geq q_c$. However, the correlation between the evolved states above $q_c$ is clearly different in the two methods.

cond-mat.stat-mech↗

A stochastic opinion dynamics model with domain size dependent dynamic evolution

We introduce a stochastic model of binary opinion dynamics in one dimension. The binary opinions $\pm 1$ are analogous to up and down Ising spins and in the equivalent spin system, only the spins at the domain boundary can flip. The probability that a spin at the boundary is up is taken as $P_{up} = \frac {s_{up}} {s_{up} + δs_{down}}$ where $s_{up} (s_{down})$ denotes the size of the domain with up (down) spins neighbouring it. With $x$ fraction of up spins initially, a phase transition is observed in terms of the exit probability and the phase boundary is obtained in the $δ-x$ plane. In addition, we investigate the coarsening behaviour starting from a completely random state; conventional scaling is observed only at the phase transition point $δ= 1$. The scaling behaviour is compared to other dynamical phenomena; the model apparently belongs to a new dynamical universility class as far as persistence is concerned although the dynamical exponent, equal to one, is identical to a similar model with no stochasticity.

cond-mat.stat-mech↗

Susceptible-Infected-Recovered model on Euclidean network

We consider the Susceptible-Infected-Recovered (SIR) epidemic model on a Euclidean network in one dimension in which nodes at a distance $l$ are connected with probability $P(l) \propto l^{-δ}$ in addition to nearest neighbors. The topology of the network changes as $δ$ is varied and its effect on the SIR model is studied. $R(t)$, the recovered fraction of population up to time $t$, and $τ$, the total duration of the epidemic are calculated for different values of the infection probability $q$ and $δ$. A threshold behavior is observed for all $δ$ up to $δ\approx 2.0$; above the threshold value $q = q_c$, the saturation value $R_{sat}$ attains a finite value. Both $R_{sat}$ and $τ$ show scaling behavior in a finite system of size $N$; $R_{sat} \sim N^{-β/{\tildeν}} g_1[(q-q_c)N^{1/{\tilde ν}}]$ and $τ\sim N^{μ/{\tildeν}} g_2[(q-q_c)N^{1/\tildeν}]$. $q_c$ is constant for $0 \leq δ< 1$ and increases with $δ$ for $1<δ\lesssim 2$. Mean field behavior is seen up to $δ\approx 1.3$; weak dependence on $δ$ is observed beyond this value of $δ$.The distribution of the outbreak sizes is also estimated and found to be unimodal for $q < q_c$ and bimodal for $q > q_c$. The results are compared to static percolation phenomenaand also to mean field results for finite systems. Discussions on the properties of the Euclidean network are made in the light of the present results.

physics.soc-ph↗