Fitness noise in the Bak-Sneppen evolution model in high dimensions.

We study the Bak-Sneppen evolution model on a regular hypercubic lattice in high dimensions. Recent work [Phys. Rev.

Finite-size and finite-time scaling for kinetic rough interfaces.

We consider discrete models of kinetic rough interfaces that exhibit space-time scale invariance in height-height correlation. We use the generic scaling theory of Ramasco et al. [Phys.

Fitness fluctuations in the Bak-Sneppen model.

We study the one-dimensional Bak-Sneppen model for the evolution of species in an ecosystem. Of particular interest are the temporal fluctuations in fitness variables. We numerically compute the power spectral density and apply the finite-size scaling method to get data collapse.

Spatio-temporal analysis of air quality and its relationship with COVID-19 lockdown over Dublin.

Air pollution has become one of the biggest challenges for human and environmental health. Major pollutants such as Nitrogen Dioxide (NO ), Sulphur Dioxide (SO ), Ozone (O ), Carbon Monoxide (CO), and Particulate matter (PM and PM) are being ejected in a large quantity every day. Initially, authorities did not implement the strictest mitigation policies due to pressures of balancing the economic needs of people and public safety.

Finite-size scaling of critical avalanches.

We examine probability distribution for avalanche sizes observed in self-organized critical systems. While a power-law distribution with a cutoff because of finite system size is typical behavior, a systematic investigation reveals that it may also decrease with increasing the system size at a fixed avalanche size. We implement the scaling method and identify scaling functions.

Linking space-time correlations for a class of self-organized critical systems.

The hypothesis of self-organized criticality explains the existence of long-range "space-time" correlations, observed inseparably in many natural dynamical systems. A simple link between these correlations is yet unclear, particularly in fluctuations at an "external drive" timescale. As an example, we consider a class of sandpile models displaying nontrivial correlations.

Critical Pólya urn.

We propose a variant model of the Pólya urn process, where the dynamics consist of two competing elements: suppression of growth and enhancement of dormant character. Here the level of such features is controlled by an internal parameter in a random manner, so that the system self-organizes and characteristic observables exhibit scale invariance, suggesting the existence of criticality. Varying the internal control parameter, one can explain interesting universality classes for avalanche-type events.

Correspondence between a noisy sample-space-reducing process and records in correlated random events.

We study survival time statistics in a noisy sample-space-reducing (SSR) process. Our simulations suggest that both the mean and standard deviation scale as ∼N/N^{λ}, where N is the system size and λ is a tunable parameter that characterizes the process. The survival time distribution has the form P_{N}(τ)∼N^{-θ}J(τ/N^{θ}), where J is a universal scaling function and θ=1-λ.

General mechanism for the 1/f noise.

We consider the response of a memoryless nonlinear device that acts instantaneously, converting an input signal ξ(t) into an output η(t) at the same time t. For input Gaussian noise with power-spectrum 1/f^{α}, the nonlinearity can modify the spectral index of the output to give a spectrum that varies as 1/f^{α^{'}} with α^{'}≠α. We show that the value of α^{'} depends on the nonlinear transformation and can be tuned continuously.

Survival-time statistics for sample space reducing stochastic processes.

Stochastic processes wherein the size of the state space is changing as a function of time offer models for the emergence of scale-invariant features observed in complex systems. I consider such a sample-space reducing (SSR) stochastic process that results in a random sequence of strictly decreasing integers {x(t)},0≤t≤τ, with boundary conditions x(0)=N and x(τ) = 1. This model is shown to be exactly solvable: P_{N}(τ), the probability that the process survives for time τ is analytically evaluated.

Scaling behavior in probabilistic neuronal cellular automata.

We study a neural network model of interacting stochastic discrete two-state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective temperature). There are avalanches of neuronal activity, namely, spatially and temporally contiguous sites of activity; a detailed numerical study of these activity avalanches is presented, and single, joint, and marginal probability distributions are computed.

Power spectrum of mass and activity fluctuations in a sandpile.

We consider a directed Abelian sandpile on a strip of size 2×n, driven by adding a grain randomly at the left boundary after every T timesteps. We establish the exact equivalence of the problem of mass fluctuations in the steady state and the number of zeros in the ternary-base representation of the position of a random walker on a ring of size 3^{n}. We find that while the fluctuations of mass have a power spectrum that varies as 1/f for frequencies in the range 3^{-2n}≪f≪1/T, the activity fluctuations in the same frequency range have a power spectrum that is linear in f.