Geometrical exponents of contour loops on synthetic multifractal rough surfaces: multiplicative hierarchical cascade p model

Invariant correlated optical fields driven by multiplicative noise

We describe the evolution of a linear transmittance when it is perturbed with multiplicative noise; the evolution is approximated through an ensemble of random transmittances that are used to generate diffraction fields. The randomness induces a competition mechanism between noise and transmittance, and it is identified through the self-correlation function. We show that the geometry of the self-correlation function is a single peak preserved in the diffraction field that can be matched with localization-like effects. To corroborate the theoretical predictions, we perform an experiment using a linear grating where the noise is approximated by a stochastic Markov chain. Experimental results are shown.

Random deposition with a power-law noise model: Multiaffine analysis

We study the random deposition model with power-law distributed noise and rare-event dominated fluctuation. In this model instead of particles with unit sizes, rods with variable lengths are deposited onto the substrate. The length of each rod is chosen from a power-law distribution P(l)∼l^{-(μ+1)}, and the site at which each rod is deposited is chosen randomly. The results show that for μ<μ_{c}=3 the log-log diagram of roughness, W(t), versus deposition time, t, increases as a step function, where the roughness in each interval acts as W_{loc}(t)≈t^{β_{loc}}. The local growth exponent, β_{loc}, is zero for μ=1. By increasing the μ exponent, the value of β_{loc} is increased. It tends to the growth exponent of the random distribution model with Gaussian noise, β=1/2, at μ_{c}=3. The fractal analysis of the height fluctuations for this model was performed by multifractal detrended fluctuation analysis algorithm. The results show multiaffinity behavior for the height fluctuations at μ<μ_{c} and the multiaffinity strength is greater for smaller values of the μ exponent.

Modeling and statistical analysis of non-Gaussian random fields with heavy-tailed distributions

In this paper, we investigate and develop an alternative approach to the numerical analysis and characterization of random fluctuations with the heavy-tailed probability distribution function (PDF), such as turbulent heat flow and solar flare fluctuations. We identify the heavy-tailed random fluctuations based on the scaling properties of the tail exponent of the PDF, power-law growth of qth order correlation function, and the self-similar properties of the contour lines in two-dimensional random fields. Moreover, this work leads to a substitution for the fractional Edwards-Wilkinson (EW) equation that works in the presence of μ-stable Lévy noise. Our proposed model explains the configuration dynamics of the systems with heavy-tailed correlated random fluctuations. We also present an alternative solution to the fractional EW equation in the presence of μ-stable Lévy noise in the steady state, which is implemented numerically, using the μ-stable fractional Lévy motion. Based on the analysis of the self-similar properties of contour loops, we numerically show that the scaling properties of contour loop ensembles can qualitatively and quantitatively distinguish non-Gaussian random fields from Gaussian random fluctuations.

Scale-invariant puddles in graphene: Geometric properties of electron-hole distribution at the Dirac point

We characterize the carrier density profile of the ground state of graphene in the presence of particle-particle interaction and random charged impurity in zero gate voltage. We provide detailed analysis on the resulting spatially inhomogeneous electron gas, taking into account the particle-particle interaction and the remote Coulomb disorder on an equal footing within the Thomas-Fermi-Dirac theory. We present some general features of the carrier density probability measure of the graphene sheet. We also show that, when viewed as a random surface, the electron-hole puddles at zero chemical potential show peculiar self-similar statistical properties. Although the disorder potential is chosen to be Gaussian, we show that the charge field is non-Gaussian with unusual Kondev relations, which can be regarded as a new class of two-dimensional random-field surfaces. Using Schramm-Loewner (SLE) evolution, we numerically demonstrate that the ungated graphene has conformal invariance and the random zero-charge density contours are SLE_{κ} with κ=1.8±0.2, consistent with c=-3 conformal field theory.