Scaling characteristics of fractional diffusion processes in the presence of power-law distributed random noise

Abstract: We present results of the numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys L\'evy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of $\mu$-stable L\'evy noise. e study the scaling properties of the global width and two point correlation functions, we then compare the analytical and numerical results for the growth exponent $\beta$ and the roughness exponent $\alpha$. We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of $\mu$-stable L\'evy noise display special scaling properties in the probability distribution function (PDF). Finally, we study numerically the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent $\beta$ and to confirm the validity of our numerical analysis. The proposed fractional langevin equation can be used for modeling, analysis and characterization of experimental data, such as solar flare fluctuations, turbulent heat flow and etc.