Analysis of power-law exponents by maximum-likelihood maps

Abstract

Maximum-likelihood exponent maps have been studied as a technique to increase the understanding and improve the fit of power-law exponents to experimental and numerical simulation data, especially when they exhibit both upper and lower cut-offs. The use of the technique is tested by analyzing seismological data, acoustic emission data and avalanches in numerical simulations of the 3D-Random Field Ising model. In the different examples we discuss the nature of the deviations observed in the exponent maps and some relevant conclusions are drawn for the physics behind each phenomenon.