Caminhantes aleatórios com perfil de memória binomial

Abstract

Great has been the interest in anomalous diffusion because they are present in several areas of knowledge. The introduction of a memory profile in random walk environment give them a non-Markovian stochastic dynamics, whose temporal correlations may create superdiffusion, persistence and log-periodicity. We present an overview of memory profile literature and introduce our model. The binomial memory model can select different memory loss regions, from the old to the recent one. Thus, we investigate the impact of memory loss location on superdiffusive behavior of a random walker and unify some literature results. We verify that old memory generates higher superdiffusion measured by the Hurst coefficient, while recent memory tends to decrease superdiffusion, causing more walkers to undergo normal diffusion. We also investigate the short initial memory region, with zero tending standard deviation. We observe log-periodicity for some walkers suggesting different regions of log-periodic behavior, including those considered as normal diffusion. A particularity of the binomial model is an extremely symmetric result to Hxr diagram.