New possible properties of atomic nuclei investigated by non linear methods: Fractal and recurrence quantification analysis

dc.creatorConte, Elio
dc.creatorKhrennikov, Andrei Yu.
dc.creatorZbilut, Joseph P.
dc.date2007-04-06
dc.date.accessioned2026-07-07T07:55:36Z
dc.date.available2026-07-07T07:55:36Z
dc.descriptionFor the first time we apply the methodologies of nonlinear analysis to investigate atomic matter. We use these methods in the analysis of Atomic Weights and of Mass Number of atomic nuclei. Using the AutoCorrelation Function and Mutual Information we establish the presence of nonlinear effects in the mechanism of increasing mass of atomic nuclei considered as a function of the atomic number. We find that increasing mass is divergent, possibly chaotic. We also investigate the possible existence of a Power Law for atomic nuclei and, using also the technique of the variogram, we conclude that a fractal regime could superintend to the mechanism of increasing mass for nuclei. Finally, using the Hurst exponent, evidence is obtained that the mechanism of increasing mass in atomic nuclei is in the fractional Brownian regime. The most interesting results are obtained by using Recurrence Quantification Analysis (RQA). New recurrences, psudoperiodicities, self-resemblance and class of self-similarities are identified with values of determinism showing oscillating values indicating the presence of more or less stability during the process of increasing mass of atomic nuclei. In brief, new regimes of regularities are identified for atomic nuclei that deserve to be studied by future researches. In particular an accurate analysis of binding energy values by nonlinear methods is further required.
dc.description42 pages including figures
dc.identifierhttps://arxiv.org/abs/0704.0903
dc.identifierhttp://arxiv.org/abs/0704.0903
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/127022
dc.subjectGeneral Physics
dc.titleNew possible properties of atomic nuclei investigated by non linear methods: Fractal and recurrence quantification analysis
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