NONLINEARITY AND CHAOS IN ⁸B SOLAR NEUTRINO FLUX SIGNALS FROM SUDBURY NEUTRINO OBSERVATORY

Abstract

The Sudbury neutrino observatory (SNO) detects 8 B solar neutrino fluxes from both the D2O and Salt detector. In the present analysis we have taken into consideration the flux data from 2nd November, 1999 to 27th May, 2001 from the D2O detector and that from 26th July, 2001 to 28th August, 2003 from the Salt detector. We have applied Delay Vector Variance analysis, 0-1 test, correlation dimension analysis, largest Lyapunov exponent method, recurrence plot and recurrence quantification analysis to explore the complexity and chaosity in these two time series. Present study reveals deterministic chaotic behaviour of these two signals which in turn suggests that long-term forecasting is not possible for these two signals but short-term forecasting can be made provided the model for the process dynamics is known to us.

Analysis of fractality and complexity of the planetary K-index

“…Moreover, if the correlation dimension is found to have finite integer value, the system dynamics exhibit non-chaotic and strongly periodic deterministic quality. But its fractional value with smaller magnitude implies that the process can be considered as a low dimensional deterministic chaotic one [52][53][54]. So, the fractional correlation dimension of 0.7348 gives the notion that variation of the geomagnetic storm is absolutely a chaotic process having low-dimensional determinism.…”

Complexity and periodicity of daily mean temperature and dew-point across India

“…Recurrence plot (RP) is a graphical tool introduced by Eckmann et al (1987) in order to extract qualitative characteristics of a time series. It exhibits characteristic patterns for typical dynamical behaviour of a signal or time series (Khondekar et al 2012). For example, a collection of single recurrence points, homogeneously and irregularly distributed over the whole plot, reveals stochastic behaviour of the signal.…”