English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Complex network approaches have been recently developed as an alternativeframework to study the statistical features of time-series data. We perform avisibility-graph analysis on both the daily and monthly sunspot series. Basedon the data, we propose two ways to construct the network: one is from theoriginal observable measurements and the other is from anegative-inverse-transformed series. The degree distribution of the derivednetworks for the strong maxima has clear non-Gaussian properties, while thedegree distribution for minima is bimodal. The long-term variation of thecycles is reflected by hubs in the network which span relatively large timeintervals. Based on standard network structural measures, we propose tocharacterize the long-term correlations by waiting times between two subsequentevents. The persistence range of the solar cycles has been identified over15\,--\,1000 days by a power-law regime with scaling exponent $\gamma = 2.04$of the occurrence time of the two subsequent and successive strong minima. Incontrast, a persistent trend is not present in the maximal numbers, althoughmaxima do have significant deviations from an exponential form. Our resultssuggest some new insights for evaluating existing models. The power-law regimesuggested by the waiting times does indicate that there are some level ofpredictable patterns in the minima.

Complex Network Approach to the Statistical Features of the Sunspot Series