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

Periodograms are common tools used to search for periodic signals in unevenlyspaced time series. The significance of periodogram peaks is often assessedusing false alarm probability (FAP), which in most studies assumes uncorrelatednoise and is computed using numerical methods such as bootstrapping or MonteCarlo. These methods have a high computational cost, especially for low FAPlevels, which are of most interest. We present an analytical estimate of theFAP of the periodogram in the presence of correlated noise, which isfundamental to analyze astronomical time series correctly. The analyticalestimate that we derive provides a very good approximation of the FAP at a muchlower cost than numerical methods. We validate our analytical approach bycomparing it with Monte Carlo simulations. Finally, we discuss the sensitivityof the method to different assumptions in the modeling of the noise.

Efficient modeling of correlated noise I. Statistical significance of periodogram peaks