Understanding the Lomb-Scargle Periodogram
2017/03/28 by Jake Vanderplas, Jacob T. VanderPlas · 3 voices · 65 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Blind Source Separation Techniques #Chaos control and synchronization #Fractal and DNA sequence analysis #astro-ph.IM
paper · pdf · doi:10.3847/1538-4365/aab766
55 pages, 26 figures. Code available at https://github.com/jakevdp/PracticalLombScargle/
arxiv created 2017/03/28 · openalex publication_date 2018/05/01 · arxiv updated 2018/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Abstract
The Lomb-Scargle periodogram is a well-known algorithm for detecting and characterizing periodic signals in unevenly-sampled data. This paper presents a conceptual introduction to the Lomb-Scargle periodogram and important practical considerations for its use. Rather than a rigorous mathematical treatment, the goal of this paper is to build intuition about what assumptions are implicit in the use of the Lomb-Scargle periodogram and related estimators of periodicity, so as to motivate important practical considerations required in its proper application and interpretation.
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