% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Peil:643486,
      author       = {Peñil, P. and Torres-Albà, N. and Rico, A. and Buson,
                      Sara and Ajello, M. and Domínguez, A. and Adhikari, S.},
      title        = {{D}istortions in periodicity analysis of blazars – {II}:
                      the impact of gaps},
      journal      = {Monthly notices of the Royal Astronomical Society},
      volume       = {544},
      number       = {4},
      issn         = {0035-8711},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {PUBDB-2026-00233},
      pages        = {4665 - 4688},
      year         = {2025},
      note         = {cc-by},
      abstract     = {Time series analysis is fundamental to characterizing the
                      variability inherent in multiwavelength emissions from
                      blazars. However, a major observational challenge lies in
                      the need for well-sampled, temporally uniform data, which is
                      often hindered by irregular sampling and data gaps. These
                      gaps can significantly affect the reliability and accuracy
                      of methods used to probe source variability. This paper
                      investigates the impact of such observational gaps on time
                      series analysis of blazar emissions. To do so, we
                      systematically evaluate how these gaps alter observed
                      variability patterns, mask genuine periodic signals, and
                      introduce false periodicity detections. This evaluation is
                      conducted using both simulated and real observational data.
                      We assess a range of widely used time series analysis
                      methods, including the Lomb–Scargle periodogram, phase
                      dispersion minimization, and the recently proposed singular
                      spectrum analysis (SSA). Our results demonstrate a clear and
                      significant degradation in period detection reliability when
                      the percentage of gaps exceeds 50 per cent. In such cases,
                      the period-significance relationship becomes increasingly
                      distorted, often leading to misleading results. Among the
                      tested methods, SSA stands out for its ability to yield
                      consistent and robust detections despite high data
                      incompleteness. Additionally, the analysed methods tend to
                      identify artificial periodicities of around one year, likely
                      due to seasonal sampling effects, which can result in false
                      positives if not carefully recognized. Finally, the periods
                      detected with ≥ 3σ confidence are unlikely to result from
                      stochastic processes or from the presence of gaps in the
                      analysed time series.},
      cin          = {$Z_GA$},
      ddc          = {520},
      cid          = {$I:(DE-H253)Z_GA-20210408$},
      pnm          = {613 - Matter and Radiation from the Universe (POF4-613) /
                      DFG project G:(GEPRIS)443220636 - FOR 5195: Relativistische
                      Jets in Aktiven Galaxien (443220636)},
      pid          = {G:(DE-HGF)POF4-613 / G:(GEPRIS)443220636},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1093/mnras/staf1842},
      url          = {https://bib-pubdb1.desy.de/record/643486},
}