Abstract

Abstract Quasi-periodic pulsations (QPPs) appear to be a common feature observed in the light curves of both solar and stellar flares. However, their quasi-periodic nature, along with the fact that they can be small in amplitude and short-lived, makes QPPs difficult to unequivocally detect. In this paper, we test the strengths and limitations of state-of-the-art methods for detecting QPPs using a series of hare-and-hounds exercises. The hare simulated a set of flares, both with and without QPPs of a variety of forms, while the hounds attempted to detect QPPs in blind tests. We use the results of these exercises to create a blueprint for anyone who wishes to detect QPPs in real solar and stellar data. We present eight clear recommendations to be kept in mind for future QPP detections, with the plethora of solar and stellar flare data from new and future satellites. These recommendations address the key pitfalls in QPP detection, including detrending, trimming data, accounting for colored noise, detecting stationary-period QPPs, detecting QPPs with nonstationary periods, and ensuring that detections are robust and false detections are minimized. We find that QPPs can be detected reliably and robustly by a variety of methods, which are clearly identified and described, if the appropriate care and due diligence are taken.

Highlights

  • Solar flares are multi-wavelength, powerful, impulsive energy releases on the Sun

  • A background trend is often observed in addition to the underlying flare shape itself

  • Automated Flare Inference of Oscillations (AFINO) is described in detail in Inglis et al (2015, 2016); here, we summarize the key steps in the method

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Summary

44. ISSN 0067-0049

Link: Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University’s research output. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. Solar Physics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USA. Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, 3665 Discovery Drive, Boulder, Colorado 80303, USA. Centre (Received January 1, 2018; Revised January 7, 2018; Accepted August 7, 2019)

INTRODUCTION
SIMULATIONS OF QPP FLARES
Single exponential-decaying sinusoidal QPPs
Two exponentially-decaying sinusoidal QPPs
Non-stationary sinusoidal QPPs
Multiple flares
Background trends
Real flares
HARE-AND-HOUNDS EXERCISES
E G E G tpeak2
METHODS
Gaussian Process Regression - JRAD
Wavelet Analysis - LAH
Relaxed AFINO - LAH in HH1
Forward modelling of QPP signals - DJP
Periodogram-based significance testing – CEP
Smoothing and periodogram – TVD
HH2: False alarm rates
Skill Scores
HH1: The quality of detections
Comparison of AFINO methods
Empirical Mode Decomposition results
Real Flares
Impact of trimming
Non-stationary QPPs
HH3 and the impact of smoothing
BEST PRACTICE BLUEPRINT FOR THE DETECTION OF QPPS
FUTURE PROSPECTS
Full Text
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