TY - JOUR
T1 - Novel Data Analysis Techniques in Coronal Seismology
AU - Anfinogentov, Sergey A.
AU - Antolin, Patrick
AU - Inglis, Andrew R.
AU - Kolotkov, Dmitrii
AU - Kupriyanova, Elena G.
AU - McLaughlin, James A.
AU - Nisticò, Giuseppe
AU - Pascoe, David J.
AU - Prasad, S. Krishna
AU - Yuan, Ding
N1 - Funding information: S.A. acknowledges support from the Ministry of Science and Higher Education of the Russian Federation and from the Russian Foundation of Basic Research (projects 18-29-21016 mk and 19-52-53045 gfen_a). J.A.M. acknowledges UK Science and Technology Facilities Council (STFC) support from grant ST/T000384/1. P.A. acknowledges funding from his STFC Ernest Rutherford Fellowship (No. ST/R004285/2). DJP was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 724326) and the C1 grant TRACEspace of Internal Funds KU Leuven. DYK thanks STFC for the grant ST/T000252/1, and the the Ministry of Science and Higher Education of the Russian Federation for financial support. SKP is grateful to FWO Vlaanderen for a senior postdoctoral fellowship (No. 12ZF420N). GN acknowledges the Rita Levi Montalcini 2017 fellowship funded by the Italian Ministry of Education, University and Research. DY is supported by the National Natural Science Foundation of China (NSFC, 12173012, 12111530078), the Shenzhen Technology Project (GXWD20201230155427003-20200804151658001).
PY - 2022/4/1
Y1 - 2022/4/1
N2 - We review novel data analysis techniques developed or adapted for the field of coronal seismology. We focus on methods from the last ten years that were developed for extreme ultraviolet (EUV) imaging observations of the solar corona, as well as for light curves from radio and X-ray. The review covers methods for the analysis of transverse and longitudinal waves; spectral analysis of oscillatory signals in time series; automated detection and processing of large data sets; empirical mode decomposition; motion magnification; and reliable detection, including the most common pitfalls causing artefacts and false detections. We also consider techniques for the detailed investigation of MHD waves and seismological inference of physical parameters of the coronal plasma, including restoration of the three-dimensional geometry of oscillating coronal loops, forward modelling and Bayesian parameter inference.
AB - We review novel data analysis techniques developed or adapted for the field of coronal seismology. We focus on methods from the last ten years that were developed for extreme ultraviolet (EUV) imaging observations of the solar corona, as well as for light curves from radio and X-ray. The review covers methods for the analysis of transverse and longitudinal waves; spectral analysis of oscillatory signals in time series; automated detection and processing of large data sets; empirical mode decomposition; motion magnification; and reliable detection, including the most common pitfalls causing artefacts and false detections. We also consider techniques for the detailed investigation of MHD waves and seismological inference of physical parameters of the coronal plasma, including restoration of the three-dimensional geometry of oscillating coronal loops, forward modelling and Bayesian parameter inference.
KW - Sun: corona
KW - Sun: waves
KW - Magnetohydrodynamics
KW - Data processing
UR - https://www.scopus.com/pages/publications/85126785093
U2 - 10.1007/s11214-021-00869-w
DO - 10.1007/s11214-021-00869-w
M3 - Review article
SN - 0038-6308
VL - 218
JO - Space Science Reviews
JF - Space Science Reviews
IS - 3
M1 - 9
ER -