Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data

Details Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data

Dec 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010agufmsh11a1615i&link_type=abstract

American Geophysical Union, Fall Meeting 2010, abstract #SH11A-1615

Astronomy and Astrophysics

Astrophysics

[7509] Solar Physics, Astrophysics, And Astronomy / Corona, [7546] Solar Physics, Astrophysics, And Astronomy / Transition Region, [7594] Solar Physics, Astrophysics, And Astronomy / Instruments And Techniques

Scientific paper

Ireland et al. (2010) recently published a Bayesian-probability based automated oscillation detection algorithm that finds areas of the solar corona that support spatially contiguous oscillatory signals. The major advantages of this algorithm are that it requires no special knowledge of the noise characteristics or possible frequency content of the signal, yet can calculate a probability that a time series supports a signal in a given frequency range. This leads to an algorithm which detects pixel areas where each pixel has a high probability of supporting an oscillatory signal; however, the pixels in these areas are not necessarily oscillating coherently. Earlier, McIntosh et al. (2008) described another algorithm that first Fourier filters time series data around a known frequency, and then calculates the local coherence of the filtered signals in order to find areas of the solar corona that exhibit locally strongly coherent signals in narrow frequency ranges. The major advantages of this algorithm are that locally coherent signals are found, and that it is simple to calculate other parameters such as the phase speed. This leads to an algorithm that finds groups of pixels that are coherent in narrow frequency ranges, but that are not necessarily oscillatory in nature. In this work we combine these two recently published automated oscillatory signal detection algorithms and compare the new hybrid algorithm to the progenitor algorithms. The new algorithm is applied to Advanced Imaging Assembly (AIA) 94, 131, 171, 193, 211 and 335 Å data from the Solar Dynamics Observatory, and we will give some first results. We also discuss the use of this algorithm in a detection pipeline to provide near-real time measurements of groups of coherently oscillating pixels.

Affiliated with

Also associated with

No associations

Rating

Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automated detection of oscillatory signals in the solar atmosphere: first results from SDO-AIA data will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1506396