Above the Noise: The Search for Periodicities in the Inner Heliosphere

Abstract

Remote sensing of coronal and heliospheric periodicities can provide vital insight into the local conditions and dynamics of the solar atmosphere. We seek to trace long (one hour or longer) periodic oscillatory signatures (previously identified above the limb in the corona by, e.g., Telloni et al. in Astrophys. J. 767, 138, 2013) from their origin at the solar surface out into the heliosphere. To do this, we combined on-disk measurements taken by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) and concurrent extreme ultra-violet (EUV) and coronagraph data from one of the Solar Terrestrial Relations Observatory (STEREO) spacecraft to study the evolution of two active regions in the vicinity of an equatorial coronal hole over several days in early 2011. Fourier and wavelet analysis of signals were performed. Applying white-noise-based confidence levels to the power spectra associated with detrended intensity time series yields detections of oscillatory signatures with periods from 6 -13 hours in both AIA and STEREO data. As was found by Telloni et al. (2013), these signatures are aligned with local magnetic structures. However, typical spectral power densities all vary substantially as a function of period, indicating spectra dominated by red (rather than white) noise. Contrary to the white-noise-based results, applying global confidence levels based on a generic backgroundnoise model (allowing a combination of white noise, red noise, and transients following Auchère et al. in Astrophys. J. 825, 110, 2016) without detrending the time series uncovers only sporadic, spatially uncorrelated evidence of periodic signatures in either instrument. Automating this method to individual pixels in the STEREO/COR coronagraph field of view is non-trivial. Efforts to identify and implement a more robust automatic background noise model fitting procedure are needed.B J. Threlfall

The Coronal Monsoon: Thermal Nonequilibrium Revealed by Periodic Coronal Rain

“…For each PSD, the significance of a peak of power at a given frequency ν must be determined with respect to the mean value s n ( ) of the power expected at this frequency from random fluctuations in the absence of a coherent signal (see Section3 of Auchère et al 2016a). While many coronal time series have power-law-like PSDs (Gruber et al 2011;Auchère et al 2014;Froment et al 2015;Inglis et al 2015Inglis et al , 2016Ireland et al 2015;Threlfall et al 2017), finding a generic model of noise able to accurately reproduce all the observed spectral shapes has proved to be challenging (Threlfall et al 2017). Since periodic signals affect isolated frequency bins, this problem is circumvented in our code by estimating the expected power at each frequency from its average over the 18 neighboring bins.…”

Propagation of waves above a plage as observed by IRIS and SDO

“…Recently, Auchère et al (2016) proposed a generic noise model for an EUV TS (using AIA high-temperature filter observations) and have also shown that smoothing can add artificial periodicities. After Auchère et al (2016), Threlfall et al (2017) have also adopted the same generic noise model for EUV TS under different physical conditions of solar atmosphere. Auchère et al (2016) proposed that the generic noise model is a linear combination of the power law, kappa function, and white noise.…”

“…Similarly, low frequencies do not show the difference between the plage and surrounding region but have high power in comparison to the power inherited in the high frequency range.Hence, on-average, the Fourier power behavior suggests that the dynamics of the plage region is inherited within the regime of intermediate frequencies.Then, we applied for the first time a generic noise model to estimate the confidence levels using wavelet analysis on photospheric and TR TS. The noise model has been previously applied only for coronal TS(Auchère et al 2016;Threlfall et al 2017). Previous scientific works have utilized either a white or red noise model to calculate confidence levels, which can give erroneous confidence levels.…”

Light variations due to the line-driven wind instability and wind blanketing in O stars

“…On the other hand, it is possible to compute the Fourier spectrum of the light curves, fit the spectrum by some phenomenological model, and compare the fit parameters derived for observed and simulated light curves. Similar techniques are used to study time series in various contexts, for example, light curves of X-ray binaries (Burderi et al 1993), solar flare data (Threlfall et al 2017), or to search for granulation in Cepheids (Derekas et al 2017).…”