Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userAnalyzing supergranular power spectra using helioseismic normal-mode coupling
117
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Normal-mode coupling is a technique applied to probe the solar interior using surface observations of oscillations. The technique, which is straightforward to implement, makes more use of the seismic information in the wavefield than other comparable local imaging techniques and therefore has the potential to significantly improve current capabilities. Here, we examine supergranulation power spectra using mode-coupling analyses of intermediate-to-high-degree modes by invoking a Cartesian-geometric description of wave propagation under the assumption that the localized patches are much smaller in size than the solar radius. We extract the supergranular power spectrum and compare the results with prior helioseismic studies. Measurements of the dispersion relation and life times of supergranulation, obtained using near surface modes (f and p$_1$), are in accord with the literature. We show that the cross-coupling between the p$_2$ and p$_3$ acoustic modes, which are capable of probing greater depths, are also sensitive to supergranulation.
rate research
Read More
Retrograde Rossby waves, measured to have significant amplitudes in the Sun, likely have notable implications for various solar phenomena. Rossby waves create small-amplitude, very-low frequency motions (on the order of the rotation rate and lower), which in turn shift the resonant frequencies and eigenfunctions of the acoustic modes of the Sun. The detection of even azimuthal orders Rossby modes using mode coupling presents additional challenges and prior work therefore only focused on odd orders. Here, we successfully extend the methodology to measure even azimuthal orders as well. We analyze 4 and 8 years of Helioseismic and Magnetic Imager (HMI) data and consider coupling between different-degree acoustic modes (of separations 1 and 3 in harmonic degree). The technique uses couplings between different frequency bins to capture the temporal variability of the Rossby modes. We observe significant power close to the theoretical dispersion relation for sectoral Rossby modes (where the azimuthal order is same as harmonic degree, s = |t|). Our results are consistent with prior measurements of Rossby modes with azimuthal orders over the range t = 4 to 16 with maximum power occurring at mode t = 8. The amplitudes of these modes vary from 1 to 2 m/s. We place an upper bound of 0.2 m/s on the sectoral t = 2 mode, which we do not detect in our measurements. This effort adds credence to the mode-coupling methodology in helioseismology
Several spectral fluctuation measures of random matrix theory (RMT) have been applied in the study of spectral properties of networks. However, the calculation of those statistics requires performing an unfolding procedure, which may not be an easy task. In this work, network spectra are interpreted as time series, and we show how their short and long-range correlations can be characterized without implementing any previous unfolding. In particular, we consider three different representations of Erdos-Renyi (ER) random networks: standard ER networks, ER networks with random-weighted self-edges, and fully random-weighted ER networks. In each case, we apply singular value decomposition (SVD) such that the spectra are decomposed in trend and fluctuation normal modes. We obtain that the fluctuation modes exhibit a clear crossover between the Poisson and the Gaussian orthogonal ensemble statistics when increasing the average degree of ER networks. Moreover, by using the trend modes, we perform a data-adaptive unfolding to calculate, for comparison purposes, traditional fluctuation measures such as the nearest neighbor spacing distribution, number variance $Sigma$2, as well as $Delta$3 and {delta}n statistics. The thorough comparison of RMT short and long-range correlation measures make us identify the SVD method as a robust tool for characterizing random network spectra.
A new fitting methodology is presented which is equally well suited for the estimation of low-, medium-, and high-degree mode parameters from $m$-averaged solar oscillation power spectra of widely differing spectral resolution. This method, which we call the Windowed, MuLTiple-Peak, averaged spectrum, or WMLTP Method, constructs a theoretical profile by convolving the weighted sum of the profiles of the modes appearing in the fitting box with the power spectrum of the window function of the observing run using weights from a leakage matrix that takes into account both observational and physical effects, such as the distortion of modes by solar latitudinal differential rotation. We demonstrate that the WMLTP Method makes substantial improvements in the inferences of the properties of the solar oscillations in comparison with a previous method that employed a single profile to represent each spectral peak. We also present an inversion for the internal solar structure which is based upon 6,366 modes that we have computed using the WMLTP method on the 66-day long 2010 SOHO/MDI Dynamics Run. To improve both the numerical stability and reliability of the inversion we developed a new procedure for the identification and correction of outliers in a frequency data set. We present evidence for a pronounced departure of the sound speed in the outer half of the solar convection zone and in the subsurface shear layer from the radial sound speed profile contained in Model~S of Christensen-Dalsgaard and his collaborators that existed in the rising phase of Solar Cycle~24 during mid-2010.
Small scale magnetic fields (magnetic elements) are ubiquitous in the solar photosphere. Their interaction can provide energy to the upper atmospheric layers, and contribute to heat the solar corona. In this work, the dynamic properties of magnetic elements in the quiet Sun are investigated. The high number of magnetic elements detected in a supegranular cell allowed us to compute their displacement spectrum $langle(Delta r)^2rangleproptotau^gamma$ (being $gamma>0$, and $tau$ the time since the first detection), separating the contribution of the network (NW) and the internetwork (IN) regions. In particular, we found $gamma=1.27pm0.05$ and $gamma=1.08pm0.11$ in NW (at smaller and larger scales, respectively), and $gamma=1.44pm0.08$ in IN. These results are discussed in light of the literature on the topic, as well as the implications for the build up of the magnetic network.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
