Low-frequency solar p modes as seen by GOLF and GONG instruments

TL;DR

This paper adapts the collapsogram technique to combined GOLF and GONG data to improve detection and analysis of low-frequency solar p modes with low signal-to-noise ratios.

Contribution

It introduces a novel method combining GOLF and GONG data using collapsograms to enhance low-frequency solar p mode analysis.

Findings

Effective extraction of low-frequency p modes from combined data

Improved signal-to-noise ratio in mode detection

Enhanced understanding of solar interior dynamics

Abstract

In the case of spatially-revolved helioseismic data (such as MDI, GONG, HMI), the usual mode-fitting analysis consists of fitting the 2l+1 individual m-spectra of a given multiplet (n, l) either individually or simultaneously. Such fitting methods fail to obtain reliable estimates of the mode parameters (frequency, splitting, ...) when the signal-to-noise ratio (SNR) is low, which makes those methods not suitable when one wants to look at the low-amplitude, long-lived solar p modes in the low-frequency range. Instead, Salabert et al. (2007) developed a new method to extract the mode parameters by adjusting the rotation- and structure-induced frequency shift for each m-spectrum to minimize the mode width in the m-averaged spectrum (a "collapsogram"). The m-averaged spectrum technique, applied to the spatially-resolved GONG and MDI data, appeared to be a powerful tool for low SNR modes in the low-frequency range. Another possibility to increase the SNR is to combine data from different instruments (Garcia et al. 2004a). We present here an adaptation of both techniques: the "collapsograms" applied to a combination of observations from a Sun-as-a-star instrument, GOLF, and a disk-imaged one, GONG.