Development of a new analysis technique to measure low radial-order p modes in spatially-resolved helioseismic data

TL;DR

This paper introduces a novel analysis technique for helioseismic data that improves the detection of low radial-order p modes by optimizing the $m$-averaged spectrum, enabling measurements at lower frequencies than traditional methods.

Contribution

The paper develops a new method to accurately estimate mode shifts in helioseismic data, enhancing the detection of low radial-order p modes in spatially-resolved observations.

Findings

Successfully applied to GONG data for modes with 1 ≤ ℓ ≤ 25.

Allows measurement of lower-frequency modes than classic peak-fitting.

Demonstrates the potential advantage of the new technique.

Abstract

In order to take full advantage of the long time series collected by the GONG and MDI helioseismic projects, we present here an adaptation of the rotation-corrected $m$-averaged spectrum technique in order to observe low radial-order solar p modes. Modeled profiles of the solar rotation demonstrated the potential advantage of such a technique. Here we develop a new analysis procedure which finds the best estimates of the shift of each $m$ of a given ($n,\ell$) multiplet, commonly expressed as an expansion in a set of orthogonal polynomials, which yield the narrowest mode in the $m$-averaged spectrum. We apply the technique to the GONG data for modes with $1 \leq \ell \leq 25$ and show that it allows us to measure lower-frequency modes than with classic peak-fitting analysis of the individual-$m$ spectra.