Pseudo-global Fitting of Gapped Helioseismic Data

TL;DR

The paper introduces a pseudo-global fitting algorithm for helioseismic data that reduces bias in mode parameter estimates, especially in gapped time-series, improving analysis of ground-based solar observations.

Contribution

A novel pseudo-global fitting method that effectively reduces bias in helioseismic mode parameter estimation, including in gapped data, combining global and local fitting advantages.

Findings

Reduces bias in frequency and asymmetry estimates.

Effective in analyzing gapped helioseismic data.

Applicable to ground-based solar observations like BiSON.

Abstract

Mode fitting or "peak-bagging" is an important procedure in helioseismology allowing one to determine the various mode parameters of solar oscillations. We have recently developed a new "pseudo-global" fitting algorithm as a way of reducing the systematic bias in the fits of certain mode parameters that are seen when using "local" fitting techniques to analyse "sun-as-a-star" p-mode data. This new algorithm has been designed specifically to gain the advantages of fitting the entire power spectrum, while retaining the efficiency of local fitting techniques. Using simulated data with a full fill we have previously shown that the pseudo-global routine reduces the bias in estimates of the frequencies and asymmetries and in the estimates of the solar background when compared with a traditional fitting technique. Here we present results that show that the pseudo-global routine is also effective in reducing bias in the parameter estimates when the time-series has significant gaps. As such we are now able to employ the routine in order to fit ground based helioseismic data such as that collected by the Birmingham Solar Oscillations Network (BiSON).