Efficient Pseudo-Global Fitting for Helioseismic Data

Mode fitting or "peak bagging" is an important procedure in helioseismology allowing one to determine the various mode parameters of solar oscillations. Here we describe a way of reducing the systematic bias in the fits of certain mode parameters that are seen when using "local" fitting techniques to analyze the Sun-as-a-star p-mode power spectrum. To do this we have developed a new "pseudo-global" fitting algorithm designed to gain the advantages of fitting the entire power spectrum, but without the problems involved in fitting a model incorporating many hundreds of parameters. We have performed a comparative analysis between the local and pseudo-global peak-bagging techniques by fitting the "limit" profiles of simulated helioseismic data. Results show that for asymmetric modes the traditional fitting technique returns systematically biased estimates of the central frequency parameter. This bias is significantly reduced when employing the pseudo-global routine. Similarly, we show that estimates of the background returned from the pseudo-global routine match the input values much more closely than the estimates from the local fitting method. We have also used the two fitting techniques to analyze a set of real solar data collected by the Global Oscillations at Low Frequencies instrument on board the ESA/NASA Solar and Heliospheric Observatory spacecraft. Similar differences between the estimated frequencies returned by the two techniques are seen when fitting both the real and simulated data. We show that the background fits returned by the pseudo-global routine more closely match the estimate of the background one can infer from interpolating between fits to the high and low frequency ends of the p-mode power spectrum.