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The art of fitting p-mode spectra. I. Maximum likelihood estimation

Appourchaux, T.; Gizon, L.; Rabello-Soares, M. -C.

In this article we present our state of the art of fitting helioseismic p-mode spectra. We give a step by step recipe for fitting the spectra: statistics of the spectra both for spatially unresolved and resolved data, the use of Maximum Likelihood estimates, the statistics of the p-mode parameters, the use of Monte-Carlo simulation and the signifi…

Spectral decomposition by genetic forward modelling

Judge, P. G.; Brown, J. C.; Charbonneau, P. +3 more

We discuss the analysis of real and simulated line spectra using a genetic forward modelling technique. We show that this Genetic Algorithm (GA) based technique experiences none of the user bias or systematic problems that arise when faced with poorly sampled or noisy data. An important feature of this technique is the ease with which rigid a prio…

Numerical simulation of observations with GOLF on board SOHO

Roca Cortes, T.; Garcia, R. A.; Regulo, C.

The main objective of the GOLF Experiment (Global Oscillations at Low Frequencies) on-board the SOHO (Solar and Heliospheric Observatory) space mission is the quantitative knowledge of the internal structure of the Sun by measuring the spectrum of its global oscillations in a wide frequency range (30 nHz to 6 mHz). There is special interest in det…

The Arcetri spectral code for thin plasmas

Landini, M.; Landi, E.

The Arcetri spectral code allows to evaluate the spectrum of the radiation emitted by hot and optically thin plasmas in the spectral range 1 - 2000 Angstroms. The database has been updated including atomic data and radiative and collisional rates to calculate level population and line emissivities for a number of ions of the minor elements; a crit…

The art of fitting p-mode spectra. II. Leakage and noise covariance matrices

Appourchaux, T.; Gizon, L.; Rabello-Soares, M. -C.

In Part I we have developed a theory for fitting p-mode Fourier spectra assuming that these spectra have a multi-normal distribution. We showed, using Monte-Carlo simulations, how one can obtain p-mode parameters using ``Maximum Likelihood Estimators". In this article, hereafter Part II, we show how to use the theory developed in Part I for fittin…