Power spectrum modelisation of helioseismic data: an application to the measurement of solar p-mode uncertainties

Details Power spectrum modelisation of helioseismic data: an application to the measurement of solar p-mode uncertainties Power spectrum modelisation of helioseismic data: an application to the measurement of solar p-mode uncertainties

May 1998

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998a%26a...333..362f&link_type=abstract

Astronomy and Astrophysics, v.333, p.362-368 (1998)

Astronomy and Astrophysics

Astrophysics

15

Sun: Oscillations, Methods: Statistical

Scientific paper

We estimate the statistical uncertainties of low-l solar p-modes parameters based on a Monte Carlo approach. Random perturbations of ideal Lorentz profiles L(a nu _i) can provide many estimations of the set of p-modes parameters a and allow one to estimate statistical error-bars sigma_ {a} by modelling the parameters' distribution function. Unlike frequencies, which show symmetric distributions, amplitudes and linewidths have asymmetric probability density function similar to the distribution function for time-averaged energies of stochastically excited solar p-modes (Kumar, 1988). A comparison between sigma_ ν and uncertainties based on Hessian's computation (Libbrecht 1992, Toutain and Appourchaux 1994) shows a nice agreement. However, our error-bars take into account more statistical effects, and rely less on the initial parameters' estimation. Such a technique has been used on the IRIS power spectra computed from gapped data, and on one GONG power spectrum computed from almost continuous data. We also present IRIS linewidths and error bars averaged over the years 1989-92 and computed with a fitting strategy using imposed frequency which improves the value of both the parameter and its uncertainty.

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