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

Astronomy and Astrophysics – Astrophysics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

17 pages with tex and ps files, submitted to A&A, thierrya@so.estec.esa.nl

Scientific paper

10.1051/aas:1998440

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 fitting real data. We introduce 4 new diagnostics in helioseismology: the $(m,\nu)$ echelle diagramme, the cross echelle diagramme, the inter echelle diagramme, and the ratio cross spectrum. These diagnostics are extremely powerful to visualize and understand the covariance matrices of the Fourier spectra, and also to find bugs in the data analysis code. These diagrammes can also be used to derive quantitative information on the mode leakage and noise covariance matrices. Numerous examples using the LOI/SOHO and GONG data are given.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

The art of fitting p-mode spectra: Part II. Leakage and noise covariance matrices does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with The art of fitting p-mode spectra: Part II. Leakage and noise covariance matrices, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The art of fitting p-mode spectra: Part II. Leakage and noise covariance matrices will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-562099

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.