Journal
ASTRONOMY & ASTROPHYSICS
Volume 486, Issue 2, Pages 637-646Publisher
EDP SCIENCES S A
DOI: 10.1051/0004-6361:200809719
Keywords
polarization; stars : magnetic fields; methods : numerical
Categories
Ask authors/readers for more resources
Aims. Our main objective is to develop a denoising strategy to increase the signal to noise ratio of individual spectral lines of stellar spectropolarimetric observations. Methods. We use a multivariate statistics technique called Principal Component Analysis. The cross-product matrix of the observations is diagonalized to obtain the eigenvectors in which the original observations can be developed. This basis is such that the first eigenvectors contain the greatest variance. Assuming that the noise is uncorrelated a denoising is possible by reconstructing the data with a truncated basis. We propose a method to identify the number of eigenvectors for an effcient noise filtering. Results. Numerical simulations are used to demonstrate that an important increase of the signal to noise ratio per spectral line is possible using PCA denoising techniques. It can be also applied for detection of magnetic fields in stellar atmospheres. We analyze the relation between PCA and commonly used techniques like line addition and least-squares deconvolution. Moreover, PCA is very robust and easy to compute.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available