Astronomy and Astrophysics – Astrophysics
Scientific paper
Oct 1998
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1998a%26as..132..145m&link_type=abstract
Astronomy and Astrophysics Supplement, v.132, p.145-153
Astronomy and Astrophysics
Astrophysics
19
Sun: Uv Radiation, Methods: Data Analysis, Techniques: Spectroscopic, Line: Identification, Profiles
Scientific paper
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 priori constraints can be applied to the data. These constraints make the GA decomposition much more accurate and stable, especially at the limit of instrumental resolution, than decomposition algorithms commonly in use.
Brown John C.
Charbonneau Patrick
Diver Declan A.
Ireland Jack
Judge Philip G.
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