2016MNRAS.456.3774W


Query : 2016MNRAS.456.3774W

2016MNRAS.456.3774W - Mon. Not. R. Astron. Soc., 456, 3774-3781 (2016/March-2)

ALFA: an automated line fitting algorithm.

WESSON R.

Abstract (from CDS):

I present the automated line fitting algorithm, alfa, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which require the identification of spectral features suspected to be emission lines, alfa instead uses a list of lines which are expected to be present to construct a synthetic spectrum. The parameters used to construct the synthetic spectrum are optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. I show that the results are in excellent agreement with those measured manually for a number of spectra. Where discrepancies exist, the manually measured fluxes are found to be less accurate than those returned by alfa. Together with the code neat, alfa provides a powerful way to rapidly extract physical information from observations, an increasingly vital function in the era of highly multiplexed spectroscopy. The two codes can deliver a reliable and comprehensive analysis of very large data sets in a few hours with little or no user interaction.

Abstract Copyright: © 2016 The Author Published by Oxford University Press on behalf of the Royal Astronomical Society (2016)

Journal keyword(s): line: identification - methods: data analysis - H ii regions - planetary nebulae: general

Simbad objects: 2

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Number of rows : 2
N Identifier Otype ICRS (J2000)
RA
ICRS (J2000)
DEC
Mag U Mag B Mag V Mag R Mag I Sp type #ref
1850 - 2026
#notes
1 PN Tc 1 PN 17 45 35.2879212240 -46 05 23.717122728   11.30 11.49     PCyg 280 0
2 NGC 6778 PN 19 18 24.9542333399 -01 35 47.155403881   13.747 12.721     ~ 272 0

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