ULySS: A Full Spectrum Fitting Package
TL;DR: An easy-to-use full-spectrum fitting package to fit spectroscopic observations against a linear combination of non-linear model components convolved with a parametric line-of-sight velocity distribution and the importance of determining the shape of the continuum simultaneously to the other parameters is shown.
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Abstract: Aims. We provide an easy-to-use full-spectrum fitting package and explore its applications to (i) the determination of the stellar atmospheric parameters and (ii) the study of the history of stellar populations. Methods. We developed ULySS, a package to fit spectroscopic observations against a linear combination of non-linear model components convolved with a parametric line-of-sight velocity distribution. The minimization can be either local or global, and determines all the parameters in a single fit. We use chi2 maps, convergence maps and Monte-Carlo simulations to study the degeneracies, local minima and to estimate the errors. Results. We show the importance of determining the shape of the continuum simultaneously to the other parameters by including a multiplicative polynomial in the model (without prior pseudo-continuum determination, or rectification of the spectrum). We also stress the benefice of using an accurate line-spread function, depending on the wavelength, so that the line-shape of the models properly match the observation. For simple models, i. e., to measure the atmospheric parameters or the age/metallicity of a single-age stellar population, there is often a unique minimum, or when local minima exist they can unambiguously be recognized. For more complex models, Monte-Carlo simulations are required to assess the validity of the solution. Conclusions. The ULySS package is public, simple to use and flexible. The full spectrum fitting makes optimal usage of the signal.
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References
Stellar population synthesis at the resolution of 2003
Gustavo Bruzual,Stephane Charlot +1 more
TL;DR: In this article, the spectral evolution of stellar populations at ages between 100,000 yr and 20 Gyr at a resolution of 3 A across the whole wavelength range from 3200 to 9500 A for a wide range of metallicities.
12K
•Book
Solving least squares problems
Charles L. Lawson,Richard J. Hanson +1 more
- 01 Jun 1974
TL;DR: Since the lm function provides a lot of features it is rather complicated so it is going to instead use the function lsfit as a model, which computes only the coefficient estimates and the residuals.
8.3K
Parametric Recovery of Line‐of‐Sight Velocity Distributions from Absorption‐Line Spectra of Galaxies via Penalized Likelihood
Michele Cappellari,Eric Emsellem +1 more
TL;DR: In this paper, the authors investigate the accuracy of the parametric recovery of the line-of-sight velocity distribution (LOSVD) of the stars in a galaxy while working in pixel space.
2.4K
A survey of galaxy redshifts. I. Data reduction techniques.
John L. Tonry,Marc Davis +1 more
TL;DR: In this article, the uncertainty of a measured redshift, for the internal broadening of the object, and for the uncertainties of this broadening is analyzed. But the method of analyzing velocity dispersions is new and quite promising.
1.7K
Medium-resolution isaac newton telescope library of empirical spectra
Patricia Sanchez-Blazquez,Patricia Sanchez-Blazquez,Patricia Sanchez-Blazquez,Reynier Peletier,Reynier Peletier,J. Jiménez-Vicente,Nicolás Cardiel,A. J. Cenarro,Jesús Falcón-Barroso,Javier Gorgas,Selim O. Selam,Alexandre Vazdekis +11 more
TL;DR: In this paper, a stellar library for stellar population synthesis modelling is presented, which consists of 985 stars spanning a large range in atmospheric parameters and is obtained at the 2.5m Isaac Newton Telescope and cover the range λλ 3525-7500 A at 2.3 A spectral resolution.
1.7K