DOOp, an automated wrapper for DAOSPEC^⋆

¹ Dipartimento di Fisica e AstronomiaUniversità di Padova, vicolo Osservatorio 3, 35122 Padova, Italy
e-mail: tristan.cantat@oapd.inaf.it
² INAF − Osservatorio Astronomico di Padova, vicolo Osservatorio 5, 35122 Padova, Italy
³ Dipartimento di Fisica e Astronomia, Università di Bologna, Viale Berti Pichat 6/2, 40127 Bologna, Italy
⁴ INAF − Osservatorio Astronomico di Bologna, via Ranzani 1, 40127 Bologna, Italy
⁵ ASI Science Data Center, 00044 Frascati, Italy
⁶ Department of Astronomy, Indiana University, Bloomington, IN 47405, USA
⁷ Massachusetts Institute of Technology and Kavli Institute for Astrophysics and Space Research, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
⁸ INAF − Osservatorio Astrofisico di Arcetri, Largo Enrico Fermi 5, 50125 Firenze, Italy

Received: 24 August 2013
Accepted: 4 December 2013

Abstract

Context. Large spectroscopic surveys such as the Gaia-ESO Survey produce huge quantities of data. Automatic tools are necessary to efficiently handle this material. The measurement of equivalent widths in stellar spectra is traditionally done by hand or with semi-automatic procedures that are time-consuming and not very robust with respect to the repeatability of the results.

Aims. The program DAOSPEC is a tool that provides consistent measurements of equivalent widths in stellar spectra while requiring a minimum of user intervention. However, it is not optimised to deal with large batches of spectra, as some parameters still need to be modified and checked by the user. Exploiting the versatility and portability of BASH, we have built a pipeline called DOOp (DAOSPEC Option Optimiser) automating the procedure of equivalent widths measurement with DAOSPEC.

Methods. DOOp is organised in different modules that run one after the other to perform specific tasks, taking care of the optimisation of the parameters needed to provide the final equivalent widths, and providing log files to ensure better control over the procedure.

Results. In this paper, making use of synthetic and observed spectra, we compare the performance of DOOp with other methods, including DAOSPEC used manually. The measurements made by DOOp are identical to the ones produced by DAOSPEC when used manually, while requiring less user intervention, which is especially convenient when dealing with a large quantity of spectra. Like DAOSPEC, DOOp shows its best performance on high-resolution spectra (R > 20   000) and high signal-to-noise ratio (S/N > 30), with uncertainties ranging from 6 mÅ to 2 mÅ. The only subjective parameter that remains is the choice of the normalisation, as the user still has to make a choice on the order of the polynomial used for the continuum fitting. As a test, we use the equivalent widths measured by DOOp to re-derive the stellar parameters of four well-studied stars.