4.7 Article

Empirical calibrations of optical absorption-line indices based on the stellar library MILES

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 406, Issue 1, Pages 165-180

Publisher

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2010.16683.x

Keywords

line: profiles; stars: abundances; stars: fundamental parameters

Funding

  1. Science and Technology Facilities Council [ST/F002335/1] Funding Source: researchfish
  2. STFC [ST/F002335/1] Funding Source: UKRI

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Stellar population models of absorption-line indices are an important tool for the analysis of stellar population spectra. They are most accurately modelled through empirical calibrations of absorption-line indices with the stellar parameters such as effective temperature, metallicity and surface gravity, which are the so-called fitting functions. Here we present new empirical fitting functions for the 25 optical Lick absorption-line indices based on the new stellar library Medium resolution INT Library of Empirical Spectra (MILES). The major improvements with respect to the Lick/IDS library are the better sampling of stellar parameter space, a generally higher signal-to-noise ratio and a careful flux calibration. In fact, we find that errors on individual index measurements in MILES are considerably smaller than in Lick/IDS. Instead, we find the rms of the residuals between the final fitting functions and the data to be dominated by errors in the stellar parameters. We provide fitting functions for both Lick/IDS and MILES spectral resolutions and compare our results with other fitting functions in the literature. A fortran 90 code is available online in order to simplify the implementation in stellar population models. We further calculate the offsets in index measurements between the Lick/IDS system to a flux-calibrated system. For this purpose, we use the three libraries MILES, ELODIE and STELIB. We find that offsets are negligible in some cases, most notably for the widely used indices H beta, Mgb, Fe5270 and Fe5335. In a number of cases, however, the difference between the flux-calibrated library and Lick/IDS is significant with the offsets depending on index strengths. Interestingly, there is no general agreement between the three libraries for a large number of indices, which hampers the derivation of a universal offset between the Lick/IDS and flux-calibrated systems.

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