Knowles, AT, Sansom, AE, Vazdekis, A and Allende Prieto, C (2023) sMILES SSPs: a library of semi-empirical MILES stellar population models with variable [α/Fe] abundances. Monthly Notices of the Royal Astronomical Society, 523 (3). pp. 3450-3470. ISSN 0035-8711
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Abstract
We present a new library of semi-empirical stellar population models that are based on the empirical MILES and semi-empirical sMILES stellar libraries. The models span a large range of age and metallicity, in addition to an [α/Fe] coverage from -0.2 to +0.6 dex, at MILES resolution (FWHM = Å) and wavelength coverage (Å). These models are aimed at exploring abundance ratios in the integrated light from stellar populations in star clusters and galaxies. Our approach is to build SSPs from semi-empirical stars at particular [α/Fe] values, thus producing new SSPs at a range of [α/Fe] values from sub-solar to super-solar. We compare these new SSPs with previously published and well-used models and find similar abundance pattern predictions, but with some differences in age indicators. We illustrate a potential application of our new SSPs, by fitting them to the high signal-to-noise data of stacked SDSS galaxy spectra. Age, metallicity, and [α/Fe] trends were measured for galaxy stacks with different stellar velocity dispersions and show systematic changes, in agreement with previous analyses of subsets of those data. These new SSPs are made publicly available.
Item Type: | Article |
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Additional Information: | This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2023 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. |
Uncontrolled Keywords: | 0201 Astronomical and Space Sciences; Astronomy & Astrophysics |
Subjects: | Q Science > QB Astronomy Q Science > QC Physics |
Divisions: | Research and Innovation Services |
Publisher: | Oxford University Press (OUP) |
SWORD Depositor: | A Symplectic |
Date Deposited: | 25 Mar 2024 15:17 |
Last Modified: | 04 Nov 2024 14:45 |
DOI or ID number: | 10.1093/mnras/stad1647 |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/22909 |
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