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Twenty years ago, Burstein et al. (1984)suggested that strong CN and Hbeta absorption meant younger ages among globular clusters in the Andromeda galaxy (M31), unless blue stars above the main-sequence turnoff or on the horizontal branch were uncommonly prominent. Here we test these suggestions by fitting the detailed mid-ultraviolet (2280-3120A) and optical (3850-4750A) spectra of one moderately metal-rich M31 globular cluster, G1. We explore the effects of a wide range of non-solar temperatures and abundance ratios, by combining a small set of theoretical stellar spectra like those of Peterson et al. (2001) that were calculated using extensively updated atomic-line constants. To match the mid-UV fluxes of G1, we find that hot components with Teff >= 8000K must be included. We obtain a very good fit with cool and hot blue horizontal branch (BHB) stars, but less satisfactory fits for blue straggler stars, those hotter than the main-sequence turnoff. The G1 color-magnitude diagram does show cool BHB stars, and the color of its giant branch supports the metallicity of one-sixth the solar value that we deduce. The turnoff temperature of the best-fit model is consistent with that of turnoff stars in galactic globular clusters and the field halo, indicating G1 is comparably old. Because metal-rich cool BHB and extremely blue HB stars have now been found within our own Galaxy, we suggest that these hot horizontal-branch stars be considered in fitting spectra of metal-rich populations such as the Andromeda globular clusters, to avoid possible underestimates of their ages. We plan to make the relevant spectral calculations available as part of our Hubble Treasury Program.
We have analyzed new HST/ACS and HST/WFC3 imaging in F475W and F814W of two previously-unobserved fields along the M31 minor axis to confirm our previous constraints on the shape of M31s inner stellar halo. Both of these new datasets reach a depth of
Blue horizontal-branch stars are Population II objects which are burning helium in their core and possess a hydrogen-burning shell and radiative envelope. Because of their low rotational velocities, diffusion has been predicted to work in their atmos
We investigate the performance of some common machine learning techniques in identifying BHB stars from photometric data. To train the machine learning algorithms, we use previously published spectroscopic identifications of BHB stars from SDSS data.
The distribution of Milky Way halo blue horizontal-branch (BHB) stars is examined using action-based extended distribution functions (EDFs) that describe the locations of stars in phase space, metallicity, and age. The parameters of the EDFs are fitt
Context: Blue horizontal-branch stars are very old objects that can be used as markers in studies of the Galactic structure and formation history. To create a clean sky catalogue of blue horizontal-branch stars, we cross-matched the Gaia data release