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We compare theoretical dust yields for stars with mass 1 Msun < mstar < 8 Msun, and metallicities 0.001 < Z < 0.008 with observed dust production rates (DPR) by carbon- rich and oxygen-rich Asymptotic Giant Branch (C-AGB and O-AGB) stars in the Large and Small Magellanic Clouds (LMC, SMC). The measured DPR of C-AGB in the LMC are reproduced only if the mass loss from AGB stars is very efficient during the carbon-star stage. The same yields over-predict the observed DPR in the SMC, suggesting a stronger metallicity dependence of the mass-loss rates during the carbon- star stage. DPR of O-AGB stars suggest that rapid silicate dust enrichment occurs due to efficient hot-bottom-burning if mstar > 3 Msun and Z > 0.001. When compared to the most recent observations, our models support a stellar origin for the existing dust mass, if no significant destruction in the ISM occurs, with a contribution from AGB stars of 70% in the LMC and 15% in the SMC.
The dust reservoir in the interstellar medium of a galaxy is constantly being replenished by dust formed in the stellar winds of evolved stars. Due to their vicinity, nearby irregular dwarf galaxies the Magellanic Clouds provide an opportunity to obt
(abridged)Variability is a key property of stars on the asymptotic giant branch (AGB). Their pulsation period is related to the luminosity and mass-loss rate of the star. The long-period variables (LPVs) and Mira variables are the most prominent of a
We employ newly computed grids of spectra reprocessed by dust for estimating the total dust production rate (DPR) of carbon stars in the Small Magellanic Cloud (SMC). For the first time, the grids of spectra are computed as a function of the main ste
We present ESO/VLT spectra in the 2.9-4.1 micron range for a large sample of infrared stars in the Small Magellanic Cloud (SMC), mainly carbon stars, massive oxygen-rich Asymptotic Giant Branch (AGB) stars, and red supergiants. Strong emission from P
The properties of carbon stars in the Magellanic Clouds (MCs) and their total dust production rates are predicted by fitting their spectral energy distributions (SED) over pre-computed grids of spectra reprocessed by dust. The grids are calculated as