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Tag: <span>red supergiant</span>

Tag: red supergiant

New paper: de Wit et al. 2025: Investigating episodic mass loss in evolved massive stars: III. Spectroscopy of dusty massive stars in three northern galaxies

This is the complementary work to that of Alceste’s published some time ago, covering the southern galaxies. Now it was Stephan and Gonzalo’s turn to lead this the paper for the northern galaxies, observed with the 10.4 m GTC. We managed to classify 122 additional sources, increasing the number of …

New Paper: Antoniadis et al. 2025: Investigating the metallicity dependence of the mass-loss rate relation of red supergiants

Kostas has been actively working on determining the mass loss rate for Red Supergiants across various metallicities. We had plenty of these sources for NGC 6822 so it was natural to include them in a straight comparison with SMC, LMC and the Milky Way. However, each of these galaxies have …

New Paper: Muñoz-Sanchez et al. 2024: The dramatic transition of the extreme Red Supergiant WOH G64 to a Yellow Hypergiant

This is of the most intriguing object. We are still puzzled about its nature. From a red supergiant, it became a yellow one within months to year, showing B[e] characteristics. We are not certain if this is the correct answer or something else is undergoing. But definitely an exciting object …

New paper: Zapartas et al. 2024: The effect of mass loss in models of red supergiants in the Small Magellanic Cloud:

During the ASSESS project we carried out tons of observations and careful analysis in order to identify mass-losing evolved stars. At the same time though, Manos Zapartas was taking advantage of the new red supergiant mass loss fits we managed and put them into some perspective with theory. Equipped with …

New paper: de Wit et al. 2024: Investigating episodic mass loss in evolved massive stars: II. Physical properties of red supergiants at subsolar metallicity

Stephan extends the work he has performed previously in the Magellanic Clouds to RSGs identified in the ASSESS project in galaxies at subsolar metallicity. Investigating episodic mass loss in evolved massive stars: II. Physical properties of red supergiants at subsolar metallicity S. de Wit, A.Z. Bonanos, K. Antoniadis, E. Zapartas, …

New paper: Establishing a mass-loss rate relation for red supergiants in the Large Magellanic Cloud

This is a paper led by Kostas from the ASSESS team where we investigated the mass-loss in LMC/s RSGs. Interestingly this made its way to the astrobites site. Establishing a mass-loss rate relation for red supergiants in the Large Magellanic Cloud K. Antoniadis, A.Z. Bonanos, S. de Wit, E. Zapartas, …

New Paper: Evolved Massive Stars at Low-metallicity V. Mass-Loss Rate of Red Supergiant Stars in the Small Magellanic Cloud

Evolved Massive Stars at Low-metallicity V. Mass-Loss Rate of Red Supergiant Stars in the Small Magellanic Cloud Ming Yang (杨明), Alceste Z. Bonanos, Biwei Jiang (姜碧沩), Emmanouil Zapartas, Jian Gao (高健), Yi Ren(任逸), Man I Lam (林敏仪), Tianding Wang (王天丁), Grigoris Maravelias, Panagiotis Gavras, Shu Wang (王舒), Xiaodian Chen (陈孝钿), …

New Paper: Properties of luminous red supergiant stars in the Magellanic Clouds

Properties of luminous red supergiant stars in the Magellanic Clouds S. de Wit, A.Z. Bonanos, F. Tramper, M. Yang, G. Maravelias, K. Boutsia, N. Britavskiy, and E. Zapartas There is evidence that some red supergiants (RSGs) experience short lived phases of extreme mass loss, producing copious amounts of dust. These …

New paper: Using machine learning to investigate the populations of dusty evolved stars in various metallicities

This is actually a preview of what will follow after the first paper of the machine-learning classifier. We put it into action to get predictions for a number of galaxies and we start exploring the results. Of more interest is the fractions of the populations with metallicity, although a more …

EAS 2021 poster contributions

Three poster contributions during EAS 2021 with the following … statistics: all of them on massive stars,  two within the framework of the ASSESS project, and two on machine-learning applications. 1. Applying machine-learning methods to build a photometric classifier for massive stars in nearby galaxies Grigoris Maravelias, Alceste Bonanos, Frank …