40 citations · 180 across the 13 of their papers we have counts for
17 papers · 1 filter
An automated activity classification tool for optical galaxy spectra
C. Daoutis, A. Zezas, E. Kyritsis +2
Reliable, versatile galaxy activity diagnostics are essential for understanding galaxy evolution. Traditional methods frequently necessitate extensive preprocessing, such as starli…
A machine-learning photometric classifier for massive stars in nearby galaxies II. The catalog
G. Maravelias, A. Z. Bonanos, K. Antoniadis +8
Mass loss is a key aspect of stellar evolution, particularly in evolved massive stars, yet episodic mass loss remains poorly understood. To investigate this, we need evolved massiv…
From seagull to hummingbird: New diagnostic methods for resolving galaxy activity
C. Daoutis, A. Zezas, E. Kyritsis +2
Context. A major challenge in astrophysics is classifying galaxies by their activity. Current methods often require multiple diagnostics to capture the full range of galactic activ…
Using machine learning to investigate the populations of dusty evolved stars in various metallicities
Grigoris Maravelias, Alceste Z. Bonanos, Frank Tramper +7
Mass loss is a key property to understand stellar evolution and in particular for low-metallicity environments. Our knowledge has improved dramatically over the last decades both f…
The Star Formation Reference Survey-V: the effect of extinction, stellar mass, metallicity, and nuclear activity on star-formation rates based on H emission
Konstantinos Kouroumpatzakis, Andreas Zezas, Alexandros Maragkoudakis +5
We present new H photometry for the Star-Formation Reference Survey (SFRS), a representative sample of star-forming galaxies in the local Universe. Combining these data with the…
The Star Formation Reference Survey. IV. Stellar mass distribution of local star-forming galaxies
Paolo Bonfini, Andreas Zezas, Matthew L. N. Ashby +5
We constrain the mass distribution in nearby, star-forming galaxies with the Star Formation Reference Survey (SFRS), a galaxy sample constructed to be representative of all known c…