Related papers: Analyzer of Spectra for Age Determination (ASAD) -…
The field of galaxy evolution will make a great leap forward in the next decade as a consequence of the huge effort by the scientific community in multi-object spectroscopic facilities. To maximise the impact of such incoming data, the…
The ACS Survey of Galactic Globular Clusters is a Hubble Space Telescope (HST) Treasury program designed to provide a new large, deep and homogeneous photometric database. Based on observations from this program, we have measured precise…
Constraints on the formation and evolution of the Milky Way Galaxy require multi-dimensional measurements of kinematics, abundances, and ages for a large population of stars. Ages for luminous giants, which can be seen to large distances,…
We present flux-calibrated integrated spectra in the optical range (3700-6800 \AA) obtained at Complejo Astron\'omico El Leoncito (CASLEO, Argentina) for a sample of 10 concentrated star clusters belonging to the Large Magellanic Cloud…
In this fourth paper of a series on the precision of ages of stellar populations obtained through the full-spectrum fitting technique, we present a first systematic analysis that compare the age, metallicity and reddening of star clusters…
We present a new method for the evaluation of the age and age-spread among pre-main-sequence (PMS) stars in star-forming regions in the Magellanic Clouds, accounting simultaneously for photometric errors, unresolved binarity, differential…
The pixel-to-pixel spectral fitting technique is often used in studies of stellar populations. It enables the user to infer several parameters from integrated light spectra such as ages and chemical abundances. In this paper, we examine the…
We investigate the precision of the ages and metallicities of 21,000 mock simple stellar populations (SSPs) determined through full-spectrum fitting. The mock SSPs cover an age range of 6.8 $<$ log (age/yr) $<$ 10.2, for three wavelength…
Accurate measurements of statistical properties, such as the star formation rate and the lifetime of young stellar objects (YSOs) in different stages, is essential for constraining star formation theories. However, it is a difficult task to…
A new Monte Carlo method has been developed in order to derive ages of young embedded clusters within massive star forming regions where there is strong differential reddening. After foreground and infrared excess source candidates are…
We present a new technique to segregate old and young stellar populations in galactic spectra using machine learning methods. We used an ensemble of classifiers, each classifier in the ensemble specializes in young or old populations and…
We investigate current problems in obtaining reliable ages for old stellar systems based on stellar population synthesis modelling of their integrated spectra. In particular, we address the large ages derived for the globular cluster 47…
Age is one of the most fundamental parameters of stars, yet it is one of the hardest to determine as it requires modelling various aspects of stellar formation and evolution. When we compare the ages derived from isochronal and dynamical…
Autism Spectrum Disorder (ASD) is one neuro developmental disorder that is now widespread in the world. ASD persists throughout the life of an individual, impacting the way they behave and communicate, resulting to notable deficits…
We present a detailed analysis of our ability to determine stellar masses, ages, reddening and extinction values, and star formation rates of high-redshift galaxies by modeling broad-band SEDs with stellar population synthesis. In order to…
The exact period determination of a multi-periodic variable star based on its luminosity time series data is believed a task requiring skill and experience. Thus the majority of available time series analysis techniques require human…
The large majority of extragalactic star cluster studies done to date have essentially used two or three-passband aperture photometry, combined with theoretical stellar population synthesis models, to obtain age estimates. The accuracy to…
Machine Learning (ML) is used to tackle various tasks, such as disease classification and prediction. The effectiveness of ML models relies heavily on having large amounts of complete data. However, healthcare data is often limited or…
Spectral type recognition is an important and fundamental step of large sky survey projects in the data reduction for further scientific research, like parameter measurement and statistic work. It tends out to be a huge job to manually…
The oscillation spectra of solar-type stars may in the not-too- distant future be used to constrain certain properties of the stars. The CD diagram of large versus small frequency separations is one of the powerful tools available to infer…