Related papers: Random Forest Classification of Stars in the Galac…
The supermassive black hole candidate at the Galactic Center is surrounded by a parsec-scale star cluster, which contains a number of early type stars. The presence of such stars has been called a "paradox of youth" as star formation in the…
We quantify the effects of \emph{morphological k-correction} at $1<z<2$ by comparing morphologies measured in the K and I-bands in the COSMOS area. Ks-band data have indeed the advantage of probing old stellar populations for $z<2$,…
(abridged) In this paper we revisit the problem of inferring the innermost structure of the Milky Way's nuclear star cluster via star counts, to clarify whether it displays a core or a cusp around the central black hole. Through image…
Lopsided galaxies are late-type galaxies with a non-axisymmetric disk due to an uneven distribution of their stellar mass. Despite being a relatively common perturbation, several questions regarding its origin and the information that can…
(abridged) Mass loss is a key parameter in the evolution of massive stars, with discrepancies between theory and observations and with unknown importance of the episodic mass loss. To address this we need increased numbers of classified…
A random forest is a popular tool for estimating probabilities in machine learning classification tasks. However, the means by which this is accomplished is unprincipled: one simply counts the fraction of trees in a forest that vote for a…
The Magellanic Clouds (MCs) are excellent locations to study stellar dust emission and its contribution to galaxy evolution. Through spectral and photometric classification, MCs can serve as a unique environment for studying stellar…
We present a metallicity analysis of 83 late-type giants within the central 1 pc of the Milky Way. K-band spectroscopy of these stars were obtained with the medium-spectral resolution integral-field spectrograph NIFS on Gemini North using…
The center of our galaxy is home to a massive black hole, SgrA*, and a nuclear star cluster containing stellar populations of various ages. While the late type stars may be too old to have retained memory of their initial orbital…
To identify member populations of IC 1396, we employ the random forest (RF) classifier of machine learning technique. Random forest classifier is an ensemble of individual decision trees suitable for large, high-dimensional datasets. The…
We present a classification of galaxies in the Pan-STARRS1 (PS1) 3$\pi$ survey based on their recent star formation history and morphology. Specifically, we train and test two Random Forest (RF) classifiers using photometric features…
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…
The paper describes an application of the tree classification method Random Forest (RF), as used in the analysis of data from the ground-based gamma telescope MAGIC. In such telescopes, cosmic gamma-rays are observed and have to be…
We present a population analysis of the nuclear stellar cluster of the Milky Way based on adaptive optics narrow band spectral energy distributions. We find strong evidence for the lack of a stellar cusp and a similarity of the late type…
In order to understand stellar evolution, it is crucial to efficiently determine stellar surface rotation periods. An efficient tool to automatically determine reliable rotation periods is needed when dealing with large samples of stellar…
We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…
Information on the spectral types of stars is of great interest in view of the exploitation of space-based imaging surveys. In this article, we investigate the classification of stars into spectral types using only the shape of their…
The discovery of exoplanets has expanded our understanding of planetary systems and opened new avenues for astronomical research. In this study, we present a machine learning (ML) framework for exoplanet identification using a time-series…
We present the results of the first systematic search for spectroscopic binaries within the central 2 x 3 arcsec$^2$ around the supermassive black hole at the center of the Milky Way galaxy. This survey is based primarily on over a decade…
While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ~ 22 mag…