Related papers: Identifying Evolutionary Stages of Molecular Clump…
Massive star-forming regions with observed infall motions are good sites for studying the birth of massive stars. In this paper, 405 compact sources have been extracted from the APEX Telescope Large Area Survey of the Galaxy (ATLASGAL)…
Galaxy morphology reflects structural properties which contribute to understand the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented…
We describe the results of observations of galaxy clusters conducted with ISOCAM on-board the Infrared Space Observatory. Our research is aimed at understanding the processes driving galaxy evolution in dense environments, free from the…
Machine learning (ML) is quickly emerging as a powerful tool with diverse applications across an extremely broad spectrum of disciplines and commercial endeavors. Typically, ML is used as a black box that provides little illuminating…
Grids of stellar models are useful tools to derive the properties of stellar clusters, in particular young clusters hosting massive stars, and to provide information on the star formation process in various mass ranges. Because of their…
Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be…
Unsupervised feature learning has made great strides with contrastive learning based on instance discrimination and invariant mapping, as benchmarked on curated class-balanced datasets. However, natural data could be highly correlated and…
Context: Despite their profound effect on the universe, the formation of massive stars and stellar clusters remains elusive. In the past decade, compelling evidence has emerged that suggests Infrared Dark Clouds (IRDCs) may be precursors to…
The exploration of planetary bodies in our Solar system and beyond relies on the processing and interpretation of large, spatio-temporally inconsistent, and heterogeneous datasets. Recent advances in machine learning (ML) provide…
We propose a method for the unsupervised clustering of hyperspectral images based on spatially regularized spectral clustering with ultrametric path distances. The proposed method efficiently combines data density and geometry to…
In this work we used unsupervised machine learning methods in order to find possible clustering structures in superconducting materials data sets. We used the SuperCon database, as well as our own data sets complied from literature, in…
This work proposes a multiple machine learning method (MMLM) aiming to improve the accuracy and robustness in the analysis of star clusters. The MMLM performance is evaluated by applying it to the reanalysis of the old binary cluster…
The progenitors of high-mass stars and clusters are still challenging to recognise. Only unbiased surveys, sensitive to compact regions of high dust column density, can unambiguously reveal such a small population of particularly massive…
The diffuse starlight extending throughout massive galaxy clusters, known as intracluster light (ICL), has the potential to be read as a memoir of mass accretion: informative, individual, and yet imperfect. Here, we combine dark matter-only…
Recent surveys of dust continuum emission at sub-mm wavelengths have shown that filamentary molecular clouds are ubiquitous along the Galactic plane. These structures are inhomogeneous, with over-densities that are sometimes associated with…
The intracluster light (ICL) is a luminous component of galaxy clusters composed of stars that are gravitationally bound to the cluster potential but do not belong to the individual galaxies. Previous studies of the ICL have shown that its…
The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15,000 sq deg of the sky. Euclid is expected to detect ~12 billion astronomical sources,…
In this work, we aim to characterise high-mass clumps with infall motions. We selected 327 clumps from the Millimetre Astronomy Legacy Team 90-GHz (MALT90) survey, and identified 100 infall candidates. Combined with the results of He et al.…
(abridged) The old Star Cluster (SC) systems surrounding any sofar investigated galaxy represent a powerful tool for the understanding of the cosmological evolution of their host galaxies. Phases of enhanced cluster formation can be…
Morphological classification conveys abundant information on the formation, evolution, and environment of galaxies. In this work, we refine the two-step galaxy morphological classification framework ({\tt\string USmorph}), which employs a…