The ESA Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF) project is an automated spectral feature fitting routine developed within the SPIRE instrument team to extract all prominent spectral features from all publicly available SPIRE FTS observations. In this work, we

Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called "big data", which will require the deployment of accurate and efficient machine-learning (ML) methods. In this work, we analyze the miniJPAS survey, which observed about ∼1 deg 2 of the AEGIS field with 56 narrow-band filters and 4 ugri broad-band

Aims: Large radial velocity variations in the LAMOST spectra of giant stars have been used to infer the presence of unseen companions. Some of them have been proposed as possible black hole candidates. We test this selection by investigating the classification of the one candidate that has a known X-ray counterpart (UCAC4 721-037069). Methods: We

Modelling dust formation in single stars evolving through the carbon-star stage of the asymptotic giant branch (AGB) reproduces well the mid-infrared colours and magnitudes of most of the C-rich sources in the Large Magellanic Cloud (LMC), apart from a small subset of extremely red objects (EROs). An analysis of the spectral energy distributions of

We use deep learning to explore the nature of observed giant clumps in high-redshift disc galaxies, based on their identification and classification in cosmological simulations. Simulated clumps are detected using the 3D gas and stellar densities in the VELA zoom-in cosmological simulation suite, with ${\sim}25\ \rm {pc}$ maximum resolution