Related papers: Classifying Cool Dwarfs: Comprehensive Spectral Ty…
We investigate how feature selection algorithms can enable accurate, reference-free classification of materials using sparse-frequency terahertz (THz) reflection spectroscopy. Three classes of feature selection strategies are evaluated.…
We present the results of a study aiming at retrieving the fundamental parameters of M dwarfs from spectra secured with SPIRou, the near-infrared high-resolution spectropolarimeter installed at the Canada-France-Hawaii Telescope (CFHT), in…
We have calculated a grid of more than 700 model atmospheres valid for a wide range of parameters encompassing the coolest known M~dwarfs, M~subdwarfs and brown dwarf candidates: $1500\le \teff \le 4000\,$K, $3.5\le \log(g)\le 5.5$, and…
Recent developments in applied mathematics increasingly employ machine learning (ML)-particularly supervised learning-to accelerate numerical computations, such as solving nonlinear partial differential equations. In this work, we extend…
Mid-infrared data, including Spitzer warm-IRAC [3.6] and [4.5] photometry, is critical for understanding the cold population of brown dwarfs now being found, objects which have more in common with planets than stars. As effective…
Despite their large number in the Galaxy, M dwarfs remain elusive objects and the modeling of their photospheres has long remained a challenge (molecular opacities, dust cloud formation). Our objectives are to validate the BT-Settl model…
Low-mass objects are ubiquitous in our Galaxy. Their low temperature provides them with complex atmospheres characterised by the presence of strong molecular absorption bands which, together with their faintness, have made their accurate…
In this brief contribution, I touch on a subset of recent efforts in spectral and opacity modeling aimed at improving our understanding of brown dwarfs, L dwarfs, and T dwarfs. I discuss theoretical calculations of the alkali line profiles,…
We present a spectroscopic analysis of nearly 8000 late-type dwarfs in the Sloan Digital Sky Survey. Using the Halpha emission line as an activity indicator, we investigate the fraction of active stars as a function of spectral type and…
We present $Spitzer$ IRS 5--14 $\mu$m spectra and 16 $\mu$m and 22 $\mu$m photometry of the T2.5 companion to the $\sim$300 Myr-old G0V star HN Peg. We incorporate previous 0.8--5 $\mu$m observations to obtain the most comprehensive…
(Abridged) Low-mass stars have been recognised as promising targets in the search for rocky, small planets with the potential of supporting life. Doppler search programmes using high-resolution spectrographs like HARPS or HARPS-N are…
M dwarfs are key targets for high-resolution spectroscopic analyses due to a high incidence of these stars in the solar neighbourhood and their importance as exoplanetary hosts. Several methodological challenges make such analyses…
We present a machine learning search for local, low-mass galaxies ($z < 0.02$ and $10^6 M_\odot < M_* < 10^9 M_\odot$) using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We introduce the spectrally…
Deep neural networks (DNNs) suffer from the spectral bias, wherein DNNs typically exhibit a tendency to prioritize the learning of lower-frequency components of a function, struggling to capture its high-frequency features. This paper is to…
Despite their ability to represent highly expressive functions, deep learning models seem to find simple solutions that generalize surprisingly well. Spectral bias -- the tendency of neural networks to prioritize learning low frequency…
We present new JHKL'M' photometry on the MKO system for a large sample of L and T dwarfs identified from SDSS and 2MASS and classified according to the scheme of Geballe et al. (2002). We have compiled a sample of 105 L and T dwarfs that…
I review the optical and near-infrared spectral characteristics of the extremely cool dwarfs grouped under the new classification of type L. These include both very low-mass stars and brown dwarfs, and we discuss the likely temperature…
We apply the capabilities of machine learning (ML) to discern patterns in order to classify metal-poor stars. To do so, we train an ML model on a bank of nucleosynthesis calculations derived from hydrodynamic simulations for events such as…
A search of the Sloan Digital Sky Survey spectroscopic database has turned up 23 new ultra-cool subdwarfs, low-mass metal-poor stars of spectral subtype M 7.0 or later. Spectra from these red objects all show very strong molecular bands of…
We design a convolutional neural network (CNN) incorporating channel attention and spatial attention mechanisms to predict atmospheric parameters of hot subdwarfs. The experimental dataset comprises spectra at nine distinct signal-to-noise…