Related papers: Intercomparison of Brown Dwarf Model Grids and Atm…

This paper compares the performances of three supervised machine learning algorithms in terms of predictive ability and model interpretation on structured or tabular data. The algorithms considered were scikit-learn implementations of…

Wildfires present intricate challenges for prediction, necessitating the use of sophisticated machine learning techniques for effective modeling\cite{jain2020review}. In our research, we conducted a thorough assessment of various machine…

Ultra-cool brown dwarfs offer a unique window into understanding substellar atmospheric physics and chemistry. Their strong molecular absorption bands at infrared wavelengths, Jupiter-like radii, cool temperatures, and lack of complicating…

The determination of atmospheric parameters of white dwarf stars (WDs) is crucial for researches on them. Traditional methodology is to fit the model spectra to observed absorption lines and report the parameters with the lowest $\chi ^2$…

We propose a machine-learning-based technique to determine the number density of radio sources as a function of their flux density, for use in next-generation radio surveys. The method uses a convolutional neural network trained on…

In this paper, we review the current theory of very low mass stars model atmospheres including the coolest known M~dwarfs, M~subdwarfs, and brown dwarfs, i.e. T$_{eff} \leq 5,000 $K and $-2.0 \le [M/H] \le +0.0$. We discuss ongoing efforts…

We fit a sample of 49 R=6000 NIR (0.9 - 2.5 micron) T dwarf spectra obtained with Magellan's FIRE spectrograph with two different atmospheric model sets to compare the derived physical parameters such as Teff, log g, cloud opacity, and…

We test state-of-the-art model atmospheres for young very low-mass stars and brown dwarfs in the infrared, by comparing the predicted synthetic photometry over 1.2-24 {\mu}m to the observed photometry of M-type spectral templates in…

The construction and implementation of atmospheric model grids is a popular tool in exoplanet characterisation. These typically vary a number of parameters linearly, containing one model for every combination of parameter values. Here we…

In this paper we present a catalogue of 11,745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3…

We present an analysis of low-resolution infrared spectra for 25 brown dwarf candidates in the NGC 1333 molecular cloud. Candidates were chosen on the basis of their association with the high column density cloud core, and near-infrared…

We conduct a statistical analysis of a combined sample of direct imaging data, totalling nearly 250 stars. The stars cover a wide range of ages and spectral types, and include five detections ($\kappa$ And b, two $\sim$60 M$_{\rm J}$ brown…

Brown Dwarf atmosphere are a chemically extremely rich, one example being the formation of clouds driven by the phase-non-equilibrium of the atmospheric gas. Cloud formation modelling is an integral part of any atmosphere simulation used to…

Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each…

Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are appealing due to their thermodynamic consistency with the…

We build random forests models to predict elastic properties and mechanical hardness of a compound, using only its chemical formula as input. The model training uses over 10,000 target compounds and 60 features based on stoichiometric…

We developed a simple, physical and self-consistent cloud model for brown dwarfs and young giant exoplanets. We compared different parametrisations for the cloud particle size, by either fixing particle radii, or fixing the mixing…

The majority of brown dwarfs show some level of photometric or spectro-photometric variability in different wavelength ranges. This variability allow us to trace the 3D atmospheric structures of variable brown dwarfs and directly-imaged…

Wildfire forecasting problems usually rely on complex grid-based mathematical models, mostly involving Computational fluid dynamics(CFD) and Celluar Automata, but these methods have always been computationally expensive and difficult to…

Biophysical models offer valuable insights into climate-phenology relationships in both natural and agricultural settings. However, there are substantial structural discrepancies across models which require site-specific recalibration,…