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We present a JWST imaging survey of I Zw 18, the archetypal extremely metal-poor, star-forming (SF), blue compact dwarf galaxy. With an oxygen abundance of only $\sim$3% $Z_{\odot}$, it is among the lowest-metallicity systems known in the…
With their high angular resolutions of 30--100 mas, large fields of view, and complex optical systems, imagers on next-generation optical/near-infrared space observatories, such as the Near-Infrared Camera (NIRCam) on the James Webb Space…
The study of faint solar system objects is a promising avenue for understanding the origin and evolution of planetary systems. However, such objects are difficult to detect in conventional surveys. Here we introduce heliostack, an algorithm…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
The James Webb Space Telescope (JWST) has enabled the discovery of a significant population of galaxies at z > 10. Our understanding of the astrophysical properties of these galaxies relies on fitting templates developed using models…
Digital synoptic sky surveys pose several new object classification challenges. In surveys where real-time detection and classification of transient events is a science driver, there is a need for an effective elimination of…
Dusty stellar point sources are a significant stage in stellar evolution and contribute to the metal enrichment of galaxies. These objects can be classified using photometric and spectroscopic observations with color-magnitude diagrams…
Next generation observatories will enable us to study the first billion years of our Universe in unprecedented detail. Foremost among these are 21-cm interferometry with the HERA and the SKA, and high-$z$ galaxy observations with the James…
The Chinese Space Station Survey Telescope (CSST) aims to map the universe across an unprecedented dynamic range of stellar densities, spanning from extragalactic voids to the crowded Galactic center (e.g. a few stars and galaxies in the…
We aim to develop a model-driven deep learning approach to age determination, by training neural networks on stellar evolutionary grids. Contrary to the usual data-driven deep learning approach of using prior age estimates as training data,…
Deep learning based object detection has achieved great success. However, these supervised learning methods are data-hungry and time-consuming. This restriction makes them unsuitable for limited data and urgent tasks, especially in the…
Studies in the past few decades have investigated young stellar object evolution based on their spectral energy distribution (SED). The SED is heavily influenced not only by evolutionary stage, but also the morphology of the young star.…
Context. In modern astronomy, machine learning has proved to be efficient and effective to mine the big data from the newesttelescopes. Spectral surveys enable us to characterize millions of objects, while long exposure time observations…
The James Webb Space Telescope (JWST) is a large (6.6m), cold (50K), infrared-optimized space observatory that will be launched early in the next decade. The observatory will have four instruments: a near-infrared camera, a near-infrared…
The Mid-Infrared Instrument (MIRI) for the {\em James Webb Space Telescope} (JWST) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich {\em Spitzer}-IRS spectroscopic data-set and…
Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such…
We have entered the era of the James Webb Space Telescope (JWST). We use the first JWST transmission spectrum of the hot Saturn-mass exoplanet, WASP-39 b, obtained with the NIRSpec instrument in the 3-5 $\mu$m range to investigate (a) what…
We present the serendipitous discovery of a late T-type brown dwarf candidate in JWST NIRCam observations of the Early Release Science Abell 2744 parallel field. The discovery was enabled by the sensitivity of JWST at 4~$\mu$m wavelengths…
Contemporary exoplanet and brown dwarf atmospheric research relies heavily on retrieval frameworks to recover thermal and chemical properties and perform model comparison in an observational data-driven approach. However, the computational…
The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several million celestial sources. In the case of variable stars, supervised learning…