Related papers: Enhancing Ly{\alpha} Emitter Identification in HET…
The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is an unbiased, massively multiplexed spectroscopic survey, designed to measure the expansion history of the universe through low-resolution ($R\sim750$) spectra of Lyman-Alpha…
The Hobby-Eberly Telescope (HET) Dark Energy Experiment (HETDEX) is undertaking a blind wide-field low-resolution spectroscopic survey of 540 square degrees of sky to identify and derive redshifts for a million Lyman-alpha emitting galaxies…
We present extended Lyman-{\alpha} (Ly{\alpha}) emission out to 800 kpc of 1034 [O III]-selected galaxies at redshifts 1.9<z<2.35 using the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The locations and redshifts of the galaxies…
Context: Narrow-band surveys for Ly-alpha emitters (LAEs) is a powerful tool in detecting high, and very high, redshift galaxies. Even though samples are growing at redshifts z = 3 - 6, the nature of these galaxies is still poorly known.…
We present a spectroscopic survey of Ly$\alpha$ emitters (LAEs) at $z\approx5.7$ using the multi-object spectrograph M2FS on the Magellan Clay telescope. This is part of a high-redshift galaxy survey carried out in several well-studied deep…
We describe the results of a new, wide-field survey for z=3.1 Ly-alpha emission-line galaxies (LAEs) in the Extended Chandra Deep Field South (ECDF-S). By using a nearly top-hat 5010 Angstrom filter and complementary broadband photometry…
We present Ly$\alpha$ and ultraviolet-continuum (UV) luminosity functions (LFs) of galaxies and active galactic nuclei (AGN) at $z=2.0-3.5$ determined by the un-targetted optical spectroscopic survey of the Hobby-Eberly Telescope Dark…
We apply a Machine Learning technique known as Convolutional Denoising Autoencoder to denoise synthetic images of state-of-the-art radio telescopes, with the goal of detecting the faint, diffused radio sources predicted to characterise the…
Stellar population measurements in integral field unit surveys are often limited by low signal-to-noise ratios (S/N) in low-surface-brightness spaxels. Using controlled synthetic experiments, we test whether deep-learning-based denoising…
We investigate the physical properties of Lyman-alpha emitters (LAEs) and non-Lyman-alpha emitters (non-LAEs) at z$\sim$4.8--9.6 via a stacking analysis of 253 JWST/NIRSpec spectra of galaxies observed as part of the JWST Advanced Deep…
Laser absorption spectroscopy (LAS) is a well-established technique for non-intrusive measurement of gas species in combustion and atmospheric environments, but conventional methods struggle with multi-species mixtures under dynamic or…
The ubiquity and relative ease of discovery make $2\lesssim z\lesssim 5$ Ly$\alpha$ emitting galaxies (LAEs) ideal tracers for cosmology. In addition, because Ly$\alpha$ is a resonance line, but frequently observed at large equivalent…
Being the most prominent HI line, Ly$\alpha$ permeates the cosmic web in emission. Despite its potential as a cosmological probe, its detection on large scales remains elusive. We present a new methodology to perform Ly$\alpha$ intensity…
Ly$\alpha$ Emitters (LAEs) may represent an important galaxy population in the low mass regime. We present our deep narrowband imaging surveys in the COSMOS and ECDF-S fields and study the properties of LAEs at $z=2.23\pm0.03$. The…
We present a novel dehazing and low-light enhancement method based on an illumination map that is accurately estimated by a convolutional neural network (CNN). In this paper, the illumination map is used as a component for three different…
The Ly-alpha luminosity function (LF) of high-redshift Ly-alpha emitters (LAEs) is one of the few observables of the re-ionization epoch accessible to date with 8-10 m class telescopes. The evolution with redshift allows one to constrain…
Lyman Alpha Emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrow-band photometric surveys. In ground-based spectroscopy, it can be difficult to distinguish the sharp LAE peak from…
Semantic segmentation of electron microscopy (EM) is an essential step to efficiently obtain reliable morphological statistics. Despite the great success achieved using deep convolutional neural networks (CNNs), they still produce coarse…
Single-Molecule Localization Microscopy (SMLM) has expanded our ability to visualize subcellular structures but is limited in its temporal resolution. Increasing emitter density will improve temporal resolution, but current analysis…
The extreme learning machine (ELM) method can yield highly accurate solutions to linear/nonlinear partial differential equations (PDEs), but requires the last hidden layer of the neural network to be wide to achieve a high accuracy. If the…