Related papers: Enhancing Ly{\alpha} Emitter Identification in HET…

We conducted a deep narrow-band imaging survey with the Subaru Prime Focus Camera on the Subaru Telescope and constructed a sample of Ly$\alpha$ emitters (LAEs) at z=2.53 in the UDS-CANDELS field where a sample of H$\alpha$ emitters (HAEs)…

This paper presents a comparison of several Convolutional Neural Network (CNN) models for extracting target signals in highly noisy measurement conditions. Four CNN architectures were investigated. The first comprises six consecutive…

The physical processes which make a galaxy a Lyman Alpha Emitter have been extensively studied for the past 25 years. However, the correlations between physical and morphological properties of galaxies and the strength of the Ly$\alpha$…

We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and associated statistics. The training dataset comprises 2000…

This paper establishes a data-driven modeling framework for lean Hydrogen (H2)-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particularly challenging since H2 molecules diffuse much faster than…

Electron energy-loss spectroscopy (EELS) coupled with scanning transmission electron microscopy (STEM) is a powerful technique to determine materials composition and bonding with high spatial resolution. Noise is often a limitation…

We study a sample of 14 spectroscopically confirmed Ly$\alpha$ Emitters (LAEs) in the late era of reionization (at redshift $z\approx6$) based on the JWST/NIRCam imaging dataset. These LAEs with high Ly$\alpha$ luminosity of $L$(Ly$\alpha$)…

Lyman-Alpha Emitters (LAEs) are star-forming galaxies with significant Ly$\alpha$ emission and are often used as tracers of large-scale structure at high redshift. We explore the relationship between the Ly$\alpha$ line profile and…

The recent discovery of enormous Ly$\alpha$ nebulae (ELANe), characterized by physical extents $>200$ kpc and Ly$\alpha$ luminosities $>10^{44}$ erg s$^{-1}$, provide a unique opportunity to study the intergalactic and circumgalactic medium…

DESI is a groundbreaking international project to observe more than 40 million quasars and galaxies over a 5-year period to create a 3D map of the sky. This map will enable us to probe multiple aspects of cosmology, from dark energy to…

We present the Lyman-$a$ (Lya) Luminosity Function (LF) at $2.05<z<3.75$, estimated from a sample of 67 Lya-emitter (LAE) candidates in the J-PAS Pathfinder surveys: miniJPAS and J-NEP. These two surveys cover a total effective area of…

High-impedance faults (HIF) are difficult to detect because of their low current amplitude and highly diverse characteristics. In recent years, machine learning (ML) has been gaining popularity in HIF detection because ML techniques learn…

We present a novel method to investigate cosmic reionization, using joint spectral information on high redshift Lyman Alpha Emitters (LAE) and quasars (QSOs). Although LAEs have been proposed as reionization probes, their use is hampered by…

Deep learning with a convolutional neural network (CNN) has been proved to be very effective in feature extraction and representation of images. For image classification problems, this work aim at finding which classifier is more…

Using the results from a previously developed Lyman Alpha/continuum production/transmission and dust enrichment model for Lyman Alpha Emitters (LAEs), based on cosmological SPH simulations, we assess the detectability of their…

We develop a novel deep contour detection algorithm with a top-down fully convolutional encoder-decoder network. Our proposed method, named TD-CEDN, solves two important issues in this low-level vision problem: (1) learning multi-scale and…

Encoder--decoder neural networks (EDNN) condense information most relevant to the output of the feedforward network to activation values at a bottleneck layer. We study the use of this architecture in emulation and interpretation of…

It is critical yet challenging for deep learning models to properly characterize uncertainty that is pervasive in real-world environments. Although a lot of efforts have been made, such as heteroscedastic neural networks (HNNs), little work…

Ly$\alpha$ emitters (LAEs) have now been discovered out to redshift $z=13$, and are valuable probes of the reionization history at redshifts beyond the reach of other currently available tracers. Most inferences of the neutral hydrogen…

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…