相关论文: Emission Line Predictions for Mock Galaxy Catalogu…

New surveys such as ESA's Euclid mission are planned to map with unprecedented precision the large-scale structure of the Universe by measuring the 3D positions of tens of millions of galaxies. It is necessary to develop theoretically…

In this paper we discuss an application of machine learning based methods to the identification of candidate AGN from optical survey data and to the automatic classification of AGNs in broad classes. We applied four different machine…

We present the {\sc warpfield} emission predictor, {\sc warpfield-emp}, which couples the 1D stellar feedback code {\sc warpfield} with the {\sc cloudy} \hii region/PDR code and the {\sc polaris} radiative transfer code, in order to make…

The study of strong-lensing systems conventionally involves constructing a mass distribution that can reproduce the observed multiply-imaging properties. Such mass reconstructions are generically non-unique. Here, we present an alternative…

A numerous population of weak line galaxies (WLGs) is often left out of statistical studies on emission line galaxies (ELGs) due to the absence of an adequate classification scheme, since classical diagnostic diagrams, like [OIII]/Hb vs…

This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…

Modeling of strongly gravitationally lensed galaxies is often required in order to use them as astrophysical or cosmological probes. With current and upcoming wide-field imaging surveys, the number of detected lenses is increasing…

Emission line galaxies (ELGs) are now the preeminent tracers of large-scale structure at z>0.8 due to their high density and strong emission lines, which enable accurate redshift measurements. However, relatively little is known about ELG…

Determining the distribution of redshifts of galaxies observed by wide-field photometric experiments like the Dark Energy Survey is an essential component to mapping the matter density field with gravitational lensing. In this work we…

We analyze the absorption and emission-line profiles produced by a set of simple, cool gas wind models motivated by galactic-scale outflow observations. We implement monte carlo radiative transfer techniques that track the propagation of…

We develop a prescription for estimating the interstellar medium oxygen abundances of distant star-forming galaxies using the ratio EWR_{23} formed from the equivalent widths of the [O II] 3727, [O III] 4959,5007 and Hbeta nebular emission…

Infrared fine-structure emission lines from trace metals are powerful diagnostics of the interstellar medium in galaxies. We explore the possibility of studying the redshifted far-IR fine-structure line emission using the three-dimensional…

For the extremely bright lensed galaxy SDSS J1723+3411 at z=1.3293 , we analyze spatially integrated MMT, Keck, and Hubble Space Telescope spectra that fully cover the rest-frame wavelength range of 1400 to 7200 Angstroms. We also analyze…

We study galaxies in JADES Deep to study the evolution of the ionising photon production efficiency, $\xi_{\rm{ion}}$, observed to increase with redshift. We estimate $\xi_{\rm{ion}}$ for a sample of 677 galaxies at $z \sim 4 - 9$ using…

Extreme Emission Line Galaxies (EELGs) stand as remarkable objects due to their extremely metal poor environment and intense star formation. Considered as local analogues of high-redshift galaxies in the peak of their star-forming activity,…

False-positive emission-line detections bias our understanding of astronomical sources; for example, falsely identifying $z\sim3-4$ passive galaxies as $z>10$ galaxies leads to incorrect number counts and flawed tests of cosmology. In this…

This is the third in a series of papers that develop a new and flexible model to predict weak-lensing (WL) peak counts, which have been shown to be a very valuable non-Gaussian probe of cosmology. In this paper, we compare the cosmological…

We present a novel graph-based machine learning classifier for identifying the dark matter cosmic web environments of galaxies. Large galaxy surveys offer comprehensive statistical views of how galaxy properties are shaped by large-scale…

We present an automatic method based on machine-learning convolutional neural network (CNN) architecture to detect Lyman alpha emitters (LAE) hidden in the Data Release 1 spectroscopic dataset of the Dark Energy Spectroscopic Instrument…

Precision cosmology requires accurate galaxy redshifts, but next generation optical surveys will observe unprecedented numbers of resolved galaxies, placing strain on the amount of spectroscopic follow-up required. We show how useful…