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Strong gravitational lensing is a powerful tool to provide constraints on galaxy mass distributions and cosmological parameters, such as the Hubble constant, $H_0$. Nevertheless, inference of such parameters from images of lensing systems…

We present predictions for the outcome of deep galaxy surveys with the $James$ $Webb$ $Space$ $Telescope$ ($JWST$) obtained from a physical model of galaxy formation in $\Lambda$CDM. We use the latest version of the GALFORM model, embedded…

星系天体物理 · 物理学 2017-12-27 William Cowley , Carlton Baugh , Shaun Cole , Carlos Frenk , Cedric Lacey

Identifying active galactic nuclei (AGN) is extremely important for understanding galaxy evolution and its connection with the assembly of supermassive black holes (SMBH). With the advent of deep and high angular resolution imaging surveys…

星系天体物理 · 物理学 2026-02-18 Berta Margalef-Bentabol , Lingyu Wang , Antonio La Marca , Vicente Rodriguez-Gomez

The James Webb Space Telescope (JWST) will enable the detection of optical emission lines in galaxies spanning a broad range of luminosities out to redshifts z>10. Measurements of key galaxy properties, such as star formation rate and…

We present the first James Webb Space Telescope/NIRCam-led determination of $7<z<9$ galaxy properties based on broadband imaging from 0.8 to 5~$\mathrm{\mu m}$ as part of the GLASS-JWST Early Release Science program. This is the deepest…

We present a new method of predicting the ages of galaxies using a machine learning (ML) algorithm with the goal of providing an alternative to traditional methods. We aim to match the ability of traditional models to predict the ages of…

星系天体物理 · 物理学 2024-06-14 Laura. J. Hunt , Kevin. A. Pimbblet , David. M. Benoit

A new approach to estimating photometric redshifts - using Artificial Neural Networks (ANNs) - is investigated. Unlike the standard template-fitting photometric redshift technique, a large spectroscopically-identified training set is…

天体物理学 · 物理学 2009-11-07 Andrew E. Firth , Ofer Lahav , Rachel S. Somerville

We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract…

星系天体物理 · 物理学 2020-04-28 A. Ćiprijanović , G. F. Snyder , B. Nord , J. E. G. Peek

Galaxy groups are essential for studying the distribution of matter on a large scale in redshift surveys and for deciphering the link between galaxy traits and their associated halos. In this work, we propose a widely applicable method for…

宇宙学与河外天体物理 · 物理学 2025-04-03 Juntao Ma , Jie Wang , Tianxiang Mao , Hongxiang Chen , Yuxi Meng , Xiaohu Yang , Qingyang Li

Galaxies are theorized to form and co-evolve with their dark matter halos, such that their stellar masses and halo masses should be well-correlated. However, it is not known whether other observable galaxy features, such as their…

宇宙学与河外天体物理 · 物理学 2024-07-19 Austin J. Larson , John F. Wu , Craig Jones

The first billion years of the Universe is a pivotal time: stars, black holes (BHs) and galaxies form and assemble, sowing the seeds of galaxies as we know them today. Detecting, identifying and understand- ing the first galaxies and BHs is…

星系天体物理 · 物理学 2017-11-15 Marta Volonteri , Amy Reines , Hakim Atek , Daniel P. Stark , Maxime Trebitsch

We present synthetic observations for the first generations of galaxies in the Universe and make predictions for future deep field observations for redshifts greater than 6. Due to the strong impact of nebular emission lines and the…

天体物理仪器与方法 · 物理学 2017-06-20 Kirk S. S. Barrow , John H. Wise , Michael L. Norman , Brian W. O'Shea , Hao Xu

We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics using reinforcement learning. The most important halo…

星系天体物理 · 物理学 2021-07-14 Benjamin P. Moster , Thorsten Naab , Magnus Lindström , Joseph A. O'Leary

We present a systematic search for broad-line active galactic nuclei (AGNs) in the ALPINE-CRISTAL-JWST sample of 18 star-forming galaxies ($M_\star>10^{9.5}~M_{\odot}$) at redshifts $z=4.4-5.7$. Using JWST/NIRSpec IFU, we identify 7 AGN…

At high redshift, due to both observational limitations and the variety of galaxy morphologies in the early universe, measuring galaxy structure can be challenging. Non-parametric measurements such as the CAS system have thus become an…

星系天体物理 · 物理学 2021-09-08 C. Tohill , L. Ferreira , C. J. Conselice , S. P. Bamford , F. Ferrari

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will produce several billion photometric redshifts (photo-$z$'s), enabling cosmological analyses to select a subset of galaxies with the most accurate photo-$z$. We…

宇宙学与河外天体物理 · 物理学 2021-12-08 Adam Broussard , Eric Gawiser

The long-anticipated James Webb Space Telescope (JWST) will be able to directly detect large samples of galaxies at very high redshift. Using the well-established, computationally efficient Santa Cruz semi-analytic model, with recently…

We explore spectroscopic and photometric methods for identifying high-redshift galaxies containing an Active Galactic Nucleus (AGN) with JWST observations. After demonstrating the limitations of standard optical methods, which appear…

Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of…

天体物理仪器与方法 · 物理学 2022-08-24 Biprateep Dey , Brett H. Andrews , Jeffrey A. Newman , Yao-Yuan Mao , Markus Michael Rau , Rongpu Zhou

The accuracy of galaxy photometric redshift (photo-$z$) can significantly affect the analysis of weak gravitational lensing measurements, especially for future high-precision surveys. In this work, we try to extract photo-$z$ information…

宇宙学与河外天体物理 · 物理学 2022-04-11 Xingchen Zhou , Yan Gong , Xian-Min Meng , Ye Cao , Xuelei Chen , Zhu Chen , Wei Du , Liping Fu , Zhijian Luo
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