The LOFAR Two-metre Sky Survey: Deep Fields data release 1. V. Survey description, source classifications, and host galaxy properties

Monthly Notices of the Royal Astronomical Society Oxford University Press 523:2 (2023) 1729-1755

Authors:

Pn Best, R Kondapally, Wl Williams, Rk Cochrane, Kj Duncan, Cl Hale, P Haskell, K Małek, I McCheyne, Djb Smith, L Wang, A Botteon, M Bonato, M Bondi, G Calistro Rivera, F Gao, G Gürkan, Mj Hardcastle, Matthew J Jarvis, B Mingo, H Miraghaei, Lk Morabito, D Nisbet, I Prandoni, Hja Röttgering, J Sabater, T Shimwell, C Tasse, R van Weeren

Abstract:

Source classifications, stellar masses, and star-formation rates are presented for ≈80 000 radio sources from the first data release of the Low Frequency Array Two-metre Sky Survey (LoTSS) Deep Fields, which represents the widest deep radio survey ever undertaken. Using deep multi-wavelength data spanning from the ultraviolet to the far-infrared, spectral energy distribution (SED) fitting is carried out for all of the LoTSS Deep host galaxies using four different SED codes, two of which include modelling of the contributions from an active galactic nucleus (AGN). Comparing the results of the four codes, galaxies that host a radiative AGN are identified, and an optimized consensus estimate of the stellar mass and star-formation rate for each galaxy is derived. Those galaxies with an excess of radio emission over that expected from star formation are then identified, and the LoTSS Deep sources are divided into four classes: star-forming galaxies, radio-quiet AGN, and radio-loud high-excitation and low-excitation AGN. Ninety-five per cent of the sources can be reliably classified, of which more than two-thirds are star-forming galaxies, ranging from normal galaxies in the nearby Universe to highly-starbursting systems at z > 4. Star-forming galaxies become the dominant population below 150-MHz flux densities of ≈1 mJy, accounting for 90 per cent of sources at S150MHz ∼ 100 μJy. Radio-quiet AGN comprise ≈10 per cent of the overall population. Results are compared against the predictions of the SKADS and T-RECS radio sky simulations, and improvements to the simulations are suggested.

The DEHVILS survey overview and initial data release: high-quality near-infrared Type Ia supernova light curves at low redshift

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 522:2 (2023) 2478-2494

Authors:

Erik R Peterson, David O Jones, Daniel Scolnic, Bruno O Sánchez, Aaron Do, Adam G Riess, Sam M Ward, Arianna Dwomoh, Thomas de Jaeger, Saurabh W Jha, Kaisey S Mandel, Justin DR Pierel, Brodie Popovic, Benjamin M Rose, David Rubin, Benjamin J Shappee, Stephen Thorp, John L Tonry, R Brent Tully, Maria Vincenzi

No evidence for p- or d-wave dark matter annihilation from local large-scale structure

ArXiv 2304.10301 (2023)

Authors:

Andrija Kostić, Deaglan J Bartlett, Harry Desmond

The physics of indirect estimators of Lyman Continuum escape and their application to high-redshift JWST galaxies

(2023)

Authors:

Nicholas Choustikov, Harley Katz, Aayush Saxena, Alex Cameron, Julien Devriendt, Adrianne Slyz, Joki Rosdahl, Jeremy Blaizot, Leo Michel-Dansac

The CAMELS Project: Public Data Release

Astrophysical Journal Supplement Series 265:2 (2023)

Authors:

F Villaescusa-Navarro, S Genel, D Anglés-Alcázar, LA Perez, P Villanueva-Domingo, D Wadekar, H Shao, FG Mohammad, S Hassan, E Moser, ET Lau, LF Machado Poletti Valle, A Nicola, L Thiele, Y Jo, OHE Philcox, BD Oppenheimer, M Tillman, CH Hahn, N Kaushal, A Pisani, M Gebhardt, AM Delgado, J Caliendo, C Kreisch, KWK Wong, WR Coulton, M Eickenberg, G Parimbelli, Y Ni, UP Steinwandel, V La Torre, R Dave, N Battaglia, D Nagai, DN Spergel, L Hernquist, B Burkhart, D Narayanan, B Wandelt, RS Somerville, GL Bryan, M Viel, Y Li, V Irsic, K Kraljic, F Marinacci, M Vogelsberger

Abstract:

The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io.