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The CAMELS multifield data set: Learning the universe’s fundamental parameters with artificial intelligence
(IOP, 2022)
We present the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set
(CMD), a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of
cosmic ...
Inferring halo masses with graph neural networks
(Institute of Physics, 2022)
Understanding the halo–galaxy connection is fundamental in order to improve our knowledge on the nature and
properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions,
...
Mergers, starbursts, and quenching in the SIMBA simulation
(MNRAS, 2019-07-29)
We use the SIMBAcosmological galaxy formation simulation to investigate the relationship
between major mergers ( 4:1), starbursts, and galaxy quenching. Mergers are identified via
sudden jumps in stellar mass M∗ well ...
The physical nature of circumgalactic medium absorbers in SIMBA
(Oxford University Press, 2023)
We study the nature of the low-redshift circumgalactic medium (CGM) in the SIMBA cosmological simulations as traced by
ultraviolet absorption lines around galaxies in bins of stellar mass (M > 1010M) for star-forming, ...
Dusty starbursts masquerading as ultra-high redshift galaxies in jwst ceers observations
(American Astronomical Society, 2023)
Lyman-break galaxy (LBG) candidates at z 10 are rapidly being identified in James Webb Space Telescope
(JWST)/NIRCam observations. Due to the (redshifted) break produced by neutral hydrogen absorption of restframe UV ...
Redshift evolution of galaxy group X-ray properties in the SIMBA simulations
(Oxford University Press, 2023)
We examine the evolution of intragroup gas rest-frame X-ray scaling relations for group-sized haloes (M500 = 1012.3–1015 M)
in the SIMBA galaxy formation simulation. X-ray luminosity LX versus M500 shows increasing deviation ...