Massive galaxies at z>3.5 assembled stars earlier than theoretical models predict and exhibit gray dust attenuation, especially at the highest masses.
The EAGLE simulations of galaxy formation: Public release of particle data
6 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
This manual accompanies the release of the particle data for 24 simulations of the EAGLE suite of cosmological hydrodynamical simulations of galaxy formation by the virgo consortium. It describes how to download these snapshots and how to extract datasets from them, emphasising the meaning of variables, and their units. We provide examples for extracting the particle data in python. This data release complements our earlier release of numerous integrated properties of the galaxies in EAGLE through an SQL relational database. This database has been updated to include the additional simulations that are part of the present data release. Scientists wanting to use EAGLE may find it useful to first investigate whether their analysis can be performed using the database, before accessing the particle data. The particles in the snapshot files are indexed by a peano-hilbert key. This allows for an eased extraction of simply connected spatial volumes, without needing to read the entire snapshot. This makes it possible to analyse many aspects of galaxies using modest computing resources, even when using EAGLE simulations with large numbers of particles. A reading routine is provided to simplify this process.
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ARTEMIS and EAGLE simulations classify L* galaxies by central BH-to-stellar-mass ratio and trace how merger history drives divergence in BH growth, star formation, and morphology, offering an explanation for the observed scatter and for MW/M31 differences.
TNG100 and EAGLE hydrodynamical simulations underproduce faint compact galaxies at z>3 relative to CANDELS observations even after forward modeling and completeness corrections, with the mismatch linked to both detection effects and simulation physics.
Filament stacking outperforms pair stacking for HI detection in cosmic filaments, reaching column densities of 10^16-10^17 cm^-2 post-masking in simulations while pair stacking is heavily suppressed.
Disc galaxies inhibit supermassive black hole growth by preserving rotational support in central gas, while mergers in ellipticals disrupt this support and enable rapid accretion.
Simulations from COSMOS2020 show masking recovers [CII] above 300 GHz in ideal conditions but noise prevents useful S/N until near the end of 2000-hour observations.
citing papers explorer
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Massive Galaxies Form Early and Gray: Stellar Assembly and Dust Attenuation at $\mathbf{z>3.5}$ from CAPERS
Massive galaxies at z>3.5 assembled stars earlier than theoretical models predict and exhibit gray dust attenuation, especially at the highest masses.
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Co-evolution of Supermassive Black Holes and their Host L* galaxies: implications for Milky Way and M31
ARTEMIS and EAGLE simulations classify L* galaxies by central BH-to-stellar-mass ratio and trace how merger history drives divergence in BH growth, star formation, and morphology, offering an explanation for the observed scatter and for MW/M31 differences.
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Probing the faint end of simulated galaxy counts at z>3
TNG100 and EAGLE hydrodynamical simulations underproduce faint compact galaxies at z>3 relative to CANDELS observations even after forward modeling and completeness corrections, with the mismatch linked to both detection effects and simulation physics.
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Detection of HI filament: Pair Stacking vs. Filament Stacking
Filament stacking outperforms pair stacking for HI detection in cosmic filaments, reaching column densities of 10^16-10^17 cm^-2 post-masking in simulations while pair stacking is heavily suppressed.
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Galaxy discs regulate the growth of supermassive black holes
Disc galaxies inhibit supermassive black hole growth by preserving rotational support in central gas, while mergers in ellipticals disrupt this support and enable rapid accretion.
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Testing masking effectiveness using multi-line image cubes based on COSMOS2020 for [CII] line intensity mapping at $z_{[CII]} > 3.5$
Simulations from COSMOS2020 show masking recovers [CII] above 300 GHz in ideal conditions but noise prevents useful S/N until near the end of 2000-hour observations.