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Winds versus jets: a comparison between black hole feedback modes in simulations of idealized galaxy groups and clusters (2023)
Journal Article

Using the SWIFT simulation code, we compare the effects of different forms of active galactic nuclei (AGNs) feedback in idealized galaxy groups and clusters. We first present a physically motivated model of black hole (BH) spin evolution and a numeri... Read More about Winds versus jets: a comparison between black hole feedback modes in simulations of idealized galaxy groups and clusters.

The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys (2023)
Journal Article

We introduce the Virgo Consortium’s FLAMINGO suite of hydrodynamical simulations for cosmology and galaxy cluster physics. To ensure the simulations are sufficiently realistic for studies of large-scale structure, the subgrid prescriptions for stella... Read More about The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys.

The buildup of galaxies and their spheroids: The contributions of mergers, disc instabilities, and star formation (2022)
Journal Article

We use the GALFORM semi-analytical model of galaxy formation and the Planck-Millennium simulation to investigate the origins of stellar mass in galaxies and their spheroids. We compare the importance of mergers and disc instabilities, as well as the... Read More about The buildup of galaxies and their spheroids: The contributions of mergers, disc instabilities, and star formation.

Efficient exploration and calibration of a semi-analytical model of galaxy formation with deep learning (2021)
Journal Article

We implement a sample-efficient method for rapid and accurate emulation of semi-analytical galaxy formation models over a wide range of model outputs. We use ensembled deep learning algorithms to produce a fast emulator of an updated version of the G... Read More about Efficient exploration and calibration of a semi-analytical model of galaxy formation with deep learning.

Determining the systemic redshift of Lyman α emitters with neural networks and improving the measured large-scale clustering (2020)
Journal Article

We explore how to mitigate the clustering distortions in Lyman α emitter (LAE) samples caused by the misidentification of the Lyman α (⁠Lyα⁠) wavelength in their Lyα line profiles. We use the Lyα line profiles from our previous LAE theoretical model... Read More about Determining the systemic redshift of Lyman α emitters with neural networks and improving the measured large-scale clustering.

Qwind code release. A non-hydrodynamical approach to modelling line-driven winds in active galactic nuclei (2020)
Journal Article

UV line driven winds may be an important part of the AGN feedback process, but understanding their impact is hindered by the complex nature of the radiation hydrodynamics. Instead, we have taken the approach pioneered by Risaliti & Elvis, calculating... Read More about Qwind code release. A non-hydrodynamical approach to modelling line-driven winds in active galactic nuclei.