arXiv subjects

Harry George Chittenden

Publications and source records attributed to Harry George Chittenden.

5 recordsLinked to original sources

arXiv2026

On the unique evolutionary mechanisms of massive quiescent galaxies in the epoch of reionisation

We investigate the evolutionary histories of a population of high mass, high redshift, quiescent galaxies in the cosmohydrodynamical simulation Thesan, studying the characteristic properties of their haloes and environments over the epoch of reionisation. Thesan employs a modified version of the Arepo moving-mesh code utilised in IllustrisTNG, which incorporates on-the-fly radiative transfer to couple haloes and galaxies with the evolving radiation field. Thesan exhibits nine massive quiescent galaxies at $z=5.5$, in a $(95.5 \text{cMpc})^3$ volume, with no counterpart in IllustrisTNG. A numerical issue in the simulation reduces AGN feedback efficiency by a factor of 25 while enhancing accretion rates, creating a regime of suppressed feedback. We find their stellar mass assembles rapidly through smooth halo accretion in dense environments, particularly from massive neighbouring structures, while their early-forming haloes develop fast-growing potential wells hosting massive black holes. This suppressed feedback allows prolonged black hole growth before eventual kinetic-mode quenching, providing insight into galaxy evolution under weakened AGN regulation. We find that megaparsec-scale overdensities and halo masses continue growing after quenching, suggesting these galaxies will reside in some of the largest haloes and densest regions of space by $z=6$. With massive quiescent galaxies found in JWST data, the identification of such galaxies in Thesan enables isolation of halo and environmental conditions most conducive to their evolution under this suppressed feedback regime, guiding future deep surveys and N-body simulation studies of analogous systems.

astro-ph.GA↗

arXiv2025

Connecting Environment, Star Formation History, and Morphology of Massive Quiescent Galaxies at $3<z<4$ with JWST

We present the morphological properties of 17 spectroscopically confirmed massive quiescent galaxies ($10.2 < \log(M_{\ast}/M_{\odot}) < 11.2$) at $3.0 < z < 4.3$, observed with JWST/NIRSpec and NIRCam. Using Sérsic profile fits to F277W and F444W imaging, we derive the size-mass relation and find typical sizes of $\sim$0.6--0.8 kpc at $M_{\ast} = 5 \times 10^{10}~M_{\odot}$, consistent with $\sim$7$\times$ growth from $z \sim 4$ to the present, including $\sim$2$\times$ by $z \sim 2$. We find tentative evidence that formation history and morphology jointly influence galaxy sizes: late-forming bulge-dominated galaxies appear more compact by $\sim$0.2-0.3 dex relative to the expected relation, while late-forming disk-dominated galaxies are larger. Using a random forest regressor, we identify local environmental density, quantified by $\log(1+δ^{\prime}_{3})$ from the three nearest neighbors, as the strongest predictor of bulge-to-total ratio ($B/T$), which spans 0.25-1. In the {\sc IllustrisTNG} simulation, the ex-situ stellar mass fraction ($f_{\ast,\mathrm{ex\text{-}situ}}$) -- a proxy for mergers -- is instead the dominant predictor of $B/T$. Galaxies with high $B/T$ in dense environments show bursty star formation and short quenching timescales ($\lesssim0.4$ Gyr), consistent with bulge growth through merger-driven starbursts; in simulations, such systems exhibit elevated ex-situ fractions ($\sim$20-30%). In contrast, some high-$B/T$ galaxies in intermediate-density environments have low ex-situ fractions, suggesting that additional processes -- such as violent disk instabilities -- also contribute. These results point to multiple bulge growth pathways at high redshift, unified by rapid gas accretion, central starbursts, and AGN feedback, as predicted by cosmological simulations.

astro-ph.GA↗

arXiv2025

Optimised neural network predictions of galaxy formation histories using semi-stochastic corrections

We present a novel methodology to improve predictions of galaxy formation histories by incorporating semi-stochastic corrections to account for short-timescale variability. Our paper addresses limitations in existing models that capture broad trends in galaxy evolution, but fail to reproduce the bursty nature of star formation and chemical enrichment, resulting in inaccurate predictions of key observables such as stellar masses, optical spectra, and colour distributions. We introduce a simple technique to add a stochastic components by utilizing the power spectra of galaxy formation histories. We justify our stochastic approach by studying the correlation between the phases of the halo mass assembly and star-formation histories in the IllustrisTNG simulation, and we find that they are correlated only on timescales longer than 6 Gyr, with a strong dependence on galaxy type. We demonstrate our approach by applying our methodology to the predictions on a neural network trained on hydrodynamical simulations, which failed to recover the high-frequency components of star-formation and chemical enrichment histories. Our methodology successfully recovers realistic variability in galaxy properties at short timescales. It significantly improves the accuracy of predicted stellar masses, metallicities, spectra, and colour distributions and provides a practical framework for generating large, realistic mock galaxy catalogs, while also enhancing our understanding of the complex interplay between galaxy evolution and dark matter halo assembly.

astro-ph.GA↗

arXiv2025

Evaluating the galaxy formation histories predicted by a neural network in pure dark matter simulations

We investigate a series of galaxy properties computed using the merger trees and environmental histories from dark matter only cosmological simulations, using a semi-recurrent neural network producing self-consistent predictions of galaxy evolution, and using stochastic improvements to this model based on similarly predicted Fourier Transforms. We apply these methods to the dark matter only runs of the IllustrisTNG simulations to understand the effects of baryon removal, and to the gigaparsec-volume pure dark matter simulation Uchuu, to understand the effects of the lower resolution or alternative metrics for halo properties. We find that the machine learning model recovers accurate summary statistics derived from the predicted star formation and stellar metallicity histories, and correspondent spectroscopy and photometry. However, the inaccuracies of the model's application to dark simulations are substantial for low mass and slowly growing haloes. For these objects, the halo mass accretion rate is exaggerated due to the lack of stellar feedback, yet the formation of the halo can be severely limited by the absence of low mass progenitors in a low resolution simulation. Furthermore, differences in the structure and environment of higher mass haloes results in an overabundance of red, quenched galaxies. These results signify progress towards a machine learning model which builds high fidelity mocks based on a physical interpretation of the galaxy-halo connection, yet they illustrate the need to account for differences in halo properties and the resolution of the simulation.

astro-ph.CO↗

arXiv2022

Modelling the galaxy-halo connection with semi-recurrent neural networks

We present an artificial neural network design in which past and present-day properties of dark matter halos and their local environment are used to predict time-resolved star formation histories and stellar metallicity histories of central and satellite galaxies. Using data from the IllustrisTNG simulations, we train a TensorFlow-based neural network with two inputs: a standard layer with static properties of the dark matter halo, such as halo mass and starting time; and a recurrent layer with variables such as overdensity and halo mass accretion rate, evaluated at multiple time steps from $0 \leq z \lesssim 20$. The model successfully reproduces key features of the galaxy halo connection, such as the stellar-to-halo mass relation, downsizing, and colour bimodality, for both central and satellite galaxies. We identify mass accretion history as crucial in determining the geometry of the star formation history and trends with halo mass such as downsizing, while environmental variables are important indicators of chemical enrichment. We use these outputs to compute optical spectral energy distributions, and find that they are well matched to the equivalent results in IllustrisTNG, recovering observational statistics such as colour bimodality and mass-magnitude diagrams.

astro-ph.GA↗