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Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine-learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation historyv_peak, cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, withv_peakproviding the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only ≲10% of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos,more »to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics.

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ABSTRACT We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantized variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that includes: (1) consideration of the clustering performance simultaneously when learning features from images; (2) allowing for various distance thresholds within the HC algorithm; (3) using the galaxy orientation to determine the number of clusters. This set-up provides 27 clusters created with this unsupervised learning that we show are well separated based on galaxy shape and structure (e.g. Sérsic index, concentration, asymmetry, Gini coefficient). These resulting clusters also correlate well with physical properties such as the colour–magnitude diagram, and span the range of scaling relations such as mass versus size amongst the different machine-defined clusters. When we merge these multiple clusters into two large preliminary clusters to provide a binary classification, an accuracy of $\sim 87{{\ \rm per\ cent}}$ is reached using an imbalanced data set, matching real galaxy distributions, which includes 22.7 per cent early-type galaxies and 77.3 per cent late-type galaxies. Comparing the given clusters with classic Hubble types (ellipticals, lenticulars, early spirals, late spirals, and irregulars), we show that there is an intrinsic vagueness in visual classification systems, in particularmore »galaxies with transitional features such as lenticulars and early spirals. Based on this, the main result in this work is not how well our unsupervised method matches visual classifications and physical properties, but that the method provides an independent classification that may be more physically meaningful than any visually based ones.« less

ABSTRACT Galaxy clustering measurements can be used to constrain many aspects of galaxy evolution, including galaxy host halo masses, satellite quenching efficiencies, and merger rates. We simulate JWST galaxy clustering measurements at z ∼ 4–10 by utilizing mock galaxy samples produced by an empirical model, the universemachine. We also adopt the survey footprints and typical depths of the planned joint NIRCam and NIRSpec Guaranteed Time Observation program planned for Cycle 1 to generate realistic JWST survey realizations and to model high-redshift galaxy selection completeness. We find that galaxy clustering will be measured with ≳5σ significance at z ∼ 4–10. Halo mass precisions resulting from Cycle 1 angular clustering measurements will be ∼0.2 dex for faint (−18 ≳ $\mathit {M}_{\mathrm{UV}}^{ }$ ≳ −19) galaxies at z ∼ 4–10 as well as ∼0.3 dex for bright ($\mathit {M}_{\mathrm{UV}}^{ }$ ∼ −20) galaxies at z ∼ 4–7. Dedicated spectroscopic follow-up over ∼150 arcmin2 would improve these precisions by ∼0.1 dex by removing chance projections and low-redshift contaminants. Future JWST observations will therefore provide the first constraints on the stellar–halo mass relation in the epoch of reionization and substantially clarify how this relation evolves at z > 4. We also find that ∼1000 individual satellites will be identifiable at z ∼ 4–8 with JWST, enabling strong tests of satellite quenchingmore »evolution beyond currently available data (z ≲ 2). Finally, we find that JWST observations can measure the evolution of galaxy major merger pair fractions at z ∼ 4–8 with ∼0.1–0.2 dex uncertainties. Such measurements would help determine the relative role of mergers to the build-up of stellar mass into the epoch of reionization.« less

ABSTRACT We present improved results of the measurement of the correlation between galaxies and the intergalactic medium transmission at the end of reionization. We have gathered a sample of 13 spectroscopically confirmed Lyman-break galaxies (LBGs) and 21 Lyman-α emitters (LAEs) at angular separations 20 arcsec ≲ θ ≲ 10 arcmin (∼0.1–4 pMpc at z ∼ 6) from the sightlines to eight background z ≳ 6 quasars. We report for the first time the detection of an excess of Lyman-α transmission spikes at ∼10–60 cMpc from LAEs (3.2σ) and LBGs (1.9σ). We interpret the data with an improved model of the galaxy–Lyman-α transmission and two-point cross-correlations, which includes the enhanced photoionization due to clustered faint sources, enhanced gas densities around the central bright objects and spatial variations of the mean free path. The observed LAE(LBG)–Lyman-α transmission spike two-point cross-correlation function (2PCCF) constrains the luminosity-averaged escape fraction of all galaxies contributing to reionization to $\langle f_{\rm esc} \rangle _{M_{\rm UV}\lt -12} = 0.14_{-0.05}^{+0.28}\, (0.23_{-0.12}^{+0.46})$. We investigate if the 2PCCF measurement can determine whether bright or faint galaxies are the dominant contributors to reionization. Our results show that a contribution from faint galaxies ($M_{\rm UV} \gt -20 \, (2\sigma)$) is necessary to reproduce themore »observed 2PCCF and that reionization might be driven by different sub-populations around LBGs and LAEs at z ∼ 6.« less