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The properties of galaxies in low-density regions of the universe suggest an interplay between galaxy formation and environment. However, the specific reason why this particular large-scale environment influences the evolution of galaxies remains unclear. This paper examines the properties and evolutionary paths of galaxies within cosmic voids using the Illustris TNG300 simulation. The population of void galaxies at z = 0 has a higher star formation rate, a smaller stellar-to-halo-mass ratio, higher gas metallicity, and lower stellar metallicity in comparison with non-void galaxies at fixed stellar mass. Our analysis shows that these differences are mainly due to the characteristics of galaxies classified as satellites, for which the largest differences between void and non-void samples are found. Although the mean number of mergers is similar between void and non-void samples at a fixed stellar mass, void galaxies tend to experience mergers at later times, resulting in a more recent accumulation of accreted stellar mass. While the mean net accreted mass is comparable for high-mass galaxies, low-mass void galaxies tend to exhibit higher fractions of accreted stars than non-void galaxies. This finding challenges the common notion that void galaxies predominantly experience growth with infrequent mergers or interactions. With this paper, we also publicly release our void catalogue as part of the IllustrisTNG project. [ABSTRACT FROM AUTHOR]

It is crucial for a deeper understanding of the formation and evolution of galaxies in the Universe to study stellar mass (M *) and star formation rate (SFR). Traditionally, astronomers infer the properties of galaxies from spectra, which are highly informative, but expensive and hard to be obtained. Fortunately, modern sky surveys obtained a vast amount of high-spatial-resolution photometric images. The photometric images are obtained relatively economically than spectra, and it is very helpful for related studies if M * and SFR can be estimated from photometric images. Therefore, this paper conducted some preliminary researches and explorations on this regard. We constructed a deep learning model named Galaxy Efficient Network (GalEffNet) for estimating integrated M * and specific star formation rate (sSFR) from Dark Energy Spectroscopic Instrument galaxy images. The GalEffNet primarily consists of a general feature extraction module and a parameter feature extractor. The research results indicate that the proposed GalEffNet exhibits good performance in estimating M * and sSFR, with σ reaching 0.218 and 0.410 dex. To further assess the robustness of the network, prediction uncertainty was performed. The results show that our model maintains good consistency within a reasonable bias range. We also compared the performance of various network architectures and further tested the proposed scheme using image sets with various resolutions and wavelength bands. Furthermore, we conducted applicability analysis on galaxies of various sizes, redshifts, and morphological types. The results indicate that our model performs well across galaxies with various characteristics and indicate its potentials of broad applicability. [ABSTRACT FROM AUTHOR]

Modern cosmological hydrodynamical galaxy simulations provide tens of thousands of reasonably realistic synthetic galaxies across cosmic time. However, quantitatively assessing the level of realism of simulated universes in comparison to the real one is difficult. In this paper of the Extracting Reality from Galaxy Observables with Machine Learning series, we utilize contrastive learning to directly compare a large sample of simulated and observed galaxies based on their stellar-light images. This eliminates the need to specify summary statistics and allows to exploit the whole information content of the observations. We produce survey-realistic galaxy mock data sets resembling real Hyper Suprime-Cam (HSC) observations using the cosmological simulations TNG50 and TNG100. Our focus is on galaxies with stellar masses between 109 and 1012 M⊙ at z  = 0.1–0.4. This allows us to evaluate the realism of the simulated TNG galaxies in comparison to actual HSC observations. We apply the self-supervised contrastive learning method Nearest Neighbour Contrastive Learning to the images from both simulated and observed data sets (g -, r -, i -bands). This results in a 256-dimensional representation space, encoding all relevant observable galaxy properties. First, this allows us to identify simulated galaxies that closely resemble real ones by seeking similar images in this multidimensional space. Even more powerful, we quantify the alignment between the representations of these two image sets, finding that the majority (≳ 70 per cent) of the TNG galaxies align well with observed HSC images. However, a subset of simulated galaxies with larger sizes, steeper Sérsic profiles, smaller Sérsic ellipticities, and larger asymmetries appears unrealistic. We also demonstrate the utility of our derived image representations by inferring properties of real HSC galaxies using simulated TNG galaxies as the ground truth. [ABSTRACT FROM AUTHOR]

We present the 'Cosmological Jellyfish' project – a citizen-science classification program to identify jellyfish (JF) galaxies within the IllustrisTNG cosmological simulations. JF are satellite galaxies that exhibit long trailing gas features – 'tails' – extending from their stellar body. Their distinctive morphology arises due to ram-pressure stripping (RPS) as they move through the background gaseous medium. Using the TNG50 and TNG100 simulations, we construct a sample of |$\sim 80\, 000$| satellite galaxies spanning an unprecedented range of stellar masses, |$10^{8.3}{-}10^{12.3}\, \mathrm{M_\odot }$|⁠ , and host masses, |$M_\mathrm{200,c}=10^{10.4}{-}10^{14.6}\, \mathrm{M_\odot }$| back to z  = 2. Based on this sample, |$\sim 90\, 000$| galaxy images were presented to volunteers in the citizen-science Zooniverse platform, who were asked to determine whether the galaxy image resembles a JF. Based on volunteer votes, each galaxy received a score determining if it is a JF or not. This paper describes the project, the inspected satellite sample, the methodology, and the classification process that resulted in a data set of 5307 visually identified JF galaxies. We find that JF is common in nearly all group- and cluster-sized systems, with the JF fraction increasing with host mass and decreasing with satellite stellar mass. We highlight JF galaxies in three relatively unexplored regimes: low-mass hosts of |$M_\mathrm{200,c}\sim 10^{11.5}{-}10^{13}\, \mathrm{M_\odot }$|⁠ , radial positions within hosts exceeding the virial radius R 200, c, and at high redshift up to z  = 2. The full data set of our JF scores is publicly available and can be used to select and study JF galaxies in the IllustrisTNG simulations. [ABSTRACT FROM AUTHOR]

The current properties of globular cluster systems (GCSs) in the nearby Universe are a consequence of an evolutionary history ruled by accretion and disruption processes. The analysis of scaling relations for GCSs is crucial for understanding the relevance of different physical processes involved in their origin and subsequent survival. In this work, radial profiles are calculated for a sample of GCSs associated with nearby massive galaxies. This is supplemented with results from our previous papers, achieving a total sample of 53 GCSs with radial profiles homogeneously calculated, and spanning more than two orders of magnitude in stellar mass of the host galaxy. Scaling relations involving different parameters of the GCSs are obtained for the entire sample, and their significance in terms of different scenarios is considered. Finally, the results are analysed in the literature context. [ABSTRACT FROM AUTHOR]

When a galaxy falls into a cluster, its outermost parts are the most affected by the environment. In this paper, we are interested in studying the influence of a dense environment on different galaxy's components to better understand how this affects the evolution of galaxies. We use, as laboratory for this study, the Hydra cluster which is close to virialization; yet it still shows evidence of substructures. We present a multiwavelength bulge–disc decomposition performed simultaneously in 12 bands from S-PLUS (Southern Photometric Local Universe Survey) data for 52 galaxies brighter than mr  = 16. We model the galaxies with a Sérsic profile for the bulge and an exponential profile for the disc. We find that the smaller, more compact, and bulge-dominated galaxies tend to exhibit a redder colour at a fixed stellar mass. This suggests that the same mechanisms (ram-pressure and tidal stripping) that are causing the compaction in these galaxies are also causing them to stop forming stars. The bulge size is unrelated to the galaxy's stellar mass, while the disc size increases with greater stellar mass, indicating the dominant role of the disc in the overall galaxy mass–size relation found. Furthermore, our analysis of the environment unveils that quenched galaxies are prevalent in regions likely associated with substructures. However, these areas also harbour a minority of star-forming galaxies, primarily resulting from galaxy interactions. Lastly, we find that ∼37 per cent of the galaxies exhibit bulges that are bluer than their discs, indicative of an outside-in quenching process in this type of dense environments. [ABSTRACT FROM AUTHOR]