Letizia Pasqua Cassara

Context . Galaxy evolution in dense environments, such as clusters, is strongly affected by environmental processes, which can significantly alter both morphology and star formation activity. Studying galaxies over a wide range of cluster-centric distances makes it possible to probe how these mechanisms operate across different environmental densities and to investigate pre-processing in the cluster infall regions. The Antlia cluster is particularly interesting due to its proximity and dynamical stage, but it still lacks investigation towards larger radii from the cluster core. Aims . We investigated how galaxy morphology and star formation rates vary due to environmental effects, extending this analysis out to 5 R ₂₀₀ using Southern Photometric Local Universe Survey (S-PLUS) data. Methods . We derived star formation rates from H α emission using the J 0660 band of S-PLUS and the Sérsic index using GALFITM , for which we limit our analysis to galaxies with magnitudes brighter than m _r = 16. Our main analysis focuses on 154 galaxies with spectroscopic redshifts consistent with the Antlia cluster. We split galaxies between early- and late-type systems (ETGs and LTGs, respectively), using a combination of colour ( u − r ) and Sérsic index, and between quenched and star-forming (QGs and SFGs, respectively). We further explored their environmental dependence using projected phase–space diagrams, substructure, and projected local density. Results . We find that the Antlia cluster and its infall regions are dominated by SFGs from 1 to 5 R ₂₀₀ , whereas within 1 R ₂₀₀ it exhibits a higher fraction of QGs. Early-type galaxies and LTGs show similar radial trends to those of QGs and SFGs, respectively. However, within 1 R ₂₀₀ , Antlia exhibits approximately the same fraction of ETGs and LTGs. Regarding the local density (Σ ₁₀ [Mpc ⁻² ]), QGs dominate regions with log(Σ ₁₀ [Mpc ⁻² ]) ≳ 1.5, while LTGs dominate regions with log(Σ ₁₀ [Mpc ⁻² ]) ≲ 1.0. We also identify substructures extending from the central regions to the outskirts of the cluster. Substructures outside the central region are dominated by SFGs and LTGs, with fractions similar to those of non-substructure galaxies. However, when the massive central structure is included, the SFG fraction within substructures decreases relative to galaxies not associated with any detected substructure, suggesting that the central structure hosts a more environmentally processed population. Conclusions . Altogether, the presence of a massive substructure in the central region ( R < 1 R ₂₀₀ ), together with additional substructures detected out to 5 R ₂₀₀ , indicates that the Antlia cluster is still undergoing mass assembly through group accretion. This is consistent with Antlia being a dynamically active and young system assembling its galaxy population.

We present a study of the galaxy merger and interaction activity within the Hyperion Proto-supercluster at z ∼ 2.5 in an effort to assess the occurrence of galaxy mergers and interactions in contrast to the coeval field and their impact on the buildup of stellar mass in high-density environments at higher redshifts. For this work, we utilized data from the Charting Cluster Construction with VUDS and ORELSE Survey (C3VO) along with extensive spectroscopic and photometric datasets available for the COSMOS field – including the HST -Hyperion Survey. To evaluate potential merger and interaction activity, we measured the fraction of galaxies with close kinematic companions ( f _ckc ) both within Hyperion and the coeval field by means of a Monte Carlo (MC) methodology developed in this work that probabilistically employs our entire combined spectroscopic and photometric dataset. We validated our f _ckc MC methodology on a simulated lightcone built from the GAlaxy Evolution and Assembly (GAEA) semi-analytic model, and we determined correction factors that account for the underlying spectroscopic sampling rate of our dataset. We find that galaxies in Hyperion have close kinematic companions ≳2.5× more than galaxies in the field and measure a corrected f _ckc = 59 ⁺⁹ ₋₁₀ % for Hyperion and a corrected f _ckc = 23 ^+1.7 _−1.8 % for the surrounding field; a ≳3 σ difference. The enhancement in f _ckc likely correlates to an enhancement in the merger and interaction activity within the high-density environment of Hyperion and matches the trend seen in other structures. The rate of merger and interactions within the field implied from our field f _ckc measurement is well aligned with values measured from other observations in similar redshift ranges. The enhanced f _ckc measured within Hyperion suggests that merger and interaction activity play an important role in the mass growth of galaxies in denser environments at higher redshifts.

We carried out a study on the relationship between galaxy environments and their active galactic nucleus (AGN) activity at high redshifts (2.0 < z < 4.0). Specifically, we studied the AGN fraction in galaxies residing in a range of environments at these redshifts, from field galaxies to the densest regions of highly overdense peaks in the GOODS-S extragalactic field. Utilizing the extensive photometric and spectroscopic observations in this field, we measured the local overdensities ( σ _δ ) and global overdensities across a broad a range of environments, including those in massive (M _tot ≥ 10 ^14.8 M _⊙ ) protostructures. We employed a multiwavelength AGN catalog consisting of AGNs in nine different categories. Our analysis shows a higher AGN fraction (10.9 _−2.3 ^+3.6 %) for galaxies in the highest local overdensity regions compared to the AGN fraction (1.9 _−0.3 ^+0.4 %) in the corresponding coeval field galaxies (a ∼4 σ difference). This trend of increasing AGN fraction in denser environments relative to the field is present in all redshift bins. We also find this trend to be consistent across all five AGN categories that have a sufficient number of AGNs to make a meaningful comparison: the mid-infrared (MIR) spectral energy distribution (SED), MIR color, X-ray luminosity, X-ray-luminosity-to-radio-luminosity-ratio, and optical-spectroscopy. Our results also demonstrate a clear trend for higher (∼4×) AGN fractions in denser local overdensity environments for a given stellar mass. Additionally, we observe the same trend (though at a lower significance) with the global environment of galaxies, measured using a metric based on the projected distance of galaxies from their nearest massive ( M _tot > 10 ^12.8 M _⊙ ) overdense ( σ _δ > 5.0) peak, normalized with respect to the size of the peak. These findings indicate that the prevalence of AGN activity is highly dependent on the environment a host galaxy resides in, even at early times in the formation history of the Universe.

With the 4-metre Multi-Object Spectroscopic Telescope (4MOST) expected to provide an influx of transient spectra when it begins observations in early 2026 we consider the potential for real-time classification of these spectra. We investigate three extant spectroscopic transient classifiers: the Deep Automated Supernova and Host classifier (dash), Next Generation SuperFit (ngsf), and SuperNova IDentification (snid), with a focus on comparing the completeness and purity of the transient samples they produce. We manually simulate fibre losses critical for accurately determining host contamination and use the 4MOST Exposure Time Calculator to produce realistic, 4MOST-like, host-galaxy contaminated spectra. We investigate the three classifiers individually and in all possible combinations. We find that a combination of dash and ngsf can produce a supernova (SN) Ia sample with a purity of 99.9 per cent, while successfully classifying 70 per cent of SNe Ia. However, it struggles to classify non-SN Ia transients. We investigate photometric cuts to transient magnitude and the transient’s fraction of total fibre flux, finding that both can be used to improve non-SN Ia transient classification completeness by 8–44 per cent with SNe Ibc benefitting the most and superluminous (SL) SNe the least. Finally, we present an example classification plan for live classification and the predicted purities and completeness across five transient classes: Ia, Ibc, II, SL, and non-SN transients. We find that it is possible to classify 75 per cent of input spectra with $>$70 per cent purity in all classes except non-SN transients. Precise values can be varied using different classifiers and photometric cuts to suit the needs of a given study.

We present new K-band spectroscopy for the giant elliptical galaxy M87 in the Virgo cluster, taken with the Large Binocular Telescope Utility Camera in the Infrared (LUCI) spectrograph at the Large Binocular Telescope (LBT). The new data are used to study line strengths of K-band absorption features from different chemical species, namely Fe, Mg, Ca, Na, and CO, as a function of galactocentric distance, out to ∼40″ from the center (about half of the galaxy effective radius). The radial trends of spectral indices are compared to those for the bulge of M31, observed with the same instrument. For M87, most K-band indices exhibit flat radial profiles, with the exception of NaI2.21, which decreases outward, with a negative radial gradient. Significant offsets are found between indices for M87 and those for the bulge of M31, the latter having weaker line strengths for almost all features, but Fe and Ca, for which we find similar trends in both systems. We find that the behavior of CO features – most prominent in giant stars – is difficult to explain, consistent with previous results for the central regions of massive galaxies. In particular, the CO indices are stronger in M87 than M31, and do not exhibit significant radial gradients in M87, despite its IMF being bottom heavier than M31 especially in its central region. Predictions of state-of-the-art stellar population models, based on results from the optical spectral range, are able to match only the Na and Ca indices of M87, while a significant mismatch is found for all other indices. This shows that state-of-the-art stellar population models should be improved significantly in order to provide reliable constraints on the stellar population content of galaxies in the near-infrared spectral range.

The cosmic star formation rate density, molecular gas density, and active galactic nucleus (AGN) activity of the Universe peak at z∼2–3, demonstrating the Universe is most active at this epoch. The nature of the galaxies at these redshifts and their properties as a function of their environment are particularly interesting with respect to our understanding of the mechanisms driving their star formation and quenching. At z∼2.5, the massive (∼4.8×10¹⁵ M_⊙) proto-supercluster Hyperion, consisting of seven groups and peaks and extending over a co-moving volume of 60×60×150 Mpc³, is an excellent laboratory for probing the properties and evolution of galaxies as a function of their environments. We used a large compilation of photometric (optical to radio wavelengths, COSMOS2020, COSMOS-Super-deblended, and A³COSMOS), and spectroscopic (C3VO, HST-Hyperion, VUDS, zCOSMOS, DEIMOS10K, and MAGAZ3NE) data to assign membership and study the relation between the local environment and the molecular gas mass, the star-formation rate (SFR), gas depletion timescales, and quenching mechanisms. We find that the depletion timescales and the molecular gas fractions decrease and SFR increases in denser environments at the ∼2σ level, suggesting accelerated evolution in the densest regions of this proto-supercluster resulting from gas stripping, over-consumption, and/or cessation of cold flows. Dedicated observations at sub-millimeter (sub-mm) wavelengths will enable further spectroscopic confirmations and better coverage at these wavelengths, thereby offering more conclusive results on the environmental implications on gas reservoirs of galaxies in Hyperion.

CHANCES, the CHileAN Cluster galaxy Evolution Survey, will study the evolution of galaxies in and around 100 massive galaxy clusters from the local Universe out to z = 0.45, and two superclusters at z ∼ 0.05 that contain roughly 25 Abell clusters each. CHANCES will use the new 4MOST Spectroscopic Survey Facility on the VISTA 4m telescope to obtain spectra for ∼500 000 galaxies with magnitudes r_AB < 20.4, providing comprehensive spectroscopic coverage of each cluster out to 5r₂₀₀. Its wide and deep scope will trace massive and dwarf galaxies from the surrounding filaments and groups to the cores of galaxy clusters. This will enable the study of galaxy preprocessing and of the role of the evolving environment on galaxy evolution. In this paper, we present and characterise the sample of clusters and superclusters to be targeted by CHANCES. We used literature catalogues based on X-ray emission and the Sunyaev–Zel’dovich effect to define the cluster sample in a homogeneous way, with attention to cluster mass and redshift, as well as the availability of ancillary data. We calibrated literature mass estimates from various surveys against each other and provide an initial mass estimate for each cluster, which we used to define the radial extent of the 4MOST coverage. We also present an initial assessment of the structure surrounding these clusters based on the redMaPPer red-sequence algorithm as a preview of some of the science CHANCES will enable.

The Charting Cluster Construction with VUDS and ORELSE (C3VO) survey is an ongoing imaging and spectroscopic campaign aiming to map out the growth of structure up to z ∼ 5 and was born from the combination of the Visible Multi-Object Spectrograph Ultra Deep Survey and the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey. As we previously accomplished with the ORELSE survey, we apply our technique known as Voronoi tessellation Monte Carlo (VMC) mapping to search for serendipitous galaxy overdensities at 2 < z < 5 in the three C3VO fields. We also apply the same technique to mock observations of simulated galaxies with properties derived from the GAlaxy Evolution and Assembly semianalytic model in order to judge the effectiveness of our search algorithm as a function of redshift, total mass, and fraction of spectroscopic redshifts. We find completeness and purity values of the order of 30%–50% for log ( M z = 0 / M ⊙ ) > 14 and 2 < z < 4, with a strong dependence on mass and redshift, with values as high as ∼80% and ∼70%, respectively, in the best-case scenario for log ( M z = 0 / M ⊙ ) > 14.5 . In the C3VO fields, we were able to recover many of the previously known structures in the literature as well as find hundreds of new overdensity candidates, once again demonstrating the powerful capabilities of VMC mapping when applied to wide-field optical and infrared galaxy evolution surveys at ever higher redshifts.

Context. The William Herschel Telescope Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph that allows us to collect about one thousand spectra over a 3 square degree field in one observation. The WEAVE Stellar Population Survey (WEAVE-StePS) in the next 5 years will exploit this new instrument to obtain high-S/N spectra for a magnitude-limited (I_AB = 20.5) sample of ∼25 000 galaxies at moderate redshifts (z ≥ 0.3), providing insights into galaxy evolution in this as yet unexplored redshift range. Aims. We aim to test novel techniques for retrieving the key physical parameters of galaxies from WEAVE-StePS spectra using both photometric and spectroscopic (spectral indices) information for a range of noise levels and redshift values. Methods. We simulated ∼105 000 galaxy spectra assuming star formation histories with an exponentially declining star formation rate, covering a wide range of ages, stellar metallicities, specific star formation rates (sSFRs), and dust extinction values. We considered three redshifts (i.e. z = 0.3, 0.55, and 0.7), covering the redshift range that WEAVE-StePS will observe. We then evaluated the ability of the random forest and K-nearest neighbour algorithms to correctly predict the average age, metallicity, sSFR, dust attenuation, and time since the bulk of formation, assuming no measurement errors. We also checked how much the predictive ability deteriorates for different noise levels, with S/N_I,obs = 10, 20, and 30, and at different redshifts. Finally, the retrieved sSFR was used to classify galaxies as part of the blue cloud, green valley, or red sequence. Results. We find that both the random forest and K-nearest neighbour algorithms accurately estimate the mass-weighted ages, u-band-weighted ages, and metallicities with low bias. The dispersion varies from 0.08–0.16 dex for age and 0.11–0.25 dex for metallicity, depending on the redshift and noise level. For dust attenuation, we find a similarly low bias and dispersion. For the sSFR, we find a very good constraining power for star-forming galaxies, log sSFR ≳ −11, where the bias is ∼0.01 dex and the dispersion is ∼0.10 dex. However, for more quiescent galaxies, with log sSFR ≲ −11, we find a higher bias, ranging from 0.61 to 0.86 dex, and a higher dispersion, ∼0.4 dex, depending on the noise level and redshift. In general, we find that the random forest algorithm outperforms the K-nearest neighbours. Finally, we find that the classification of galaxies as members of the green valley is successful across the different redshifts and S/Ns. Conclusions. We demonstrate that machine learning algorithms can accurately estimate the physical parameters of simulated galaxies for a WEAVE-StePS-like dataset, even at relatively low S/N_I, obs = 10 per Å spectra with available ancillary photometric information. A more traditional approach, Bayesian inference, yields comparable results. The main advantage of using a machine learning algorithm is that, once trained, it requires considerably less time than other methods.