arXiv subjects

I. Marini

Publications and source records attributed to I. Marini.

14 recordsLinked to original sources

arXiv2026

What's Missing in AGN Feedback? Lessons learnt from Magneticum, IllustrisTNG and Simba

Accurately balancing gas reservoirs, star formation, and feedback across cosmic time remains a central challenge for galaxy formation models in modern hydrodynamical simulations. While different feedback prescriptions reproduce selected local galaxy properties with varying success, the most pronounced discrepancies emerge in predictions for the hot gas content of dark matter halos. We examine three state-of-the-art cosmological simulations: Magneticum, IllustrisTNG, and SIMBA, which struggle to simultaneously reproduce observed galaxy and halo gas properties in the local Universe. We confront their predictions with spatially resolved galaxy data from MaNGA and recent constraints on the hot gas mass fraction-halo mass (fgas-Mh) relation from eROSITA and Sunyaev-Zel'dovich (SZ) measurements. Reproducing the observed fgas-Mh relation requires strong active galactic nucleus (AGN) feedback. However, such feedback often leads to excessive quenching in simulated galaxy populations. Magneticum and SIMBA match the observed gas fraction relation but predict an overabundance of quenched galaxies. In contrast, IllustrisTNG implements weaker AGN feedback, yielding more realistic star-forming fractions but systematically overpredicting hot gas masses in massive groups and poor clusters. Overall, these tensions indicate current feedback models remain incomplete, not only in the total energy injected but also in the timing, location, and coupling of this energy to the surrounding gas. Our results therefore highlight the need to revisit subgrid feedback prescriptions and develop more self-consistent models capable of simultaneously regulating galaxy growth and the thermodynamic properties of halo gas. Motivated by this discrepancy, a companion study will explore whether the feedback strengths required to match halo gas constraints inevitably lead to overquenching and distorted galaxy demographics.

astro-ph.GA↗

arXiv2026

The kinematic imprinting of environmental quenching in $z<0.2$ galaxies

We present the first systematic census of quenching mechanisms using kinematic asymmetries in a large sample of $\sim$6,700 galaxies from the MaNGA survey, providing a unified view of what halts star formation in the local Universe ($z<0.2$). We quantify stellar and nebular gas disturbances through the higher-order terms of a Fourier series expansion. These asymmetries serve as powerful diagnostics, as different quenching mechanisms leave distinct kinematic signatures on gas and stars. Our analysis reveals that the most effective quenching pathways leave minimal kinematic imprints by the time galaxies are fully quenched. This "kinematic regularity" points toward slow-acting processes (>3 Gyr) such as starvation and maintenance feedback. A striking finding emerges from our mass-matched analysis: quenched symmetric satellites are significantly more compact than their asymmetric counterparts ($3.4\sigma$), a trend that is even more pronounced for symmetric centrals ($12.3\sigma$). Our results suggest that environment drives the dominant satellite quenching pathway through rapid gas stripping followed by long-term starvation. These compact, kinematically undisturbed satellites (the most representative case within our sample) have undergone intense gas stripping and central compaction, creating bulge-like structures with old, metal-rich stellar populations. Combined with halo gas cut-off and the prevention of cosmological accretion due to starvation, this creates an irreversible quenching path. Conversely, the larger sizes of disturbed, quenched centrals are consistent with merger-driven growth. Internal processes, likely driven by the AGN cycle over 1-3 Gyr that prevents hot halo gas cooling, sustain quenching maintenance in this population. The absence of asymmetric satellites in the star-forming regime suggests environmental quenching operates without significant kinematic perturbation.

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arXiv2025

Robustness of pairwise kinematic Sunyaev-Zel'dovich effect to optical-cluster-selection bias

The pairwise kinematic Sunyaev-Zel'dovich(kSZ) effect measures both the pairwise motion between galaxy groups and clusters and the amount of gas within them, providing a tracer for cosmic growth. To interpret the cosmological information in the kSZ measurements, it is crucial to understand the optical-cluster-selection bias on the kSZ observables. Line-of-sight structures that contribute to both the optical observable (e.g. richness) and the cosmological signal can induce a correlation between these two quantities at a fixed cluster mass. The selection bias arising from this correlation is a key systematic effect for cosmological analyses. For cosmological observables such as cluster abundance and weak lensing, controlling this selection bias may help explain the tension between the DES-Y1 results and the Planck constraints. In order to test for a kSZ effect equivalent of such a bias, we adopted an alternative mock richness based on galaxy counts within cylindrical volumes along the line of sight. We applied the cylindrical count method to hydrodynamical simulations across a wide range of galaxy-selection criteria, assigning richness consistent with DES-Y1 to the mock clusters. When comparing optically selected clusters to mass-selected halos, we find no significant bias on pairwise kSZ signals, pairwise velocities, or optical depth within our uncertainty limits of approximately 16, 10, and 8 per cent, respectively.

astro-ph.CO↗

arXiv2025

The eROSITA view on the halo mass-temperature relation: From low-mass groups to massive clusters

Galaxy groups and clusters are among the best probes of structure formation and growth in a cosmological context. Most of their baryonic component is dominated by the intracluster medium (ICM), whose thermodynamical properties serve as indicators of the halo's dynamical state and can be used for the halo mass determination in the self-similar scenario. However, baryonic processes, such as AGN feedback and gas cooling, may affect the global properties of the ICM, especially in the group regime. These effects might lead to deviations from self-similar predictions in galaxy groups' scaling relations, while they remain in place for massive galaxy clusters. Additionally, the low-mass end of the scaling relations, ranging from $10^{13}$ to $10^{14} M_\odot$, remains unclear and poorly populated, as current X-ray surveys detect only the brightest groups. Here, we present the Mass-Temperature relation across the full mass range, from massive clusters to low-mass groups ($10^{13}M_\odot$), as observed by eROSITA. Using spectral stacking from eROSITA eRASS1 data for optically selected galaxy groups, we find that, in the lower mass range, galaxy groups follow the power-law relation known for galaxy clusters. We further validate these results by conducting the same stacking procedure on mock eRASS:4 data using the Magneticum hydrodynamical simulation. This indicates that AGN feedback is more likely to affect the distribution of baryons in the intragroup medium rather than the overall halo gas temperature. No significant changes in the Mass-Temperature relation slope suggest that temperature can serve as a reliable mass proxy across the entire mass range. This validates the use of temperature-derived masses, particularly in cosmological studies, significantly broadening the mass range and enabling applications such as improving the cluster mass function studies and cosmological parameter estimate.

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arXiv2025

The impact of assembly history on the X-ray detectability of halos. From galaxy groups to galaxy clusters

Galaxy groups represent a significant fraction of the halo population, playing a crucial role in galaxy formation and evolution. However, their detection in X-rays remains challenging, raising questions about the physical mechanisms driving their detectability in current surveys. Using the Magneticum simulations, we construct a mock X-ray lightcone of the local Universe ($z<0.2$) to investigate the selection function of galaxy groups and clusters. We find that AGN activity is a key driver of baryon depletion, but late-time mergers boost X-ray brightness by replenishing the gas reservoir in the halos, highlighting the interplay between feedback processes and the environment. Our analysis shows that X-ray bright groups experience sustained late-time mass accretion, maintaining higher gas fractions and fueling the central supermassive black holes (SMBH), further increasing the X-ray emissivity in the core. In contrast, X-ray faint groups form earlier and lose most of their gas over time, resembling fossil groups. Magneticum predicts strong anti-correlations between gas fraction (or X-ray luminosity) and SMBH mass, stellar mass (both in the central galaxy and intracluster light), and group richness at fixed halo mass. We derive predictions on the hot gas fraction at fixed halos mass (e.g. a group of total mass $M_{500}=10^{13} M_{\odot}$ can have hot gas fractions in the range $f_\mathrm{gas}=0.02-0.06$ and a central SMBH with a median mass of $M_\mathrm{BH}=10^9 M_{\odot}$ and a scatter of $0.5$ dex) compatible with the most recent measurements of the baryonic fraction. These findings will aid the interpretation of future X-ray surveys, demonstrating the power of simulation-based inference.

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arXiv2024

Average X-ray properties of galaxy groups. From Milky Way-like halos to massive clusters

This study examines the average X-ray properties of massive halos at z< 0.2, covering the largest halo mass range to date, from Milky Way-like halos to massive clusters. The analysis is based on stacking in the eFEDS area of the GAMA galaxy group sample, validated with synthetic data that mimic observed eROSITA X-ray and GAMA optical data using Magneticum lightcones. Stacking was conducted in halo mass bins and tested for AGN and X-ray binary contamination, systematics in the halo mass proxy, and uncertainties in optical group centers. The study provides average X-ray surface brightness profiles in six mass bins, spanning Milky Way-like systems to poor clusters. The scatter in the X-ray luminosity-mass (LX-M) relation is attributed to gas concentration: low X-ray luminosity systems at fixed halo mass exhibit lower central gas concentrations than high-luminosity systems, consistent with Magneticum predictions. However, discrepancies in dark matter concentration arise, with Magneticum predicting undetected groups as older and more relaxed, while observations suggest the opposite. New LX-M relations are presented covering three decades of halo mass. These relations fit a single power law, aligning with previous studies. Magneticum matches observed gas distributions across all masses, whereas IllustrisTNG, EAGLE, Simba, and FLAMINGO exhibit significant discrepancies at various mass scales. Simulations calibrated on local galaxy properties accurately reproduce central galaxies but fail to capture gas properties. Conversely, simulations like Magneticum excel in gas predictions but produce overly massive central galaxies. Further exploration of gas and dark matter distributions and their effects on galaxy properties is critical to comprehending the role of gravitational forces and feedback in shaping large-scale structure and galaxy evolution.

astro-ph.GA↗

arXiv2024

Detecting clusters and groups of galaxies populating the local Universe in large optical spectroscopic surveys

Wide-field cosmological surveys provide hundreds of thousands of spectroscopically confirmed galaxy groups and clusters, valuable for tracing baryonic matter distribution. However, controlling systematics in identifying host dark matter halos and estimating their properties is crucial. We evaluate three group detection methods on a simulated dataset replicating the GAMA selection to understand systematics and selection effects. This is key for interpreting data from SDSS, GAMA, DESI, WAVES, and leveraging optical catalogues in the (X-ray) eROSITA era to quantify baryonic mass in galaxy groups. Using a lightcone from the Magneticum hydrodynamical simulation, we simulate a spectroscopic galaxy survey in the local Universe (down to $z<0.2$ and stellar mass completeness $M_{\star}\geq10^{9.8} M_{\odot}$). We assess completeness and contamination of reconstructed halo catalogues, evaluate membership accuracy, and analyse the halo mass recovery rate of group finders. All three group finders achieve high completeness ($>80\%$) at group and cluster scales, confirming optical selection's suitability for dense regions. Contamination at low masses ($M_{200}<10^{13} M_{\odot}$) arises from interlopers and fragmentation. Membership is at least 70\% accurate above the group mass scale, but inaccuracies bias halo mass estimates using galaxy velocity dispersion. Alternative proxies, like total stellar luminosity or mass, yield more accurate halo masses. The cumulative luminosity function of galaxy members matches predictions, showing the group finders' accuracy in identifying galaxy populations. These results confirm the reliability and completeness of spectroscopic catalogues produced by state-of-the-art group finders. This supports studies requiring large spectroscopic samples of galaxy groups and clusters, as well as investigations into galaxy evolution across diverse environments.

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arXiv2024

The perils of stacking optically selected groups in eROSITA data. The Magneticum perspective

Hydrodynamical simulation predictions are often compared with observational data without fully accounting for systematics and biases specific to observational techniques. Using the magnetohydrodynamical simulation Magneticum, we generate mock eROSITA eRASS:4 data, combined with GAMA-like spectroscopic surveys and optically selected galaxy catalogs from the same light-cone, to analyze hot gas properties in galaxy groups via a stacking technique. This study aims to (i) incorporate observational systematics into predictions and (ii) evaluate the reliability of stacking techniques for determining average X-ray properties of galaxy groups. Our analysis provides X-ray emission predictions from Magneticum, including contributions from AGN, X-ray binaries (XRBs), and the Intra-Group Medium (IGM) as a function of halo mass, covering Milky Way (MW)-like groups to poor clusters. We find that AGN and XRBs dominate the X-ray surface brightness profiles of low-mass halos. The reliability of stacking techniques is tested by reproducing input X-ray surface brightness and electron density profiles, accounting for completeness and contamination of prior samples, miscentering of optical group centers, uncertainties in X-ray emissivity due to gas temperature and metallicity assumption, and systematics in halo mass proxies. The halo mass proxy emerges as the primary source of systematics, affecting X-ray surface brightness and scaling relations. We show that stacked X-ray luminosity-mass relations are flatter than input relations but consistent with observations. Additionally, the retrieved hot gas fraction-mass relation aligns well with observational data. These results highlight the need to account for systematic errors when comparing stacking techniques to other methods using different prior catalogs or predictions.

astro-ph.GA↗

arXiv2024

The hot gas mass fraction in halos. From Milky Way-like groups to massive clusters

By using eROSITA data in the eFEDS area, we provide a measure of the hot gas fraction vs. halo mass relation over the largest halo mass range, from Milky Way-sized halos to massive clusters, and to the largest radii ever probed so far in local systems. To cope with the incompleteness and selection biases of the X-ray selection, we apply the stacking technique in eROSITA data of a highly complete and tested sample of optically selected groups. The method has been extensively tested on mock observations. In massive clusters, the hot gas alone provides a baryon budget within $R_{200}$ consistent with the cosmic value. At the same time, at the group mass scale, it accounts only for 20-40% of it. The hot gas fraction vs. halo mass relation is well-fitted by a power law, with a consistent shape and a normalization varying at maximum by a factor of 2 from $r_{500}$ to $r_{200}$. Such a relation is consistent with other works in the literature that consider X-ray survey data at the same depth as eFEDS. However, it provides a lower average gas fraction in the group regime than works based on X-ray bright group samples. The comparison of the observed relation with the predictions of several hydrodynamical simulations (BAHAMAS, FLAMINGO, SIMBA, Illustris, IllustrisTNG, MillenniumTNG, and Magneticum) shows that all simulations but Magneticum and SIMBA overpredict the gas fraction, with the largest discrepancy (up to a factor of 3) in the massive group-poor cluster halo mass range. We emphasize the need for mechanisms that can effectively expel gas to larger radii in galaxy groups without excessively quenching star formation in their member galaxies. Current hydrodynamical simulations face a significant challenge in balancing their subgrid physics: none can sufficiently evacuate gas from the halo virial region without negatively impacting the properties of the resident galaxy population.

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arXiv2024

Inferring intrahalo light from stellar kinematics -- A deep learning approach

Disentangling the stellar population in the central galaxy from the intrahalo light can help us shed light on the formation history of the host halo, as the properties of the stellar components are expected to retain traces of its formation history. Many approaches are adopted, depending on different physical assumptions (e.g. the light profile, chemical composition, and kinematical differences) and on whether the full six-dimensional phase-space information is known (much like in simulations) or whether one analyses projected quantities (i.e. observations). This paper paves the way for a new approach to bridge the gap between observational and simulation methods. We propose the use of projected kinematical information from stars in simulations in combination with deep learning to create a robust method for identifying intrahalo light in observational data to enhance understanding and consistency in studying the process of galaxy formation. Using a U-Net, we developed a methodology for predicting these contributions from a sample of mock images from hydrodynamical simulations to train, validate and test the network. Reinforced training (Attention U-Net) was used to improve the first results, as the innermost central regions of the mock images consistently overestimate the stellar intrahalo contribution. Our work shows that adequate training over a representative sample of mock images can lead to good predictions of the intrahalo light distribution. The model is mildly dependent on the training size and its predictions are less accurate when applied to mock images from different simulations. However, the main features (spatial scales and gradients of the stellar fractions) are recovered for all tests. While the method presented here should be considered as a proof of concept, future work is required to enable the application of the proposed model to observational data.

astro-ph.GA↗

arXiv2024

Detecting Galaxy Groups and AGNs populating the local Universe in the eROSITA era

The eROSITA will deliver an unprecedented volume of X-ray survey observations, 20-30 times more sensitive than ROSAT in the soft band (0.5-2 keV) and for the first time imaging in the hard band (2-10 keV) including galaxy clusters and groups along with obscured and unobscured AGNs. This calls for a powerful theoretical effort to control the systematics and biases that may affect the data analysis. We investigate the detection technique and selection effects in the galaxy group and AGN populations of a mock eROSITA survey at the depth of eRASS:4. We create a $30\times 30$ deg$^{2}$ mock observation based on the cosmological hydrodynamical simulation Magneticum Pathfinder within z=0-0.2. We combine a physical background extracted from the real eFEDS background analysis with realistic simulations of X-ray emission for the hot gas, AGNs and X-ray binaries. We apply a detection procedure equivalent to the reduction done on eRASS data and evaluate the completeness and contamination to reconstruct the luminosity functions of the extended and point sources in the catalogue. We assess the completeness of extended detections as a function of the input X-ray flux and halo. We achieve full recovery of the brightest (most massive) clusters and AGNs. However, a significant fraction of galaxy groups remains undetected. Examining the gas properties between the detected and undetected galaxy groups at fixed halo mass, we observe that the detected population exhibits, on average, higher X-ray brightness compared to the undetected ones. Moreover, we find that X-ray luminosity primarily correlates with the hot gas fraction, rather than temperature or metallicity. Our simulation suggests the presence of a systematic selection effect in current surveys, resulting in X-ray survey catalogues predominantly composed of the lowest-entropy, gas-richest, and highest surface brightness halos on galaxy group scales.

astro-ph.CO↗

arXiv2022

Machine Learning to identify ICL and BCG in simulated galaxy clusters

Nowadays, Machine Learning techniques offer fast and efficient solutions for classification problems that would require intensive computational resources via traditional methods. We examine the use of a supervised Random Forest to classify stars in simulated galaxy clusters after subtracting the member galaxies. These dynamically different components are interpreted as the individual properties of the stars in the Brightest Cluster Galaxy (BCG) and IntraCluster Light (ICL). We employ matched stellar catalogues (built from the different dynamical properties of BCG and ICL) of 29 simulated clusters from the DIANOGA set to train and test the classifier. The input features are cluster mass, normalized particle cluster-centric distance, and rest-frame velocity. The model is found to correctly identify most of the stars, while the larger errors are exhibited at the BCG outskirt, where the differences between the physical properties of the two components are less obvious. We investigate the robustness of the classifier to numerical resolution, redshift dependence (up to $z=1$), and included astrophysical models. We claim that our classifier provides consistent results in simulations for $z<1$, at different resolution levels and with significantly different subgrid models. The phase-space structure is examined to assess whether the general properties of the stellar components are recovered: (i) the transition radius between BCG-dominated and ICL-dominated region is identified at $0.04$ \r200; (ii) the BCG outskirt ($> 0.1$ \r200) is significantly affected by uncertainties in the classification process. In conclusion, this work suggests the importance of employing Machine Learning to speed up a computationally expensive classification in simulations.

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arXiv2021

Velocity dispersion of the brightest cluster galaxies in cosmological simulations

Using the DIANOGA hydrodynamical zoom-in simulation set of galaxy clusters, we analyze the dynamics traced by stars belonging to the Brightest Cluster Galaxies (BCGs) and their surrounding diffuse component, forming the intracluster light (ICL), and compare it to the dynamics traced by dark matter and galaxies identified in the simulations. We compute scaling relations between the BCG and cluster velocity dispersions and their corresponding masses (i.e. $M_\mathrm{BCG}^{\star}$- $σ_\mathrm{BCG}^{\star}$, $M_{200}$- $σ_{200}$, $M_\mathrm{BCG}^{\star}$- $M_{200}$, $σ_\mathrm{BCG}^{\star}$- $σ_{200}$), we find in general a good agreement with observational results. Our simulations also predict $σ_\mathrm{BCG}^{\star}$- $σ_{200}$ relation to not change significantly up to redshift $z=1$, in line with a relatively slow accretion of the BCG stellar mass at late times. We analyze the main features of the velocity dispersion profiles, as traced by stars, dark matter, and galaxies. As a result, we discuss that observed stellar velocity dispersion profiles in the inner cluster regions are in excellent agreement with simulations. We also report that the slopes of the BCG velocity dispersion profile from simulations agree with what is measured in observations, confirming the existence of a robust correlation between the stellar velocity dispersion slope and the cluster velocity dispersion (thus, cluster mass) when the former is computed within $0.1 R_{500}$. Our results demonstrate that simulations can correctly describe the dynamics of BCGs and their surrounding stellar envelope, as determined by the past star-formation and assembly histories of the most massive galaxies of the Universe.

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arXiv2020

On the phase-space structure of galaxy clusters from cosmological simulations

Cosmological N-body simulations represent an excellent tool to study the formation and evolution of dark matter (DM) halos and the mechanisms that have originated the universal profile at the largest mass scales in the Universe. In particular, the combination of the velocity dispersion $σ_\mathrm{v}$ with the density $ρ$ can be used to define the pseudo-entropy $S(r)=σ_\mathrm{v}^2/ρ^{\,2/3}$, whose profile is well-described by a simple power-law $S\propto\,r^{\,α}$. We analyze a set of cosmological hydrodynamical re-simulations of massive galaxy clusters and study the pseudo-entropy profiles as traced by different collisionless components in simulated galaxy clusters: DM, stars, and substructures. We analyze four sets of simulations, exploring different resolution and physics (N-body and full hydrodynamical simulations) to investigate convergence and the impact of baryons. We find that baryons significantly affect the inner region of pseudo-entropy profiles as traced by substructures, while DM particles profiles are characterized by an almost universal behavior, thus suggesting that the level of pseudo-entropy could represent a potential low-scatter mass-proxy. We compare observed and simulated pseudo-entropy profiles and find good agreement in both normalization and slope. We demonstrate, however, that the method used to derive observed pseudo-entropy profiles could introduce biases and underestimate the impact of mergers. Finally, we investigate the pseudo-entropy traced by the stars focusing our interest in the dynamical distinction between intracluster light (ICL) and the stars bound to the brightest cluster galaxy (BCG): the combination of these two pseudo-entropy profiles is well-described by a single power-law out to almost the entire cluster virial radius.

astro-ph.CO↗