arXiv subjects

Elena Rasia

Publications and source records attributed to Elena Rasia.

At least 19 recordsLinked to original sources

arXiv2026

CHEX-MATE: X-ray surface brightness discontinuities across a representative cluster sample

We analyze the presence of X-ray surface brightness (SB) discontinuities, such as shocks and cold fronts, in the intracluster medium (ICM) of the 116 galaxy clusters from the CHEX-MATE sample. These features arise from accretion-related processes, including the merging of subclumps onto the main cluster halo and the sloshing of cold gas in a higher-entropy environment. We identify these structures in the XMM CHEX-MATE maps by examining both the SB residuals, obtained by subtracting a cluster model from the observations, and the gradient variations across X-ray images. We validate our method with an extensive analysis and comparison of the discontinuities described already in the literature. Our analysis reveals 66 discontinuities, 32 of which are newly detected, in 48 objects ($\sim$41%). We find that discontinuities in relaxed systems tend to be closer to the core, weaker, and less aligned with the global X-ray morphology compared to those in disturbed systems. Using wavelet-based temperature maps, we provide a preliminary classification of these discontinuities, proposing the occurrence of 8 putative shocks and 34 cold fronts. Furthermore, about 48% of the systems with extended radio emission show evidence of ICM discontinuities; conversely, $\sim$88% of the objects with detected discontinuities have an associated diffuse radio emission. This work also explores the limitations of using XMM data, characterized by relatively low spatial resolution, for detecting and analyzing such features, highlighting the challenges and potential biases introduced by instrumental constraints.

astro-ph.CO↗

arXiv2026

Dianoga simulations of galaxy clusters and groups: Properties of the baryonic components

We introduce the Dianoga set of cosmological simulations of galaxy clusters and groups, specifically aimed at studying the impact of the implementation of AGN feedback and star formation. Using the OpenGadget3 code, we carry out simulations of 28 regions centred on massive galaxy clusters, and of a cosmological box. This generates a sample of 293 halos with M_{200}> 1.5 x 10^{13} M_{\odot}. Parameters of AGN feedback in the reference implementation were minimally calibrated exclusively to match the local relation between SMBH masses and stellar masses of host galaxies. Simulations are compared to observed galaxy stellar mass function (GSMF), stellar mass fraction in clusters and groups, BCG masses, scaling relations between ICM/IGM properties and profiles of their thermodynamical properties. In the appendix, we show how results vary as we modify the reference feedback model in six alternative configurations. Our reference model predicts a GSMF in general agreement with observations, albeit overestimated in the high end. BCG stellar masses and mass fractions are higher than observed in massive clusters, while being closer to observations for groups. Predicted properties of the ICM/IGM are in general agreement with observations, with the core regions of simulated clusters having entropy and temperature profiles that are slightly less "cool-cored" than observed. A comparison with other implementations of AGN feedback highlights that models including thermal evaporation of the sub-resolution interstellar medium succeed to bring BCG masses and stellar mass fractions closer to observation, and to increase the cool-coreness of simulated clusters. Our results demonstrate that the details of the interface between AGN energy injection and the sub-resolution interstellar medium model are at least as critical as the total feedback efficiency itself.

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arXiv2026

Imprints of Mass Accretion History on Galaxy Cluster Morphology

Variations in dynamical states of galaxy clusters can introduce biases and scatter in observable-mass relations. The dynamical state of a cluster is an emergent feature of its mass accretion history (MAH), it is therefore useful to constrain the MAH of the cluster. In this work, we characterize 305 massive clusters from The300 project by connecting features from their projected stellar distributions to their mass accretion histories (MAH). As a baseline, we first correlate host dark matter halo dynamical state indicators at $z=0$ with their MAH via the Spearman rank correlation coefficient $ρ_{\mathrm{sp}}$. Both substructure mass fraction and center-of-mass offset measurements correlate strongly with the MAH measured between $0.1\lesssim z\lesssim 1$. We repeat this exercise with morphological measurements of projected stellar density maps, many of which exhibit moderate correlation strength with different times in the MAH. Broadly, core morphological measurements ($r \leq 30\,\mathrm{kpc}$) correlate better with early-time MAH. Core-excised ($50\,\mathrm{kpc} \leq r \leq 1\,\mathrm{Mpc}$) morphological measurements correlate better with late-time MAH. We further quantify the MAH prediction power of both traditional dynamical state indicators and morphological parameters using Multivariable Conditional Abundance Matching (MultiCAM). MultiCAM employs simple rank-ordering operations, making it straightforward to translate to observed datasets. We find reasonable ($ρ_{\mathrm{sp}} \geq 0.6$) performance for predictions of the mass fraction between $1\lesssim z\lesssim 0.1$, though with notable information loss when using projected quantities. In one example application of our methodology, we use the coefficients of the MultiCAM models to select subsamples of galaxy clusters that have accreted more (or less) of their $z = 0$ mass budget over a given time frame.

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arXiv2026

Probing the baryonic--dark matter connection in galaxy clusters using X-rays with gated recurrent unit neural networks

Accurate cluster mass measurements are crucial for cosmology, yet conventional hydrostatic equilibrium (HSE) methods can suffer from systematic biases, particularly in dynamically disturbed systems. We present a gated recurrent unit (GRU) based deep learning framework for predicting three-dimensional mass profiles of galaxy clusters from spherically averaged intra-cluster medium (ICM) radial profiles. By treating ICM profiles as sequential data, the GRU captures radial dependencies and naturally handles profiles with different radial samplings. We train and validate the model using high-resolution hydrodynamical simulations from The Three Hundred Project, achieving unbiased mass predictions with a typical 1$σ$ scatter of $\sim$5% over most of the cluster region, significantly improving upon HSE estimates. The model provides radius-dependent uncertainty estimates and remains robust against variations in data quality and cluster morphology. When trained jointly on independent simulation suites (GIZMO-SIMBA and GADGET-X), it successfully generalises across both simulations. Feature importance analysis shows that enclosed gas mass is the dominant predictor, with pressure and temperature providing additional information on the radial mass distribution. We further apply the GRU model to X-ray observations of the REXCESS and X-COP cluster samples from XMM-Newton and compare the inferred mass profiles with HSE estimates. The HSE masses are systematically lower than the GRU predictions for the higher-mass X-COP sample, while the REXCESS sample shows mass differences that are close to zero on average. This work provides a data-driven framework for cluster mass inference that bridges simulations and observations and can be extended to multi-wavelength datasets, including Sunyaev-Zel'dovich and optical observations.

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arXiv2026

The Three Hundred project: Low Gas Fraction Galaxy Clusters properties and their environment

Galaxy cluster samples based on X-ray and Sunyaev-Zel'dovich (SZ) observations are affected by selection biases. These catalogs preferentially include systems with high gas content and surface brightness. Excluding objects with depleted gas content, low-gas-fraction clusters (LGFCs), could lead to an incomplete sampling. We aim to investigate the abundance and the properties of the LGFCs population using The Three Hundred hydrodynamical simulations, focusing on the Gadget-X code. In particular, we study outliers in the $f_{\mathrm{g},500} - M_{500}$ relation, environmental influences, and their behavior in key scaling relations, with a focus on the Compton-Y observable. We analyze a sample of $N_{\mathrm{tot}} = 9858$ simulated objects from The Three Hundred, in the redshift band $z \in [0;0.817]$. LGFCs are selected statistically as outliers of the $f_{\mathrm{g},500}-M_{500}$ relation. To analyze environmental effects, we compare the gas density and temperature radial profiles of LGFCs against the No-LGFCs population. Finally, we study how the temperature, entropy, and spherical Compton parameter scaling relations are affected by the inclusion of LGFCs. We find that LGFCs are preferentially found at the low-mass end and their abundance increases toward low redshift. Radial profiles of LGFCs show lower gas concentrations in the core regions and higher temperatures, suggesting a more diffuse and heated ICM. This behavior is also reflected in the entropy scaling relation, where LGFCs are extreme positive outliers. Contrary to observations, the $Y_{\mathrm{sph},500}$ values of LGFCs show no significant deviation from the general population. Nevertheless, we cannot rule out that these differences are partly driven by the mass incompleteness at the low-mass end and the environmental bias of our simulated sample.

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arXiv2026

CHEX-MATE: AMALGAM weak-lensing analysis of 41 Planck Sunyaev-Zel'dovich-selected galaxy clusters

We present a weak-lensing shear analysis of 41 Planck SZ-selected galaxy clusters at $0.11\le z\le 0.55$ from the CHEX-MATE sample, using wide-field Subaru/Suprime-Cam and CFHT/MegaPrime imaging from the AMALGAM project. We detect the azimuthally averaged weak-lensing signal around the X-ray peak of each cluster, achieving a median S/N of 6.5 per cluster. The $45^\circ$-rotated component has a median S/N of -0.1 and ranges from -1.8 to +1.8, consistent with zero. We model the excess surface mass density profile of each cluster with an NFW profile to infer weak-lensing mass and concentration constraints. The total systematic uncertainty in the weak-lensing mass calibration is assessed to be $8\%$. Using a hierarchical Bayesian framework, we then derive weak-lensing-calibrated scaling relations for the halo concentration, $c_{200}$, as a function of $M_{200}$ and redshift, and for the Planck SZ mass proxy, $M_{SZ}$, as a function of $M_{500}$ and redshift, while accounting for sample selection effects, weak-lensing modelling biases, and residual calibration uncertainty. At $M_{200}=10^{15}M_\odot$ and $z=0.25$, we find $c_{200}=3.53\pm0.71$ with an intrinsic scatter of $0.22\pm0.04$ dex. The inferred normalisation and scatter are consistent with recent $Λ$CDM predictions for massive haloes, with no significant mass or redshift dependence over the probed range. For the Planck mass proxy, our baseline regression yields $M_{SZ}/M_{500}=0.83\pm0.09$ at $M_{500}=7\times10^{14}M_\odot$ and $z=0.25$, with an intrinsic scatter of $0.10\pm0.02$ dex. A restricted model with fixed unit mass slope and no redshift evolution gives $1-b=0.72\pm0.11$. We also provide weak-lensing-calibrated posterior estimates of $M_{500}$ for the sample based on the baseline $M_{SZ}$--$M_{500}$--$z$ relation. These results provide an initial weak-lensing mass calibration for CHEX-MATE multi-probe cluster studies.

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arXiv2025

Deriving accurate galaxy cluster masses using X-ray thermodynamic profiles and graph neural networks

Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled profiles of the intra-cluster medium (ICM) inferred from X-ray observations. GNNs naturally handle inputs of variable length and resolution by representing each ICM profile as a graph, enabling accurate and flexible modeling across diverse observational conditions. We trained and tested GNN model using state-of-the-art hydrodynamical simulations of galaxy clusters from The Three Hundred Project. The mass estimates using our method exhibit no systematic bias compared to the true cluster masses in the simulations. Additionally, we achieve a scatter in recovered mass versus true mass of about 6%, which is a factor of six smaller than obtained from a standard hydrostatic equilibrium approach. Our algorithm is robust to both data quality and cluster morphology and it is capable of incorporating model uncertainties alongside observational uncertainties. Finally, we apply our technique to XMM-Newton observed galaxy cluster samples and compare the GNN derived mass estimates with those obtained with $Y_{\rm SZ}$-M$_{500}$ scaling relations. Our results provide strong evidence, at 5$σ$ level, for a mass-dependent bias in SZ derived masses, with higher mass clusters exhibiting a greater degree of deviation. Furthermore, we find the median bias to be $(1-b)=0.85_{-0.14}^{+0.34}$, albeit with significant dispersion due to its mass dependence. This work takes a significant step towards establishing unbiased observable mass scaling relations by integrating X-ray, SZ and optical datasets using deep learning techniques, thereby enhancing the role of galaxy clusters in precision cosmology.

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arXiv2025

CHEX-MATE: Cluster Multi-Probes in Three Dimensions (CLUMP-3D) II. Combined Gas and Dark Matter Analysis from X-ray, SZE, and WL

Under the standard model of hierarchical structure formation, the overall geometry of galaxy clusters is better described by a triaxial ellipse than a sphere. As a result, applying spherically-symmetric models can result in significant biases. These biases can be mitigated by fitting a triaxial model, requiring deep multiprobe data and a set of physically motivated models to describe them. Here we present a multiprobe triaxial analysis methodology based on the data available for galaxy clusters in the Cluster Heritage project with XMM-Newton - Mass Assembly and Thermodynamics at Endpoint of structure formation (CHEX-MATE), which includes X-ray data from XMM-Newton, SZ data from Planck and ACT, and WL data from Subaru. This work builds on our previous development of a gas-only X-ray and SZ triaxial fitting formalism in Paper I. We apply our approach to the CHEX-MATE cluster PSZ2 G313.33+61.13 (Abell 1689) and find that it is elongated along the line of sight relative to the plane of sky by a factor of $\mathcal{R}_{LP} = 1.27 \pm 0.02$. As a result, the WL mass obtained from our triaxial fit, $\text{M}_{200c}=(13.69_{-1.41}^{+1.56})\times10^{14} \text{M}_{\odot}$, is significantly lower than the value of $(17.77_{-1.75}^{+2.00})\times10^{14} \text{M}_{\odot}$ obtained from a spherically-symmetric fit that otherwise employs the same methodology. Our triaxial fit finds a concentration of $c_{200c}=8.55_{-1.61}^{+2.20}$, consistent with the spherically-symmetric value of $9.99_{-1.78}^{+2.26}$, which suggests that the unexpectedly high concentration in Abell 1689 is not due to triaxiality and orientation. We also measure the non-thermal pressure fraction at radii between 0.18-1.37 Mpc, finding a minimum of approximately 20 per cent at intermediate radii increasing to near 30 per cent at both the smallest and largest radii, and with a typical measurement precision of $\pm$5 per cent.

astro-ph.CO↗

arXiv2025

The Three Hundred Project: Modeling Baryon and Hot-Gas Fraction Evolution in Simulated Clusters

The baryon fraction of galaxy clusters is a powerful tool to inform on the cosmological parameters while the hot-gas fraction provides indications on the physics of the intracluster plasma and its interplay with the processes driving galaxy formation. Using cosmological hydrodynamical simulations from The Three Hundred collaboration of about 300 simulated massive galaxy clusters with median mass $M_{500}\approx7 \times 10^{14}$M$_{\odot}$ at $z=0$, we model the relations between total mass and either baryon fraction or the hot gas fractions at overdensities $Δ= 2500$, $500$, and $200$ with respect to the cosmic critical density, and their evolution from $z\sim 0$ to $z\sim 1.3$. We fit the simulation results for such scaling relations against three analytic forms (linear, quadratic, and logarithmic in a logarithmic plane) and three forms for the redshift dependence, considering as a variable both the inverse of cosmic scale factor, $(1+z)$, and the Hubble expansion rate, $E(z)$. We show that power-law dependencies on cluster mass poorly describe the investigated relations. A power-law fails to simultaneously capture the flattening of the total baryon and gas fractions at high masses, their drop at the low masses, and the transition between these two regimes. The other two functional forms provide a more accurate description of the curvature in mass scaling. The fractions measured within smaller radii exhibit a stronger evolution than those measured within larger radii. From the analysis of these simulations, we conclude that as long as we include systems in the mass range herein investigated, the baryon or gas fraction can be accurately related to the total mass through either a parabola or a logarithm in the logarithmic plane. The trends are common to all modern hydro simulations, although the amplitude of the drop at low masses might differ [Abridged].

astro-ph.CO↗

arXiv2025

The full iron budget in simulated galaxy clusters: The chemistry between gas and stars

Heavy chemical elements such as iron in the intra-cluster medium (ICM) of galaxy clusters are a signpost of the interaction between the gas and stellar components. Observations of the ICM metallicity in present-day massive systems, however, pose a challenge to the underlying assumption that the cluster galaxies have produced the amount of iron that enriches the ICM. We evaluate the iron share between ICM and stars within simulated galaxy clusters with the twofold aim of investigating the origin of possible differences with respect to observational findings and of shedding light on the observed excess of iron on the ICM with respect to expectations based on the observed stellar population. We evaluated the iron mass in gas and stars in a sample of 448 simulated systems with masses M500 > 1e14 Msun at z=0.07. These were extracted from the high-resolution (352 cMpc/h)^3 volume of the Magneticum cosmological hydrodynamical simulations. We compared our results with observational data of low-redshift galaxy clusters. The iron share in simulated clusters features a shallow dependence on the total mass, and its value is close to unity on average. In the most massive simulated systems, the iron share is thus smaller than observational values by almost an order of magnitude. The dominant contribution to this difference is related to the stellar component, whereas the chemical properties of the ICM agree well overall with the observations. We find larger stellar mass fractions in simulated massive clusters, which in turn yield higher stellar iron masses, than in observational data. Consistently with the modelling, we confirm that the stellar content within simulated present-day massive systems causes the metal enrichment in the ICM. It will be crucial to alleviate the stellar mass discrepancy between simulations and observations to definitely assess the iron budget in galaxy clusters.

astro-ph.CO↗

arXiv2025

CHEX-MATE: exploring the kinematical properties of Planck galaxy clusters

We analyse the kinematical properties of the CHEX-MATE (Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation) galaxy cluster sample. [...] We derive cluster mass profiles for 75 clusters using the \textsc{MG-MAMPOSSt} procedure, which recovers the gravitational potential and the anisotropy profiles from line-of-sight velocities and projected positions of galaxy members. The standard NFW and the Burkert models with flatter cores than NFW both adequately fit the kinematic data, with only marginal statistical preference for one model over the other. An estimation of the mass bias $(1-B_1) = M^{SZ}_{500}/M^{M}_{500} $ is performed from the comparison with SZ-X-ray-calibrated mass estimates, resulting in a value of $ 0.54 \pm 0.11$ when four evidently disturbed clusters are removed from the sample. We assess the dynamical state of the clusters by inferring the Anderson-Darling coefficient $(A^2)$ and the fraction of galaxies in substructures ($f_\text{sub}$). Except for a few cases, we found relatively low values for $A^2$, suggesting that CHEX-MATE clusters are not too far from relaxation. Moreover, no significant trends emerge among $A^2,\,f_\text{sub}$ and the difference between the log-masses estimated by \textsc{MG-MAMPOSSt} and by SZ-X-ray. We study the concentration-mass relation for the sample; despite the large scatter, we observe signs of an increasing trend for large-mass clusters, in agreement with recent theoretical expectations. Finally, the analysis of radial anisotropy profiles of member galaxies - stacked in five bins of mass and redshift - reveals that orbits tend to be isotropic at the center and more radial towards the edge, as already found in previous studies. A slight trend of increasing radial orbits at $r_{200}$ is observed in clusters with larger velocity dispersion

astro-ph.CO↗

arXiv2025

Predicting Halo Formation Time Using Machine Learning

Context:Halo formation time, which quantifies the mass assembly history of dark-matter halos, directly impacts galaxy properties and evolution. Although not directly observable, it can be inferred through proxies like star formation history or galaxy spatial distributions. Recent advances in machine learning enable more accurate predictions of halo formation time using galaxy and halo properties. Aims:This study aims to investigate a machine learning-based approach to predict halo formation time-defined as the epoch when a halo accretes half of its current mass-using both halo and baryonic properties derived from cosmological simulations. By incorporating properties associated with the brightest cluster galaxy located at the cluster center, its associated intracluster light component and satellite galaxies, we aim to surpass these analytical predictions, improve prediction accuracy and identify key properties that can provide the best proxy for the halo assembly history. Methods:Using The Three Hundred cosmological simulations, we train Random Forest (RF) and Convolutional Neural Network (CNN) models on halo and baryonic properties, such as mass, concentration, stellar and gas masses, and features of the brightest cluster galaxy and intracluster light. CNN models are trained on two-dimensional radial property maps. We also construct simple linear models using only observationally accessible features. Results:RF models show median biases of 4%-9% with standard deviations of 20%. CNN models reduce median bias to <4%, although they have higher scatter. Simple linear models using a limited number of observables achieve prediction accuracy comparable to RF models. Traditional relations between halo formation time and mass/concentration are preserved.

astro-ph.CO↗

arXiv2025

The Three Hundred Project hydrodynamical simulations: Hydrodynamical weak-lensing cluster mass biases and richnesses using different hydro models

The mass of galaxy clusters estimated from weak-lensing observations is affected by projection effects, leading to a systematic underestimation compared to the true cluster mass, varying with both mass and redshift. The magnitude depends on the criteria used to select clusters and the spatial scale over which their mass is measured. We leverage hydrodynamical simulations of galaxy clusters carried out with GadgetX and GIZMO-SIMBA as part of the Three Hundred project. We used them to quantify weak-lensing mass biases with respect also to the results from dark matter-only simulations. We also investigate how the biases propagate into the richness-mass relation. We aim to shed light on the effect of the presence of baryons on the weak-lensing mass bias and also whether this bias depends on the galaxy formation recipe; we seek to model the richness-mass relation that can be used as guidelines for observational experiments for cluster cosmology. We produced weak-lensing simulations of random projections to model the expected excess surface mass density profile of clusters up to redshift $z=1$. We then estimated the observed richness by counting the number of galaxies in a cylinder and correcting by projected contaminants. We derived the weak-lensing mass-richness relation and found consistency across hydrodynamical simulations. The intercept parameter of the relation is independent of redshift but varies with the minimum of the stellar mass to define the richness. At the same time, the slope is relatively constant up to $z=0.55$. The scatter in observed richness at a fixed weak-lensing mass increases linearly with redshift at a fixed stellar mass cut. As expected, we observed that the scatter in richness at a given true mass is smaller than at a given weak-lensing mass. Our results for the weak-lensing mass-richness relation align well with SDSS redMaPPer cluster analyses. [Abridged]

astro-ph.CO↗

arXiv2024

CHEX-MATE: Dynamical masses for a sample of 101 Planck Sunyaev-Zeldovich-selected galaxy clusters

The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a programme to study a minimally biased sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. Accurate and precise mass measurements are required to exploit CHEX-MATE as an astrophysical laboratory and a calibration sample for cosmological probes in the era of large surveys. We measured masses based on the galaxy dynamics, which are highly complementary to weak-lensing or X-ray estimates. We analysed the sample with a uniform pipeline that is stable both for poorly sampled or rich clusters - using spectroscopic redshifts from public (NED, SDSS, and DESI) or private archives - and dedicated observational programmes. We modelled the halo mass density and the anisotropy profile. Membership is confirmed with a cleaning procedure in phase space. We derived masses from measured velocity dispersions under the assumed model. We measured dynamical masses for 101 CHEX-MATE clusters with at least ten confirmed members within the virial radius r_200c. Estimated redshifts and velocity dispersions agree with literature values when available. Validation with weak-lensing masses shows agreement within 8+-16(stat.)+-5(sys.)%, and confirms dynamical masses as an unbiased proxy. Comparison with {\it Planck} masses shows them to be biased low by 34+-3(stat.)+-5(sys.)%. A follow-up spectroscopic campaign is underway to cover the full CHEX-MATE sample.

astro-ph.CO↗

arXiv2024

The Three Hundred: The existence of massive dark matter-deficient satellite galaxies in cosmological simulations

The observation of a massive galaxy with an extremely low dark matter content (i.e. NGC 1277) has posed questions about how such objects form and evolve in a hierarchical universe. We here report on the finding of several massive, dark matter-deficient galaxies in a set of 324 galaxy clusters theoretically modelled by means of full-physics hydrodynamical simulations. We first focus on two example galaxies selected amongst the most massive and dark matter-deficient ones. By tracing the evolution of these galaxies, we find that their lack of dark matter is a result of multiple pericentre passages. While orbiting their host halo, tidal interactions gradually strip away dark matter while preserving the stellar component. A statistical analysis of all massive satellite galaxies in the simulated clusters shows that the stellar-to-total mass ratio today is strongly influenced by the number of orbits and the distance at pericentres. Galaxies with more orbits and closer pericentres are more dark matter-deficient. Additionally, we find that massive, dark matter-deficient galaxies at the present day are either the remnants of very massive galaxies at infall or former central galaxies of infalling groups. We conclude that such massive yet dark matter-deficient galaxies exist and are natural by-products of typical cluster galaxy evolution, with no specific requirement for an exotic formation scenario.

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arXiv2024

Properties of the diffuse gas component in filaments detected in the Dianoga cosmological simulations

Hydrodynamical cosmological simulations are ideal laboratories where the evolution of the cosmic web can be studied. This allows for easier insight into the nature of the filaments. We investigate how the intrinsic properties of filaments are evolving in areas extracted from a larger cosmological simulation. We aim to identify significant trends in the properties of Warm-Hot Intergalactic Medium (WHIM) and suggest possible explanations. To study the filaments and their contents, we select a subset of regions from the Dianoga simulation. We analysed these regions that were simulated with different baryon physics, namely with and without the AGN feedback. We construct the cosmic web using the Sub-space Constrained Mean Shift (SCMS) algorithm and the Sequential Chain Algorithm for Resolving Filaments (SCARF). We examined the basic physical properties of filaments (length, shape, mass, radius) and analysed different gas phases (hot, WHIM and colder gas components) within those structures. The evolution of the global filament properties and the properties of the gas phases were studied in the redshift range $0 < z < 1.48$. Within our simulations, the detected filaments have, on average, lengths below $9$ Mpc. The filaments' shape correlates with their length; the longer they are, the more likely they are curved. We find that the scaling relation between mass $M$ and length $L$ of the filaments is well described by the power law $M \propto L^{1.7}$. The radial density profile is widening with redshift, meaning that the radius of the filaments is getting larger over time. The fraction of gas mass in the WHIM phase does not depend on the model and is rising towards lower redshifts. However, the included baryon physics has a strong impact on the metallicity of gas in filaments, indicating that the AGN feedback impacts the metal content already at redshifts of $z \sim 2$.

astro-ph.CO↗

arXiv2024

CHEX-MATE : turbulence in the ICM from X-ray surface brightness fluctuations

The intra-cluster medium is prone to turbulent motion that will contribute to the non-thermal heating of the gas, complicating the use of galaxy clusters as cosmological probes. Indirect approaches can estimate the intensity and structure of turbulent motions by studying the associated fluctuations in gas density and X-ray surface brightness. In this work, we want to constrain the gas density fluctuations at work in the CHEX-MATE sample to obtain a detailed view of their properties in a large population of clusters. We use a simulation-based approach to constrain the parameters of the power spectrum of density fluctuations, assuming a Kolmogorov-like spectrum and including the sample variance, further providing an approximate likelihood for each cluster. This method requires clusters to be not too disturbed, as fluctuations can originate from dynamic processes such as merging. Accordingly, we remove the less relaxed clusters (centroid shift $w>0.02$) from our sample, resulting in a sample of 64 clusters. We define different subsets of CHEX-MATE to determine properties of density fluctuations as a function of dynamical state, mass and redshift, and investigate the correlation with the presence or not of a radio halo. We found a positive correlation between the dynamical state and density fluctuation variance, a non-trivial behaviour with mass and no specific trend with redshift or the presence/absence of a radio halo. The injection scale is mostly constrained by the core region. The slope in the inertial range is consistent with Kolmogorov theory. When interpreted as originating from turbulent motion, the density fluctuations in $R_{500}$ yield an average Mach number of $M_{3D}\simeq 0.4\pm 0.2$, an associated non-thermal pressure support of $ P_{turb}/P_{tot}\simeq (9\pm 6) \%$ or a hydrostatic mass bias $b_{turb}\simeq 0.09\pm 0.06$, in line with what is expected from the literature.

astro-ph.CO↗

arXiv2024

Characterising the intra-cluster light in The Three Hundred simulations

We characterise the intra-cluster light (ICL) in ensembles of full-physics cluster simulations from The Three Hundred project, a suite of 324 hydrodynamical resimulations of cluster-sized halos. We identify the ICL as those stellar particles bound to the potential of the cluster itself, but not to any of its substructures, and separate the brightest cluster galaxy (BCG) by means of a fixed 50 kpc aperture. We find the total BCG+ICL mass to be in agreement with state-of-the-art observations of galaxy clusters. The ICL mass fraction of our clusters is between 30 and 50 per cent of the total stellar mass within $R_{500}$, while the BCG represents around 10 percent. We further find no trend of the ICL fraction with cluster halo mass, at least not in the range $[0.2,3]\cdot10^{15}h^{-1}M_\odot$ considered here. For the dynamical state, characterised both by theoretical estimators and by the recent merging history of the cluster, there is a clear correlation, such that more relaxed clusters and those that have undergone fewer recent mergers have a higher ICL fraction. Finally, we investigate the possibility of using the ICL to explore the dark matter (DM) component of galaxy clusters. We compute the volumetric density profile for the DM and ICL components and show that, up to $R_{500}$, the ratio between the two can be described by a power law. Working with the velocity dispersion profiles instead, we show that the ratio can be fit by a straight line. Providing the parameters of these fits, we show how the ICL can be used to infer DM properties.

astro-ph.CO↗