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S. Borgani

Publications and source records attributed to S. Borgani.

At least 19 recordsLinked to original sources

Euclid preparation. The shape of halo profiles in $Λ$CDM and non-standard cosmologies

We study the shape of three-dimensional and projected dark-matter halo profiles extracted from cosmological $N$-body simulations in $Λ$CDM and non-standard cosmologies, using the \texttt{DUSTGRAIN-PF} and \texttt{DEMNUni} suites. The models considered include massive neutrinos, $f(\mathcal{R})$ gravity, and dynamical dark energy. By comparing density, mass, velocity-dispersion, and excess-surface-density profiles up to $5\,r_{500{\rm c}}$, we quantify the differential imprint of non-standard physics on halo structure in view of \textit{Euclid} cluster WL studies. Our main analysis is performed at $z=1.1$, a high-redshift regime where the weak-lensing signal-to-noise starts to degrade, providing a conservative stress test for detectability; for \texttt{DUSTGRAIN-PF} we additionally analyse $z=0.5$ and $z=0.3$ snapshots. In low-mass haloes ($M_{\rm 200c}<7\times10^{13}\,M_\odot$), $f(\mathcal{R})$ gravity produces deviations of order $10\,\%$ in projected and three-dimensional profiles, especially in the outskirts where screening is less efficient. Massive neutrinos partially reduce this signal, reflecting the competition between free streaming and fifth-force-enhanced growth. Dynamical dark energy and massive-neutrino cosmologies generally induce smaller, few-percent deviations, with the largest effects again found in low-mass haloes and at large radii. Under simplified assumptions for \Euclid WL, detecting such profile differences at $z=1.1$ requires stacks of $\sim10^5$ haloes, while a few thousands haloes may be sufficient at $z\lesssim0.5$. This further calls for the need of integrating such precise modelling of non-standard effects -- along with other observational effects -- in any likelihood involving \textit{Euclid} WL masses to avoid non-negligible systematic biases. Concentration--mass relations show weaker cosmology dependence, typically at the $\sim5\,\%$ level. [...]

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Euclid preparation. XCI. Validation method for the detections in the Euclid Catalogue of Galaxy Clusters using external data

We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number of optically-selected galaxy clusters over the approximately 14000 square degrees of its extragalactic sky survey. Extending out well beyond redshift unity, the catalogue will contain many new high-redshift clusters, while at lower redshifts a fraction of the clusters will have been observed in other surveys. Identifying these known clusters as counterparts to the Euclid-detected clusters is an important step in the validation and construction of the ECGC to augment information with external observables. We present a set of catalogues and meta-catalogues of known clusters that we have assembled for this step, and we illustrate their application and our methodology using the Dark Energy Survey Year 1 RedMaPPer cluster catalogue in lieu of the future ECGC. In the process of this work, we have constructed and delivered an updated EC-RedMaPPer catalogue with multi-wavelength counterparts.

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Euclid preparation. CosmoPostProcess: A simulation calibrated framework for weak lensing selection bias in richness-selected galaxy clusters

We present \texttt{CosmoPostProcess}, a simulation-based forward-modelling algorithm calibrated to reproduce Euclid optical cluster observables. Its main deliverable is a correction for stacked surface-density profiles, binned in richness and redshift, accounting for selection systematics in richness-selected samples relative to unbiased references. We focus on the Euclid richness definition foreseen for cosmological analyses, which does not apply a colour selection; red-sequence richness is not considered. The algorithm processes $N$-body simulations by painting galaxies with a halo-occupation model and emulating survey detection and richness assignment. We also implement a novel estimate of optical cluster centres from projected galaxy densities, validated against Euclid pipelines. Baryonic effects are included through a correction calibrated on hydrodynamical simulations; the baryon-corrected excess surface density agrees within \(2\,\%\) over \(r\in[0.1,\,5]\,h^{-1}\,\mathrm{Mpc}\). Selection-bias contributions are assessed by varying cosmology and the mass--richness relation. Projection-induced selection bias follows a robust pattern: correlated large-scale structure projected along the line of sight enhances the stacked profile near the one-halo to two-halo transition, peaking at about \(1\,h^{-1}\,\mathrm{Mpc}\) with an amplitude of \(20\!-\!40\,\%\), depending on richness and redshift. The effect is mild at low and intermediate redshift ($z\lesssim0.7$), at the few-percent level, but becomes more relevant at higher redshift ($z\gtrsim0.7$). Baryonic modifications remain sub-dominant outside the core, at about \(2\,\%\) beyond \(r\gtrsim0.3\,h^{-1}\,\mathrm{Mpc}\). The framework delivers radial profile corrections with uncertainties, combining projection-induced selection bias, baryonic physics, and miscentring, to control systematics in Euclid DR1 cluster cosmology. (abridged)

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Euclid: Systematic uncertainties from the halo mass conversion on galaxy cluster number count data analyses

The large catalogues of galaxy clusters expected from the Euclid survey will enable cosmological analyses of cluster number counts that require accurate cosmological model predictions. One possibility is to use parametric fits calibrated against $N$-body simulations, that capture the cosmological parameter dependence of the halo mass function. Several studies have shown that this can be obtained through a calibration against haloes with spherical masses defined at the virial overdensity. In contrast, if different mass definitions are used for the HMF and the scaling relation, a mapping between them is required. Here, we investigate the impact of such a mapping on the cosmological parameter constraints inferred from galaxy cluster number counts. Using synthetic data from $N$-body simulations, we show that the standard approach, which relies on assuming a concentration-mass relation, can introduce significant systematic bias. In particular, depending on the mass definition and the relation assumed, this can lead to biased constraints at more than 2$σ$ level. In contrast, we find that in all the cases we have considered, the mass conversion based on the halo sparsity statistics result in a systematic bias smaller than the statistical error.

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Euclid: Exploring observational systematics in cluster cosmology -- a comprehensive analysis of cluster counts and clustering

This study explores the impact of observational and modelling systematic effects on cluster number counts and cluster clustering and provides model prescriptions for their joint analysis, in the context of the \Euclid survey. Using 1000 \Euclid-like cluster catalogues, we investigate the effect of systematic uncertainties on cluster summary statistics and their auto- and cross-covariance, and perform a likelihood analysis to evaluate their impact on cosmological constraints, with a focus on the matter density parameter $Ω_{\rm m}$ and on the power spectrum amplitude $σ_8$. Combining cluster clustering with number counts significantly improves cosmological constraints, with the figure of merit increasing by over 300\% compared to number counts alone. We confirm that the two probes are uncorrelated, and the cosmological constraints derived from their combination are almost insensitive to the cosmology dependence of the covariance. We find that photometric redshift uncertainties broaden cosmological posteriors by 20--30\%, while secondary effects like redshift-space distortions (RSDs) have a smaller impact on the posteriors -- 5\% for clustering alone, 10\% when combining probes -- but can significantly bias the constraints if neglected. We show that clustering data below $60\,h^{-1}\,$Mpc provides additional constraining power, while scales larger than acoustic oscillation scale add almost no information on $Ω_{\rm m}$ and $σ_8$ parameters. RSDs and photo-$z$ uncertainties also influence the number count covariance, with a significant impact, of about 15--20\%, on the parameter constraints.

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Euclid preparation: TBD. The impact of line-of-sight projections on the covariance between galaxy cluster multi-wavelength observable properties -- insights from hydrodynamic simulations

Cluster cosmology can benefit from combining multi-wavelength studies, which can benefit from characterising the correlation coefficients between different mass-observable relations. In this work, we aim to provide information on the scatter, the skewness, and the covariance of various mass-observable relations in galaxy clusters in cosmological hydrodynamic simulations. This information will help future analyses to better tackle accretion histories and projection effects and model mass observable relations for cosmology studies.We identify galaxy clusters in Magneticum Box2b simulations with mass $M_{\rm 200c}>10^{14} {\rm M}_\odot$ at redshift $z=0.24$ and $z=0.90$. Our analysis includes \Euclid-derived properties such as richness, stellar mass, lensing mass, and concentration. Additionally, we investigate complementary multi-wavelength data, including X-ray luminosity, integrated Compton-$y$ parameter, gas mass, and temperature. The impact of projection effects on mass-observable residuals and correlations is then examined. At intermediate redshift ($z=0.24$), projection effects impact lensing concentration, richness, and gas mass the most in terms of scatter and skewness of log-residuals of scaling relations. The contribution of projection effects can be significant enough to boost a spurious hot- vs. cold-baryons correlation and consequently hide underlying correlations due to halo accretion histories. At high redshift ($z=0.9$), the richness has a much lower scatter (of log-residuals), and the quantity that is most impacted by projection effects is the lensing mass. Lensing concentration reconstruction, in particular, is affected by deviations of the reduced-shear profile shape from the one derived by an NFW profile rather than interlopers in the line of sight.

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Feeding and feedback processes in the Spiderweb proto-intracluster medium

We present the detailed analysis of the thermal, diffuse emission of the proto-intracluster medium (ICM) detected in the halo of the Spiderweb Galaxy at z=2.16, within a radius of $\sim$ 150 kpc. We combined deep X-ray data from Chandra and millimeter observations of the Sunyaev-Zeldovich (SZ) effect obtained by ALMA. Thanks to independent measurements of the pressure profile from ALMA SZ observation and the electron density profile from the available X-ray data, we derived, for the first time, the temperature profile in the ICM of a z>2 protocluster. It reveals the presence of a strong cool core (comparable to the local ones) that may host a significant mass deposition flow, consistent with measured local star formation values. We also find mild evidence of an asymmetry in the X-ray surface brightness distribution, which may be tentatively associated with a cavity carved into the proto-ICM by the radio jets or, alternatively, may be due to the young dynamical status of the halo. The cooling time of baryons in the core of the Spiderweb Protocluster is estimated to be $\sim$ 0.1 Gyr, implying that the baryon cycle in the first stages of the protocluster formation is characterised by a high-duty cycle and a very active environment. In the case of the Spiderweb protocluster, we are witnessing the presence of a strongly peaked core that is possibily hosting a cooling flow with a mass deposition rate up to 250-1000 $M_{\odot}$/yr, responsible for feeding both the central supermassive black hole and the high star formation rate observed in the Spiderweb Galaxy. This phase is expected to be rapidly followed by active galactic nucleus feedback events, whose onset may have already left an imprint in the radio and X-ray appearance of the Spiderweb protocluster, eventually driving the ICM into a self-regulated, long-term evolution in less than one Gyr.

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Euclid preparation. L. Calibration of the linear halo bias in $Λ(ν)$CDM cosmologies

The Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric galaxy cluster survey. This paper focuses on enhancing the precision of halo bias (HB) predictions, which is crucial for deriving cosmological constraints from the clustering of galaxy clusters. Our study is based on the peak-background split (PBS) model linked to the halo mass function (HMF); it extends with a parametric correction to precisely align with results from an extended set of $N$-body simulations carried out with the OpenGADGET3 code. Employing simulations with fixed and paired initial conditions, we meticulously analyze the matter-halo cross-spectrum and model its covariance using a large number of mock catalogs generated with Lagrangian Perturbation Theory simulations with the PINOCCHIO code. This ensures a comprehensive understanding of the uncertainties in our HB calibration. Our findings indicate that the calibrated HB model is remarkably resilient against changes in cosmological parameters including those involving massive neutrinos. The robustness and adaptability of our calibrated HB model provide an important contribution to the cosmological exploitation of the cluster surveys to be provided by the Euclid mission. This study highlights the necessity of continuously refining the calibration of cosmological tools like the HB to match the advancing quality of observational data. As we project the impact of our model on cosmological constraints, we find that, given the sensitivity of the Euclid survey, a miscalibration of the HB could introduce biases in cluster cosmology analyses. Our work fills this critical gap, ensuring the HB calibration matches the expected precision of the Euclid survey. The implementation of our model is publicly available in https://github.com/TiagoBsCastro/CCToolkit.

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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.

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Euclid preparation. XXXIX. The effect of baryons on the Halo Mass Function

The Euclid photometric survey of galaxy clusters stands as a powerful cosmological tool, with the capacity to significantly propel our understanding of the Universe. Despite being sub-dominant to dark matter and dark energy, the baryonic component in our Universe holds substantial influence over the structure and mass of galaxy clusters. This paper presents a novel model to precisely quantify the impact of baryons on galaxy cluster virial halo masses, using the baryon fraction within a cluster as proxy for their effect. Constructed on the premise of quasi-adiabaticity, the model includes two parameters calibrated using non-radiative cosmological hydrodynamical simulations and a single large-scale simulation from the Magneticum set, which includes the physical processes driving galaxy formation. As a main result of our analysis, we demonstrate that this model delivers a remarkable one percent relative accuracy in determining the virial dark matter-only equivalent mass of galaxy clusters, starting from the corresponding total cluster mass and baryon fraction measured in hydrodynamical simulations. Furthermore, we demonstrate that this result is robust against changes in cosmological parameters and against varying the numerical implementation of the sub-resolution physical processes included in the simulations. Our work substantiates previous claims about the impact of baryons on cluster cosmology studies. In particular, we show how neglecting these effects would lead to biased cosmological constraints for a Euclid-like cluster abundance analysis. Importantly, we demonstrate that uncertainties associated with our model, arising from baryonic corrections to cluster masses, are sub-dominant when compared to the precision with which mass-observable relations will be calibrated using Euclid, as well as our current understanding of the baryon fraction within galaxy clusters.

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CHEX-MATE: Robust reconstruction of temperature profiles in galaxy clusters with XMM-Newton

The "Cluster HEritage project with \xmm: Mass Assembly and Thermodynamics at the Endpoint of structure formation" (CHEX-MATE) is a multi-year Heritage program, to obtain homogeneous XMM-Newton observations of a representative sample of 118 galaxy clusters. The observations are tuned to reconstruct the distribution of the main thermodynamic quantities of the ICM up to $R_{500}$ and to obtain individual mass measurements, via the hydrostatic-equilibrium equation, with a precision of 15-20%. Temperature profiles are a necessary ingredient for the scientific goals of the project and it is thus crucial to derive the best possible temperature measurements from our data. This is why we have built a new pipeline for spectral extraction and analysis of XMM-Newton data, based on a new physically motivated background model and on a Bayesian approach with Markov Chain Monte Carlo (MCMC) methods, that we present in this paper for the first time. We applied this new method to a subset of 30 galaxy clusters representative of the CHEX-MATE sample and show that we can obtain reliable temperature measurements up to regions where the source intensity is as low as 20% of the background, keeping systematic errors below 10%. We compare the median profile of our sample and the best fit slope at large radii with literature results and we find a good agreement with other measurements based on XMM-Newton data. Conversely, when we exclude from our analysis the most contaminated regions, where the source intensity is below 20 of the background, we find significantly flatter profiles, in agreement with predictions from numerical simulations and independent measurements with a combination of Sunyaev-Zeldovich and X-ray imaging data.

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Euclid preparation. XXXII. Evaluating the weak lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations

The photometric catalogue of galaxy clusters extracted from ESA Euclid data is expected to be very competitive for cosmological studies. Using state-of-the-art hydrodynamical simulations, we present systematic analyses simulating the expected weak lensing profiles from clusters in a variety of dynamic states and at wide range of redshifts. In order to derive cluster masses, we use a model consistent with the implementation within the Euclid Consortium of the dedicated processing function and find that, when jointly modelling mass and the concentration parameter of the Navarro-Frenk-White halo profile, the weak lensing masses tend to be, on average, biased low by 5-10% with respect to the true mass, up to z=0.5. Using a fixed value for the concentration $c_{200} = 3$, the mass bias is diminished below 5%, up to z=0.7, along with its relative uncertainty. Simulating the weak lensing signal by projecting along the directions of the axes of the moment of inertia tensor ellipsoid, we find that orientation matters: when clusters are oriented along the major axis, the lensing signal is boosted, and the recovered weak lensing mass is correspondingly overestimated. Typically, the weak lensing mass bias of individual clusters is modulated by the weak lensing signal-to-noise ratio, related to the redshift evolution of the number of galaxies used for weak lensing measurements: the negative mass bias tends to be larger toward higher redshifts. However, when we use a fixed value of the concentration parameter, the redshift evolution trend is reduced. These results provide a solid basis for the weak-lensing mass calibration required by the cosmological application of future cluster surveys from Euclid and Rubin.

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CHEX-MATE: Constraining the origin of the scatter in galaxy cluster radial X-ray surface brightness profiles

We investigate the statistical properties and the origin of the scatter within the spatially resolved surface brightness profiles of the CHEX-MATE sample, formed by 118 galaxy clusters selected via the SZ effect. These objects have been drawn from the Planck SZ catalogue and cover a wide range of masses, M$_{500}=[2-15] \times 10^{14} $M$_{\odot}$, and redshift, z=[0.05,0.6]. We derived the surface brightness and emission measure profiles and determined the statistical properties of the full sample. We found that there is a critical scale, R$\sim 0.4 R_{500}$, within which morphologically relaxed and disturbed object profiles diverge. The median of each sub-sample differs by a factor of $\sim 10$ at $0.05\,R_{500}$. There are no significant differences between mass- and redshift-selected sub-samples once proper scaling is applied. We compare CHEX-MATE with a sample of 115 clusters drawn from the The Three Hundred suite of cosmological simulations. We found that simulated emission measure profiles are systematically steeper than those of observations. For the first time, the simulations were used to break down the components causing the scatter between the profiles. We investigated the behaviour of the scatter due to object-by-object variation. We found that the high scatter, approximately 110%, at $R<0.4R_{500}$ is due to a genuine difference between the distribution of the gas in the core. The intermediate scale, $R_{500} =[0.4-0.8]$, is characterised by the minimum value of the scatter on the order of 0.56, indicating a region where cluster profiles are the closest to the self-similar regime. Larger scales are characterised by increasing scatter due to the complex spatial distribution of the gas. Also for the first time, we verify that the scatter due to projection effects is smaller than the scatter due to genuine object-by-object variation in all the considered scales. [abridged]

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Euclid preparation. XXIV. Calibration of the halo mass function in $Λ(ν)$CDM cosmologies

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quantity. We present a new calibration of the analytic HMF, at the level of accuracy and precision required for the uncertainty in this quantity to be subdominant with respect to other sources of uncertainty in recovering cosmological parameters from Euclid cluster counts. Our model is calibrated against a suite of N-body simulations using a Bayesian approach taking into account systematic errors arising from numerical effects in the simulation. First, we test the convergence of HMF predictions from different N-body codes, by using initial conditions generated with different orders of Lagrangian Perturbation theory, and adopting different simulation box sizes and mass resolution. Then, we quantify the effect of using different halo-finder algorithms, and how the resulting differences propagate to the cosmological constraints. In order to trace the violation of universality in the HMF, we also analyse simulations based on initial conditions characterised by scale-free power spectra with different spectral indexes, assuming both Einstein--de Sitter and standard $Λ$CDM expansion histories. Based on these results, we construct a fitting function for the HMF that we demonstrate to be sub-percent accurate in reproducing results from 9 different variants of the $Λ$CDM model including massive neutrinos cosmologies. The calibration systematic uncertainty is largely sub-dominant with respect to the expected precision of future mass-observation relations; with the only notable exception of the effect due to the halo finder, that could lead to biased cosmological inference.

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Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analysis response to variations of the covariance, and investigate the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the 2-point correlation function of galaxy clusters. By introducing few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with 10 per cent accuracy, with differences of about 5 per cent on the figure of merit of the cosmological parameters $Ω_{\rm m}$ and $σ_8$. Also, we find that the cosmology-dependence of the covariance adds valuable information that is not contained in the mean value, significantly improving the constraining power of cluster clustering. Finally, we find that the cosmological figure of merit can be further improved by taking mass binning into account. Our results have significant implications for the derivation of cosmological constraints from the 2-point clustering statistics of the Euclid survey of galaxy clusters.

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The 700 ks Chandra Spiderweb Field II: Evidence for inverse-Compton and thermal diffuse emission in the Spiderweb galaxy

We present the X-ray imaging and spectral analysis of the diffuse emission around the Spiderweb galaxy at z=2.16 and of its nuclear emission, based on a deep (700 ks) Chandra observation. We characterize the nuclear emission and computed the contamination in the surrounding regions due to the wings of the instrument PSF. Then, we quantified the extended emission within 12". We find that the Spiderweb galaxy hosts a mildly absorbed quasar, with modest yet significant variability on a timescale of ~1 year. We find that the emission in the jet regions is well described by a power law with Gamma~2-2.5, and it is consistent with IC upscattering of the CMB photons by the relativistic electrons. We also find a roughly symmetric, diffuse emission within a radius of ~100 kpc. This emission is consistent with thermal bremsstrahlung from a hot ICM with a temperature of kT=2.0_{-0.4}^{+0.7} keV, and a metallicity of Z<1.6Z_sun. The average electron density within 100 kpc is n_e=(1.51+-0.24+-0.14)E-2 cm^{-3}, corresponding to an upper limit for the total ICM mass of <=(1.76+-0.30+-0.17)E+12 M_sun (where error bars are 1 sigma statistical and systematic, respectively). If we apply hydrostatic equilibrium to the ICM, we measure a total gravitational mass M(<100 kpc)=(1.5^{+0.5}_{-0.3})E+13 M_sun and, extrapolating at larger radii, we estimate a total mass M_{500}=(3.2^{+1.1}_{-0.6})E+13 M_sun within a radius of r_{500}=(220+-30) kpc. We conclude that the Spiderweb protocluster shows significant diffuse emission within a radius of 12 arcsec, whose major contribution is provided by IC scattering associated with the radio jets. Outside the jet regions, we also identified thermal emission within a radius of ~100 kpc, revealing the presence of hot, diffuse baryons that may represent the embryonic virialized halo of the forming cluster.

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The Spiderweb proto-cluster is being magnetized by its central radio jet

We present deep broadband radio polarization observations of the Spiderweb radio galaxy (J1140-2629) in a galaxy proto-cluster at $z=2.16$. These yield the most detailed polarimetric maps yet made of a high redshift radio galaxy. The intrinsic polarization angles and Faraday Rotation Measures (RMs) reveal coherent magnetic fields spanning the $\sim60$ kpc length of the jets, while $\sim50$% fractional polarizations indicate these fields are well-ordered. Source-frame absolute RM values of $\sim1,000$ rad/m/m are typical, and values up to $\sim11,100$ rad/m/m are observed. The Faraday-rotating gas cannot be well-mixed with the synchrotron-emitting gas, or stronger-than-observed depolarization would occur. Nevertheless, an observed spatial coincidence between a localized absolute RM enhancement of $\sim1,100$ rad/m/m, a bright knot of Ly$α$ emission, and a deviation of the radio jet provide direct evidence for vigorous jet-gas interaction. We detect a large-scale RM gradient totaling $\sim1,000$s rad/m/m across the width of the jet, suggesting a net clockwise (as viewed from the AGN) toroidal magnetic field component exists at 10s-of-kpc-scales, which we speculate may be associated with the operation of a Poynting-Robertson cosmic battery. We conclude the RMs are mainly generated in a sheath of hot gas around the radio jet, rather than the ambient foreground proto-cluster gas. The estimated magnetic field strength decreases by successive orders-of-magnitude going from the jet hotspots ($\sim90$ $μ$G) to the jet sheath ($\sim10$ $μ$G) to the ambient intracluster medium ($\sim1$ $μ$G). Synthesizing our results, we propose that the Spiderweb radio galaxy is actively magnetizing its surrounding proto-cluster environment, with possible implications for theories of the origin and evolution of cosmic magnetic fields.

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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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