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Matteo Maturi

Publications and source records attributed to Matteo Maturi.

At least 37 records · Page 2Linked to original sources

AMICO galaxy clusters in KiDS-DR3: constraints on $Λ$CDM from extreme value statistics

We constrain the $Λ$CDM cosmological parameter $σ_{8}$ by applying the extreme value statistics for galaxy cluster mass on the AMICO KiDS-DR3 catalog. We sample the posterior distribution of the parameters by considering the likelihood of observing the largest cluster mass value in a sample of $N_{\textrm{obs}} = 3644$ clusters with intrinsic richness $λ^{*} > 20$ in the redshift range $z\in[0.10, 0.60]$. We obtain $σ_{8}=0.90_{-0.18}^{+0.20}$, consistent within $1σ$ with the measurements obtained by the Planck collaboration and with previous results from cluster cosmology exploiting AMICO KiDS-DR3. The constraints could improve by applying this method to forthcoming missions, such as $\textit{Euclid}$ and LSST, which are expected to deliver thousands of distant and massive clusters.

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Exploring the mass and redshift dependence of the cluster pressure profile with stacks on thermal SZ maps

We provide novel constraints on the parameters defining the universal pressure profile (UPP) within clusters of galaxies, and explore their dependence on the cluster mass and redshift, from measurements of Sunyaev-Zel'dovich Compton-$y$ profiles. We employ both the $\textit{Planck}$ 2015 MILCA and the ACT-DR4 $y$ maps over the common $\sim 2,100\,\text{deg}^2$ footprint. We combine existing cluster catalogs based on KiDS, SDSS and DESI observations, for a total of 23,820 clusters spanning the mass range $10^{14.0}\,\text{M}_{\odot}<M_{500}<10^{15.1}\,\text{M}_{\odot}$ and the redshift range $0.02<z<0.98$. We split the clusters into three independent bins in mass and redshift; for each combination we detect the stacked SZ cluster signal and extract the mean $y$ angular profile. The latter is predicted theoretically adopting a halo model framework, and MCMCs are employed to estimate the UPP parameters, the hydrostatic mass bias $b_{\rm h}$ and possible cluster miscentering effects. We constrain $[P_0,c_{500},α,β]$ to $[5.9,2.0,1.8,4.9]$ with $\textit{Planck}$ and to $[3.8,1.3,1.0,4.4]$ with ACT using the full cluster sample, in agreement with previous findings. We do not find any compelling evidence for a residual mass or redshift dependence, thus expanding the validity of the cluster pressure profile over much larger $M_{500}$ and $z$ ranges; this is the first time the model has been tested on such a large (complete and representative) cluster sample. Finally, we obtain loose constraints on the hydrostatic mass bias in the range 0.2-0.3, again in broad agreement with previous works.

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Properties and observables of massive galaxies in self-interacting dark matter cosmologies

We use hydrodynamical cosmological simulations to test the differences between cold and self-interacting dark matter models (CDM and SIDM) in the mass range of massive galaxies ($10^{12}M_{\odot}h^{-1} 10^{13}M_{\odot}h^{-1}$) show cored profiles, while the least massive ones ($M<10^{12.5}M_{\odot}h^{-1}$) have cuspier profiles. Finally, we compare the predictions of our simulations to observational results, by looking at the dark matter fractions and the distribution of strong lensing Einstein radii. We find that in SIDM the DM-fractions decrease more rapidly with increasing stellar mass than in CDM, leading to lower fractions at $M_{*}>10^{11}M_{\odot}$, a distinctive signature of SIDM. At the same time, the distribution of Einstein radii, derived from both CDM and SIDM hydro runs, is comparable to observed samples of strong lenses with $M>10^{13}M_{\odot}h^{-1}$. We conclude that the interplay between self-interaction and baryons can greatly reduce the expected differences between CDM and SIDM models at this mass scale, and that techniques able to separate the dark and luminous mass in the inner regions of galaxies are needed to constrain self-interactions.

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Rubin-Euclid Derived Data Products: Initial Recommendations

This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an initial set of Derived Data products (DDPs) that could realize the science goals enabled by joint processing. All interested Rubin and Euclid data rights holders were invited to contribute via an online discussion forum and a series of virtual meetings. Strong interest in enhancing science with joint DDPs emerged from across a wide range of astrophysical domains: Solar System, the Galaxy, the Local Volume, from the nearby to the primaeval Universe, and cosmology.

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AMICO galaxy clusters in KiDS-DR3: Measurement of the halo bias and power spectrum normalization from a stacked weak lensing analysis

Galaxy clusters are biased tracers of the underlying matter density field. At very large radii beyond about 10 Mpc/\textit{h}, the shear profile shows evidence of a second-halo term. This is related to the correlated matter distribution around galaxy clusters and proportional to the so-called halo bias. We present an observational analysis of the halo bias-mass relation based on the AMICO galaxy cluster catalog, comprising around 7000 candidates detected in the third release of the KiDS survey. We split the cluster sample into 14 redshift-richness bins and derive the halo bias and the virial mass in each bin by means of a stacked weak lensing analysis. The observed halo bias-mass relation and the theoretical predictions based on the $Λ$CDM standard cosmological model show an agreement within $2σ$. The mean measurements of bias and mass over the full catalog give $M_{200c} = (4.9 \pm 0.3) \times 10^{13} M_{\odot}/\textit{h}$ and $b_h σ_8^2 = 1.2 \pm 0.1$. With the additional prior of a bias-mass relation from numerical simulations, we constrain the normalization of the power spectrum with a fixed matter density $Ω_m = 0.3$, finding $σ_8 = 0.63 \pm 0.10$.

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AMICO galaxy clusters in KiDS-DR3: the impact of estimator statistics on the luminosity-mass scaling relation

As modern-day precision cosmology aims for statistical uncertainties of the percent level or lower, it becomes increasingly important to reconsider estimator assumptions at each step of the process, and their consequences on the statistical variability of the scientific results. We compare $L^1$ regression statistics to the weighted mean, the canonical $L^2$ method based on Gaussian assumptions, for inference of the weak gravitational shear signal from a catalog of background ellipticity measurements around a sample of clusters, in many recent analyses a standard step in the process. We use the shape measurements of background sources around 6925 AMICO clusters detected in the KiDS 3rd data release. We investigate the robustness of our results and the dependence of uncertainties on the signal-to-noise ratios of the background source detections. Using a halo model approach, we derive lensing masses from the estimated excess surface density profiles. The highly significant shear signal allows us to study the scaling relation between the $r$-band cluster luminosity $L_{200}$, and the derived lensing mass $M_{200}$. We show the results of the scaling relations derived in 13 bins in $L_{200}$, with a tightly constrained power law slope of $\sim 1.24\pm 0.08$. We observe a small, but significant relative bias of a few percent in the recovered excess surface density profiles between the two regression methods, which translates to a $1σ$ difference in $M_{200}$. The efficiency of $L^1$ is at least that of the weighted mean, relatively increasing with higher signal-to-noise shape measurements. Our results indicate the relevance of optimizing the estimator for infering the gravitational shear from a distribution of background ellipticities. The interpretation of measured relative biases can be gauged by deeper observations, while increased computation times remain feasible.

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AMICO galaxy clusters in KiDS-DR3: cosmological constraints from large-scale stacked weak lensing profiles

Context. The large-scale mass distribution around dark matter haloes hosting galaxy clusters provides sensitive cosmological information. Aims. In this work, we make use of a large photometric galaxy cluster sample, constructed from the public Third Data Release of the Kilo-Degree Survey, and the corresponding shear signal, to assess cluster masses and test the concordance $Λ$-cold dark matter ($Λ$CDM) model. In particular, we study the weak gravitational lensing effects on scales beyond the cluster virial radius, where the signal is dominated by correlated and uncorrelated matter density distributions along the line-of-sight. The analysed catalogue consists of 6962 galaxy clusters, in the redshift range $0.1 \leq z \leq 0.6$ and with signal-to-noise ratio larger than 3.5. Methods. We perform a full Bayesian analysis to model the stacked shear profiles of these clusters. The adopted likelihood function considers both the small-scale 1-halo term, used primarily to constrain the cluster structural properties, and the 2-halo term, that can be used to constrain cosmological parameters. Results. We find that the adopted modelling is successful to assess both the cluster masses and the total matter density parameter, $Ω_M$, when fitting shear profiles up to the largest available scales of 35 Mpc/h. Moreover, our results provide a strong observational evidence of the 2-halo signal in the stacked gravitational lensing of galaxy clusters, further demonstrating the reliability of this probe for cosmological studies. The main result of this work is a robust constraint on $Ω_M$, assuming a flat $Λ$CDM cosmology. We get $Ω_M = 0.29 \pm 0.02$, estimated from the full posterior probability distribution, consistent with the estimates from cosmic microwave background experiments.

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AMICO galaxy clusters in KiDS-DR3: galaxy population properties and their redshift dependence

A catalogue of galaxy clusters was obtained in an area of 414 sq deg up to a redshift $z\sim0.8$ from the Data Release 3 of the Kilo-Degree Survey (KiDS-DR3), using the Adaptive Matched Identifier of Clustered Objects (AMICO) algorithm. The catalogue and the calibration of the richness-mass relation were presented in two companion papers. Here we describe the selection of the cluster central galaxy and the classification of blue and red cluster members, and analyze the main cluster properties, such as the red/blue fraction, cluster mass, brightness and stellar mass of the central galaxy, and their dependence on redshift and cluster richness. We use the Illustris-TNG simulation, which represents the state-of-the-art cosmological simulation of galaxy formation, as a benchmark for the interpretation of the results. A good agreement with simulations is found at low redshifts ($z \le 0.4$), while at higher redshifts the simulations indicate a lower fraction of blue galaxies than what found in the KiDS-AMICO catalogue: we argue that this may be due to an underestimate of star-forming galaxies in the simulations. The selection of clusters with a larger magnitude difference between the two brightest central galaxies, which may indicate a more relaxed cluster dynamical status, improves the agreement between the observed and simulated cluster mass and stellar mass of the central galaxy. We also find that at a given cluster mass the stellar mass of blue central galaxies is lower than that of the red ones.

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CoMaLit -- VI. Intrinsic scatter in stacked relations. The weak lensing AMICO galaxy clusters in KiDS-DR3

Unbiased and precise mass calibration of galaxy clusters is crucial to fully exploit galaxy clusters as cosmological probes. Stacking of weak lensing signal allows us to measure observable-mass relations down to less massive halos halos without extrapolation. We propose a Bayesian inference method to constrain the intrinsic scatter of the mass proxy in stacked analyses. The scatter of the stacked data is rescaled with respect to the individual scatter based on the number of binned clusters. We apply this method to the galaxy clusters detected with the AMICO (Adaptive Matched Identifier of Clustered Objects) algorithm in the third data release of the Kilo-Degree Survey. The results confirm the optical richness as a low scatter mass proxy. Based on the optical richness and the calibrated weak lensing mass-richness relation, mass of individual objects down to ~10^13 solar masses can be estimated with a precision of ~20 per cent.

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The BUFFALO HST Survey

The Beyond Ultra-deep Frontier Fields and Legacy Observations (BUFFALO) is a 101 orbit + 101 parallel Cycle 25 Hubble Space Telescope Treasury program taking data from 2018-2020. BUFFALO will expand existing coverage of the Hubble Frontier Fields (HFF) in WFC3/IR F105W, F125W, and F160W and ACS/WFC F606W and F814W around each of the six HFF clusters and flanking fields. This additional area has not been observed by HST but is already covered by deep multi-wavelength datasets, including Spitzer and Chandra. As with the original HFF program, BUFFALO is designed to take advantage of gravitational lensing from massive clusters to simultaneously find high-redshift galaxies which would otherwise lie below HST detection limits and model foreground clusters to study properties of dark matter and galaxy assembly. The expanded area will provide a first opportunity to study both cosmic variance at high redshift and galaxy assembly in the outskirts of the large HFF clusters. Five additional orbits are reserved for transient followup. BUFFALO data including mosaics, value-added catalogs and cluster mass distribution models will be released via MAST on a regular basis, as the observations and analysis are completed for the six individual clusters.

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Model-Independent Determination of the Cosmic Growth Factor

Since the discovery of the accelerated cosmic expansion, one of the most important tasks in observational cosmology is to determine the nature of the dark energy. We should build our understanding on a minimum of assumptions in order to avoid biases from assumed cosmological models. The two most important functions describing the evolution of the universe and its structures are the expansion function E(a) and the linear growth factor D_+(a). The expansion function has been determined in previous papers in a model-independent way using distance moduli to type-Ia supernovae and assuming only a metric theory of gravity, spatial isotropy and homogeneity. Here, we extend this analysis in three ways: (1) We extend the data sample by combining the Pantheon measurements of type-Ia supernovae with measurements of baryonic acoustic oscillations; (2) we substantially simplify and generalise our method for reconstructing the expansion function; and (3) we use the reconstructed expansion function to determine the linear growth factor of cosmic structures, equally independent of specific assumptions on an underlying cosmological model other than the usual spatial symmetries. We show that the result is quite insensitive to the initial conditions for solving the growth equation, leaving the present-day matter-density parameter Ω_m0 as the only relevant parameter for an otherwise purely empirical and accurate determination of the growth factor.

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AMICO galaxy clusters in KiDS-DR3: weak-lensing mass calibration

We present the mass calibration for galaxy clusters detected with the AMICO code in KiDS DR3 data. The cluster sample comprises $\sim$ 7000 objects and covers the redshift range 0.1 < $z$ < 0.6. We perform a weak lensing stacked analysis by binning the clusters according to redshift and two different mass proxies provided by AMICO, namely the amplitude $A$ (measure of galaxy abundance through an optimal filter) and the richness $λ^*$ (sum of membership probabilities in a consistent radial and magnitude range across redshift). For each bin, we model the data as a truncated NFW profile plus a 2-halo term, taking into account uncertainties related to concentration and miscentring. From the retrieved estimates of the mean halo masses, we construct the $A$-$M_{200}$ and the $λ^*$-$M_{200}$ relations. The relations extend over more than one order of magnitude in mass, down to $M_{200} \sim 2 (5) \times 10^{13} M_\odot/h$ at $z$ = 0.2 (0.5), with small evolution in redshift. The logarithmic slope is $\sim 2.0$ for the $A$-mass relation, and $\sim 1.7$ for the $λ^*$-mass relation, consistent with previous estimations on mock catalogues and coherent with the different nature of the two observables.

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Detecting strongly lensed supernovae at z ~ 5-7 with LSST

Supernovae (SNe) could be powerful probes of the properties of stars and galaxies at high redshifts in future surveys. Wide fields and longer exposure times are required to offset diminishing star formation rates and lower fluxes to detect useful numbers of events at high redshift. In principle, the Large Synoptic Survey Telescope (LSST) could discover large numbers of early SNe because of its wide fields but only at lower redshifts because of its AB mag limit of ~ 24. But gravitational lensing by galaxy clusters and massive galaxies could boost flux from ancient SNe and allow LSST to detect them at earlier times. Here, we calculate detection rates for lensed SNe at z ~ 5 - 7 for LSST. We find that the LSST Wide Deep Fast survey could detect up to 120 lensed Population (Pop) I and II SNe but no lensed Pop III SNe. Deep-drilling programs in a single 10 square degree FoV could detect Pop I and II core-collapse SNe and Pop III pair-instability SNe at AB magnitudes of 27 - 28 and 26, respectively. An alternative deep survey over 80 nights with a one-year cadence could find ~ 8 Pop III SNe.

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AMICO galaxy clusters in KiDS-DR3: sample properties and selection function

We present the first catalogue of galaxy cluster candidates derived from the third data release of the Kilo Degree Survey (KiDS-DR3). The sample of clusters has been produced using the Adaptive Matched Identifier of Clustered Objects (AMICO) algorithm. In this analysis AMICO takes advantage of the luminosity and spatial distribution of galaxies only, not considering colours. In this way, we prevent any selection effect related to the presence or absence of the red-sequence in the clusters. The catalogue contains 7988 candidate galaxy clusters in the redshift range 0.1 3.5 with a purity approaching 95% over the entire redshift range. In addition to the catalogue of galaxy clusters we also provide a catalogue of galaxies with their probabilistic association to galaxy clusters. We quantify the sample purity, completeness and the uncertainties of the detection properties, such as richness, redshift, and position, by means of mock galaxy catalogues derived directly from the data. This preserves their statistical properties including photo-z uncertainties, unknown absorption across the survey, missing data, spatial correlation of galaxies and galaxy clusters. Being based on the real data, such mock catalogues do not have to rely on the assumptions on which numerical simulations and semi-analytic models are based on. This paper is the first of a series of papers in which we discuss the details and physical properties of the sample presented in this work.

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EasyCritics I: Efficient detection of strongly-lensing galaxy groups and clusters in wide-field surveys

We present EasyCritics, an algorithm to detect strongly-lensing groups and clusters in wide-field surveys without relying on a direct recognition of arcs. EasyCritics assumes that light traces mass in order to predict the most likely locations of critical curves from the observed fluxes of luminous red early-type galaxies in the line of sight. The positions, redshifts and fluxes of these galaxies constrain the idealized gravitational lensing potential as a function of source redshift up to five free parameters, which are calibrated on few known lenses. From the lensing potential, EasyCritics derives the critical curves for a given, representative source redshift. The code is highly parallelized, uses fast Fourier methods and, optionally, GPU acceleration in order to process large datasets efficiently. The search of a $\smash{1 \, \mathrm{deg}^2}$ field of view requires less than 1 minute on a modern quad-core CPU, when using a pixel resolution of $0.25''/\mathrm{px}$. In this first part of a paper series on EasyCritics, we describe the main underlying concepts and present a first demonstration on data from the Canada-France-Hawaii-Telescope Lensing Survey. We show that EasyCritics is able to identify known group- and cluster-scale lenses, including a cluster with two giant arc candidates that were previously missed by automated arc detectors.

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AMICO: optimised detection of galaxy clusters in photometric surveys

We present AMICO (Adaptive Matched Identifier of Clustered Objects), a new algorithm for the detection of galaxy clusters in photometric surveys. AMICO is based on the Optimal Filtering technique, which allows to maximise the signal-to-noise ratio of the clusters. In this work we focus on the new iterative approach to the extraction of cluster candidates from the map produced by the filter. In particular, we provide a definition of membership probability for the galaxies close to any cluster candidate, which allows us to remove its imprint from the map, allowing the detection of smaller structures. As demonstrated in our tests, this method allows the deblending of close-by and aligned structures in more than $50\%$ of the cases for objects at radial distance equal to $0.5 \times R_{200}$ or redshift distance equal to $2 \times σ_z$, being $σ_z$ the typical uncertainty of photometric redshifts. Running AMICO on mocks derived from N-body simulations and semi-analytical modelling of the galaxy evolution, we obtain a consistent mass-amplitude relation through the redshift range $0.3 < z < 1$, with a logarithmic slope $\sim 0.55$ and a logarithmic scatter $\sim 0.14$. The fraction of false detections is steeply decreasing with S/N, and negligible at S/N > 5.

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Weak gravitational lensing

According to the theory of general relativity, masses deflect light in a way similar to convex glass lenses. This gravitational lensing effect is astigmatic, giving rise to image distortions. These distortions allow to quantify cosmic structures statistically on a broad range of scales, and to map the spatial distribution of dark and visible matter. We summarise the theory of weak gravitational lensing and review applications to galaxies, galaxy clusters and larger-scale structures in the Universe.

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De-noising the galaxies in the Hubble XDF with EMPCA

We present a method to model optical images of galaxies using Expectation Maximization Principal Components Analysis (EMPCA). The method relies on the data alone and does not assume any pre-established model or fitting formula. It preserves the statistical properties of the sample, minimizing possible biases. The precision of the reconstructions appears to be suited for photometric, morphological and weak lensing analysis, as well as the realization of mock astronomical images. Here, we put some emphasis on the latter because weak gravitational lensing is entering a new phase in which systematics are becoming the major source of uncertainty. Accurate simulations are necessary to perform a reliable calibration of the ellipticity measurements on which the final bias depends. As a test case, we process $7038$ galaxies observed with the ACS/WFC stacked images of the Hubble eXtreme Deep Field (XDF) and measure the accuracy of the reconstructions in terms of their moments of brightness, which turn out to be comparable to what can be achieved with well-established weak-lensing algorithms.

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