arXiv subjects

Fabio Bellagamba

Publications and source records attributed to Fabio Bellagamba.

15 recordsLinked to original sources

arXiv2022

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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arXiv2021

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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arXiv2021

SEAGLE--II: Constraints on feedback models in galaxy formation from massive early type strong lens galaxies

We use nine different galaxy formation scenarios in ten cosmological simulation boxes from the EAGLE suite of ΛCDM hydrodynamical simulations to assess the impact of feedback mechanisms in galaxy formation and compare these to observed strong gravitational lenses. To compare observations with simulations, we create strong lenses with $M_\star$ > $10^{11}$ $M_\odot$ with the appropriate resolution and noise level, and model them with an elliptical power-law mass model to constrain their total mass density slope. We also obtain the mass-size relation of the simulated lens-galaxy sample. We find significant variation in the total mass density slope at the Einstein radius and in the projected stellar mass-size relation, mainly due to different implementations of stellar and AGN feedback. We find that for lens selected galaxies, models with either too weak or too strong stellar and/or AGN feedback fail to explain the distribution of observed mass-density slopes, with the counter-intuitive trend that increasing the feedback steepens the mass density slope around the Einstein radius ($\approx$ 3-10 kpc). Models in which stellar feedback becomes inefficient at high gas densities, or weaker AGN feedback with a higher duty cycle, produce strong lenses with total mass density slopes close to isothermal (i.e. -d log(ρ)/d log(r) $\approx$ 2.0) and slope distributions statistically agreeing with observed strong lens galaxies in SLACS and BELLS. Agreement is only slightly worse with the more heterogeneous SL2S lens galaxy sample. Observations of strong-lens selected galaxies thus appear to favor models with relatively weak feedback in massive galaxies.

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arXiv2020

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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arXiv2020

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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arXiv2019

The Strong Gravitational Lens Finding Challenge

Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of millions of images and deriving scientific results from them will require quantifying the efficiency and bias of any search method. To achieve these objectives automated methods must be developed. Because gravitational lenses are rare objects reducing false positives will be particularly important. We present a description and results of an open gravitational lens finding challenge. Participants were asked to classify 100,000 candidate objects as to whether they were gravitational lenses or not with the goal of developing better automated methods for finding lenses in large data sets. A variety of methods were used including visual inspection, arc and ring finders, support vector machines (SVM) and convolutional neural networks (CNN). We find that many of the methods will be easily fast enough to analyse the anticipated data flow. In test data, several methods are able to identify upwards of half the lenses after applying some thresholds on the lens characteristics such as lensed image brightness, size or contrast with the lens galaxy without making a single false-positive identification. This is significantly better than direct inspection by humans was able to do. (abridged)

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arXiv2019

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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arXiv2018

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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arXiv2018

SEAGLE - I: A pipeline for simulating and modeling strong lenses from cosmological hydrodynamic simulations

In this paper we introduce the SEAGLE (i.e. Simulating EAGLE LEnses) program, that approaches the study of galaxy formation through strong gravitational lensing, using a suite of high-resolution hydrodynamic simulations, Evolution and Assembly of GaLaxies and their Environments (EAGLE) project. We introduce the simulation and analysis pipeline and present the first set of results from our analysis of early-type galaxies. We identify and extract an ensemble of simulated lens galaxies and use the GLAMER ray-tracing lensing code to create mock lenses similar to those observed in the SLACS and SL2S surveys, using a range of source parameters and galaxy orientations, including observational effects such as the Point-Spread-Function (PSF), pixelization and noise levels, representative of single-orbit observations with the Hubble Space Telescope (HST) using the ACS-F814W filter. We subsequently model these mock lenses using the code LENSED, treating them in the same way as observed lenses. We also estimate the mass model parameters directly from the projected surface mass density of the simulated galaxy, using an identical mass model family. We perform a three-way comparison of all the measured quantities with real lenses. We find the average total density slope of EAGLE lenses, $t=2.26\; (0.25\; \rm{rms})$ to be higher than SL2S, $t=2.16$ or SLACS, $t=2.08$. We find a very strong correlation between the external shear ($γ$) and the complex ellipticity ($ε$), with $γ\sim ε/4$. This correlation indicates a degeneracy in the lens mass modeling. We also see a dispersion between lens modeling and direct fitting results, indicating systematical biases.

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arXiv2017

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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arXiv2016

Zooming into the Cosmic Horseshoe: new insights on the lens profile and the source shape

The gravitational lens SDSS J1148+1930, also known as the Cosmic Horseshoe, is one of the biggest and of the most detailed Einstein rings ever observed. We use the forward reconstruction method implemented in the lens fitting code Lensed to investigate with great detail the properties of the lens and of the background source. We model the lens with different mass distributions, focusing in particular on the determination of the slope of the dark matter component. The inherent degeneracy between the lens slope and the source size can be broken when we can isolate separate components of each lensed image, as in this case. For an elliptical power law model, $κ(r) \sim r^{-t}$, the results favour a flatter-than-isothermal slope with a maximum-likelihood value t = 0.08. Instead, when we consider the contribution of the baryonic matter separately, the maximum-likelihood value of the slope of the dark matter component is t = 0.31 or t = 0.44, depending on the assumed Initial Mass Function. We discuss the origin of this result by analysing in detail how the images and the sources change when the slope t changes. We also demonstrate that these slope values at the Einstein radius are not inconsistent with recent forecast from the theory of structure formation in the LambdaCDM model.

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arXiv2016

Lensed: a code for the forward reconstruction of lenses and sources from strong lensing observations

Robust modelling of strong lensing systems is fundamental to exploit the information they contain about the distribution of matter in galaxies and clusters. In this work, we present Lensed, a new code which performs forward parametric modelling of strong lenses. Lensed takes advantage of a massively parallel ray-tracing kernel to perform the necessary calculations on a modern graphics processing unit (GPU). This makes the precise rendering of the background lensed sources much faster, and allows the simultaneous optimisation of tens of parameters for the selected model. With a single run, the code is able to obtain the full posterior probability distribution for the lens light, the mass distribution and the background source at the same time. Lensed is first tested on mock images which reproduce realistic space-based observations of lensing systems. In this way, we show that it is able to recover unbiased estimates of the lens parameters, even when the sources do not follow exactly the assumed model. Then, we apply it to a subsample of the SLACS lenses, in order to demonstrate its use on real data. The results generally agree with the literature, and highlight the flexibility and robustness of the algorithm.

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arXiv2015

Searching for galaxy clusters in the VST-KiDS Survey

We present the methods and first results of the search for galaxy clusters in the Kilo Degree Survey (KiDS). The adopted algorithm and the criterium for selecting the member galaxies are illustrated. Here we report the preliminary results obtained over a small area (7 sq. degrees), and the comparison of our cluster candidates with those found in the RedMapper and SZ Planck catalogues; the analysis to a larger area (148 sq. degrees) is currently in progress. By the KiDS cluster search, we expect to increase the completeness of the clusters catalogue to z = 0.6-0.7 compared to RedMapper.

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arXiv2012

Accuracy of photometric redshifts for future weak lensing surveys from space

Photometric redshifts are a key tool to extract as much information as possible from planned cosmic shear experiments. In this work we aim to test the performances that can be achieved with observations in the near-infrared from space and in the optical from the ground. This is done by performing realistic simulations of multi-band observations of a patch of the sky, and submitting these mock images to software usually applied to real images to extract the photometry and then a redshift estimate for each galaxy. In this way we mimic the most relevant sources of uncertainty present in real data analysis, including blending and light pollution between galaxies. As an example we adopt the infrared setup of the ESA-proposed Euclid mission, while we simulate different observations in the optical, modifying filters, exposure times and seeing values. Finally, we consider directly some future ground-based experiments, such as LSST, Pan-Starrs and DES. The results highlight the importance of u-band observations, especially to discriminate between low (z < 0.5) and high (z ~ 3) redshifts, and the need for good observing sites, with seeing FWHM < 1. arcsec. The former of these indications clearly favours the LSST experiment as a counterpart for space observations, while for the other experiments we need to exclude at least 15 % of the galaxies to reach a precision in the photo-zs equal to $<\frac{σ_z}{1+z}>$ < 0.05.

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arXiv2010

Optimal filtering of optical and weak lensing data to search for galaxy clusters: application to the COSMOS field

Galaxy clusters are usually detected in blind optical surveys via suitable filtering methods. We present an optimal matched filter which maximizes their signal-to-noise ratio by taking advantage of the knowledge we have of their intrinsic physical properties and of the data noise properties. In this paper we restrict our application to galaxy magnitudes, positions and photometric redshifts if available, and we also apply the filter separately to weak lensing data. The method is suitable to be naturally extended to a multi-band approach which could include not only additional optical bands but also observables with different nature such as X-rays. For each detection, the filter provides its significance, an estimate for the richness and for the redshift even if photo-z are not given. The provided analytical error estimate is tested against numerical simulations. We finally apply our method to the COSMOS field and compare the results with previous cluster detections obtained with different methods. Our catalogue contains 27 galaxy clusters with minimal threshold at 3-sigma level including both optical and weak-lensing information.

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