arXiv subjects

Nicola R. Napolitano

Publications and source records attributed to Nicola R. Napolitano.

At least 73 records · Page 4Linked to original sources

arXiv2020

Rejection criteria based on outliers in the KiDS photometric redshifts and PDF distributions derived by machine learning

The Probability Density Function (PDF) provides an estimate of the photometric redshift (zphot) prediction error. It is crucial for current and future sky surveys, characterized by strict requirements on the zphot precision, reliability and completeness. The present work stands on the assumption that properly defined rejection criteria, capable of identifying and rejecting potential outliers, can increase the precision of zphot estimates and of their cumulative PDF, without sacrificing much in terms of completeness of the sample. We provide a way to assess rejection through proper cuts on the shape descriptors of a PDF, such as the width and the height of the maximum PDF's peak. In this work we tested these rejection criteria to galaxies with photometry extracted from the Kilo Degree Survey (KiDS) ESO Data Release 4, proving that such approach could lead to significant improvements to the zphot quality: e.g., for the clipped sample showing the best trade-off between precision and completeness, we achieve a reduction in outliers fraction of $\simeq 75\%$ and an improvement of $\simeq 6\%$ for NMAD, with respect to the original data set, preserving the $\simeq 93\%$ of its content.

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arXiv2020

KiDS+VIKING+GAMA: Testing semi-analytic models of galaxy evolution with galaxy-galaxy-galaxy lensing

Several semi-analytic models (SAMs) try to explain how galaxies form, evolve and interact inside the dark matter large-scale structure. These SAMs can be tested by comparing their predictions for galaxy-galaxy-galaxy-lensing (G3L), which is weak gravitational lensing around galaxy pairs, with observations. We evaluate the SAMs by Henriques et al. (2015; H15) and by Lagos et al. (2012; L12), implemented in the Millennium Run, by comparing their predictions for G3L to observations at smaller scales than previous studies and also for pairs of lens galaxies from different populations. We compare the G3L signal predicted by the SAMs to measurements in the overlap of the Galaxy And Mass Assembly survey (GAMA), the Kilo-Degree Survey (KiDS), and the VISTA Kilo-degree Infrared Galaxy survey (VIKING), splitting lens galaxies into two colour and five stellar-mass samples. Using an improved G3L estimator, we measure the three-point correlation of the matter distribution for mixed lens pairs with galaxies from different samples, and unmixed lens pairs with galaxies from the same sample. Predictions by the H15 SAM agree with the observations for all colour-selected and all but one stellar-mass-selected sample with 95% confidence. Deviations occur for lenses with stellar masses below $9.5h^{-2}\mathrm{M}_\odot$ at scales below $0.2h^{-1}\mathrm{Mpc}$. Predictions by the L12 SAM for stellar-mass selected samples and red galaxies are significantly higher than observed, while the predicted signal for blue galaxy pairs is too low. The L12 SAM predicts more pairs of small stellar-mass and red galaxies than the H15 SAM and the observations, as well as fewer pairs of blue galaxies. Likely explanations are different treatments of environmental effects by the SAMs and different models of the initial mass function. We conclude that G3L provides a stringent test for models of galaxy formation and evolution.

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arXiv2020

Building the largest spectroscopic sample of ultra-compact massive galaxies with the Kilo Degree Survey

Ultra-compact massive galaxies UCMGs, i.e. galaxies with stellar masses $M_{*} > 8 \times 10^{10} M_{\odot}$ and effective radii $R_{e} < 1.5$ kpc, are very rare systems, in particular at low and intermediate redshifts. Their origin as well as their number density across cosmic time are still under scrutiny, especially because of the paucity of spectroscopically confirmed samples. We have started a systematic census of UCMG candidates within the ESO Kilo Degree Survey, together with a large spectroscopic follow-up campaign to build the largest possible sample of confirmed UCMGs. This is the third paper of the series and the second based on the spectroscopic follow-up program. Here, we present photometrical and structural parameters of 33 new candidates at redshifts $0.15 \lesssim z \lesssim 0.5$ and confirm 19 of them as UCMGs, based on their nominal spectroscopically inferred $M_{*}$ and $R_{e}$. This corresponds to a success rate of $\sim 58\%$, nicely consistent with our previous findings. The addition of these 19 newly confirmed objects, allows us to fully assess the systematics on the system selection, and finally reduce the number density uncertainties. Moreover, putting together the results from our current and past observational campaigns and some literature data, we build the largest sample of UCMGs ever collected, comprising 92 spectroscopically confirmed objects at $0.1 \lesssim z \lesssim 0.5$. This number raises to 116, allowing for a $3σ$ tolerance on the $M_{*}$ and $R_{e}$ thresholds for the UCMG definition. For all these galaxies we have estimated the velocity dispersion values at the effective radii which have been used to derive a preliminary mass-velocity dispersion correlation.

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arXiv2019

GAMA+KiDS: Alignment of galaxies in galaxy groups and its dependence on galaxy scale

Intrinsic galaxy alignments are a source of bias for weak lensing measurements as well as a tool for understanding galaxy formation and evolution. In this work, we measure the alignment of shapes of satellite galaxies, in galaxy groups, with respect to the brightest group galaxy (BGG), as well as alignments of the BGG shape with the satellite positions, using the highly complete Galaxy And Mass Assembly (GAMA) spectroscopic survey and deep imaging from the Kilo Degree Survey. We control systematic errors with dedicated image simulations and measure accurate shapes using the DEIMOS shape measurement method. We find a significant satellite radial alignment signal, which vanishes at large separations from the BGG. We do not identify any strong trends of the signal with galaxy absolute magnitude or group mass. The alignment signal is dominated by red satellites. We also find that the outer regions of galaxies are aligned more strongly than their inner regions, by varying the radial weight employed during the shape measurement process. This behaviour is evident for both red and blue satellites. BGGs are also found to be aligned with satellite positions, with this alignment being stronger when considering the innermost satellites, using red BGGs and the shape of the outer region of the BGG. Lastly, we measure the global intrinsic alignment signal in the GAMA sample for two different radial weight functions and find no significant difference.

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arXiv2019

KiDS-SQuaD II: Machine learning selection of bright extragalactic objects to search for new gravitationally lensed quasars

The KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD) aims at finding as many previously undiscovered gravitational lensed quasars as possible in the Kilo Degree Survey. This is the second paper of this series where we present a new, automatic object classification method based on machine learning technique. The main goal of this paper is to build a catalogue of bright extragalactic objects (galaxies and quasars), from the KiDS Data Release 4, with a minimum stellar contamination, preserving the completeness as much as possible, to then apply morphological methods to select reliable gravitationally lensed (GL) quasar candidates. After testing some of the most used machine learning algorithms, decision trees based classifiers, we decided to use CatBoost, that was specifically trained with the aim of creating a sample of extragalactic sources as clean as possible from stars. We discuss the input data, define the training sample for the classifier, give quantitative estimates of its performances, and finally describe the validation results with Gaia DR2, AllWISE, and GAMA catalogues. We have built and make available to the scientific community the KiDS Bright EXtraGalactic Objects catalogue (KiDS-BEXGO), specifically created to find gravitational lenses. This is made of $\approx6$ millions of sources classified as quasars ($\approx 200\,000$) and galaxies ($\approx 5.7$M), up to $r<22^m$. From this catalog we selected 'Multiplets': close pairs of quasars or galaxies surrounded by at least one quasar, presenting the 12 most reliable gravitationally lensed quasar candidates, to demonstrate the potential of the catalogue, which will be further explored in a forthcoming paper. We compared our search to the previous one, presented in the first paper from this series, showing that employing a machine learning method decreases the stars-contaminators within the GL candidates.

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arXiv2019

Halo mass estimates from the Globular Cluster populations of 175 Low Surface Brightness Galaxies in the Fornax Cluster

The halo masses $M_{halo}$ of low surface brightness (LSB) galaxies are critical measurements for understanding their formation processes. One promising method to estimate a galaxy's $M_{halo}$ is to exploit the empirical scaling relation between $M_{halo}$ and the number of associated globular clusters ($N_{\mathrm{GC}}$). We use a Bayesian mixture model approach to measure $N_{\mathrm{GC}}$ for 175 LSB ($23\leq\left\langle μ_{e,r} \right\rangle [\mathrm{mag\ arcsec}^{-2}]\leq 28$) galaxies in the Fornax cluster using the Fornax Deep Survey (FDS) data; this is the largest sample of low mass galaxies so-far analysed for this kind of study. The proximity of the Fornax cluster means that we can measure galaxies with much smaller physical sizes ($0.3\leq r_{e,r}\ [\mathrm{kpc}]\leq 9.5$) compared to previous studies of the GC systems of LSB galaxies, probing stellar masses down to $M_{*}\sim10^{5}\mathrm{M_{\odot}}$. The sample also includes \nudg\ ultra-diffuse galaxies (UDGs), with projected $r$-band half-light radii greater than 1.5 kpc. Our results are consistent with an extrapolation of the $M_{*}-M_{halo}$ relation predicted from abundance matching. In particular, our UDG measurements are consistent with dwarf sized halos, having typical masses between $10^{10}$ and $10^{11}\mathrm{M_{\odot}}$. Overall, our UDG sample is statistically indistinguishable from smaller LSB galaxies in the same magnitude range. We do not find any candidates likely to be as rich as some of those found in the Coma cluster. We suggest that environment might play a role in producing GC-rich LSB galaxies.

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arXiv2018

Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Density Functions (PDFs) is still an open problem. First, because it is difficult to accurately assess the contribution from different sources of errors, namely internal to the method itself and from the photometric features defining the available parameter space. Second, because the problem of defining a robust statistical method, always able to quantify and qualify the PDF estimation validity, is still an open issue. We present a comparison among PDFs obtained using three different methods on the same data set: two ML techniques, METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts) and ANNz2, plus the spectral energy distribution template fitting method, BPZ. The photometric data were extracted from the KiDS (Kilo Degree Survey) ESO Data Release 3, while the spectroscopy was obtained from the GAMA (Galaxy and Mass Assembly) Data Release 2. The statistical evaluation of both individual and stacked PDFs was done through quantitative and qualitative estimators, including a dummy PDF, useful to verify whether different statistical estimators can correctly assess PDF quality. We conclude that, in order to quantify the reliability and accuracy of any zphot PDF method, a combined set of statistical estimators is required.

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arXiv2018

VEGAS: A VST Early-type GAlaxy Survey. III. Mapping the galaxy structure, interactions and intragroup light in the NGC 5018 group

Most of the galaxies in the Universe at present day are in groups, which are key to understanding the galaxy evolution. In this work we present a new deep mosaic of 1.2 x 1.0 square degrees of the group of galaxies centered on NGC 5018, acquired at the ESO VLT Survey Telescope. We use u, g, r images to analyse the structure of the group members and to estimate the intra-group light. Taking advantage of the deep and multiband photometry and of the large field of view of the VST telescope, we studied the structure of the galaxy members and the faint features into the intra-group space and we give an estimate of the intragroup diffuse light in the NGC 5018 group of galaxies. We found that ~ 41% of the total g-band luminosity of the group is in the form of intragroup light (IGL). The IGL has a (g - r) color consistent with those of other galaxies in the group, indicating that the stripping leading to the formation of IGL is ongoing. From the study of this group we can infer that there are at least two different interactions involving the group members: one between NGC 5018 and NGC 5022, which generates the tails and ring-like structures detected in the light, and another between NGC 5022 and MCG-03-34-013 that have produced the HI tail. A minor merging event also happened in the formation history of NGC 5018 that have perturbed the inner structure of this galaxy.

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arXiv2018

Weak Lensing Study in VOICE Survey I: Shear Measurement

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is a Guaranteed Time program carried out with the ESO/VST telescope to provide deep optical imaging over two 4 deg$^2$ patches of the sky centred on the CDFS and ES1 pointings. We present the cosmic shear measurement over the 4 deg$^2$ covering the CDFS region in the $r$-band using LensFit. Each of the four tiles of 1 deg$^2$ has more than one hundred exposures, of which more than 50 exposures passed a series of image quality selection criteria for weak lensing study. The $5σ$ limiting magnitude in $r$- band is 26.1 for point sources, which is $\sim$1 mag deeper than other weak lensing survey in the literature (e.g. the Kilo Degree Survey, KiDS, at VST). The photometric redshifts are estimated using the VOICE $u,g,r,i$ together with near-infrared VIDEO data $Y,J,H,K_s$. The mean redshift of the shear catalogue is 0.87, considering the shear weight. The effective galaxy number density is 16.35 gal/arcmin$^2$, which is nearly twice the one of KiDS. The performance of LensFit on such a deep dataset was calibrated using VOICE-like mock image simulations. Furthermore, we have analyzed the reliability of the shear catalogue by calculating the star-galaxy cross-correlations, the tomographic shear correlations of two redshift bins and the contaminations of the blended galaxies. As a further sanity check, we have constrained cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. For a flat $Λ$CDM model we have obtained $Σ_8$ = $σ_8(Ω_m/0.3)^{0.5}$ = $0.68^{+0.11}_{-0.15}$.

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arXiv2018

Galaxy and Mass Assembly (GAMA): Variation in Galaxy Structure Across the Green Valley

Using a sample of 472 local Universe (z<0.06) galaxies in the stellar mass range 10.25 < log M*/M_sun < 10.75, we explore the variation in galaxy structure as a function of morphology and galaxy colour. Our sample of galaxies is sub-divided into red, green and blue colour groups and into elliptical and non-elliptical (disk-type) morphologies. Using KiDS and VIKING derived postage stamp images, a group of eight volunteers visually classified bars, rings, morphological lenses, tidal streams, shells and signs of merger activity for all systems. We find a significant surplus of rings ($2.3σ$) and lenses ($2.9σ$) in disk-type galaxies as they transition across the green valley. Combined, this implies a joint ring/lens green valley surplus significance of $3.3σ$ relative to equivalent disk-types within either the blue cloud or the red sequence. We recover a bar fraction of ~44% which remains flat with colour, however, we find that the presence of a bar acts to modulate the incidence of rings and (to a lesser extent) lenses, with rings in barred disk-type galaxies more common by ~20-30 percentage points relative to their unbarred counterparts, regardless of colour. Additionally, green valley disk-type galaxies with a bar exhibit a significant $3.0σ$ surplus of lenses relative to their blue/red analogues. The existence of such structures rules out violent transformative events as the primary end-of-life evolutionary mechanism, with a more passive scenario the favoured candidate for the majority of galaxies rapidly transitioning across the green valley.

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arXiv2017

Large Synoptic Survey Telescope Galaxies Science Roadmap

The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of galaxies, dark matter, and black holes over cosmic time. The LSST Galaxies Science Collaboration has identified a host of preparatory research tasks required to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. This Galaxies Science Roadmap provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The Galaxies Science Roadmap will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era.

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arXiv2017

Halo ellipticity of GAMA galaxy groups from KiDS weak lensing

We constrain the average halo ellipticity of ~2 600 galaxy groups from the Galaxy And Mass Assembly (GAMA) survey, using the weak gravitational lensing signal measured from the overlapping Kilo Degree Survey (KiDS). To do so, we quantify the azimuthal dependence of the stacked lensing signal around seven different proxies for the orientation of the dark matter distribution, as it is a priori unknown which one traces the orientation best. On small scales, the major axis of the brightest group/cluster member (BCG) provides the best proxy, leading to a clear detection of an anisotropic signal. In order to relate that to a halo ellipticity, we have to adopt a model density profile. We derive new expressions for the quadrupole moments of the shear field given an elliptical model surface mass density profile. Modeling the signal with an elliptical Navarro-Frenk-White (NFW) profile on scales < 250 kpc, which roughly corresponds to half the virial radius, and assuming that the BCG is perfectly aligned with the dark matter, we find an average halo ellipticity of e_h=0.38 +/- 0.12. This agrees well with results from cold-dark-matter-only simulations, which typically report values of e_h ~ 0.3. On larger scales, the lensing signal around the BCGs does not trace the dark matter distribution well, and the distribution of group satellites provides a better proxy for the halo's orientation instead, leading to a 3--4 sigma detection of a non-zero halo ellipticity at scales between 250 kpc and 750 kpc. Our results suggest that the distribution of stars enclosed within a certain radius forms a good proxy for the orientation of the dark matter within that radius, which has also been observed in hydrodynamical simulations.

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arXiv2017

Cooperative photometric redshift estimation

In the modern galaxy surveys photometric redshifts play a central role in a broad range of studies, from gravitational lensing and dark matter distribution to galaxy evolution. Using a dataset of about 25,000 galaxies from the second data release of the Kilo Degree Survey (KiDS) we obtain photometric redshifts with five different methods: (i) Random forest, (ii) Multi Layer Perceptron with Quasi Newton Algorithm, (iii) Multi Layer Perceptron with an optimization network based on the Levenberg-Marquardt learning rule, (iv) the Bayesian Photometric Redshift model (or BPZ) and (v) a classical SED template fitting procedure (Le Phare). We show how SED fitting techniques could provide useful information on the galaxy spectral type which can be used to improve the capability of machine learning methods constraining systematic errors and reduce the occurrence of catastrophic outliers. We use such classification to train specialized regression estimators, by demonstrating that such hybrid approach, involving SED fitting and machine learning in a single collaborative framework, is capable to improve the overall prediction accuracy of photometric redshifts.

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arXiv2016

A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data

Photometric redshifts (photo-z's) are fundamental in galaxy surveys to address different topics, from gravitational lensing and dark matter distribution to galaxy evolution. The Kilo Degree Survey (KiDS), i.e. the ESO public survey on the VLT Survey Telescope (VST), provides the unprecedented opportunity to exploit a large galaxy dataset with an exceptional image quality and depth in the optical wavebands. Using a KiDS subset of about 25,000 galaxies with measured spectroscopic redshifts, we have derived photo-z's using i) three different empirical methods based on supervised machine learning, ii) the Bayesian Photometric Redshift model (or BPZ), and iii) a classical SED template fitting procedure (Le Phare). We confirm that, in the regions of the photometric parameter space properly sampled by the spectroscopic templates, machine learning methods provide better redshift estimates, with a lower scatter and a smaller fraction of outliers. SED fitting techniques, however, provide useful information on the galaxy spectral type which can be effectively used to constrain systematic errors and to better characterize potential catastrophic outliers. Such classification is then used to specialize the training of regression machine learning models, by demonstrating that a hybrid approach, involving SED fitting and machine learning in a single collaborative framework, can be effectively used to improve the accuracy of photo-z estimates.

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arXiv2016

A discrete chemo-dynamical model of the giant elliptical galaxy NGC 5846: dark matter fraction, internal rotation and velocity anisotropy out to six effective radii

We construct a suite of discrete chemo-dynamical models of the giant elliptical galaxy NGC 5846. These models are a powerful tool to constrain both the mass distribution and internal dynamics of multiple tracer populations. We use Jeans models to simultaneously fit stellar kinematics within the effective radius $R_{\rm e}$, planetary nebula (PN) radial velocities out to $3\, R_{\rm e}$, and globular cluster (GC) radial velocities and colours out to $6\,R_{\rm e}$. The best-fitting model is a cored DM halo which contributes $\sim 10\%$ of the total mass within $1\,R_{\rm e}$, and $67\% \pm 10\%$ within $6\,R_{\rm e}$, although a cusped DM halo is also acceptable. The red GCs exhibit mild rotation with $v_{\rm max}/σ_0 \sim 0.3$ in the region $R > \,R_{\rm e}$, aligned with but counter-rotating to the stars in the inner parts, while the blue GCs and PNe kinematics are consistent with no rotation. The red GCs are tangentially anisotropic, the blue GCs are mildly radially anisotropic, and the PNe vary from radially to tangentially anisotropic from the inner to the outer region. This is confirmed by general made-to-measure models. The tangential anisotropy of the red GCs in the inner regions could stem from the preferential destruction of red GCs on more radial orbits, while their outer tangential anisotropy -- similar to the PNe in this region -- has no good explanation. The mild radial anisotropy of the blue GCs is consistent with an accretion scenario.

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arXiv2016

Dependence of GAMA galaxy halo masses on the cosmic web environment from 100 square degrees of KiDS weak lensing data

Galaxies and their dark matter haloes are part of a complex network of mass structures, collectively called the cosmic web. Using the tidal tensor prescription these structures can be classified into four cosmic environments: voids, sheets, filaments and knots. As the cosmic web may influence the formation and evolution of dark matter haloes and the galaxies they host, we aim to study the effect of these cosmic environments on the average mass of galactic haloes. To this end we measure the galaxy-galaxy lensing profile of 91,195 galaxies, within 0.039 < z < 0.263, from the spectroscopic Galaxy And Mass Assembly (GAMA) survey, using ~100 square degrees of overlapping data from the Kilo-Degree Survey (KiDS). In each of the four cosmic environments we model the contributions from group centrals, satellites and neighbouring groups to the stacked galaxy-galaxy lensing profiles. After correcting the lens samples for differences in the stellar mass distribution, we find no dependence of the average halo mass of central galaxies on their cosmic environment. We do find a significant increase in the average contribution of neighbouring groups to the lensing profile in increasingly dense cosmic environments. We show, however, that the observed effect can be entirely attributed to the galaxy density at much smaller scales (within 4 Mpc/h), which is correlated with the density of the cosmic environments. Within our current uncertainties we find no direct dependence of galaxy halo mass on their cosmic environment.

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arXiv2015

The first and second data releases of the Kilo-Degree Survey

The Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will image 1500 square degrees in four filters (ugri), and together with its near-infrared counterpart VIKING will produce deep photometry in nine bands. Designed for weak lensing shape and photometric redshift measurements, the core science driver of the survey is mapping the large-scale matter distribution in the Universe back to a redshift of ~0.5. Secondary science cases are manifold, covering topics such as galaxy evolution, Milky Way structure, and the detection of high-redshift clusters and quasars. KiDS is an ESO Public Survey and dedicated to serving the astronomical community with high-quality data products derived from the survey data, as well as with calibration data. Public data releases will be made on a yearly basis, the first two of which are presented here. For a total of 148 survey tiles (~160 sq.deg.) astrometrically and photometrically calibrated, coadded ugri images have been released, accompanied by weight maps, masks, source lists, and a multi-band source catalog. A dedicated pipeline and data management system based on the Astro-WISE software system, combined with newly developed masking and source classification software, is used for the data production of the data products described here. The achieved data quality and early science projects based on the data products in the first two data releases are reviewed in order to validate the survey data. Early scientific results include the detection of nine high-z QSOs, fifteen candidate strong gravitational lenses, high-quality photometric redshifts and galaxy structural parameters for hundreds of thousands of galaxies. (Abridged)

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arXiv2015

Machine Learning based photometric redshifts for the KiDS ESO DR2 galaxies

We estimated photometric redshifts (zphot) for more than 1.1 million galaxies of the ESO Public Kilo-Degree Survey (KiDS) Data Release 2. KiDS is an optical wide-field imaging survey carried out with the VLT Survey Telescope (VST) and the OmegaCAM camera, which aims at tackling open questions in cosmology and galaxy evolution, such as the origin of dark energy and the channel of galaxy mass growth. We present a catalogue of photometric redshifts obtained using the Multi Layer Perceptron with Quasi Newton Algorithm (MLPQNA) model, provided within the framework of the DAta Mining and Exploration Web Application REsource (DAMEWARE). These photometric redshifts are based on a spectroscopic knowledge base which was obtained by merging spectroscopic datasets from GAMA (Galaxy And Mass Assembly) data release 2 and SDSS-III data release 9. The overall 1 sigma uncertainty on Delta z = (zspec - zphot) / (1+ zspec) is ~ 0.03, with a very small average bias of ~ 0.001, a NMAD of ~ 0.02 and a fraction of catastrophic outliers (| Delta z | > 0.15) of ~0.4%.

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