arXiv subjects
Publications and source records attributed to S. Cavuoti.
We present new constraints on sub-GeV dark matter particles scattering off electrons in argon based on an analysis of ionization signal data from the DarkSide-50 detector.
We present results from an ongoing investigation using the Kilo Degree Survey (KiDS) on the VLT Survey Telescope (VST) to provide a census of ultra-compact massive galaxies (UCMGs), defined as galaxies with stellar masses $M_{\rm \star} > 8 \times 10^{10} \rm M_{\odot}$ and effective radii $R_{\rm e} < 1.5\,\rm kpc$. UCMGs, which are expected to have undergone very few merger events, provide a unique view on the accretion history of the most massive galaxies in the Universe. Over an effective sky area of nearly 330 square degrees, we select UCMG candidates from KiDS multi-colour images, which provide high quality structural parameters, photometric redshifts and stellar masses. Our sample of $\sim 1000$ photometrically selected UCMGs at $z < 0.5$ represents the largest sample of UCMG candidates assembled to date over the largest sky area. In this paper we present the first effort to obtain their redshifts using different facilities, starting with first results for 28 candidates with redshifts $z < 0.5$, obtained at NTT and TNG telescopes. We confirmed, as bona fide UCMGs, 19 out of the 28 candidates with new redshifts. A further 46 UCMG candidates are confirmed with literature spectroscopic redshifts (35 at $z < 0.5$), bringing the final cumulative sample of spectroscopically-confirmed lower-z UCMGs to 54 galaxies, which is the largest sample at redshifts below $0.5$. We use these spectroscopic redshifts to quantify systematic errors in our photometric selection, and use these to correct our UCMG number counts. We finally compare the results to independent datasets and simulations.
We present the results of a search for dark matter WIMPs in the mass range below 20 GeV/c^2 using a target of low-radioactivity argon. The data were obtained using the DarkSide-50 apparatus at Laboratori Nazionali del Gran Sasso (LNGS). The analysis is based on the ionization signal, for which the DarkSide-50 time projection chamber is fully efficient at 0.1 keVee. The observed rate in the detector at 0.5 keVee is about 1.5 events/keVee/kg/day and is almost entirely accounted for by known background sources. We obtain a 90% C.L. exclusion limit above 1.8 GeV/c^2 for the spin-independent cross section of dark matter WIMPs on nucleons, extending the exclusion region for dark matter below previous limits in the range 1.8-6 GeV/c^2.
We report the measurement of the longitudinal diffusion constant in liquid argon with the DarkSide-50 dual-phase time projection chamber. The measurement is performed at drift electric fields of 100 V/cm, 150 V/cm, and 200 V/cm using high statistics $^{39}$Ar decays from atmospheric argon. We derive an expression to describe the pulse shape of the electroluminescence signal (S2) in dual-phase TPCs. The derived S2 pulse shape is fit to events from the uppermost portion of the TPC in order to characterize the radial dependence of the signal. The results are provided as inputs to the measurement of the longitudinal diffusion constant DL, which we find to be (4.12 $\pm$ 0.04) cm$^2$/s for a selection of 140keV electron recoil events in 200V/cm drift field and 2.8kV/cm extraction field. To study the systematics of our measurement we examine datasets of varying event energy, field strength, and detector volume yielding a weighted average value for the diffusion constant of (4.09 $\pm$ 0.09) cm$^2$ /s. The measured longitudinal diffusion constant is observed to have an energy dependence, and within the studied energy range the result is systematically lower than other results in the literature.
We present a visual analytics tool, based on the VisIVO suite, to exploit a combination of all new-generation surveys of the Galactic Plane to study the star formation process of the Milky Way. The tool has been developed within the VIALACTEA project, founded by the 7th Framework Programme of the European Union, that creates a common forum for the major new-generation surveys of the Milky Way Galactic Plane from the near infrared to the radio, both in thermal continuum and molecular lines. Massive volumes of data are produced by space missions and ground-based facilities and the ability to collect and store them is increasing at a higher pace than the ability to analyze them. This gap leads to new challenges in the analysis pipeline to discover information contained in the data. Visual analytics focuses on handling these massive, heterogeneous, and dynamic volumes of information accessing the data previously processed by data mining algorithms and advanced analysis techniques with highly interactive visual interfaces offering scientists the opportunity for in-depth understanding of massive, noisy, and high-dimensional data.
We have obtained structural parameters of about 340,000 galaxies from the Kilo Degree Survey (KiDS) in 153 square degrees of data release 1, 2 and 3. We have performed a seeing convolved 2D single Sérsic fit to the galaxy images in the 4 photometric bands (u, g, r, i) observed by KiDS, by selecting high signal-to-noise ratio (S/N > 50) systems in every bands. We have classified galaxies as spheroids and disc-dominated by combining their spectral energy distribution properties and their Sérsic index. Using photometric redshifts derived from a machine learning technique, we have determined the evolution of the effective radius, \Re\ and stellar mass, \mst, versus redshift, for both mass complete samples of spheroids and disc-dominated galaxies up to z ~ 0.6. Our results show a significant evolution of the structural quantities at intermediate redshift for the massive spheroids ($\mbox{Log}\ M_*/M_\odot>11$, Chabrier IMF), while almost no evolution has found for less massive ones ($\mbox{Log}\ M_*/M_\odot < 11$). On the other hand, disc dominated systems show a milder evolution in the less massive systems ($\mbox{Log}\ M_*/M_\odot < 11$) and possibly no evolution of the more massive systems. These trends are generally consistent with predictions from hydrodynamical simulations and independent datasets out to redshift z ~ 0.6, although in some cases the scatter of the data is large to drive final conclusions. These results, based on 1/10 of the expected KiDS area, reinforce precedent finding based on smaller statistical samples and show the route toward more accurate results, expected with the the next survey releases.
We present a machine-learning photometric redshift analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the BPZ code, at least up to zphot<0.9 and r<23.5. At the bright end of r<20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared bands are added. While the fiducial four-band ugri setup gives a photo-z bias $δz=-2e-4$ and scatter $σ_z<0.022$ at mean z = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 $μ$, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives $δz<4e-5$ and $σ_z<0.019$. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimized for low-redshift studies such as galaxy-galaxy lensing, is limited to r<20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation.
In the last decade, astronomers have found a new type of supernova called `superluminous supernovae' (SLSNe) due to their high peak luminosity and long light-curves. These hydrogen-free explosions (SLSNe-I) can be seen to z~4 and therefore, offer the possibility of probing the distant Universe. We aim to investigate the possibility of detecting SLSNe-I using ESA's Euclid satellite, scheduled for launch in 2020. In particular, we study the Euclid Deep Survey (EDS) which will provide a unique combination of area, depth and cadence over the mission. We estimated the redshift distribution of Euclid SLSNe-I using the latest information on their rates and spectral energy distribution, as well as known Euclid instrument and survey parameters, including the cadence and depth of the EDS. We also applied a standardization method to the peak magnitudes to create a simulated Hubble diagram to explore possible cosmological constraints. We show that Euclid should detect approximately 140 high-quality SLSNe-I to z ~ 3.5 over the first five years of the mission (with an additional 70 if we lower our photometric classification criteria). This sample could revolutionize the study of SLSNe-I at z>1 and open up their use as probes of star-formation rates, galaxy populations, the interstellar and intergalactic medium. In addition, a sample of such SLSNe-I could improve constraints on a time-dependent dark energy equation-of-state, namely w(a), when combined with local SLSNe-I and the expected SN Ia sample from the Dark Energy Survey. We show that Euclid will observe hundreds of SLSNe-I for free. These luminous transients will be in the Euclid data-stream and we should prepare now to identify them as they offer a new probe of the high-redshift Universe for both astrophysics and cosmology.
Building on the successful experience in operating the DarkSide-50 detector, the DarkSide Collaboration is going to construct DarkSide-20k, a direct WIMP search detector using a two-phase Liquid Argon Time Projection Chamber (LArTPC) with an active (fiducial) mass of 23 t (20 t). The DarkSide-20k LArTPC will be deployed within a shield/veto with a spherical Liquid Scintillator Veto (LSV) inside a cylindrical Water Cherenkov Veto (WCV). Operation of DarkSide-50 demonstrated a major reduction in the dominant $^{39}$Ar background when using argon extracted from an underground source, before applying pulse shape analysis. Data from DarkSide-50, in combination with MC simulation and analytical modeling, shows that a rejection factor for discrimination between electron and nuclear recoils of $\gt3\times10^9$ is achievable. This, along with the use of the veto system, is the key to unlocking the path to large LArTPC detector masses, while maintaining an "instrumental background-free" experiment, an experiment in which less than 0.1 events (other than $ν$-induced nuclear recoils) is expected to occur within the WIMP search region during the planned exposure. DarkSide-20k will have ultra-low backgrounds than can be measured in situ. This will give sensitivity to WIMP-nucleon cross sections of $1.2\times10^{-47}$ cm$^2$ ($1.1\times10^{-46}$ cm$^2$) for WIMPs of $1$ TeV$/c^2$ ($10$ TeV$/c^2$) mass, to be achieved during a 5 yr run producing an exposure of 100 t yr free from any instrumental background. DarkSide-20k could then extend its operation to a decade, increasing the exposure to 200 t yr, reaching a sensitivity of $7.4\times10^{-48}$ cm$^2$ ($6.9\times10^{-47}$ cm$^2$) for WIMPs of $1$ TeV$/c^2$ ($10$ TeV$/c^2$) mass.
Hi-GAL is a large-scale survey of the Galactic plane, performed with Herschel in five infrared continuum bands between 70 and 500 $μ$m. We present a band-merged catalogue of spatially matched sources and their properties derived from fits to the spectral energy distributions (SEDs) and heliocentric distances, based on the photometric catalogs presented in Molinari et al. (2016a), covering the portion of Galactic plane $-71.0^{\circ}< \ell < 67.0^{\circ}$. The band-merged catalogue contains 100922 sources with a regular SED, 24584 of which show a 70 $μ$m counterpart and are thus considered proto-stellar, while the remainder are considered starless. Thanks to this huge number of sources, we are able to carry out a preliminary analysis of early stages of star formation, identifying the conditions that characterise different evolutionary phases on a statistically significant basis. We calculate surface densities to investigate the gravitational stability of clumps and their potential to form massive stars. We also explore evolutionary status metrics such as the dust temperature, luminosity and bolometric temperature, finding that these are higher in proto-stellar sources compared to pre-stellar ones. The surface density of sources follows an increasing trend as they evolve from pre-stellar to proto-stellar, but then it is found to decrease again in the majority of the most evolved clumps. Finally, we study the physical parameters of sources with respect to Galactic longitude and the association with spiral arms, finding only minor or no differences between the average evolutionary status of sources in the fourth and first Galactic quadrants, or between "on-arm" and "inter-arm" positions.
The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope. It aims to image 1500 square degrees in four filters (ugri). The core science driver is mapping the large-scale matter distribution in the Universe, using weak lensing shear and photometric redshift measurements. Further science cases include galaxy evolution, Milky Way structure, detection of high-redshift clusters, and finding rare sources such as strong lenses and quasars. Here we present the third public data release (DR3) and several associated data products, adding further area, homogenized photometric calibration, photometric redshifts and weak lensing shear measurements to the first two releases. A dedicated pipeline embedded in the Astro-WISE information system is used for the production of the main release. Modifications with respect to earlier releases are described in detail. Photometric redshifts have been derived using both Bayesian template fitting, and machine-learning techniques. For the weak lensing measurements, optimized procedures based on the THELI data reduction and lensfit shear measurement packages are used. In DR3 stacked ugri images, weight maps, masks, and source lists for 292 new survey tiles (~300 sq.deg) are made available. The multi-band catalogue, including homogenized photometry and photometric redshifts, covers the combined DR1, DR2 and DR3 footprint of 440 survey tiles (447 sq.deg). Limiting magnitudes are typically 24.3, 25.1, 24.9, 23.8 (5 sigma in a 2 arcsec aperture) in ugri, respectively, and the typical r-band PSF size is less than 0.7 arcsec. The photometric homogenization scheme ensures accurate colors and an absolute calibration stable to ~2% for gri and ~3% in u. Separately released are a weak lensing shear catalogue and photometric redshifts based on two different machine-learning techniques.
We present the VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey, a VST INAF Guaranteed Time program designed to provide optical coverage of two 4 deg$^2$ cosmic windows in the Southern hemisphere. VOICE provides the first, multi-band deep optical imaging of these sky regions, thus complementing and enhancing the rich legacy of longer-wavelength surveys with VISTA, Spitzer, Herschel and ATCA available in these areas and paving the way for upcoming observations with facilities such as the LSST, MeerKAT and the SKA. VOICE exploits VST's OmegaCAM optical imaging capabilities and completes the reduction of WFI data available within the ES1 fields as part of the ESO-Spitzer Imaging Extragalactic Survey (ESIS) program providing $ugri$ and $uBVR$ coverage of 4 and 4 deg$^2$ areas within the CDFS and ES1 field respectively. We present the survey's science rationale and observing strategy, the data reduction and multi-wavelength data fusion pipeline. Survey data products and their future updates will be released at http://www.mattiavaccari.net/voice/ and on CDS/VizieR.
The abundance of compact, massive, early-type galaxies (ETGs) provides important constraints to galaxy formation scenarios. Thanks to the area covered, depth, excellent spatial resolution and seeing, the ESO Public optical Kilo Degree Survey (KiDS), carried out with the VLT Survey Telescope (VST), offers a unique opportunity to conduct a complete census of the most compact galaxies in the Universe. This paper presents a first census of such systems from the first 156 square degrees of KiDS. Our analysis relies on g-, r-, and i-band effective radii ($R_{\rm e}$), derived by fitting galaxy images with PSF-convolved Sérsic models, high-quality photometric redshifts, $z_{\rm phot}$, estimated from machine learning techniques, and stellar masses, $M_{\rm \star}$, calculated from KiDS aperture photometry. After massiveness ($M_{\rm \star} > 8 \times 10^{10}\, \rm M_{\odot}$) and compactness ($R_{\rm e} < 1.5 \, \rm kpc$ in g-, r- and i-bands) criteria are applied, a visual inspection of the candidates plus near-infrared photometry from VIKING-DR1 are used to refine our sample. The final catalog, to be spectroscopically confirmed, consists of 92 systems in the redshift range $z \sim 0.2-0.7$. This sample, which we expect to increase by a factor of ten over the total survey area, represents the first attempt to select massive super-compact ETGs (MSCGs) in KiDS. We investigate the impact of redshift systematics in the selection, finding that this seems to be a major source of contamination in our sample. A preliminary analysis shows that MSCGs exhibit negative internal colour gradients, consistent with a passive evolution of these systems. We find that the number density of MSCGs is only mildly consistent with predictions from simulations at $z>0.2$, while no such system is found at $z < 0.2$.
The Shapley Supercluster Survey is a multi-wavelength survey covering an area of ~23 deg^2 (~260 Mpc^2 at z=0.048) around the supercluster core, including nine Abell and two poor clusters, having redshifts in the range 0.045-0.050. The survey aims to investigate the role of the cluster-scale mass assembly on the evolution of galaxies, mapping the effects of the environment from the cores of the clusters to their outskirts and along the filaments. The optical (ugri) imaging acquired with OmegaCAM on the VLT Survey Telescope is essential to achieve the project goals providing accurate multi-band photometry for the galaxy population down to m*+6. We describe the methodology adopted to construct the optical catalogues and to separate extended and point-like sources. The catalogues reach average 5sigma limiting magnitudes within a 3\arcsec diameter aperture of ugri=[24.4,24.6,24.1,23.3] and are 93% complete down to ugri=[23.8,23.8,23.5,22.0] mag, corresponding to ~m*_r+8.5. The data are highly uniform in terms of observing conditions and all acquired with seeing less than 1.1 arcsec full width at half-maximum. The median seeing in r-band is 0.6 arcsec, corresponding to 0.56 kpc h^{-1}_{70} at z=0.048. While the observations in the u, g and r bands are still ongoing, the i-band observations have been completed, and we present the i-band catalogue over the whole survey area. The latter is released and it will be regularly updated, through the use of the Virtual Observatory tools. This includes 734,319 sources down to i=22.0 mag and it is the first optical homogeneous catalogue at such a depth, covering the central region of the Shapley supercluster.
The ESO Public Kilo-Degree Survey (KiDS) is an optical wide-field imaging survey carried out with the VLT Survey Telescope and the OmegaCAM camera. KiDS will scan 1500 square degrees in four optical filters (u, g, r, i). Designed to be a weak lensing survey, it is ideal for galaxy evolution studies, thanks to the high spatial resolution of VST, the good seeing and the photometric depth. The surface photometry have provided with structural parameters (e.g. size and Sérsic index), aperture and total magnitudes have been used to derive photometric redshifts from Machine learning methods and stellar masses/luminositites from stellar population synthesis. Our project aimed at investigating the evolution of the colour and structural properties of galaxies with mass and environment up to redshift $z \sim 0.5$ and more, to put constraints on galaxy evolution processes, as galaxy mergers.
We forecast dark energy constraints that could be obtained from a new large sample of Type Ia supernovae where those at high redshift are acquired with the Euclid space mission. We simulate a three-prong SN survey: a z<0.35 nearby sample (8000 SNe), a 0.2<z<0.95 intermediate sample (8800 SNe), and a 0.75<z<1.55 high-z sample (1700 SNe). The nearby and intermediate surveys are assumed to be conducted from the ground, while the high-z is a joint ground- and space-based survey. This latter survey, the "Dark Energy Supernova Infra-Red Experiment" (DESIRE), is designed to fit within 6 months of Euclid observing time, with a dedicated observing program. We simulate the SN events as they would be observed in rolling-search mode by the various instruments, and derive the quality of expected cosmological constraints. We account for known systematic uncertainties, in particular calibration uncertainties including their contribution through the training of the supernova model used to fit the supernovae light curves. Using conservative assumptions and a 1-D geometric Planck prior, we find that the ensemble of surveys would yield competitive constraints: a constant equation of state parameter can be constrained to sigma(w)=0.022, and a Dark Energy Task Force figure of merit of 203 is found for a two-parameter equation of state. Our simulations thus indicate that Euclid can bring a significant contribution to a purely geometrical cosmology constraint by extending a high-quality SN Hubble diagram to z~1.5. We also present other science topics enabled by the DESIRE Euclid observations
We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data rates, and an ever-increasing complexity, now entering the Petascale regime. Telescopes and observatories from both ground and space, covering a full range of wavelengths, feed the data via processing pipelines into dedicated archives, where they can be accessed for scientific analysis. Most of the large archives are connected through the Virtual Observatory framework, that provides interoperability standards and services, and effectively constitutes a global data grid of astronomy. Making discoveries in this overabundance of data requires applications of novel, machine learning tools. We describe some of the recent examples of such applications.
Accurate photometric redshifts for large samples of galaxies are among the main products of modern multiband digital surveys. Over the last decade, the Sloan Digital Sky Survey (SDSS) has become a sort of benchmark against which to test the various methods. We present an application of a new method to the estimation of photometric redshifts for the galaxies in the SDSS Data Release 9 (SDSS-DR9). Photometric redshifts for more than 143 million galaxies were produced and made available at the URL: http://dame.dsf.unina.it/catalog/DR9PHOTOZ/. The MLPQNA (Multi Layer Perceptron with Quasi Newton Algorithm) model provided within the framework of the DAMEWARE (DAta Mining and Exploration Web Application REsource) is an interpolative method derived from machine learning models. The obtained redshifts have an overall uncertainty of sigma=0.023 with a very small average bias of about 3x10^-5, and a fraction of catastrophic outliers of about 5%. This result is slightly better than what was already available in the literature, particularly in terms of the smaller fraction of catastrophic outliers.