arXiv subjects

Mattia Vaccari

Publications and source records attributed to Mattia Vaccari.

At least 55 records · Page 3Linked to original sources

arXiv2022

LADUMA: Discovery of a luminous OH megamaser at $z > 0.5$

In the local Universe, OH megamasers (OHMs) are detected almost exclusively in infrared-luminous galaxies, with a prevalence that increases with IR luminosity, suggesting that they trace gas-rich galaxy mergers. Given the proximity of the rest frequencies of OH and the hyperfine transition of neutral atomic hydrogen (HI), radio surveys to probe the cosmic evolution of HI in galaxies also offer exciting prospects for exploiting OHMs to probe the cosmic history of gas-rich mergers. Using observations for the Looking At the Distant Universe with the MeerKAT Array (LADUMA) deep HI survey, we report the first untargeted detection of an OHM at $z > 0.5$, LADUMA J033046.20$-$275518.1 (nicknamed "Nkalakatha"). The host system, WISEA J033046.26$-$275518.3, is an infrared-luminous radio galaxy whose optical redshift $z \approx 0.52$ confirms the MeerKAT emission line detection as OH at a redshift $z_{\rm OH} = 0.5225 \pm 0.0001$ rather than HI at lower redshift. The detected spectral line has 18.4$σ$ peak significance, a width of $459 \pm 59\,{\rm km\,s^{-1}}$, and an integrated luminosity of $(6.31 \pm 0.18\,{\rm [statistical]}\,\pm 0.31\,{\rm [systematic]}) \times 10^3\,L_\odot$, placing it among the most luminous OHMs known. The galaxy's far-infrared luminosity $L_{\rm FIR} = (1.576 \pm 0.013) \times 10^{12}\,L_\odot$ marks it as an ultra-luminous infrared galaxy; its ratio of OH and infrared luminosities is similar to those for lower-redshift OHMs. A comparison between optical and OH redshifts offers a slight indication of an OH outflow. This detection represents the first step towards a systematic exploitation of OHMs as a tracer of galaxy growth at high redshifts.

astro-ph.GA↗

arXiv2021

A Comparison of Deep Learning Architectures for Optical Galaxy Morphology Classification

The classification of galaxy morphology plays a crucial role in understanding galaxy formation and evolution. Traditionally, this process is done manually. The emergence of deep learning techniques has given room for the automation of this process. As such, this paper offers a comparison of deep learning architectures to determine which is best suited for optical galaxy morphology classification. Adapting the model training method proposed by Walmsley et al in 2021, the Zoobot Python library is used to train models to predict Galaxy Zoo DECaLS decision tree responses, made by volunteers, using EfficientNet B0, DenseNet121 and ResNet50 as core model architectures. The predicted results are then used to generate accuracy metrics per decision tree question to determine architecture performance. DenseNet121 was found to produce the best results, in terms of accuracy, with a reasonable training time. In future, further testing with more deep learning architectures could prove beneficial.

cs.LG↗

arXiv2021

Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks

We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using Convolutional Neural Networks (CNNs). We train two different CNNs on composite images produced by superimposing simulated gravitational arcs on real Luminous Red Galaxies observed in VOICE. Specifically, the first CNN is trained on single-band images and more easily identifies systems with large Einstein radii, while the second one, trained on composite RGB images, is more accurate in retrieving systems with smaller Einstein radii. We apply both networks to real data from the VOICE survey, taking advantage of the high limiting magnitude (26.1 in the r-band) and low PSF FWHM (0.8" in the r-band) of this deep survey. We analyse $\sim21,200$ images with $mag_r<21.5$, identifying 257 lens candidates. To retrieve a high-confidence sample and to assess the accuracy of our technique, nine of the authors perform a visual inspection. Roughly 75% of the systems are classified as likely lenses by at least one of the authors. Finally, we assemble the LIVE sample (Lenses In VoicE) composed by the 16 systems passing the chosen grading threshold. Three of these candidates show likely lensing features when observed by the Hubble Space Telescope. This work represents a further confirmation of the ability of CNNs to inspect large samples of galaxies searching for gravitational lenses. These algorithms will be crucial to exploit the full scientific potential of forthcoming surveys with the Euclid satellite and the Vera Rubin Observatory

astro-ph.GA↗

arXiv2021

Photometric Redshifts in the W-CDF-S and ELAIS-S1 Fields Based on Forced Photometry from 0.36 -- 4.5 Microns

The W-CDF-S and ELAIS-S1 fields will be two of the LSST Deep Drilling fields, but the availability of spectroscopic redshifts within these two fields is still limited on deg^2 scales. To prepare for future science, we use EAZY to estimate photometric redshifts (photo-zs) in these two fields based on forced-photometry catalogs. Our photo-z catalog consists of ~0.8 million sources covering 4.9 deg^2 in W-CDF-S and ~0.8 million sources covering 3.4 deg^2 in ELAIS-S1, among which there are ~0.6 (W-CDF-S) and ~0.4 (ELAIS-S1) million sources having signal-to-noise-ratio (SNR) > 5 detections in more than 5 bands. By comparing photo-zs and available spectroscopic redshifts, we demonstrate the general reliability of our photo-z measurements. Our photo-z catalog is publicly available at \doi{10.5281/zenodo.4603178}.

astro-ph.GA↗

arXiv2021

A Multi-Band Forced-Photometry Catalog in the ELAIS-S1 Field

The ELAIS-S1 field will be an LSST Deep Drilling field, and it also has extensive multiwavelength coverage. To improve the utility of the existing data, we use The Tractor to perform forced-photometry measurements in this field. We compile data in 16 bands from the DeepDrill, VIDEO, DES, ESIS, and VOICE surveys. Using a priori information from the high-resolution fiducial images in VIDEO, we model the images in other bands and generate a forced-photometry catalog. This technique enables consistency throughout different surveys, deblends sources from low-resolution images, extends photometric measurements to a fainter magnitude regime, and improves photometric-redshift estimates. Our catalog contains over 0.8 million sources covering a 3.4 deg2 area in the VIDEO footprint and is available at 10.5281/zenodo.4540178.

astro-ph.GA↗

arXiv2021

CNN Architecture Comparison for Radio Galaxy Classification

The morphological classification of radio sources is important to gain a full understanding of galaxy evolution processes and their relation with local environmental properties. Furthermore, the complex nature of the problem, its appeal for citizen scientists and the large data rates generated by existing and upcoming radio telescopes combine to make the morphological classification of radio sources an ideal test case for the application of machine learning techniques. One approach that has shown great promise recently is Convolutional Neural Networks (CNNs). Literature, however, lacks two major things when it comes to CNNs and radio galaxy morphological classification. Firstly, a proper analysis of whether overfitting occurs when training CNNs to perform radio galaxy morphological classification using a small curated training set is needed. Secondly, a good comparative study regarding the practical applicability of the CNN architectures in literature is required. Both of these shortcomings are addressed in this paper. Multiple performance metrics are used for the latter comparative study, such as inference time, model complexity, computational complexity and mean per class accuracy. As part of this study we also investigate the effect that receptive field, stride length and coverage has on recognition performance. For the sake of completeness, we also investigate the recognition performance gains that we can obtain by employing classification ensembles. A ranking system based upon recognition and computational performance is proposed. MCRGNet, Radio Galaxy Zoo and ConvXpress (novel classifier) are the architectures that best balance computational requirements with recognition performance.

astro-ph.GA↗

arXiv2020

New constraints on the 1.4 GHz source number counts and luminosity functions in the Lockman Hole field

We present a study of the 1173 sources brighter than $S_{1.4\,\rm GHz}= 120\,μ$Jy detected over an area of $\simeq 1.4\,\hbox{deg}^{2}$ in the Lockman Hole field. Exploiting the multi-band information available in this field for $\sim$79% of the sample, sources have been classified into radio loud (RL) active galactic nuclei (AGNs), star forming galaxies (SFGs) and radio quiet (RQ) AGNs, using a variety of diagnostics available in the literature. Exploiting the observed tight anti-correlations between IRAC band 1 or band 2 and the source redshift we could assign a redshift to 177 sources missing a spectroscopic measurement or a reliable photometric estimate. A Monte Carlo approach was used to take into account the spread around the mean relation. The derived differential number counts and luminosity functions at several redshifts of each population show a good consistency with models and with earlier estimates made using data from different surveys and applying different approaches. Our results confirm that below $\sim300\,μ$Jy SFGs$+$RQ AGNs overtake RL AGNs that dominate at brighter flux densities. We also confirm earlier indications of a similar evolution of RQ AGNs and SFGs. Finally, we discuss the angular correlation function of our sources and highlight its sensitivity to the criteria used for the classification.

astro-ph.GA↗

arXiv2020

Quasars That Have Transitioned from Radio-quiet to Radio-loud on Decadal Timescales Revealed by VLASS and FIRST

We have performed a search over 3440 deg$^2$ of Epoch 1 (2017-2019) of the Very Large Array Sky Survey to identify unobscured quasars in the optical ($0.2 < z < 3.2$) and obscured active galactic nuclei (AGN) in the infrared that have brightened dramatically in the radio over the past one to two decades. These sources would have been previously classified as "radio-quiet" quasars based on upper limits from the Faint Images of the Radio Sky at Twenty Centimeters survey (1993-2011), but they are now consistent with "radio-loud" quasars ($L_{\rm 3\,GHz} = 10^{40 - 42} \,\, {\rm erg} \,{\rm s}^{-1}$). A quasi-simultaneous, multiband ($\sim1-18$ GHz) follow-up study of 14 sources with the VLA has revealed compact sources ($<0.1^{\prime \prime}$ or $<1$ kpc) with peaked radio spectral shapes. The high-amplitude variability over decadal timescales at 1.5 GHz (100% to $>$2500%), but roughly steady fluxes over a few months at 3 GHz, are inconsistent with extrinsic variability due to propagation effects, thus favoring an intrinsic origin. We conclude that our sources are powerful quasars hosting compact/young jets. This challenges the generally accepted idea that "radio-loudness" is a property of the quasar/AGN population that remains fixed on human timescales. Our study suggests that frequent episodes of short-lived AGN jets that do not necessarily grow to large scales may be common at high redshift. We speculate that intermittent but powerful jets on subgalactic scales could interact with the interstellar medium, possibly driving feedback capable of influencing galaxy evolution.

astro-ph.GA↗

arXiv2020

The VLA-COSMOS 3 GHz Large Project: Evolution of specific star formation rates out to $z\sim5$

We provide a coherent, uniform measurement of the evolution of the logarithmic star formation rate (SFR) - stellar mass ($M_*$) relation, called the main sequence of star-forming galaxies (MS), for galaxies out to $z\sim5$. We measure the MS using mean stacks of 3 GHz radio continuum images to derive average SFRs for $\sim$200,000 mass-selected galaxies at $z>0.3$ in the COSMOS field. We describe the MS relation adopting a new model that incorporates a linear relation at low stellar mass (log($M_*$/M$_\odot$)$<$10) and a flattening at high stellar mass that becomes more prominent at low redshift ($z<1.5$). We find that the SFR density peaks at $1.5<z<2$ and at each epoch there is a characteristic stellar mass ($M_* = 1 - 4 \times 10^{10}\mathrm{M}_\odot$) that contributes the most to the overall SFR density. This characteristic mass increases with redshift, at least to $z\sim2.5$. We find no significant evidence for variations in the MS relation for galaxies in different environments traced by the galaxy number density at $0.3<z<3$, nor for galaxies in X-ray groups at $z\sim0.75$. We confirm that massive bulge-dominated galaxies have lower SFRs than disk-dominated galaxies at a fixed stellar mass at $z<1.2$. As a consequence, the increase in bulge-dominated galaxies in the local star-forming population leads to a flattening of the MS at high stellar masses. This indicates that "mass-quenching" is linked with changes in the morphological composition of galaxies at a fixed stellar mass.

astro-ph.GA↗

arXiv2020

Infrared luminosity functions and dust mass functions in the EAGLE simulation

We present infrared luminosity functions and dust mass functions for the EAGLE cosmological simulation, based on synthetic multi-wavelength observations generated with the SKIRT radiative transfer code. In the local Universe, we reproduce the observed infrared luminosity and dust mass functions very well. Some minor discrepancies are encountered, mainly in the high luminosity regime, where the EAGLE-SKIRT luminosity functions mildly but systematically underestimate the observed ones. The agreement between the EAGLE-SKIRT infrared luminosity functions and the observed ones gradually worsens with increasing lookback time. Fitting modified Schechter functions to the EAGLE-SKIRT luminosity and dust mass functions at different redshifts up to $z=1$, we find that the evolution is compatible with pure luminosity/mass evolution. The evolution is relatively mild: within this redshift range, we find an evolution of $L_{\star,250}\propto(1+z)^{1.68}$, $L_{\star,\text{TIR}}\propto(1+z)^{2.51}$ and $M_{\star,\text{dust}}\propto(1+z)^{0.83}$ for the characteristic luminosity/mass. For the luminosity/mass density we find $\varepsilon_{250}\propto(1+z)^{1.62}$, $\varepsilon_{\text{TIR}}\propto(1+z)^{2.35}$ and $ρ_{\text{dust}}\propto(1+z)^{0.80}$, respectively. The mild evolution of the dust mass density is in relatively good agreement with observations, but the slow evolution of the infrared luminosity underestimates the observed luminosity evolution significantly. We argue that these differences can be attributed to increasing limitations in the radiative transfer treatment due to increasingly poorer resolution, combined with a slower than observed evolution of the SFR density in the EAGLE simulation and the lack of AGN emission in our EAGLE-SKIRT post-processing recipe.

astro-ph.GA↗

arXiv2020

Variability and transient search in the SUDARE-VOICE field: a new method to extract the light curves

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey, in synergy with the SUDARE survey, is a deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). The observations for the CDFS field comprise about 4.38 deg$^2$ down to $r\sim26$ mag. The total on-sky time spans over four years in this field, distributed over four adjacent sub-fields. In this paper, we use the multi-epoch $r$-band imaging data to measure the variability of the detected objects and search for transients. We perform careful astrometric and photometric calibrations and point spread function (PSF) modeling. A new method, referring to as differential running-average photometry, is proposed to measure the light curves of the detected objects. With the method, the difference of PSFs between different epochs can be reduced, and the background fluctuations are also suppressed. Detailed uncertainty analysis and detrending corrections on the light curves are performed. We visually inspect the light curves to select variable objects, and present some objects with interesting light curves. Further investigation of these objects in combination with multi-band data will be presented in our forthcoming paper.

astro-ph.IM↗

arXiv2019

The role of environment in galaxy evolution in the SERVS Survey I: density maps and cluster candidates

We use photometric redshifts derived from new $u$-band through 4.5$μ$m Spitzer IRAC photometry in the 4.8\,deg$^2$ of the XMM-LSS field to construct surface density maps in the redshift range 0.1-1.5. Our density maps show evidence for large-scale structure in the form of filaments spanning several tens of Mpc. Using these maps, we identify 339 overdensities that our simulated lightcone analysis suggests are likely associated with dark matter haloes with masses, $M_{\rm halo}$, log($M_{\rm halo}/M_{\odot})>$13.7. From this list of overdensities we recover 43 of 70 known X-ray detected and spectroscopically confirmed clusters. The missing X-ray clusters are largely at lower redshifts and lower masses than our target log($M_{\rm halo}/M_{\odot})>$13.7. The bulk of the overdensities are compact, but a quarter show extended morphologies which include likely projection effects, clusters embedded in apparent filaments as well as at least one potential cluster merger (at $z\sim1.28$). The strongest overdensity in our highest redshift slice (at $z\sim1.5$) shows a compact red galaxy core potentially implying a massive evolved cluster.

astro-ph.GA↗

arXiv2019

HELP: A catalogue of 170 million objects, selected at 0.36-4.5 $μ$m, from 1270 deg.$^{2}$ of prime extragalactic fields

We present an optical to near-infrared selected astronomical catalogue covering 1270 deg.$^2$. This is the first attempt to systematically combine data from 23 of the premier extragalactic survey fields - the product of a vast investment of telescope time. The fields are those imaged by the Herschel Space Observatory which form the Herschel Extragalactic Legacy Project (HELP). Our catalogue of 170 million objects is constructed by a positional cross match of 51 public surveys. This high resolution optical, near-infrared, and mid-infrared catalogue is designed for photometric redshift estimation, extraction of fluxes in lower resolution far-infrared maps, and spectral energy distribution modelling. It collates, standardises, and provides value added derived quantities including corrected aperture magnitudes and astrometry correction over the Herschel extragalactic wide fields for the first time. $grizy$ fluxes are available on all fields with $g$ band data reaching $5σ$ point-source depths in a 2 arcsec aperture of 23.5, 24.4, and 24.6 (AB) mag at the 25th, 50th, and 75th percentiles, by area covered, across all HELP fields. It has $K$ or $K_s$ coverage over 1146 deg.$^2$ with depth percentiles of 20.2, 20.4, and 21.0 mag respectively. The IRAC Ch 1 band is available over 273 deg.$^2$ with depth percentiles of 17.7, 21.4, and 22.2 mag respectively. This paper defines the "masterlist" objects for the first data release (DR1) of HELP. This large sample of standardised total and corrected aperture fluxes, uniform quality flags, and completeness measures provides large well understood statistical samples over the full Herschel extragalactic sky.

astro-ph.GA↗

arXiv2019

Voyage 2050 White Paper: All-Sky Visible and Near Infrared Space Astrometry

A new all-sky visible and Near-InfraRed (NIR) space astrometry mission with a wavelength cutoff in the K-band is not just focused on a single or small number of key science cases. Instead, it is extremely broad, answering key science questions in nearly every branch of astronomy while also providing a dense and accurate visible-NIR reference frame needed for future astronomy facilities. For almost 2 billion common stars the combination of Gaia and a new all-sky NIR astrometry mission would provide much improved proper motions, answering key science questions -- from the solar system and stellar systems, including exoplanet systems, to compact galaxies, quasars, neutron stars, binaries and dark matter substructures. The addition of NIR will result in up to 8 billion newly measured stars in some of the most obscured parts of our Galaxy, and crucially reveal the very heart of the Galactic bulge region. In this white paper we argue that rather than improving on the accuracy, a greater overall science return can be achieved by going deeper than Gaia and by expanding the wavelength range to the NIR.

astro-ph.IM↗

arXiv2018

Extreme submillimetre starburst galaxies

We use two catalogues, a Herschel catalogue selected at 500 mu (HerMES) and an IRAS catalogue selected at 60 mu (RIFSCz), to contrast the sky at these two wavelengths. Both surveys demonstrate the existence of extreme starbursts, with star-formation rates (SFRs) > 5000 Msun/yr. The maximum intrinsic star-formation rate appears to be ~30,000 Msun/yr. The sources with apparent SFR estimates higher than this are in all cases either lensed systems, blazars, or erroneous photometric redshifts. At redshifts of 3 to 5, the time-scale for the Herschel galaxies to make their current mass of stars at their present rate of formation ~ 10^8 yrs, so these galaxies are making a significant fraction of their stars in the current star-formation episode. Using dust mass as a proxy for gas mass, the Herschel galaxies at redshift 3 to 5 have gas masses comparable to their mass in stars. Of the 38 extreme starbursts in our Herschel survey for which we have more complete SED information, over 50% show evidence for QSO-like optical emission, or exhibit AGN dust tori in the mid-infrared SEDs. In all cases however the infrared luminosity is dominated by a starburst component. We derive a mean covering factor for AGN dust as a function of redshift and derive black hole masses and black hole accretion rates. There is a universal ratio of black-hole mass to stellar mass, ~ 10^{-3}, driven by the strong period of star-formation and black-hole growth at z = 1-5.

astro-ph.GA↗

arXiv2018

The FIRST Classifier: Compact and Extended Radio Galaxy Classification using Deep Convolutional Neural Networks

Upcoming surveys with new radio observatories such as the Square Kilometer Array will generate a wealth of imaging data containing large numbers of radio galaxies. Different classes of radio galaxies can be used as tracers of the cosmic environment, including the dark matter density field, to address key cosmological questions. Classifying these galaxies based on morphology is thus an important step toward achieving the science goals of next generation radio surveys. Radio galaxies have been traditionally been classified as Fanaroff-Riley (FR) I and II, although some exhibit more complex 'bent' morphologies arising from environmental factors or intrinsic properties. In this work we present the FIRST Classifier, an on-line system for automated classification of Compact and Extended radio sources. We developed the FIRST Classifier based on a trained Deep Convolutional Neural Network Model to automate the morphological classification of compact and extended radio sources observed in the FIRST radio survey. Our model achieved an overall accuracy of 97% and a recall of 98%, 100%, 98% and 93% for Compact, BENT, FRI and FRII galaxies respectively. The current version of the FIRST classifier is able to predict the morphological class for a single source or for a list of sources as Compact or Extended (FRI, FRII and BENT).

astro-ph.GA↗

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 $Σ_8$ = $σ_8(Ω_m/0.3)^{0.5}$ = $0.68^{+0.11}_{-0.15}$.

astro-ph.CO↗

arXiv2018

Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg$^2$ down to $r_\mathrm{AB}$$\sim$26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for $r$-band images with seeing $\le$ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of $\sim$3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of $\sim$0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to $\sim$0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.

astro-ph.CO↗