UWCScholar :: Browsing by Author "Vaccari, Mattia"

Browsing by Author "Vaccari, Mattia"

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Commensal transient searches with meerkat in gamma-ray burst and supernova fields
(Institute of Physics, 2025) Vaccari, Mattia; Chastain, Sarah; van der Horst, Alexander
The sensitivity and field of view of the MeerKAT radio telescope provide excellent opportunities for commensal transient searches. We carry out a commensal transient search in supernova and short gamma-ray burst fields using methodologies established by S. I. Chastain et al. We search for transients in MeerKAT L-band images with integration times of 30 minutes, finding 13 variable sources. We compare these sources to the VLASS and RACS survey data, and examine possible explanations for the variability. Additionally, for one of these sources we examine archival Chandra ACIS data. We find that 12 of these sources are consistent with variability due to interstellar scintillation. The remaining source could possibly have some intrinsic variability. We also split the MeerKAT L band into upper and lower halves, and search for transients in images with an integration time of 8 s. We find a source with a duration of 8-16 s that is highly polarized at the lowest frequencies. This source is spatially coincident with a star detected by the Transiting Exoplanet Survey Satellite. We conclude that this source may be consistent with a stellar flare. Finally, we calculate accurate upper and lower limits on the transient rate using transient simulations.
A Comparison of deep learning architectures for optical galaxy morphology classification
(International Conference on Electrical, Computer and Energy Technologies (ICECET), 2021) Fielding, Ezra; Nyirenda, Clement N.; Vaccari, Mattia
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.
Cosmos2020: A panchromatic view of the universe to z∼10 from two complementary catalogs
(IOP Publishing, 2022) Weaver, John R.; Kauffmann, Olivier; Vaccari, Mattia
The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, THE FARMER, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes.
Data intensive research and data carpentries at UWC
(University of the Western Cape, 2020) Vaccari, Mattia; Schäfer, Sarah
Euclid: the early release observations lens search experiment
(EDP Sciences, 2025) Vaccari, Mattia; Acevedo Barroso, Javier A.; O'Riordan, Conor M.
We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution IE band and the lower-resolution YE, JE, and HE bands. Each extended source brighter than magnitude 23 in IE was inspected by 41 expert human classifiers. This amounts to 12 086 stamps of 1000 × 1000. We found 3 grade A and 13 grade B candidates. We assessed the validity of these 16 candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full 14 000 deg2 of the Euclid Wide Survey should contain 100 000+-7030000000 galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of 170 000 discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range 000 . 68 < θE < 100 . 24, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small-Einstein-radius systems. Whilst it is implausible to visually inspect the full Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around 105 galaxy-scale lenses.
Evidence for inverse Compton scattering in high-redshift Lyman-break galaxies
(Oxford University Press, 2025) Whittam, Imogen H.; Jarvis, Matthew J.; Taylor, Andrew Russell; Vaccari, Mattia
Radio continuum emission provides a unique opportunity to study star formation unbiased by dust obscuration. However, if radio observations are to be used to accurately trace star formation to high redshifts, it is crucial that the physical processes that affect the radio emission from star-forming galaxies are well understood. While inverse Compton (IC) losses from the cosmic microwave background (CMB) are negligible in the local universe, the rapid increase in the strength of the CMB energy density with redshift [∼ (1 + z)4] means that this effect becomes increasingly important at z ≿ 3. Using a sample of ∼ 200 000 high-redshift (3 < z < 5) Lyman-break galaxies selected in the rest-frame ultraviolet (UV), we have stacked radio observations from the MIGHTEE survey to estimate their 1.4-GHz flux densities. We find that for a given rest-frame UV magnitude, the 1.4-GHz flux density and luminosity decrease with redshift. We compare these results to the theoretical predicted effect of energy losses due to IC scattering off the CMB, and find that the observed decrease is consistent with this explanation. We discuss other possible causes for the observed decrease in radio flux density with redshift at a given UV magnitude, such as a top-heavy initial mass function at high redshift or an evolution of the dust properties, but suggest that IC scattering is the most compelling explanation.
Galaxy–galaxy lensing in the voice deep survey
(EDP Sciences, 2022) Luo, Ruibiao; Fu, Liping; Vaccari, Mattia
The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg2 of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of magAB is up to 26.1 (5σ limiting) in r-band. We estimate the excess surface density (ESD; ∆Σ) based on galaxy–galaxy measurements around galaxies at lower redshift (0.10 < zl < 0.35) while we select the background sources as those at higher redshift ranging from 0.3 to 1.5. The foreground galaxies are divided into two major categories according to their colour (blue and red), each of which has been further divided into high- and low-stellar-mass bins. The halo masses of the samples are then estimated by modelling the signals, and the posterior of the parameters are sampled using a Monte Carlo Markov chain process. We compare our results with the existing stellar-to-halo mass relation (SHMR) and find that the blue low-stellar-mass bin (median M∗ = 108.31 M ) deviates from the SHMR relation whereas the other three samples agree well with empirical curves. We interpret this discrepancy as the effect of the low star-formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area.
Hydra I: An extensible multi-source-finder comparison and cataloguing tool
(Cambridge University Press, 2023) Boyce, M. M.; Hopkins, A. M.; Vaccari, Mattia
The latest generation of radio surveys are now producing sky survey images containing many millions of radio sources. In this context it is highly desirable to understand the performance of radio image source finder (SF) software and to identify an approach that optimises source detection capabilities. We have created Hydra to be an extensible multi-SF and cataloguing tool that can be used to compare and evaluate different SFs. Hydra, which currently includes the SFs Aegean, Caesar, ProFound, PyBDSF, and Selavy, provides for the addition of new SFs through containerisation and configuration files. The SF input RMS noise and island parameters are optimised to a 90% “percentage real detections” threshold (calculated from the difference between detections in the real and inverted images), to enable comparison between SFs.
Hydra ii: Characterisation of Aegean, Caesar, profound, pybdsf, and selavy source finders
(Cambridge University Press, 2023) Boyce, M. M.; Hopkins, A. M.; Vaccari, Mattia
We present a comparison between the performance of a selection of source finders using a new software tool called Hydra. The companion paper, Paper I, introduced the Hydra tool and demonstrated its performance using simulated data. Here we apply Hydra to assess the performance of different source finders by analysing real observational data taken from the Evolutionary Map of the Universe (EMU) Pilot Survey. EMU is a wide-field radio continuum survey whose primary goal is to make a deep (20μJy/beam RMS noise), intermediate angular resolution (15′′), 1 GHz survey of the entire sky south of +30◦ declination, and expecting to detect and catalogue up to 40 million sources. With the main EMU survey expected to begin in 2022 it is highly desirable to understand the performance of radio image source finder software and to identify an approach that optimises source detection capabilities. Hydra has been developed to refine this process, as well as to deliver a range of metrics and source finding data products from multiple source finders. We present the performance of the five source finders tested here in terms of their completeness and reliability statistics, their flux density and source size measurements, and an exploration of case studies to highlight finder-specific limitations.
Lenses In VoicE (LIVE): Searching for strong gravitational lenses in the VOICE@VST survey using Convolutional Neural Networks
(Monthly notices of the Royal Astronomical Society, 2021) Vaccari, Mattia
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 ∼ 21, 200 images with 𝑚𝑎𝑔𝑟 < 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.
Machine learning approaches to study star formation and black hole accretion in the Meerkat/MIGHTEE survey
(University of the Western Cape, 2023) Silima, Walter; Vaccari, Mattia
Galaxy formation and evolution are driven by two main physical processes: star formation and black hole accretion. Both processes can be traced via the synchrotron emission at radio wavelengths. However, a reliable classification of radio sources as star-formation-dominated sources (or Star-Forming Galaxies, SFGs) and blackhole- accretion-dominated sources (or Active Galactic Nuclei, AGN) is non-trivial and often requires extensive use of multi-wavelength data. Although significant effort has been put into classifying radio sources as SFGs or AGN over the decades, the rapid growth of radio data available from facilities such as the South African MeerKAT telescope, the Australian Square Kilometre Array Pathfinder (ASKAP), and eventually the Square Kilometre Array (SKA) requires the development of efficient and reliable automated classification techniques.
Machine-learning approaches for classifying star-forming galaxies and active galactic nuclei from MIGHTEE-detected radio sources in the COSMOS field
(Oxford University Press, 2025) Silima, Walter; An, Fangxia; Vaccari, Mattia; Hussein, Eslam
Radio synchrotron emission originates from both massive star formation and black hole accretion, two processes that drive galaxy evolution. Efficient classification of sources dominated by either process is therefore essential for fully exploiting deep, wide-field extragalactic radio continuum surveys. In this study, we implement, optimize, and compare five widely used supervised machine-learning (ML) algorithms to classify radio sources detected in the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE)-COSMOS survey as star-forming galaxies (SFGs) and active galactic nuclei (AGNs). Training and test sets are constructed from conventionally classified MIGHTEE-COSMOS sources, and 18 physical parameters of the MIGHTEE-detected sources are evaluated as input features. As anticipated, our feature analyses rank the five parameters used in conventional classification as the most effective: the infrared–radio correlation parameter ($q_\mathrm{IR}$), the optical compactness morphology parameter (class_star), stellar mass, and two combined mid-infrared colours. By optimizing the ML models with these selected features and testing classifiers across various feature combinations, we find that model performance generally improves as additional features are incorporated. Overall, all five algorithms yield an F1-score (the harmonic mean of precision and recall) >90 per cent even when trained on only 20 per cent of the data set. Among them, the distance-based k-nearest neighbours classifier demonstrates the highest accuracy and stability, establishing it as a robust and effective method for classifying SFGs and AGNs in upcoming large radio continuum surveys.
MIGHTEE-H I: H I galaxy properties in the large-scale structure environment at z ∼ 0.37 from a stacking experiment
(Oxford University Press, 2024) Sinigaglia, Francesco; Elson, Ed; Vaccari, Mattia
We present the first measurement of H I mass of star-forming galaxies in different large scale structure environments from a blind survey at z ∼ 0.37. In particular, we carry out a spectral line stacking analysis considering 2875 spectra of colour-selected star-forming galaxies undetected in H I at 0.23 < z < 0.49 in the COSMOS field, extracted from the MIGHTEE-H I Early Science data cubes, acquired with the MeerKAT radio telescope. We stack galaxies belonging to different subsamples depending on three different definitions of large-scale structure environment: local galaxy overdensity, position inside the host dark matter halo (central, satellite, or isolated), and cosmic web type (field, filament, or knot). We first stack the full star-forming galaxy sample and find a robust H I detection yielding an average galaxy H I mass of MH I = (8.12 ± 0.75) × 109 M⊙ at ∼11.8σ. Next, we investigate the different subsamples finding a negligible difference in MH I as a function of the galaxy overdensity. We report an H I excess compared to the full sample in satellite galaxies (MH I = (11.31 ± 1.22) × 109, at ∼10.2σ) and in filaments (MH I = (11.62 ± 0.90) × 109. Conversely, we report non-detections for the central and knot galaxies subsamples, which appear to be H I-deficient.
Mightee-hi: Evolution of hi scaling relations of star-forming galaxies at z < 0.5*
(IOP Publishing, 2022) Sinigaglia, Francesco; Rodighiero, Giulia; Vaccari, Mattia
We present the first measurements of H I galaxy scaling relations from a blind survey at z > 0.15. We perform spectral stacking of 9023 spectra of star-forming galaxies undetected in H I at 0.23 < z < 0.49, extracted from MIGHTEE-H I Early Science data cubes, acquired with the MeerKAT radio telescope. We stack galaxies in bins of galaxy properties (stellar mass M*, star formation rateSFR, and specific star formation rate sSFR, with sSFR ≡ M*/SFR), obtaining 5σ detections in most cases, the strongest H I-stacking detections to date in this redshift range. With these detections, we are able to measure scaling relations in the probed redshift interval, finding evidence for a moderate evolution from the median redshift of our sample zmed ∼ 0.37 to z ∼ 0. In particular, low-M* galaxies (  ~ * log 9 10( ) M M ) experience a strong H I depletion (∼0.5 dex in log10( ) M M H I  ), while massive galaxies (  ~ * log 11 10( ) M M ) keep their H I mass nearly unchanged. When looking at the star formation activity, highly star-forming galaxies evolve significantly in MH I ( fH I, where fH I ≡ MH I/M*) at fixed SFR (sSFR), while at the lowest probed SFR (sSFR) the scaling relations show no evolution.
The nature of the microjy source population
(University of the Western Cape, 2015) Ocran Emmanuel Francis; Taylor, Russ; Vaccari, Mattia
The study of the faint radio universe and of its properties has recently become a very active field of research not only because of the much improved capabilities of the SKA pathfinders but also because of the need to better plan for SKA surveys. These new facilities will map large areas of the sky to unprecedented depths and transform radio astronomy into the leading technique for investigating the complex processes which govern the formation and evolution of galaxies. This thesis combines multi-wavelength techniques, highly relevant to future deep radio surveys, to study the properties of faint radio sources. The nature of the faint radio sources is presented, over a large GMRT survey area of an area of 1.2 deg2 comprising 2800 sources. Utilising multi-wavelength data we have matched 85% of the radio population to Spitzer/IRAC and obtained a redshift estimate for 63%. The redshift associations are a combination of photometric and spectroscopic redshift estimates. This study investigates several multi-wavelength diagnostics used to identify AGN, using radio, infrared, optical and x-ray data . This analysis shows that various diagnostics (from the radio through the X-ray ones) select fairly different types of AGNs, with an evidence of a disagreement in the number of AGNs selected by each individual diagnostics. For the sources with redshift we use a classification scheme based on radio luminosity, x-ray emission, BOSS/SDSS spectroscopy, IRAC colors satisfying the Donley criterion, and MIPS 24ɥm radio-loud AGN criteria to separate them into AGNs and SFGs. On the basis of this classification, we find that at least 12.5% of the sources with redshifts are AGNs while the remaining 87.5% are adopted as SFGs. We explore the nature of the classified sources through the far-infrared radio correlation. We measure a median qIR value of 2:45± 0:01 for the SFGs and qIR value of 2:27 ± 0:05 for the AGNs. The decrease in the median value of qIR for the AGNs is a result of the additional AGN component to radio emission for the AGN-powered sources and find tentative evidence of an evolution of the qIR with redshift.
New constraints on the evolution of the mh i−m⋆ scaling relation combining chiles and mightee-h i data
(Institute of Physics, 2025) Elson, Ed; Vaccari, Mattia; Bianchetti, Alessandro
The improved sensitivity of interferometric facilities to the 21 cm line of atomic hydrogen (H i) enables studies of its properties in galaxies beyond the local Universe. In this work, we perform a 21 cm line spectral stacking analysis combining the MeerKAT International GigaHertz Tiered Extragalactic Exploration and COSMOS H i Large Extra-galactic Survey surveys in the COSMOS field to derive a robust H i-stellar mass relation at z ≈ 0.36. In particular, by stacking thousands of star-forming galaxies subdivided into stellar mass bins, we optimize the signal-to-noise ratio of targets and derive mean H i masses in the different stellar mass intervals for the investigated galaxy population. We combine spectra from the two surveys, estimate H i masses, and derive the scaling relation log 10 M H I = ( 0.32 ± 0.04 ) log 10 M ⋆ + ( 6.65 ± 0.36 ) . Our findings indicate that galaxies at z ≈ 0.36 are H i richer than those at z ≈ 0 but H i poorer than those at z ≈ 1, with a slope consistent across redshift, suggesting that stellar mass does not significantly affect H i exchange mechanisms. We also observe a slower growth rate H i relative to the molecular gas, supporting the idea that the accretion of cold gas is slower than the rate of consumption of molecular gas to form stars. This study contributes to understanding the role of atomic gas in galaxy evolution and sets the stage for future development of the field in the upcoming Square Kilometre Array era.
New hope for obscured AGN: the PRIMA-NewAthena alliance
(SPIE, 2025) Vaccari, Mattia; Barchiesi, Luigi; Carrera, Francisco
Understanding the AGN-galaxy co-evolution, feedback processes, and the evolution of Black Hole Accretion rate Density (BHAD) requires accurately estimating the contribution of obscured Active Galactic Nuclei (AGN). However, detecting these sources is challenging due to significant extinction at the wavelengths typically used to trace their emission. We evaluate the capabilities of the proposed far-infrared observatory PRIMA and its synergies with the X-ray observatory NewAthena in detecting AGN and in measuring the BHAD. Starting from X-ray background synthesis models, we simulate the performance of NewAthena and of PRIMA in Deep and Wide surveys. Our results show that the combination of these facilities is a powerful tool for selecting and characterizing all types of AGN. Although NewAthena is particularly effective at detecting the most luminous, the unobscured, and the moderately obscured AGN, PRIMA excels at identifying heavily obscured sources, including Compton-thick AGN (of which we expect 7500 detections per deg2). We find that PRIMA will detect ∼60 times more sources than Herschel over the same area and will allow us to accurately measure the BHAD evolution up to z ∼ 8, better than any current IR or X-ray survey, finally revealing the true contribution of Compton-thick AGN to the BHAD evolution
An overview of the Dwarf Galaxy Survey
(The Astronomical Society of the Pacific, 2013) Remy-Ruyer, A.; Galametz, M.; Vaccari, Mattia; Madden, S.C.
The Dwarf Galaxy Survey (DGS) program is studying low-metallicity galax- ies using 230h of far-infrared (FIR) and submillimetre (submm) photometric and spectroscopic observations of the Herschel Space Observatory and draws to this a rich database of a wide range of wavelengths tracing the dust, gas and stars. This sample of 50 galaxies includes the largest metallicity range achievable in the local Universe including the lowest metallicity (Z) galaxies, 1/50 Z⊙, and spans 4 orders of magnitude in star formation rates. The survey is designed to get a handle on the physics of the interstellar medium (ISM) of low metallicity dwarf galaxies, especially on their dust and gas properties and the ISM heating and cooling processes. The DGS produces PACS and SPIRE maps of low-metallicity galaxies observed at 70, 100, 160, 250, 350, and 500 μm with the highest sensi- tivity achievable to date in the FIR and submm. The FIR fine-structure lines, [CII] 158μm, [OI] 63μm, [OI] 145μm, [OIII] 88μm, [NIII] 57μm and [NII] 122 and 205 μm have also been observed with the aim of studying the gas cooling in the neutral and ionized phases. The SPIRE FTS observations include many CO lines (J=4-3 to J=13-12), [NII] 205 μm and [CI] lines at 370 and 609 μm. This paper describes the sample selection and global properties of the galaxies, the observing strategy as well as the vast ancillary database available to comple- ment the Herschel observations. The scientific potential of the full DGS survey is described with some example results included.
Radio continuum spectra of SFGs in the XMM-LSS Field below threshold
(Oxford University Press, 2025) Ocran E.F.; Taylor, Andrew Russell; Vaccari, Mattia
This study investigates the radio spectral properties of KS-selected star-forming galaxies (SFGs) in the XMM-LSS (multimirror mission large-scale structure) field using extensive multiwavelength data. By employing various diagnostics, SFGs are distinguished from quiescent galaxies and AGN across seven redshift bins (0.1 ≤ z ≤ 3.0). The broad-band radio frequency spectral energy distribution is analysed at observer-frame frequencies from 144 to 1500 MHz using median stacking techniques correcting for median flux boosting. We investigate the relationship between the radio spectral index, α (where S ∝ να) and redshift (z). Our analysis reveals no significant inverse correlation between α and z, indicating that the radio spectrum remains independent with varying redshift. We fit the stacked median radio SEDs with a power law (PL), curved power law (CPL), and double power-law (DPL) models. For the DPL and CPL models, we observe a consistent steepening of the low-frequency spectral index across all redshift bins. For the CPL model, the curvature term q is greater than zero in all redshift bins. Model comparisons indicate that spectra are generally well fitted by all the models considered. At 1500 MHz, SFGs display both a steep synchrotron component and a flat free–free emission component, with a thermal fraction consistently around 11 per cent to 18 per cent. Further deep radio observations, with higher resolution to better deal with source blending and confusion noise and wider frequency coverage to better separate non-thermal and thermal radio emission, are required to reveal the detailed physical processes, thus clarifying the nature of radio sources.
Revised SWIRE photometric redshifts
(Oxford University Press, 2013) Rowan-Robinson, Michael; Gonzalez-Solares, Eduardo A.; Vaccari, Mattia; Marchetti, L.
We have revised the Spitzer Wide-Area Infrared Extragalactic survey (SWIRE) Photometric Redshift Catalogue to take account of new optical photometry in several of the SWIRE areas, and incorporating Two Micron All Sky Survey (2MASS) and UKIRT Infrared Deep Sky Survey (UKIDSS) near-infrared data. Aperture matching is an important issue for combining near-infrared and optical data, and we have explored a number of methods of doing this. The increased number of photometric bands available for the redshift solution results in improvements both in the rms error and, especially, in the outlier rate. We have also found that incorporating the dust torus emission into the quasi-stellar object (QSO) templates improves the performance for QSO redshift estimation. Our revised redshift catalogue contains over 1 million extragalactic objects, of which 26 288 are QSOs.

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