arXiv subjects

Stephen Serjeant

Publications and source records attributed to Stephen Serjeant.

At least 37 records · Page 2Linked to original sources

arXiv2024

SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). V. Confusion-limited Submillimeter Galaxy Number Counts at 450 $μ$m and Data Release for the COSMOS Field

We present confusion-limited SCUBA-2 450-$μ$m observations in the COSMOS-CANDELS region as part of the JCMT Large Program, SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). Our maps at 450 and 850 $μ$m cover an area of 450 arcmin$^2$. We achieved instrumental noise levels of $σ_{\mathrm{450}}=$ 0.59 mJy beam$^{-1}$ and $σ_{\mathrm{850}}=$ 0.09 mJy beam$^{-1}$ in the deepest area of each map. The corresponding confusion noise levels are estimated to be 0.65 and 0.36 mJy beam$^{-1}$. Above the 4 (3.5) $σ$ threshold, we detected 360 (479) sources at 450 $μ$m and 237 (314) sources at 850 $μ$m. We derive the deepest blank-field number counts at 450 $μ$m, covering the flux-density range of 2 to 43 mJy. These are in agreement with other SCUBA-2 blank-field and lensing-cluster observations, but are lower than various model counts. We compare the counts with those in other fields and find that the field-to-field variance observed at 450 $μ$m at the $R=6^\prime$ scale is consistent with Poisson noise, so there is no evidence of strong 2-D clustering at this scale. Additionally, we derive the integrated surface brightness at 450 $μ$m down to 2.1 mJy to be $57.3^{+1.0}_{-6.2}$~Jy deg$^{-2}$, contributing to (41$\pm$4)\% of the 450-$μ$m extragalactic background light (EBL) measured by COBE and Planck. Our results suggest that the 450-$μ$m EBL may be fully resolved at $0.08^{+0.09}_{-0.08}$~mJy, which extremely deep lensing-cluster observations and next-generation submillimeter instruments with large aperture sizes may be able to achieve.

astro-ph.GA↗

arXiv2024

Citizen Science in European Research Infrastructures

Major European Union-funded research infrastructure and open science projects have traditionally included dissemination work, for mostly one-way communication of the research activities. Here we present and review our radical re-envisioning of this work, by directly engaging citizen science volunteers into the research. We summarise the citizen science in the Horizon-funded projects ASTERICS (Astronomy ESFRI and Research Infrastructure Clusters) and ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI Research Infrastructures), engaging hundreds of thousands of volunteers in providing millions of data mining classifications. Not only does this have enormously more scientific and societal impact than conventional dissemination, but it facilitates the direct research involvement of what is often arguably the most neglected stakeholder group in Horizon projects, the science-inclined public. We conclude with recommendations and opportunities for deploying crowdsourced data mining in the physical sciences, noting that the primary goal is always the fundamental research question; if public engagement is the primary goal to optimise, then other, more targeted approaches may be more effective.

astro-ph.IM↗

arXiv2024

Overcoming Confusion Noise with Hyperspectral Imaging from PRIMAger

The PRobe far-Infrared Mission for Astrophysics (PRIMA) concept aims to perform mapping with spectral coverage and sensitivities inaccessible to previous FIR space telescopes. PRIMA's imaging instrument, PRIMAger, provides unique hyperspectral imaging simultaneously covering 25-235 $μ$m. We synthesise images representing a deep, 1500 hr deg$^{-2}$ PRIMAger survey, with realistic instrumental and confusion noise. We demonstrate that we can construct catalogues of galaxies with a high purity ($>95$ per cent) at a source density of 42k deg$^{-2}$ using PRIMAger data alone. Using the XID+ deblending tool we show that we measure fluxes with an accuracy better than 20 per cent to flux levels of 0.16, 0.80, 9.7 and 15 mJy at 47.4, 79.7, 172, 235 $μ$m respectively. These are a factor of $\sim$2 and $\sim$3 fainter than the classical confusion limits for 72-96 $μ$m and 126-235 $μ$m, respectively. At $1.5 \leq z \leq 2$, we detect and accurately measure fluxes in 8-10 of the 10 channels covering 47-235 $μ$m for sources with $2 \leq$ log(SFR) $\leq 2.5$, a 0.5 dex improvement on what might be expected from the classical confusion limit. Recognising that PRIMager will operate in a context where high quality data will be available at other wavelengths, we investigate the benefits of introducing additional prior information. We show that by introducing even weak prior flux information when employing a higher source density catalogue (more than one source per beam) we can obtain accurate fluxes an order of magnitude below the classical confusion limit for 96-235 $μ$m.

astro-ph.IM↗

arXiv2024

Transfer learning for galaxy feature detection: Finding Giant Star-forming Clumps in low redshift galaxies using Faster R-CNN

Giant Star-forming Clumps (GSFCs) are areas of intensive star-formation that are commonly observed in high-redshift (z>1) galaxies but their formation and role in galaxy evolution remain unclear. High-resolution observations of low-redshift clumpy galaxy analogues are rare and restricted to a limited set of galaxies but the increasing availability of wide-field galaxy survey data makes the detection of large clumpy galaxy samples increasingly feasible. Deep Learning, and in particular CNNs, have been successfully applied to image classification tasks in astrophysical data analysis. However, one application of DL that remains relatively unexplored is that of automatically identifying and localising specific objects or features in astrophysical imaging data. In this paper we demonstrate the feasibility of using Deep learning-based object detection models to localise GSFCs in astrophysical imaging data. We apply the Faster R-CNN object detection framework (FRCNN) to identify GSFCs in low redshift (z<0.3) galaxies. Unlike other studies, we train different FRCNN models not on simulated images with known labels but on real observational data that was collected by the Sloan Digital Sky Survey Legacy Survey and labelled by volunteers from the citizen science project `Galaxy Zoo: Clump Scout'. The FRCNN model relies on a CNN component as a `backbone' feature extractor. We show that CNNs, that have been pre-trained for image classification using astrophysical images, outperform those that have been pre-trained on terrestrial images. In particular, we compare a domain-specific CNN -`Zoobot' - with a generic classification backbone and find that Zoobot achieves higher detection performance and also requires smaller training data sets to do so. Our final model is capable of producing GSFC detections with a completeness and purity of >=0.8 while only being trained on ~5,000 galaxy images.

astro-ph.GA↗

arXiv2024

An upper limit to differential magnification effects in strongly gravitationally lensed galaxies

Differential magnification is now well-known to distort the spectral energy distributions of strongly gravitationally lensed galaxies. However, that does not mean that any distortions are possible. Here I prove an analytic upper bound to differential magnification effects. For example, a thermal or sub-thermal CO ladder cannot be made to appear super-thermal just from gravitational lensing, and the Balmer decrement emission line ratio H$α$:H$β$ cannot reduce below the case B prediction just from differential magnification. In general, if a physical model of a galaxy predicts upper and/or lower bounds to an emission line ratio, then those bounds also apply to the differentially magnified strongly gravitationally lensed case. This applies not just for velocity-integrated emission lines, but also for the line emission in any rest-frame velocity interval.

astro-ph.GA↗

arXiv2024

An ALMA Spectroscopic Survey of the Brightest Submillimeter Galaxies in the SCUBA-2-COSMOS Field (AS2COSPEC): Physical Properties of z=2-5 Ultra- and Hyperluminous Infrared Galaxies

We report physical properties of the brightest ($S_{870\,μ\rm m}=12.4$-$19.2\,$mJy) and not strongly lensed 18 870$\,μ$m selected dusty star-forming galaxies (DSFGs), also known as submillimeter galaxies (SMGs), in the COSMOS field. This sample is part of an ALMA band$\,$3 spectroscopic survey (AS2COSPEC), and spectroscopic redshifts are measured in 17 of them at $z=2$-$5$. We perform spectral energy distribution analyses and deduce a median total infrared luminosity of $L_{\rm IR}=(1.3\pm0.1)\times10^{13}\,L_{\odot}$, infrared-based star-formation rate of ${\rm SFR}_{\rm IR}=1390\pm150~M_{\odot}\,\rm yr^{-1}$, stellar mass of $M_\ast=(1.4\pm0.6)\times10^{11}\,M_\odot$, dust mass of $M_{\rm dust}=(3.7\pm0.5)\times10^9\,M_\odot$, and molecular gas mass of $M_{\rm gas}= (α_{\rm CO}/0.8)(1.2\pm0.1)\times10^{11}\,M_\odot$, suggesting that they are one of the most massive, ISM-enriched, and actively star-forming systems at $z=2$-$5$. In addition, compared to less massive and less active galaxies at similar epochs, SMGs have comparable gas fractions; however, they have much shorter depletion time, possibly caused by more active dynamical interactions. We determine a median dust emissivity index of $β=2.1\pm0.1$ for our sample, and by combining our results with those from other DSFG samples, we find no correlation of $β$ with redshift or infrared luminosity, indicating similar dust grain compositions across cosmic time for infrared luminous galaxies. We also find that AS2COSPEC SMGs have one of the highest dust-to-stellar mass ratios, with a median of $0.02\pm0.01$, significantly higher than model predictions, possibly due to too strong of a AGN feedback implemented in the model. Finally, our complete and uniform survey enables us to put constraints on the most massive end of the dust and molecular gas mass functions.

astro-ph.GA↗

arXiv2024

A large population of strongly lensed faint submillimetre galaxies in future dark energy surveys inferred from JWST imaging

Bright galaxies at sub-millimetre wavelengths from Herschel are now well known to be predominantly strongly gravitationally lensed. The same models that successfully predicted this strongly lensed population also predict about one percent of faint $450μ$m-selected galaxies from deep James Clerk Maxwell Telescope (JCMT) surveys will also be strongly lensed. Follow-up ALMA campaigns have so far found one potential lens candidate, but without clear compelling evidence e.g. from lensing arcs. Here we report the discovery of a compelling gravitational lens system confirming the lensing population predictions, with a $z_{s} = 3.4 {\pm} 0.4$ submm source lensed by a $z_{spec} = 0.360$ foreground galaxy within the COSMOS field, identified through public JWST imaging of a $450μ$m source in the SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES) catalogue. These systems will typically be well within the detectable range of future wide-field surveys such as Euclid and Roman, and since sub-millimetre galaxies are predominantly very red at optical/near-infrared wavelengths, they will tend to appear in near-infrared channels only. Extrapolating to the Euclid-Wide survey, we predict tens of thousands of strongly lensed near-infrared galaxies. This will be transformative for the study of dusty star-forming galaxies at cosmic noon, but will be a contaminant population in searches for strongly lensed ultra-high-redshift galaxies in Euclid and Roman.

astro-ph.GA↗

arXiv2023

FLASH: Faint Lenses from Associated Selection with Herschel

We report the ALMA Band 7 observations of 86 Herschel sources that likely contain gravitationally-lensed galaxies. These sources are selected with relatively faint 500 $μ$m flux densities between 15 to 85 mJy in an effort to characterize the effect of lensing across the entire million-source Herschel catalogue. These lensed candidates were identified by their close proximity to bright galaxies in the near-infrared VISTA Kilo-Degree Infrared Galaxy Survey (VIKING) survey. Our high-resolution observations (0.15 arcsec) confirm 47 per cent of the initial candidates as gravitational lenses, while lensing cannot be excluded across the remaining sample. We find average lensing masses (log M/M$_{\odot}$ = 12.9 $\pm$ 0.5) in line with previous experiments, although direct observations might struggle to identify the most massive foreground lenses across the remaining 53 per cent of the sample, particularly for lenses with larger Einstein radii. Our observations confirm previous indications that more lenses exist at low flux densities than expected from strong galaxy-galaxy lensing models alone, where the excess is likely due to additional contributions of cluster lenses and weak lensing. If we apply our method across the total 660 sqr. deg. H-ATLAS field, it would allow us to robustly identify 3000 gravitational lenses across the 660 square degree Herschel ATLAS fields.

astro-ph.GA↗

arXiv2023

Characterisation of Herschel-selected strong lens candidates through HST and sub-mm/mm observations

We have carried out HST snapshot observations at 1.1 $μ$m of 281 candidate strongly lensed galaxies identified in the wide-area extragalactic surveys conducted with the Herschel space observatory. Our candidates comprise systems with flux densities at $500\,μ$m$ S_{500}\geq 80$ mJy. We model and subtract the surface brightness distribution for 130 systems, where we identify a candidate for the foreground lens candidate. After combining visual inspection, archival high-resolution observations, and lens subtraction, we divide the systems into different classes according to their lensing likelihood. We confirm 65 systems to be lensed. Of these, 30 are new discoveries. We successfully perform lens modelling and source reconstruction on 23 systems, where the foreground lenses are isolated galaxies and the background sources are detected in the HST images. All the systems are successfully modelled as a singular isothermal ellipsoid. The Einstein radii of the lenses and the magnifications of the background sources are consistent with previous studies. However, the background source circularised radii (between 0.34 kpc and 1.30 kpc) are $\sim$3 times smaller than the ones measured in the sub-mm/mm for a similarly selected and partially overlapping sample. We compare our lenses with those in the SLACS survey, confirming that our lens-independent selection is more effective at picking up fainter and diffuse galaxies and group lenses. This sample represents the first step towards characterising the near-IR properties and stellar masses of the gravitationally lensed dusty star-forming galaxies.

astro-ph.GA↗

arXiv2023

Using cGANs for Anomaly Detection: Identifying Astronomical Anomalies in JWST NIRcam Imaging

We present a proof of concept for mining JWST imaging data for anomalous galaxy populations using a conditional Generative Adversarial Network (cGAN). We train our model to predict long wavelength NIRcam fluxes (LW: F277W, F356W, F444W between 2.4 to 5.0μm) from short wavelength fluxes (SW: F115W, F150W, F200W between 0.6 to 2.3μm) in approximately 2000 galaxies. We test the cGAN on a population of 37 Extremely Red Objects (EROs) discovered by the CEERS JWST Team arXiv:2305.14418. Despite their red long wavelength colours, the EROs have blue short wavelength colours (F150W \- F200W equivalently 0 mag) indicative of bimodal SEDs. Surprisingly, given their unusual SEDs, we find that the cGAN accurately predicts the LW NIRcam fluxes of the EROs. However, it fails to predict LW fluxes for other rare astronomical objects, such as a merger between two galaxies, suggesting that the cGAN can be used to detect some anomalies

astro-ph.CO↗

arXiv2023

Objects in JWST's mirrors are closer than they appear

The James Webb Space Telescope (JWST) has revealed extremely distant galaxies at unprecedentedly early cosmic epochs from its deep imaging using the technique of photometric redshift estimation, with its subsequent spectroscopy confirming their redshifts unambiguously, demonstrating the ability of JWST to probe the earliest galaxies, one of its major scientific goals. However, as larger samples continue to be followed up spectroscopically, it has become apparent that nearly all photometric redshifts at these epochs are biased high with confidence >>99%, for as yet unclear reasons. Here we show that this is the same statistical effect that was predicted in different contexts by Sir Arthur Eddington in 1913, in that there exist more lower redshift galaxies to be scattered upwards than the reverse. The bias depends on the shape of the intrinsic redshift distribution, but as an approximate heuristic, all ultra-high photometric redshift estimates must be corrected downwards by up to one standard deviation.

astro-ph.GA↗

arXiv2023

Citizen Science in the European Open Science Cloud

The European Open Science Cloud aims to make all data Findable, Accessible, Interoperable and Reusable. By far the largest community of users of the European Open Science Cloud is the science-inclined public. These users need a more curated experience of open science than subject specialists, but nevertheless make very substantial research contributions in open science, especially in crowdsourced data mining, i.e. citizen science. This short, non-technical invited review presents applications of citizen science in the European Open Science Cloud, with a particular focus on astrophysics and astroparticle physics.

astro-ph.IM↗

arXiv2023

Deep ALMA redshift search of a z~12 GLASS-JWST galaxy candidate

The James Webb Space Telescope (JWST) has discovered a surprising abundance of bright galaxy candidates in the very early Universe ($< 500$ Myrs after the Big Bang), calling into question current galaxy formation models. Spectroscopy is needed to confirm the primeval nature of these candidates, as well as to understand how the first galaxies form stars and grow. Here we present deep spectroscopic and continuum ALMA observations towards GHZ2/GLASS-z12, one of the brightest and most robust candidates at $z > 10$ identified in the GLASS-JWST Early Release Science Program. We detect a $5.8 σ$ line, offset 0.5" from the JWST position of GHZ2/GLASS-z12 that, associating it with the [OIII] 88 micron transition, implies a spectroscopic redshift of $z = 12.117 \pm 0.001$. We verify the detection using extensive statistical tests. The oxygen line luminosity places GHZ2/GLASS-z12 above the [OIII]-SFR relation for metal-poor galaxies, implying an enhancement of [OIII] emission in this system while the JWST-observed emission is likely a lower-metallicity region. The lack of dust emission seen by these observations is consistent with the blue UV slope observed by JWST, which suggest little dust attenuation in galaxies at this early epoch. Further observations will unambiguously confirm the redshift and shed light on the origins of the wide and offset line and physical properties of this early galaxy. This work illustrates the synergy between JWST and ALMA and paves the way for future spectroscopic surveys of $z > 10$ galaxy candidates.

astro-ph.GA↗

arXiv2023

UK Astronomy Science and Technology Roadmap: STFC Astronomy Advisory Panel Roadmap 2022

This document summarises the UK astronomy community's science and technology priorities for funding and investments in the coming decades, following a series of national community consultations by the Astronomy Advisory Panel of the Science and Technology Facilities Council (STFC). The facility remit of STFC is ground-based so the infrastructure recommendations are necessarily also ground-based, but the report also recognises the importance of STFC-funded technology development for, and science exploitation of, the ESA science program including but not limited to X-ray, gamma-ray and multimessenger astronomy.

astro-ph.IM↗

arXiv2022

Galaxy Zoo: Clump Scout -- Design and first application of a two-dimensional aggregation tool for citizen science

Galaxy Zoo: Clump Scout is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital Sky Survey Legacy Survey. We present a statistically driven software framework that is designed to aggregate two-dimensional annotations of clump locations provided by multiple independent Galaxy Zoo: Clump Scout volunteers and generate a consensus label that identifies the locations of probable clumps within each galaxy. The statistical model our framework is based on allows us to assign false-positive probabilities to each of the clumps we identify, to estimate the skill levels of each of the volunteers who contribute to Galaxy Zoo: Clump Scout and also to quantitatively assess the reliability of the consensus labels that are derived for each subject. We apply our framework to a dataset containing 3,561,454 two-dimensional points, which constitute 1,739,259 annotations of 85,286 distinct subjects provided by 20,999 volunteers. Using this dataset, we identify 128,100 potential clumps distributed among 44,126 galaxies. This dataset can be used to study the prevalence and demographics of giant star forming clumps in low-redshift galaxies. The code for our aggregation software framework is publicly available at: https://github.com/ou-astrophysics/BoxAggregator

astro-ph.GA↗

arXiv2022

Searching for giant planets in the outer Solar System with far-infrared all-sky surveys

We have explored a method for finding giant planets in the outer Solar System by detecting their thermal emission and proper motion between two far-infrared all-sky surveys separated by 23.4 years, taken with the InfraRed Astronomical Satellite (IRAS) and the AKARI Space Telescope. An upper distance limit of about 8,000 AU is given by both the sensitivities of these surveys and the distance at which proper motion becomes too small to be detected. This paper covers the region from 8,000 AU to 700 AU. We have used a series of filtering and SED-fitting algorithms to find candidate pairs, whose IRAS and AKARI flux measurements could together plausibly be fitted by a Planck thermal distribution for a likely planetary temperature. Theoretical studies have placed various constraints on the likely existence of unknown planets in the outer solar system. The main observational constraint to date comes from a WISE study: an upper limit on an unknown planet's mass out into the Oort cloud. Our work confirms this result for our distance range, and provides additional observational constraints for lower distances and planetary masses, subject to the proviso that the planet is not confused with Galactic cirrus. We found 535 potential candidates with reasonable spectral energy distribution (SED) fits. Most would have masses close to or below that of Neptune (~0.05 Jupiter mass), and be located below 1,000 AU. However, examination of the infrared images of these candidates suggests that none is sufficiently compelling to warrant follow-up, since all are located inside or close to cirrus clouds, which are most likely the source of the far-infrared flux.

astro-ph.EP↗

arXiv2022

An ALMA Spectroscopic Survey of the Brightest Submillimeter Galaxies in the SCUBA-2-COSMOS field (AS2COSPEC): Survey Description and First Results

We introduce an ALMA band 3 spectroscopic survey, targeting the brightest submillimeter galaxies (SMGs) in the COSMOS field. Here we present the first results based on the 18 primary SMGs that have 870 $μ$m flux densities of $S_{870}=12.4-19.3$ mJy and are drawn from a parent sample of 260 ALMA-detected SMGs from the AS2COSMOS survey. We detect emission lines in 17 and determine their redshifts to be in the range of $z=2-5$ with a median of ${3.3\pm0.3}$. We confirm that SMGs with brighter $S_{870}$ are located at higher redshifts. The data additionally cover five fainter companion SMGs, and we obtain line detection in one. Together with previous studies, our results indicate that for SMGs that satisfy our selection, their brightest companion SMGs are physically associated with their corresponding primary SMGs in $\ge40$% of the time, suggesting that mergers play a role in the triggering of star formation. By modeling the foreground gravitational fields, $<10$% of the primary SMGs can be strongly lensed with a magnification $μ>2$. We determine that about 90\% of the primary SMGs have lines that are better described by double Gaussian profiles, and the median separation of the two Gaussian peaks is 430$\pm$40 km s$^{-1}$. This allows estimates of an average baryon mass, which together with the line dispersion measurements puts our primary SMGs on the similar mass-$σ$ correlation found on local early-type galaxies. Finally, the number density of our $z>4$ primary SMGs is found to be $1^{+0.9}_{-0.6}\times10^6$ cMpc$^{-3}$, suggesting that they can be the progenitors of $z\sim3-4$ massive quiescent galaxies.

astro-ph.GA↗

arXiv2022

Detecting gravitational lenses using machine learning: exploring interpretability and sensitivity to rare lensing configurations

Forthcoming large imaging surveys such as Euclid and the Vera Rubin Observatory Legacy Survey of Space and Time are expected to find more than $10^5$ strong gravitational lens systems, including many rare and exotic populations such as compound lenses, but these $10^5$ systems will be interspersed among much larger catalogues of $\sim10^9$ galaxies. This volume of data is too much for visual inspection by volunteers alone to be feasible and gravitational lenses will only appear in a small fraction of these data which could cause a large amount of false positives. Machine learning is the obvious alternative but the algorithms' internal workings are not obviously interpretable, so their selection functions are opaque and it is not clear whether they would select against important rare populations. We design, build, and train several Convolutional Neural Networks (CNNs) to identify strong gravitational lenses using VIS, Y, J, and H bands of simulated data, with F1 scores between 0.83 and 0.91 on 100,000 test set images. We demonstrate for the first time that such CNNs do not select against compound lenses, obtaining recall scores as high as 76\% for compound arcs and 52\% for double rings. We verify this performance using Hubble Space Telescope (HST) and Hyper Suprime-Cam (HSC) data of all known compound lens systems. Finally, we explore for the first time the interpretability of these CNNs using Deep Dream, Guided Grad-CAM, and by exploring the kernels of the convolutional layers, to illuminate why CNNs succeed in compound lens selection.

astro-ph.GA↗