arXiv subjects

Stephen Serjeant

Publications and source records attributed to Stephen Serjeant.

At least 55 records · Page 3Linked to original sources

arXiv2021

Modelling high-resolution ALMA observations of strongly lensed dustystar forming galaxies detected by Herschel

We present modelling of ~0.1arcsec resolution Atacama Large Millimetre/sub-millimeter Array imaging of seven strong gravitationally lensed galaxies detected by the Herschel Space Observatory. Four of these systems are galaxy-galaxy scale strong lenses, with the remaining three being group-scale lenses. Through careful modelling of visibilities, we infer the mass profiles of the lensing galaxies and by determining the magnification factors, we investigate the intrinsic properties and morphologies of the lensed sub-millimetre sources. We find that these sub-millimetre sources all have ratios of star formation rate to dust mass that is consistent with or in excess of the mean ratio for high-redshift sub-millimetre galaxies and low redshift ultra-luminous infrared galaxies. The contribution to the infrared luminosity from possible AGN is not quantified and so could be biasing our star formation rates to higher values. The majority of our lens models have mass density slopes close to isothermal, but some systems show significant differences.

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arXiv2021

Super-resolving Herschel imaging: a proof of concept using Deep Neural Networks

Wide-field sub-millimetre surveys have driven many major advances in galaxy evolution in the past decade, but without extensive follow-up observations the coarse angular resolution of these surveys limits the science exploitation. This has driven the development of various analytical deconvolution methods. In the last half a decade Generative Adversarial Networks have been used to attempt deconvolutions on optical data. Here we present an autoencoder with a novel loss function to overcome this problem in the sub-millimeter wavelength range. This approach is successfully demonstrated on Herschel SPIRE 500$μ$m COSMOS data, with the super-resolving target being the JCMT SCUBA-2 450$μ$m observations of the same field. We reproduce the JCMT SCUBA-2 images with high fidelity using this autoencoder. This is quantified through the point source fluxes and positions, the completeness and the purity.

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arXiv2021

Identifying muon rings in VERITAS data using convolutional neural networks trained on images classified with Muon Hunters 2

Muons from extensive air showers appear as rings in images taken with imaging atmospheric Cherenkov telescopes, such as VERITAS. These muon-ring images are used for the calibration of the VERITAS telescopes, however the calibration accuracy can be improved with a more efficient muon-identification algorithm. Convolutional neural networks (CNNs) are used in many state-of-the-art image-recognition systems and are ideal for muon image identification, once trained on a suitable dataset with labels for muon images. However, by training a CNN on a dataset labelled by existing algorithms, the performance of the CNN would be limited by the suboptimal muon-identification efficiency of the original algorithms. Muon Hunters 2 is a citizen science project that asks users to label grids of VERITAS telescope images, stating which images contain muon rings. Each image is labelled 10 times by independent volunteers, and the votes are aggregated and used to assign a `muon' or `non-muon' label to the corresponding image. An analysis was performed using an expert-labelled dataset in order to determine the optimal vote percentage cut-offs for assigning labels to each image for CNN training. This was optimised so as to identify as many muon images as possible while avoiding false positives. The performance of this model greatly improves on existing muon identification algorithms, identifying approximately 30 times the number of muon images identified by the current algorithm implemented in VEGAS (VERITAS Gamma-ray Analysis Suite), and roughly 2.5 times the number identified by the Hough transform method, along with significantly outperforming a CNN trained on VEGAS-labelled data.

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arXiv2021

Mid-IR cosmological spectrophotometric surveys from space: Measuring AGN and star formation at the Cosmic Noon with a SPICA-like mission

We use the SPace Infrared telescope for Cosmology and Astrophysics (SPICA) project as a template to demonstrate how deep spectrophotometric surveys covering large cosmological volumes over extended fields (1-15 square degrees) with a mid-IR imaging spectrometer (17-36 micron) in conjunction with deep 70 micron photometry with a far-IR camera, at wavelengths which are not affected by dust extinction can answer the most crucial questions in current galaxy evolution studies. A SPICA-like mission will be able for the first time to provide an unobscured three dimensional (3-D, i.e. x, y and redshift z) view of galaxy evolution back to an age of the Universe of less than ~2 Gyrs, in the mid-IR rest-frame. This survey strategy will produce a full census of the Star formation Rate (SFR) in the Universe, using Polycyclic Aromatic Hydrocarbons (PAH) bands and fine-structure ionic lines, reaching the characteristic knee of the galaxy luminosity function, where the bulk of the population is distributed, at any redshift up to z ~3.5. Deep follow-up pointed spectroscopic observations with grating spectrometers { onboard the satellite}, across the full IR spectral range (17-210 micron), would simultaneously measure Black Hole Accretion Rate (BHAR), from high-ionization fine-structure lines, and SFR, from PAH and low- to mid-ionization lines in thousands of galaxies from solar to low metallicities, down to the knee of their luminosity functions. The analysis of the resulting atlas of IR spectra will reveal the physical processes at play in evolving galaxies across cosmic time, especially its heavily dust-embedded phase during the activity peak at the cosmic noon (z ~1-3), through IR emission lines and features that are insensitive to the dust obscuration.

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arXiv2021

An Active Galactic Nucleus Recognition Model based on Deep Neural Network

To understand the cosmic accretion history of supermassive black holes, separating the radiation from active galactic nuclei (AGNs) and star-forming galaxies (SFGs) is critical. However, a reliable solution on photometrically recognising AGNs still remains unsolved. In this work, we present a novel AGN recognition method based on Deep Neural Network (Neural Net; NN). The main goals of this work are (i) to test if the AGN recognition problem in the North Ecliptic Pole Wide (NEPW) field could be solved by NN; (ii) to shows that NN exhibits an improvement in the performance compared with the traditional, standard spectral energy distribution (SED) fitting method in our testing samples; and (iii) to publicly release a reliable AGN/SFG catalogue to the astronomical community using the best available NEPW data, and propose a better method that helps future researchers plan an advanced NEPW database. Finally, according to our experimental result, the NN recognition accuracy is around 80.29% - 85.15%, with AGN completeness around 85.42% - 88.53% and SFG completeness around 81.17% - 85.09%.

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arXiv2020

ESCAPE -- addressing Open Science challenges

ESCAPE (European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures) is an EU H2020 project that addresses the Open Science challenges shared by the astrophysics and and accelerator-based physics and nuclear physics ESFRI projects and landmarks. This project is embedded in the context of the European Open Science Cloud (EOSC) and involves activities to develop a prototype Data Lake and Science Platform, as well as support of an Open Source Software Repository, connection of the Virtual Observatory framework to EOSC, and engaging the public in citizen science. In this poster paper we provide a brief overview of the project and the results presented at ADASS.

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arXiv2020

Identification of AKARI infrared sources by Deep HSC Optical Survey: Construction of New Band-Merged Catalogue in the NEP-Wide field

The north ecliptic pole (NEP) field is a natural deep field location for many satellite observations. It has been targeted manytimes since it was surveyed by the AKARI space telescope with its unique wavelength coverage from the near- to mid-infrared(mid-IR). Many follow-up observations have been carried out and made this field one of the most frequently observed areas witha variety of facilities, accumulating abundant panchromatic data from X-ray to radio wavelength range. Recently, a deep opticalsurvey with the Hyper Suprime-Cam (HSC) at the Subaru telescope covered the NEP-Wide (NEPW) field, which enabled us toidentify faint sources in the near- and mid-IR bands, and to improve the photometric redshift (photo-z) estimation. In this work,we present newly identified AKARI sources by the HSC survey, along with multi-band photometry for 91,861 AKARI sourcesobserved over the NEPW field. We release a new band-merged catalogue combining various photometric data from GALEXUV to the submillimetre (sub-mm) bands (e.g., Herschel/SPIRE, JCMT/SCUBA-2). About 20,000 AKARI sources are newlymatched to the HSC data, most of which seem to be faint galaxies in the near- to mid-infrared AKARI bands. This cataloguemotivates a variety of current research, and will be increasingly useful as recently launched (eROSITA/ART-XC) and futurespace missions (such as JWST, Euclid, and SPHEREx) plan to take deep observations in the NEP field.

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arXiv2020

The future of astronomy with small satellites

The number of small satellites has grown dramatically in the past decade from tens of satellites per year in the mid-2010s to a projection of tens of thousands in orbit by the mid-2020s. This presents both problems and opportunities for observational astronomy. Small satellites offer complementary cost-effective capabilities to both ground-based astronomy and larger space missions. Compared to ground-based astronomy, these advantages are not just in the accessibility of wavelength ranges where the Earth's atmosphere is opaque, but also in stable, high precision photometry, long-term monitoring and improved areal coverage. Astronomy has a long history of new observational parameter spaces leading to major discoveries. Here we discuss the potential for small satellites to explore new parameter spaces in astrophysics, drawing on examples from current and proposed missions, and spanning a wide range of science goals from binary stars, exoplanets and solar system science to the early Universe and fundamental physics.

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arXiv2020

Predictions for Strong Lens Detections with the Nancy Grace Roman Space Telescope

Strong gravitational lensing is an ideal tool for mapping the distribution of dark matter and for testing the values of cosmological parameters. Forthcoming surveys such as Euclid and the Rubin Observatory LSST should increase the number of known strong lensing systems significantly, with for example over 100,000 such systems predicted in the Euclid wide survey. In this short research note we predict that approximately 17,000 strong gravitational lenses will also be detectible in the Nancy Grace Roman Space Telescope 2000 square degree survey, using the LensPop gravitational lensing model. We present predicted distributions in source and deflector redshifts, magnitudes, and magnifications. Although this survey is not primarily designed as a strong lensing detection experiment, it will still provide a large complementary catalogue to shallower, wider-area forthcoming lensing discovery projects.

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arXiv2020

The e-MERLIN Galaxy Evolution Survey (e-MERGE): Overview and Survey Description

We present an overview and description of the eMERLIN Galaxy Evolution survey (eMERGE) Data Release 1 (DR1), a large program of high-resolution 1.5 GHz radio observations of the GOODS-N field comprising $\sim140$ hours of observations with eMERLIN and $\sim40$ hours with the Very Large Array (VLA). We combine the long baselines of eMERLIN (providing high angular resolution) with the relatively closely-packed antennas of the VLA (providing excellent surface brightness sensitivity) to produce a deep 1.5 GHz radio survey with the sensitivity ($\sim 1.5μ$Jy beam$^{-1}$), angular resolution ($0.2"$--$0.7"$) and field-of-view ($\sim15' \times 15'$) to detect and spatially resolve star-forming galaxies and AGN at $z\gtrsim 1$. The goal of eMERGE is to provide new constraints on the deep, sub-arcsecond radio sky which will be surveyed by SKA1-mid. In this initial publication, we discuss our data analysis techniques, including steps taken to model in-beam source variability over a $\sim20$ year baseline and the development of new point spread function/primary beam models to seamlessly merge eMERLIN and VLA data in the $uv$ plane. We present early science results, including measurements of the luminosities and/or linear sizes of $\sim500$ galaxes selected at 1.5 GHz. In combination with deep Hubble Space Telescope observations, we measure a mean radio-to-optical size ratio of $r_{\rm eMERGE}/r_{\rm HST}\sim1.02\pm0.03$, suggesting that in most high-redshift galaxies, the $\sim$GHz continuum emission traces the stellar light seen in optical imaging. This is the first in a series of papers which will explore the $\sim$kpc-scale radio properties of star-forming galaxies and AGN in the GOODS-N field observed by eMERGE DR1.

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arXiv2019

How far can we push deconvolution? A SCUBA-2 test case

How far can we use multi-wavelength cross-identifications to deconvolve far-infrared images? In this short research note I explore a test case of CLEAN deconvolutions of simulated confused 850 micron SCUBA-2 data, and explore the possible scientific applications of combining this data with ostensibly deeper TolTEC Large Scale Structure (LSS) survey 1.1mm-2mm data. I show that the SCUBA-2 can be reconstructed to the 1.1mm LMT resolution and achieve an 850 micron deconvolved sensitivity of 0.7 mJy RMS, an improvement of at least ~1:5x over naive point source filtered images. The TolTEC/SCUBA-2 combination can constrain cold (<10K) observed-frame colour temperatures, where TolTEC alone cannot.

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arXiv2019

Spitzer catalog of Herschel-selected ultrared dusty, star-forming galaxies

The largest Herschel extragalactic surveys, H-ATLAS and HerMES, have selected a sample of "ultrared" dusty, star-forming galaxies (DSFGs) with rising SPIRE flux densities ($S_{500} > S_{350} > S_{250}$; so-called "500 $μ$m-risers") as an efficient way for identifying DSFGs at higher redshift ($z > 4$). In this paper, we present a large Spitzer follow-up program of 300 Herschel ultrared DSFGs. We have obtained high-resolution ALMA, NOEMA, and SMA data for 63 of them, which allow us to securely identify the Spitzer/IRAC counterparts and classify them as gravitationally lensed or unlensed. Within the 63 ultrared sources with high-resolution data, $\sim$65% appear to be unlensed, and $\sim$27% are resolved into multiple components. We focus on analyzing the unlensed sample by directly performing multi-wavelength spectral energy distribution (SED) modeling to derive their physical properties and compare with the more numerous $z \sim 2$ DSFG population. The ultrared sample has a median redshift of 3.3, stellar mass of 3.7 $\times$ 10$^{11}$ $M_{\odot}$, star formation rate (SFR) of 730 $M_{\odot}$yr$^{-1}$, total dust luminosity of 9.0 $\times$ 10$^{12}$ $L_{\odot}$, dust mass of 2.8 $\times$ 10$^9$ $M_{\odot}$, and V-band extinction of 4.0, which are all higher than those of the ALESS DSFGs. Based on the space density, SFR density, and stellar mass density estimates, we conclude that our ultrared sample cannot account for the majority of the star-forming progenitors of the massive, quiescent galaxies found in infrared surveys. Our sample contains the rarer, intrinsically most dusty, luminous and massive galaxies in the early universe that will help us understand the physical drivers of extreme star formation.

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arXiv2019

Using Convolutional Neural Networks to identify Gravitational Lenses in Astronomical images

The Euclid telescope, due for launch in 2021, will perform an imaging and slitless spectroscopy survey over half the sky, to map baryon wiggles and weak lensing. During the survey Euclid is expected to resolve 100,000 strong gravitational lens systems. This is ideal to find rare lens configurations, provided they can be identified reliably and on a reasonable timescale. For this reason we have developed a Convolutional Neural Network (CNN) that can be used to identify images containing lensing systems. CNNs have already been used for image and digit classification as well as being used in astronomy for star-galaxy classification. Here our CNN is trained and tested on Euclid-like and KiDS-like simulations from the Euclid Strong Lensing Group, successfully classifying 77% of lenses, with an area under the ROC curve of up to 0.96. Our CNN also attempts to classify the lenses in COSMOS HST F814W-band images. After convolution to the Euclid resolution, we find we can recover most systems that are identifiable by eye. The Python code is available on Github.

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arXiv2019

The Strong Gravitational Lens Finding Challenge

Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of millions of images and deriving scientific results from them will require quantifying the efficiency and bias of any search method. To achieve these objectives automated methods must be developed. Because gravitational lenses are rare objects reducing false positives will be particularly important. We present a description and results of an open gravitational lens finding challenge. Participants were asked to classify 100,000 candidate objects as to whether they were gravitational lenses or not with the goal of developing better automated methods for finding lenses in large data sets. A variety of methods were used including visual inspection, arc and ring finders, support vector machines (SVM) and convolutional neural networks (CNN). We find that many of the methods will be easily fast enough to analyse the anticipated data flow. In test data, several methods are able to identify upwards of half the lenses after applying some thresholds on the lens characteristics such as lensed image brightness, size or contrast with the lens galaxy without making a single false-positive identification. This is significantly better than direct inspection by humans was able to do. (abridged)

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arXiv2019

The case for a 'sub-millimeter SDSS': a 3D map of galaxy evolution to z~10

The Sloan Digital Sky Survey (SDSS) was revolutionary because of the extraordinary breadth and ambition of its optical imaging and spectroscopy. We argue that a 'sub-millimeter SDSS' - a sensitive large-area imaging+spectroscopic survey in the sub-mm window - will revolutionize our understanding of galaxy evolution in the early Universe. By detecting the thermal dust continuum emission and atomic and molecular line emission of galaxies out to z~10 it will be possible to measure the redshifts, star formation rates, dust and gas content of hundreds of thousands of high-z galaxies down to ~L*. Many of these galaxies will have counterparts visible in the deep optical imaging of the Large Synoptic Survey Telescope. This 3D map of galaxy evolution will span the peak epoch of galaxy formation all the way back to cosmic dawn, measuring the co-evolution of the star formation rate density and molecular gas content of galaxies, tracking the production of metals and charting the growth of large-scale structure.

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arXiv2019

Cosmic Dawn and Reionization: Astrophysics in the Final Frontier

The cosmic dawn and epoch of reionization mark the time period in the universe when stars, galaxies, and blackhole seeds first formed and the intergalactic medium changed from neutral to an ionized one. Despite substantial progress with multi-wavelength observations, astrophysical process during this time period remain some of the least understood with large uncertainties on our existing models of galaxy, blackhole, and structure formation. This white paper outlines the current state of knowledge and anticipated scientific outcomes with ground and space-based astronomical facilities in the 2020s. We then propose a number of scientific goals and objectives for new facilities in late 2020s to mid 2030s that will lead to definitive measurements of key astrophysical processes in the epoch of reionization and cosmic dawn.

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arXiv2018

JINGLE, a JCMT legacy survey of dust and gas for galaxy evolution studies: I. Survey overview and first results

JINGLE is a new JCMT legacy survey designed to systematically study the cold interstellar medium of galaxies in the local Universe. As part of the survey we perform 850um continuum measurements with SCUBA-2 for a representative sample of 193 Herschel-selected galaxies with M*>10^9Msun, as well as integrated CO(2-1) line fluxes with RxA3m for a subset of 90 of these galaxies. The sample is selected from fields covered by the Herschel-ATLAS survey that are also targeted by the MaNGA optical integral-field spectroscopic survey. The new JCMT observations combined with the multi-wavelength ancillary data will allow for the robust characterization of the properties of dust in the nearby Universe, and the benchmarking of scaling relations between dust, gas, and global galaxy properties. In this paper we give an overview of the survey objectives and details about the sample selection and JCMT observations, present a consistent 30 band UV-to-FIR photometric catalog with derived properties, and introduce the JINGLE Main Data Release (MDR). Science highlights include the non-linearity of the relation between 850um luminosity and CO line luminosity, and the serendipitous discovery of candidate z>6 galaxies.

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arXiv2018

The Herschel-PACS North Ecliptic Pole Survey

A detailed analysis of Herschel-PACS observations at the North Ecliptic Pole is presented. High quality maps, covering an area of 0.44 square degrees, are produced and then used to derive potential candidate source lists. A rigorous quality control pipeline has been used to create final legacy catalogues in the PACS Green 100 micron and Red 160 micron bands, containing 1384 and 630 sources respectively. These catalogues reach to more than twice the depth of the current archival Herschel/PACS Point Source Catalogue, detecting 400 and 270 more sources in the short and long wavelength bands respectively. Galaxy source counts are constructed that extend down to flux densities of 6mJy and 19mJy (50% completeness) in the Green 100 micron and Red 160 micron bands respectively. These source counts are consistent with previously published PACS number counts in other fields across the sky. The source counts are then compared with a galaxy evolution model identifying a population of luminous infrared galaxies as responsible for the bulk of the galaxy evolution over the flux range (5-100mJy) spanned by the observed counts, contributing approximate fractions of 50% and 60% to the cosmic infrared background (CIRB) at 100 microns and 160 microns respectively.

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