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Kenneth J. Duncan

Publications and source records attributed to Kenneth J. Duncan.

At least 19 recordsLinked to original sources

JWST observes the assembly of a massive galaxy at z~4

We present JWST observations of the radio galaxy TGSSJ1530+1049, spectroscopically confirmed at $z=4.0$. NIRCam images and NIRSpec/IFU spectroscopy (R=2700) show that TGSSJ1530+1049 is part of one of the densest-known structures of continuum and line-emitting objects found at these redshifts. NIRCam images show a number of distinct continuum objects and evidence of interactions traced by diffuse emission, and the NIRSpec IFU cube reveals further strong line emitting regions. We identify six continuum and four additional strong H$α$ emitting sources with weaker or no underlying continuum within the 3x3 arcsec IFU field. From spatial alignment with high-resolution radio data and emission line profiles, the radio AGN host galaxy is clearly identified. The bright H$α$ emission (but not the optical components) is distributed remarkably linearly along the radio axis, suggestive of a biconical illumination zone by a central obscured AGN. The emission line kinematics indicate jet-gas interactions on scales of a few kpc. However, due to large relative velocities and presence of underlying continuum, the alignment with the radio structure appears to be, at least partly, caused by a particular configuration of interacting galaxies. At least four objects within a 10x10 (projected) kpc$^2$ area which includes the radio source have high stellar masses ($\log(M_\star/M_\odot)>10.3$) and star formation rates in the range $70-163\,M_\odot$ yr$^{-1}$. Using a stellar mass-based analysis, we predict a total dark matter halo mass of $\approx10^{13} M_\odot$. Based on the physical separations and velocity differences between the galaxies, it is expected that these galaxies will merge to form a massive galaxy within a few Gyr. The system qualitatively resembles the forming brightest cluster galaxies in cosmological simulations that form early through a rapid succession of mergers.

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Making the most of pure parallels: Machine learning augmented photometric redshifts for sparse JWST filter sets

Photometric redshifts (photo-$z$s) are an essential tool for galaxy evolution science with JWST. However, for deep surveys with more limited filter sets (i.e. $N_{\text{filt}} \sim6$) such as large pure parallel surveys, the most commonly used template-fitting based photo-$z$ approaches can yield highly confident but spurious results for high-$z$ populations of interest. The utility and legacy value of these datasets could therefore be negatively impacted. To address this challenge, we present an application of machine learning (ML) based photo-$z$ techniques to deep JWST photometric datasets. We employ two different ML algorithms, using Gaussian processes and nearest-neighbour estimates, alongside a more standard template fitting approach. We show that simple nearest-neighbour based estimates can provide more accurate photo-$z$s than template fitting out to $z\sim8$, as well as reducing the fraction of catastrophic outliers by a factor of $\sim2-3$. Additionally, `hybrid' estimates combining template and ML can yield further improvements in overall accuracy and reliability while retaining some ability to predict photo-$z$ out to $z > 10$. The nearest-neighbour only or hybrid estimates can achieve photo-$z$s with robust scatter of $σ_{\text{NMAD}}\sim0.03-0.04$ and outlier fractions of $\sim3-10\%$ between $0 < z \lesssim 8$ from just 6 NIRCam bands, with negligible additional computational costs compared to standard template fitting. Our methodology is easily adaptable to alternative datasets, filter combinations or training samples. Overall, our results highlight the potential for even simple ML techniques to enhance the scientific return of JWST pure parallel and wide-area surveys.

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Another piece to the puzzle: radio detection of a JWST detected AGN candidate

Radio observations can provide crucial insight into the nature of a new abundant and mysterious population of dust-reddened active galactic nuclei (AGN) candidates discovered by the James Webb Space Telescope (JWST), including Little Red Dots (LRDs). In this study, we search for radio bright sources in a large sample of $\sim$700 JWST discovered AGN candidates ($z\sim2-11$) in the 0.144-3 GHz frequency range, utilizing deep radio imaging in COSMOS, GOODS-N, and GOODS-S. Only one source, PRIMER-COS 3866 at $z=4.66$, is significantly detected in our radio surveys, which has been previously identified as an X-ray AGN. Its radio properties are consistent with both an AGN and star formation origin with a spectral index of $α=-0.76^{+0.11}_{-0.09}$, radio-loudness of $R\approx0.5$, and brightness temperature limit of $T_b \gtrsim 10^{3}$ K. Our stacking results of both spectroscopically and photometrically selected AGN candidates yield non-detections in all fields, with 3$σ$ limits of $L_{1.4\text{GHz}} < 8.6\times10^{39}$ erg s$^{-1}$ (spectroscopic sample) and $L_{1.3\text{GHz}} < 1.3\times10^{39}$ erg s$^{-1}$ (photometric sample). We demonstrate that these results are still consistent with expectations from the empirical $L_X - L_{\text{H}α}$ and $L_X - L_R$ correlations established for local AGN. We argue that current radio observations in these studied fields have insufficient depth to claim JWST discovered AGN candidates are radio-weak. We project that future surveys carried out by the SKA and ngVLA should be able to obtain significant detections within a few hours, providing crucial measurements of their brightness temperature, which would allow for distinguishing between AGN and starburst-driven origins of this new abundant population.

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Galaxy Mergers in the Epoch of Reionization I: A JWST Study of Pair Fractions, Merger Rates, and Stellar Mass Accretion Rates at $z = 4.5-11.5$

We present a full analysis of galaxy major merger pair fractions, merger rates, and mass accretion rates, thus uncovering the role of mergers in galaxy formation at the earliest previously unexplored epoch of $4.5<z<11.5$. We target galaxies with masses $\log_{10}(\mathrm{M}_*/\mathrm{M}_\odot) = 8.0 - 10.0$, utilizing data from eight JWST Cycle-1 fields (CEERS, JADES GOODS-S, NEP-TDF, NGDEEP, GLASS, El-Gordo, SMACS-0723, MACS-0416), covering an unmasked area of 189.36 $\mathrm{arcmin}^2$. We develop a new probabilistic pair-counting methodology that integrates full photometric redshift posteriors and corrects for detection incompleteness to quantify close pairs with physical projected separations between 20 and 50 kpc. Our analysis reveals an increase in pair fractions up to $z = 8$, reaching $0.211 \pm 0.065$, followed by a statistically flat evolution to $z = 11.5$. We find that the galaxy merger rate increases from the local Universe up to $z = 6$ and then stabilizes at a value of $\sim 6$ Gyr$^{-1}$ up to $z = 11.5$. The redshift evolution of both pair fractions and merger rates is well described by a power-law plus exponential model. In addition, we measure that the average galaxy increases its stellar mass due to mergers by a factor of $2.77 \pm 0.99$ from redshift $z = 10.5$ to $z = 5.0$. Lastly, we investigate the impact of mergers on galaxy stellar mass growth, revealing that mergers contribute as much as $71 \pm 25\%$ to galaxy stellar mass growth. This indicates that mergers drive about half of galaxy assembly at high redshift.

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Galaxy Mergers in the Epoch of Reionization II: Major Merger-Triggered Star Formation and AGN Activities at $z =$ 4.5-8.5

Galaxy mergers are a key driver of galaxy formation and evolution, including the triggering of AGN and star formation to a still unknown degree. We thus investigate the impact of galaxy mergers on star formation and AGN activity using a sample of 3,330 galaxies at $z = [4.5, 8.5]$ from eight JWST fields (CEERS, JADES GOODS-S, NEP-TDF, NGDEEP, GLASS, El-Gordo, SMACS-0723, and MACS-0416), collectively covering an unmasked area of 189 arcmin$^2$. We focuses on star formation rate (SFR) enhancement, AGN fraction, and AGN excess in major merger ($μ> 1/4$) close-pair samples, defined by $Δz < 0.3$ and projected separations $r_p < 100$ kpc, compared to non-merger samples. We find that SFR enhancement occurs only at $r_p < 20$ kpc, with values of $0.25 \pm 0.10$ dex and $0.26 \pm 0.11$ dex above the non-merger medians for $z = [4.5, 6.5]$ and $z = [6.5, 8.5]$. No other statistically significant enhancements in galaxy sSFR or stellar mass are observed at any projected separation or redshift bin. We also compare our observational results with predictions from the SC-SAM simulation and find no evidence of star formation enhancement in the simulations at any separation range. Finally, we examine the AGN fraction and AGN excess, finding that the fraction of AGNs in AGN-galaxy pairs, relative to the total AGN population, is $3.25^{+1.50}_{-1.06}$ times greater than the fraction of galaxy pairs relative to the overall galaxy population at the same redshift. We find that nearly all AGNs have a companion within 100 kpc and observe an excess AGN fraction in close-pair samples compared to non-merger samples. This excess is found to be $1.26 \pm 0.06$ and $1.34 \pm 0.06$ for AGNs identified via the inferred BPT diagram and photometric SED selection, respectively.

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Unveiling AGN Outflows: [O iii] Outflow Detection Rates and Correlation with Low-Frequency Radio Emission

Some Active Galactic Nuclei (AGN) host outflows which have the potential to alter the host galaxy's evolution (AGN feedback). These outflows have been linked to enhanced radio emission. Here we investigate the connection between low-frequency radio emission using the International LOFAR Telescope and [O III] $λ$5007 ionised gas outflows using the Sloan Digital Sky Survey. Using the LOFAR Two-metre Sky Survey (LoTSS) Deep Fields, we select 198 AGN with optical spectra, 115 of which are detected at 144 MHz, and investigate their low-frequency radio emission properties. The majority of our sample do not show a radio excess when considering radio luminosity - SFR relationship, and are therefore not driven by powerful jets. We extract the [O III] $λ$5007 kinematics and remove AGN luminosity dependencies by matching the radio detected and non-detected AGN in $L_{\mathrm{6μm}}$ and redshift. Using both spectral fitting and $W_{80}$ measurements, we find radio detected AGN have a higher outflow rate (67.2$\pm$3.4 percent) than the radio non-detected AGN (44.6$\pm$2.7 percent), indicating a connection between ionised outflows and the presence of radio emission. For spectra where there are two components of the [O III] emission line present, we normalise all spectra by the narrow component and find that the average broad component in radio detected AGN is enhanced compared to the radio non-detected AGN. This could be a sign of higher gas content, which is suggestive of a spatial relationship between [O III] outflows and radio emission in the form of either low-powered jets or shocks from AGN winds.

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Monster radio jet (>66 kpc) observed in quasar at z$\sim$5

We present the discovery of a large extended radio jet associated with the extremely radio-loud quasar J1601+3102 at $z\sim5$ from sub-arcsecond resolution imaging at 144 MHz with the LOFAR International Telescope. These large radio lobes have been argued to remain elusive at $z>4$ due to energy losses in the synchrotron emitting plasma as a result of scattering of the strong CMB at these high redshifts. Nonetheless, the 0.3" resolution radio image of J1601+3102 reveals a Northern and Southern radio lobe located at 9 and 57 kpc from the optical quasar, respectively. The measured jet size of 66 kpc makes J1601+3102 the largest extended radio jet at $z>4$ to date. However, it is expected to have an even larger physical size in reality due to projection effects brought about by the viewing angle. Furthermore, we observe the rest-frame UV spectrum of J1601+3102 with Gemini/GNIRS to examine its black hole properties, which results in a mass of 4.5$\times$10$^{8}$ M$_{\odot}$ with an Eddington luminosity ratio of 0.45. The BH mass is relatively low compared to the known high-$z$ quasar population, which suggests that a high BH mass is not strictly necessary to generate a powerful jet. This discovery of the first $\sim100$ kpc radio jet at $z>4$ shows that these objects exist despite energy losses from Inverse Compton scattering and can put invaluable constraints on the formation of the first radio-loud sources in the early Universe.

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Flux dependence of redshift distribution and clustering of LOFAR radio sources

In this work we study the flux density dependence of the redshift distribution of low-frequency radio sources observed in the LOFAR Two-metre Sky Survey (LoTSS) deep fields and apply it to estimate the clustering length of the large-scale structure of the Universe, examining flux density limited samples (1 mJy, 2 mJy, 4 mJy and 8 mJy) of LoTSS wide field radio sources. We utilise and combine the posterior probability distributions of photometric redshift determinations for LoTSS deep field observations from three different fields (Boötes, Lockman hole and ELAIS-N1, together about $26$ square degrees of sky), which are available for between $91\%$ to $96\%$ of all sources above the studied flux density thresholds and observed in the area covered by multi-frequency data. We estimate uncertainties by a bootstrap method. We apply the inferred redshift distribution on the LoTSS wide area radio sources from the HETDEX field (LoTSS-DR1; about $424$ square degrees) and make use of the Limber approximation and a power-law model of three dimensional clustering to measure the clustering length, $r_0$, for various models of the evolution of clustering. We find that the redshift distributions from all three LoTSS deep fields agree within expected uncertainties. We show that the radio source population probed by LoTSS at flux densities above $1$ mJy has a median redshift of at least $0.9$. At $2$ mJy, we measure the clustering length of LoTSS radio sources to be $r_0 = (10.1\pm 2.6) \ h^{-1}$Mpc in the context of the comoving clustering model. Our findings are in agreement with measurements at higher flux density thresholds at the same frequency and with measurements at higher frequencies in the context of the comoving clustering model.

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The LOFAR Two-metre Sky Survey: The nature of the faint source population and SFR-radio luminosity relation using Prospector

Spectral energy distribution (SED) fitting has been extensively used to determine the nature of the faint radio source population. Recent efforts have combined fits from multiple SED-fitting codes to account for the host galaxy and any active nucleus that may be present. We show that it is possible to produce similar-quality classifications using a single energy-balance SED fitting code, Prospector, to model up to 26 bands of UV$-$far-infrared aperture-matched photometry for $\sim$31,000 sources in the ELAIS-N1 field from the LOFAR Two-Metre Sky Survey (LoTSS) Deep fields first data release. One of a new generation of SED-fitting codes, Prospector accounts for potential contributions from radiative active galactic nuclei (AGN) when estimating galaxy properties, including star formation rates (SFRs) derived using non-parametric star formation histories. Combining this information with radio luminosities, we classify 92 per cent of the radio sources as a star-forming galaxy, high/low-excitation radio galaxy, or radio-quiet AGN and study the population demographics as a function of 150 MHz flux density, luminosity, SFR, stellar mass, redshift and apparent $r$-band magnitude. Finally, we use Prospector SED fits to investigate the SFR$-$150 MHz luminosity relation for a sample of $\sim$$133,000~3.6~μ$m-selected $z<1$ sources, finding that the stellar mass dependence is significantly weaker than previously reported, and may disappear altogether at $\log_{10} (\mathrm{SFR}/M_\odot~\mathrm{yr}^{-1}) > 0.5$. This approach makes it significantly easier to classify radio sources from LoTSS and elsewhere, and may have important implications for future studies of star-forming galaxies at radio wavelengths.

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Constraining the giant radio galaxy population with machine learning and Bayesian inference

Large-scale sky surveys at low frequencies, like the LOFAR Two-metre Sky Survey (LoTSS), allow for the detection and characterisation of unprecedented numbers of giant radio galaxies (GRGs, or 'giants'). In this work, by automating the creation of radio--optical catalogues, we aim to significantly expand the census of known giants. We then combine this sample with a forward model to constrain GRG properties of cosmological interest. In particular, we automate radio source component association through machine learning and optical host identification for resolved radio sources. We create a radio--optical catalogue for the full LoTSS Data Release 2 (DR2) and select all possible giants. We combine our candidates with an existing catalogue of LoTSS DR2 crowd-sourced GRG candidates and visually confirm or reject them. To infer intrinsic GRG properties from GRG observations, we develop further a population-based forward model that takes into account selection effects and constrain its parameters using Bayesian inference. We confirm 5,647 previously unknown giants from the crowd-sourced catalogue and 2,597 previously unknown giants from the ML-driven catalogue. Our confirmations and discoveries bring the total number of known giants to at least 11,585. We predict a comoving GRG number density $n_\mathrm{GRG} = 13 \pm 10\ (100\ \mathrm{Mpc})^{-3}$, close to a recent estimate of the number density of luminous non-giant radio galaxies. We derive a current-day GRG lobe volume-filling fraction $V_\mathrm{GRG-CW}(z = 0) = 1.4 \pm 1.1 \cdot 10^{-5}$ in clusters and filaments of the Cosmic Web. Our analysis suggests that giants are more common than previously thought. Moreover, tentative results imply that it is possible that magnetic fields once contained in giants pervade a significant ($\gtrsim 10\%$) fraction of today's Cosmic Web.

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Widespread AGN feedback in a forming brightest cluster galaxy at $z=4.1$ unveiled by JWST

We present rest-frame optical spectroscopy using JWST/NIRSpec IFU for the radio galaxy TN J1338-1942 at z=4.1, one of the most luminous galaxies in the early Universe with powerful extended radio jets. Previous observations showed evidence for strong, large-scale outflows on the basis of its large (~150 kpc) halo detected in Ly-alpha, and high velocity [O II] emission features detected in ground-based IFU data. Our NIRSpec/IFU observations spatially resolve the emission line properties across the host galaxy in great detail. We find at least five concentrations of line emission, coinciding with discrete continuum features previously detected in imaging from HST and JWST, over an extent of ~2'' (~15 kpc). The spectral diagnostics enabled by NIRSpec unambiguously trace the activity of the obscured AGN plus interaction between the interstellar medium and the radio jet as the dominant mechanisms for the ionization state and kinematics of the gas in the system. A secondary region of very high ionization lies at roughly 5 kpc distance from the nucleus, and within the context of an expanding cocoon enveloping the radio lobe, this may be explained by strong shock-ionization of the entrained gas. However, it could also signal the presence of a second obscured AGN, which may also offer an explanation for an intriguing outflow feature seen perpendicular to the radio axis. The presence of a dual SMBH system in this galaxy would support that large galaxies in the early Universe quickly accumulated their mass through the merging of smaller units (each with their own SMBH), at the centers of large overdensities. The inferred black hole mass to stellar mass ratio of 0.01-0.1 for TNJ1338 points to a more rapid assembly of black holes compared to the stellar mass of galaxies at high redshifts, consistent with other recent observations.

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The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z<0.5$ cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using $>1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.

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JWST's PEARLS: TN J1338-1942 -- I. Extreme jet triggered star-formation in a $z=4.11$ luminous radio galaxy

We present the first JWST observations of the $z=4.11$ luminous radio galaxy TN J1338-1942, obtained as part of the ``Prime Extragalactic Areas for Reionization and Lensing Science'' (``PEARLS'') project. Our NIRCam observations, designed to probe the key rest-frame optical continuum and emission line features at this redshift, enable resolved spectral energy distribution modelling that incorporates both a range of stellar population assumptions and radiative shock models. With an estimated stellar mass of $\log_{10}(M/\text{M}_{\odot}) \sim 10.9$, TN J1338--1942 is confirmed to be one of the most massive galaxies known at this epoch. Our observations also reveal extremely high equivalent-width nebular emission coincident with the luminous AGN jets that is best fit by radiative shocks surrounded by extensive recent star-formation. We estimate the total star-formation rate (SFR) could be as high as $\sim1600\,\text{M}_{\odot}\,\text{yr}^{-1}$, with the SFR that we attribute to the jet induced burst conservatively $\gtrsim500\,\text{M}_{\odot}\,\text{yr}^{-1}$. The mass-weighted age of the star-formation, $t_{\text{mass}} <4$ Myr, is consistent with the likely age of the jets responsible for the triggered activity and significantly younger than that measured in the core of the host galaxy. The extreme scale of the potential jet-triggered star-formation activity indicates the potential importance of positive AGN feedback in the earliest stages of massive galaxy formation, with our observations also illustrating the extraordinary prospects for detailed studies of high-redshift galaxies with JWST.

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Finding AGN remnant candidates based on radio morphology with machine learning

Remnant radio galaxies represent the dying phase of radio-loud active galactic nuclei (AGN). Large samples of remnant radio galaxies are important for quantifying the radio galaxy life cycle. The remnants of radio-loud AGN can be identified in radio sky surveys based on their spectral index, or, complementary, through visual inspection based on their radio morphology. However, this is extremely time-consuming when applied to the new large and sensitive radio surveys. Here we aim to reduce the amount of visual inspection required to find AGN remnants based on their morphology, through supervised machine learning trained on an existing sample of remnant candidates. For a dataset of 4107 radio sources, with angular sizes larger than 60 arcsec, from the LOw Frequency ARray (LOFAR) Two-Metre Sky Survey second data release (LoTSS-DR2), we started with 151 radio sources that were visually classified as 'AGN remnant candidate'. We derived a wide range of morphological features for all radio sources from their corresponding Stokes-I images: from simple source catalogue-derived properties, to clustered Haralick-features, and self-organising map (SOM) derived morphological features. We trained a random forest classifier to separate the 'AGN remnant candidates' from the not yet inspected sources. The SOM-derived features and the total to peak flux ratio of a source are shown to be most salient to the classifier. We estimate that $31\pm5\%$ of sources with positive predictions from our classifier will be labelled 'AGN remnant candidates' upon visual inspection, while we estimate the upper bound of the $95\%$ confidence interval for 'AGN remnant candidates' in the negative predictions at $8\%$. Visual inspection of just the positive predictions reduces the number of radio sources requiring visual inspection by $73\%$.

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JWST's PEARLS: A JWST/NIRCam view of ALMA sources

We report the results of James Webb Space Telescope/NIRCam observations of 19 (sub)millimeter (submm/mm) sources detected by the Atacama Large Millimeter Array (ALMA). The accurate ALMA positions allowed unambiguous identifications of their NIRCam counterparts. Taking gravitational lensing into account, these represent 16 distinct galaxies in three fields and constitute the largest sample of its kind to date. The counterparts' spectral energy distributions from rest-frame ultraviolet to near infrared provide photometric redshifts ($1 10^{10.5}$ Msol), which are similar to sub-millimeter galaxy (SMG) hosts studied previously. However, our sample is fainter in submm/mm than the classic SMG samples are, and our sources exhibit a wider range of properties. They have dust-embedded star-formation rates as low as 10 Msol yr$^{-1}$, and the sources populate both the star-forming main sequence and the quiescent categories. The deep NIRCam data allow us to study the rest-frame near-IR morphologies. Excluding two multiply imaged systems and one quasar, the majority of the remaining sources are disk-like and show either little or no disturbance. This suggests that secular growth is a potential route for the assembly of high-mass disk galaxies. While a few hosts have large disks, the majority have small disks (median half-mass radius of 1.6 kpc). At this time, it is unclear whether this is due to the prevalence of small disks at these redshifts or some unknown selection effects of deep ALMA observations. A larger sample of ALMA sources with NIRCam observations will be able to address this question.

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The Art of Measuring Physical Parameters in Galaxies: A Critical Assessment of Spectral Energy Distribution Fitting Techniques

The study of galaxy evolution hinges on our ability to interpret multi-wavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to the wide and deep multi-waveband galaxy surveys, the volume of high quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply fourteen of the most commonly used SED fitting codes on samples from the CANDELS photometric catalogs at z~1 and z~3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust, and AGN models) on the derived stellar masses, SFRs, and A_V values. We then assess the difference among the codes on the SFR-stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (~0.1dex), SFR (~0.3dex), and dust attenuation (~0.3mag). Finally, we present some resources summarizing best practices in SED fitting.

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JWST's PEARLS: Prime Extragalactic Areas for Reionization and Lensing Science: Project Overview and First Results

We give an overview and describe the rationale, methods, and first results from NIRCam images of the JWST "Prime Extragalactic Areas for Reionization and Lensing Science" ("PEARLS") project. PEARLS uses up to eight NIRCam filters to survey several prime extragalactic survey areas: two fields at the North Ecliptic Pole (NEP); seven gravitationally lensing clusters; two high redshift proto-clusters; and the iconic backlit VV 191 galaxy system to map its dust attenuation. PEARLS also includes NIRISS spectra for one of the NEP fields and NIRSpec spectra of two high-redshift quasars. The main goal of PEARLS is to study the epoch of galaxy assembly, AGN growth, and First Light. Five fields, the JWST NEP Time-Domain Field (TDF), IRAC Dark Field (IDF), and three lensing clusters, will be observed in up to four epochs over a year. The cadence and sensitivity of the imaging data are ideally suited to find faint variable objects such as weak AGN, high-redshift supernovae, and cluster caustic transits. Both NEP fields have sightlines through our Galaxy, providing significant numbers of very faint brown dwarfs whose proper motions can be studied. Observations from the first spoke in the NEP TDF are public. This paper presents our first PEARLS observations, their NIRCam data reduction and analysis, our first object catalogs, the 0.9-4.5 $μ$m galaxy counts and Integrated Galaxy Light. We assess the JWST sky brightness in 13 NIRCam filters, yielding our first constraints to diffuse light at 0.9-4.5 μm. PEARLS is designed to be of lasting benefit to the community.

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Radio source-component association for the LOFAR Two-metre Sky Survey with region-based convolutional neural networks

Radio loud active galactic nuclei (RLAGNs) are often morphologically complex objects that can consist of multiple, spatially separated, components. Astronomers often rely on visual inspection to resolve radio component association. However, applying visual inspection to all the hundreds of thousands of well-resolved RLAGNs that appear in the images from the Low Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) at $144$ MHz, is a daunting, time-consuming process, even with extensive manpower. Using a machine learning approach, we aim to automate the radio component association of large ($> 15$ arcsec) radio components. We turned the association problem into a classification problem and trained an adapted Fast region-based convolutional neural network to mimic the expert annotations from the first LoTSS data release. We implemented a rotation data augmentation to reduce overfitting and simplify the component association by removing unresolved radio sources that are likely unrelated to the large and bright radio components that we consider using predictions from an existing gradient boosting classifier. For large ($> 15$ arcsec) and bright ($> 10$ mJy) radio components in the LoTSS first data release, our model provides the same associations for $85.3\%\pm0.6$ of the cases as those derived when astronomers perform the association manually. When the association is done through public crowd-sourced efforts, a result similar to that of our model is attained. Our method is able to efficiently carry out manual radio-component association for huge radio surveys and can serve as a basis for either automated radio morphology classification or automated optical host identification. This opens up an avenue to study the completeness and reliability of samples of radio sources with extended, complex morphologies.

astro-ph.IM