arXiv subjects

R. Shirley

Publications and source records attributed to R. Shirley.

At least 19 recordsLinked to original sources

arXiv2026

Photometric redshifts for active galactic nuclei with LePHARE for the Vera C. Rubin Observatory

Active Galactic Nuclei (AGN) play a crucial role in galaxy evolution, but they are a minority of extragalactic sources with diverse Spectral Energy Distributions (SEDs), which depend on their means of selection. Upcoming large-scale surveys such as LSST will identify many AGN, but analysis tools are not optimized for them. The limited number of photometric bands in these surveys impacts the calculation of photometric redshifts for AGN, which are essential for scientific advancement. We use LePHARE to demonstrate the impact that a limited number of bands and erroneous assumptions have on the determination of the photometric redshifts of AGN. We conduct tests on six AGN samples selected using X-ray, radio, infrared, variability, color, and spectroscopic criteria in the COSMOS field, using photometry from HSC-CLAUDS, which is closest in depth and wavelength coverage to LSST. We present the LSST pipeline for LePHARE within the Redshift Assessment Infrastructure Layers (RAIL), facilitating comparison between SED fitting and machine learning algorithms. AGN that appear as point-like sources in optical data will be assigned highly unreliable photometric redshifts if they are processed using galaxy templates. Additionally, shallow all-sky surveys (like eROSITA, WISE, and ZTF) miss many AGN. As a result, these "hidden" AGN are often misidentified as galaxies in public survey data, leading to incorrect photometric redshift. We provide the configurations that are suggested for each type of AGN alongside measures of expected performance as a function of redshift, magnitude, and selection. To facilitate studies with a panchromatic view of AGN, we also release photometric redshifts and posterior distributions for all AGN sources identified in the COSMOS field using the six criteria, based on 28-band photometry.

astro-ph.GA↗

arXiv2026

The SRG/eROSITA All-Sky Survey DR2: Cumulative X-ray catalogues from the first three surveys and multi-wavelength counterparts in the western Galactic hemisphere

The eROSITA telescope array on board the Spektrum-Roentgen-Gamma (SRG) mission began its all-sky survey program in December 2019, scanning the sky at an approximately six-month cadence. Here, we present new catalogues of point-like and extended X-ray sources derived from the first three completed eROSITA all-sky surveys (eRASS:3), covering the western Galactic hemisphere, which Germany's eROSITA consortium holds proprietary rights for. We describe the observational strategy, data processing, and analysis pipelines. We also characterise the resulting X-ray source populations. The eRASS:3 main catalogue contains nearly two million sources, including 1,911,744 point-like and 63,796 extended sources, detected in the 0.2-2.3 keV energy band, eROSITA's most sensitive energy window. This volume has doubled the X-ray source content of eRASS1 and provides a comprehensive census of X-ray-emitting objects across diverse astrophysical classes. We also released a secondary hard catalogue of nearly 15,000 sources detected in the harder 2.3-5.0 keV energy band. In addition, we released six catalogues, three for the main sample and three for the hard sample, in which we identify and classify the optical and infrared counterparts of eRASS:3 point-like sources. This approach delivers a homogeneous, high-quality identification of mostly extragalactic X-ray emitters; for example, we estimate that approximately 88% of the 1.4 million counterparts identified within the footprints of the Legacy Survey Imaging for DESI are extragalactic sources. This work has enabled the generation of samples optimised for completeness and purity, while expanding the discovery space for rare populations. The second data release (DR2) of the SRG/eROSITA all-sky survey is a catalogue-only release, comprising the catalogues presented in this work together with an updated version of the eROSITA upper flux limit server.

astro-ph.HE↗

arXiv2026

The eROSITA X-ray luminosity function of active galactic nuclei

The X-ray luminosity function (XLF) of active galactic nuclei (AGN) provides an observational probe of the growth of supermassive black holes (SMBHs) across cosmic time. With its large survey grasp, Spectrum Roentgen Gamma (SRG)/eROSITA samples the luminosity--redshift plane with a depth--area balance complementary to pencil-beam surveys, providing the volume needed to detect rare luminous AGN, previously limited by small-number statistics. We measure the soft XLF, leveraging an eROSITA sample spanning approximately eight orders of magnitude in luminosity out to $z\simeq6$. This enables us to study luminosity-dependent evolution with improved constraints, and to infer both the SMBH accretion history and optical/UV missed AGN population. We introduce a new redshift-dependent smoothly broken power-law parameterisation in which all XLF model parameters are allowed to evolve continuously with redshift. We find lower space densities for moderately and very luminous AGN at low redshift, while the abundance is higher than previously found at the highest redshifts. Comparisons to optical/UV quasar LFs converted to rest-frame $2\!-\!10\,\mathrm{keV}$ show that the UV-missed fraction decreases with luminosity, and, in the most luminous bin, increases with redshift. Integrating the XLF yields a black-hole accretion-rate density peaking at $z \simeq 1.5$, with the corresponding cumulative black-hole mass density indicating $\sim80^{+11}_{-23}\%$ obscured growth relative to locally-inferred BH mass estimates derived from scaling relations and missed by the soft X-ray selection of our sample. With this work, we release the eROSITA DR2 AGN catalogue, including counterparts and their redshift information. We then discuss how these results can inform future spectroscopic, photometric, and X-ray survey strategies aimed at improving AGN demographic constraints.

astro-ph.GA↗

arXiv2026

VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features

Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral energy distribution (SED) fitting suffers from color-redshift degeneracies, particularly for AGNs whose power-law continua hide the strong spectral features required to anchor redshift estimates. While AGN variability provides additional constraining power, existing frameworks require multi-band light curves that are not always available. This work presents VAR-PZnn, a fully connected mixture density network that integrates 26 variability features extracted from ZTF g-band light curves with optical photometry from Pan-STARRS1, mid-infrared (MIR) photometry from CatWISE, and, for a subsample, NIR photometry from UKIDSS. The model is trained and tested on 72,728 spectroscopically confirmed AGNs/QSOs spanning 0.01 < z < 4.5 and g-band magnitudes from 17 to 21.5. For the main sample, we achieve \sigma_{NMAD} = 0.058 and an outlier fraction of \eta = 8.2%, which reduces to 5.4% when the 10% of sources with the highest predicted uncertainty are excluded. An ablation study demonstrates that MIR photometry provides the dominant constraint for photo-z accuracy, while variability features serve as a secondary refiner. Using UKIDSS NIR data as a proxy for future synergies between LSST and space-based missions like Euclid and Roman, we obtain \eta = 13.3% without MIR data and \eta = 4.6% when MIR is available. We benchmark against Low-Resolution Templates (LRT) SED fitting (\eta = 28.7%) and the VAR-PZ framework; applying single-band VAR-PZ priors worsens LRT performance to \eta = 39.4% due to single-band light-curve degeneracies, confirmed via simulations (\eta = 27.6% to 28.1%). This framework provides a scalable approach for the Legacy Survey of Space and Time (LSST).

astro-ph.GA↗

arXiv2026

Euclid Quick Data Release (Q1): The impact of AGN emission on SED-derived physical properties

The Euclid Quick Data Release (Q1) is a powerful dataset to study active galactic nuclei (AGN) and their host galaxies. Deriving their physical properties through multi-component spectral energy distribution (SED) fitting is a challenging task for AGN, but it is greatly aided by the Euclid near-infrared photometry. Here we present a new method to quantify the reliability of SED-derived parameters, such as AGN bolometric and monochromatic luminosities, host's stellar mass $M_\star$, star-formation rate (SFR) and specific star-formation rate (sSFR), by using mock SEDs of AGN built by combining observed SEDs of QSOs and galaxies. We apply this methodology to the ${\sim}1$ million Q1 AGN candidates, constructing a catalogue of AGN and host galaxy properties, alongside their respective reliability values. With a reliability threshold at 0.5, we find 88\% of sources with robust stellar masses and 76\% with reliable AGN luminosities. Moreover, through SED fitting we also measure the AGN fraction $f_{\rm AGN}$ of the total mid-infrared flux and we use its lower-limit to select AGN. A $f_{\rm AGN, \, low} > 0.075$ threshold yields 85\% completeness and purity. Comparable to colour-colour AGN selections, this method has the advantage of being less affected by redshift evolution and exploring fainter magnitudes. Additionally, by comparing the AGN and host galaxy parameters across different identification methods, we find that the probed range in stellar mass and AGN luminosity can be quite different. This highlights the importance of combining different approaches and accounting for their selection biases when studying AGN and their role in galaxy evolution. Finally, for the X-ray detected sample, we present the X-ray to mid-IR luminosity relation, and the correlation between stellar mass and bolometric luminosity as a function of redshift, in good agreement with previous results.

astro-ph.GA↗

arXiv2026

The ASKAP-FLASH survey: A first look at the multiwavelength properties and redshift distribution of compact radio sources

We present the characterisation, including a photometric redshift (photo-$z$) analysis, of the optical counterparts (CTPs) to over 45 000 bright ($S_{856\rm MHz} \geq$ 30 mJy) compact radio sources, identified across all ASKAP First Large Absorption Survey in HI (FLASH) fields observed up to April 2025. These sources constitute a large, homogeneous population of background continuum sightlines specifically selected to enable statistical studies of cold gas at intermediate redshifts of $0.42 \leq z \leq 1$. As spectroscopic redshift measurements are not available for the majority of these candidate absorbers, we estimate photo-$z$s for the CTPs of all FLASH continuum sources cross-matched to the tenth data release of the DESI Legacy Imaging Surveys (LS10). Using these estimates, we establish the redshift distribution and find that approximately 13% of continuum sources lie at $z<0.42$ (foreground), 35% within the detectability range of FLASH (`in-band'), and 52% at $z>1$ (background). We examine the subset of FLASH continuum sources with CTPs in the eROSITA X-ray survey, providing additional insight into their AGN content, multiwavelength properties, and environments. Finally, we discuss how this information can be used as a statistical prior to aid in distinguishing between associated and intervening HI absorption systems and estimating the total comoving absorption path length of the survey, establishing a framework for incorporating redshift-based priors in future large radio absorption surveys. We release a catalogue of LS10 counterparts to FLASH continuum sources, providing photo-$z$ estimates, associated uncertainties, and measures of redshift degeneracies.

astro-ph.GA↗

arXiv2026

AGILE: an end-to-end Rubin-LSST simulation of AGNs, galaxies, and stars I. Software description and first data release

Contemporary large-scale surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid present an unprecedented discovery potential for studying AGNs at the population level in the big data era. However, one major challenge is the accurate identification and classification of AGNs from optical/NIR photometry, or variability data alone. In order to optimize AGN selection, classification, and systematics, as well as to test different data analysis tools, we present AGILE (AGNs In the LSST Era), an LSST end-to-end simulation software. AGILE -- developed as part of the INAF LSST in-kind contribution -- is capable of simulating the anticipated AGN population in LSST and Euclid. We based AGILE on existing simulations of galaxies and stars, while we developed an AGN recipe based on empirical relations. AGILE populates complete galaxy samples with AGNs according to the observed AGN accretion rate distribution, and each AGN is assigned an optical/UV spectral energy distribution. Optical AGN variability is added using a damped random walk model connected to the AGN physical parameters. Finally, AGILE creates both LSST-like images and related data products. Using AGILE, we build a $24$ deg$^2$ complete mock truth catalog of AGNs, galaxies, and stars with $0.2 < z < 5.5$, $\log M/M_\odot > 8.5$ (AGNs and galaxies), and $r < 27.5$ mag (stars). We perform a pilot simulation (AGILE DR1) consisting of $1$ deg$^2$ of LSST operations in the COSMOS field observed up to three years according to the survey strategy. We use AGILE DR1 to quantify the accuracy of the LSST Science Pipelines in recovering true fluxes of AGNs, galaxies, and stars. We quantify the LSST completeness and purity in recovering Type 1 AGNs using typical color-color and variability selections. We share the AGILE DR1 dataset, an ideal test-bench for further scientific exploitation.

astro-ph.GA↗

arXiv2025

SN 2021lwz: Another Exotic Luminous and Fast Evolving Optical Stripped Envelope Supernova ?

Current large-scale, high-cadence surveys, such as the ZTF, provide detections of new and rare types of transients and supernovae whose physical origins are not well understood. We investigate the nature of SN 2021lwz at a redshift $z=0.065$, an overluminous supernova (SN) of absolute magnitude, $M_{g} \sim -20.1$ AB, falling in the lower range of superluminous supernovae (SLSNe) luminosities, and discovered in a faint dwarf galaxy with an absolute magnitude of $M_{g} \simeq -14.5$ AB. SN 2021lwz is studied using optical spectroscopy, photometry and imaging linear polarimetry obtained during several follow-up campaigns. All the data are used to analyse and model the evolution of the explosion. Comparisons with other SNe of well known or rarer types are investigated. SN 2021lwz belongs to the rare class of rapidly evolving transients. The bolometric light curve rises in about $7$ days to a peak luminosity of about $5 \times 10^{43}$ erg/s, at a rate of 0.2 mag day$^{-1}$ close to the peak. Spectroscopy modelling reveals more similarities with a normal Type Ic-like SN than with a SLSN before peak, showing slightly broadened lines after peak. Light curve modelling shows that the Arnett model of the bolometric light curve using a radioactive source ($^{56}$ Ni) is not able to reasonably explain the light curve evolution. A magnetar model seems more appropriate, suggesting that the explosion of low ejecta mass ($M_{\rm ej} \sim 0.24 ~M_\odot$) took place in a low mass ($M \sim 10^{6.66}~M_\odot$) dwarf galaxy of specific star-formation rate about ten times larger than typical star-forming galaxies. In conclusion SN 2021lwz is an uncommon transient showing many similarities with several classes of transients, and with rare transients. It may be an interesting example pointing on how differences in ejecta mass and engine parameters could produce a wide range of engine-driven SESNe.

astro-ph.HE↗

arXiv2025

Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)

We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and Time (LSST) Commissioning Camera. Employing the Redshift Assessment Infrastructure Layers (RAIL) framework, we apply eight photo-z algorithms to the DP1 photometry, using deep ugrizy coverage in the Extended Chandra Deep Field South (ECDFS) field and griz data in the Rubin_SV_38_7 field. In the ECDFS field, we construct a reference catalog from spectroscopic redshift (spec-z), grism redshift (grism-z), and multiband photo-z for training and validating photo-z. Performance metrics of the photo-z are evaluated using spec-zs from ECDFS and Dark Energy Spectroscopic Instrument Data Release 1 samples. Across the algorithms, we achieve per-galaxy photo-z scatter of $\sigma_{\rm NMAD} \sim 0.03$ and outlier fractions around 10% in the 6-band data, with performance degrading at faint magnitudes and z>1.2. The overall bias and scatter of our machine-learning based photo-zs satisfy the LSST Y1 requirement. We also use our photo-z to infer the ensemble redshift distribution n(z). We study the photo-z improvement by including near-infrared photometry from the Euclid mission, and find that Euclid photometry improves photo-z at z>1.2. Our results validate the RAIL pipeline for Rubin photo-z production and demonstrate promising initial performance.

astro-ph.IM↗

arXiv2025

VAR-PZ: Constraining the Photometric Redshifts of Quasars using Variability

The Vera C. Rubin Observatory LSST is expected to discover tens of millions of new Active Galactic Nuclei (AGNs). The survey's exceptional cadence and sensitivity will enable UV/optical/NIR monitoring of a significant fraction of these objects. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshifts estimates which are traditionally much less reliable for AGN than for inactive galaxies. This work presents a novel methodology to constrain the photometric redshift of AGNs that leverages the effects of cosmological time dilation, and of the luminosity and wavelength dependence of AGN variability. Specifically, we assume that the variability can be modeled as a damped random walk (DRW) process, and adopt a parametric model to characterize the DRW timescale ($\tau$) and asymptotic amplitude of the variability (SF$_\infty$) based on the redshift, the rest-frame wavelength, and the AGN luminosity. We construct variability-based photo-$z$ priors by modeling the observed variability using the expected DRW parameters at a given redshift. These variability-based photometric redshift (VAR-PZ) priors are then combined with traditional SED fitting to improve the redshift estimates from SED fitting. Validation is performed using observational data from the SDSS, demonstrating significant reduction in catastrophic outliers by more than 10% in comparison with SED fitting techniques and improvements in redshift precision. The simulated light curves with both SDSS and LSST-like cadences and baselines confirm that, VAR-PZ will be able to constrain the photometric redshifts of SDSS-like AGNs by bringing the outlier fractions down to below 7% from 32% (SED-alone) at the end of the survey.

astro-ph.GA↗

arXiv2025

Counterpart identification and classification for eRASS1 and characterisation of the AGN content

[abridged] Accurately accounting for the AGN phase in galaxy evolution requires a large, clean AGN sample. This is now possible with SRG/eROSITA. The public Data Release 1 (DR1, Jan 31, 2024) includes 930,203 sources from the Western Galactic Hemisphere. The data enable the selection of a large AGN sample and the discovery of rare sources. However, scientific return depends on accurate characterisation of the X-ray emitters, requiring high-quality multiwavelength data. This paper presents the identification and classification of optical and infrared counterparts to eRASS1 sources using Gaia DR3, CatWISE2020, and Legacy Survey DR10 (LS10) with the Bayesian NWAY algorithm and trained priors. Sources were classified as Galactic or extragalactic via a Machine Learning model combining optical/IR and X-ray properties, trained on a reference sample. For extragalactic LS10 sources, photometric redshifts were computed using Circlez. Within the LS10 footprint, all 656,614 eROSITA/DR1 sources have at least one possible optical counterpart; about 570,000 are extragalactic and likely AGN. Half are new detections compared to AllWISE, Gaia, and Quaia AGN catalogues. Gaia and CatWISE2020 counterparts are less reliable, due to the surveys shallowness and the limited amount of features available to assess the probability of being an X-ray emitter. In the Galactic Plane, where the overdensity of stellar sources also increases the chance of associations, using conservative reliability cuts, we identify approximately 18,000 Gaia and 55,000 CatWISE2020 extragalactic sources. We release three high-quality counterpart catalogues, plus the training and validation sets, as a benchmark for the field. These datasets have many applications, but in particular empower researchers to build AGN samples tailored for completeness and purity, accelerating the hunt for the Universes most energetic engines.

astro-ph.HE↗

arXiv2025

Euclid Quick Data Release (Q1). Optical and near-infrared identification and classification of point-like X-ray selected sources

To better understand the role of active galactic nuclei (AGN) in galaxy evolution, it is crucial to achieve a complete and pure AGN census. X-ray surveys are key to this, but identifying their counterparts (CTPs) at other wavelengths remains challenging due to their larger positional uncertainties and limited availability of deeper, uniform ancillary data. Euclid is revolutionising this effort, offering extensive coverage of nearly the entire extragalactic sky, particularly in the near-infrared bands, where AGN are more easily detected. With the first Euclid Quick Data Release (Q1), we identifyed, classifyed, and determined the redshifts of Euclid CTPs to known point-like sources from major X-ray surveys, including XMM-Newton, Chandra, and eROSITA. Using Bayesian statistics, combined with machine learning (ML), we identify the CTPs to 11 286 X-ray sources from the three X-ray telescopes. For the large majority of 10 194 sources, the associations are unique, with the remaining $\sim$ 10% of multi-CTP cases equally split between XMM-Newton and eROSITA. ML is then used to distinguish between Galactic (8%) and extragalactic (92%) sources. We computed photo-zs using deep learning for the 8617 sources detected in the 10th data release of the DESI Legacy Survey, reaching an accuracy and a fraction of outliers of about 5%. Based on their X-ray luminosities, over 99% of CTPs identified as extragalactic are classified as AGN, most of which appear unobscured given their hardness ratios. With this paper, we release our catalogue, which includes identifiers, basic X-ray properties, the details of the associations, and additional features such as Galactic/extragalactic classifications and photometric/spectroscopic redshifts. We also provide probabilities for sub-selecting the sample based on purity and completeness, allowing users to tailor the sample according to their specific needs.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). The active galaxies of Euclid

We present a catalogue of candidate active galactic nuclei (AGN) in the $Euclid$ Quick Release (Q1) fields. For each $Euclid$ source we collect multi-wavelength photometry and spectroscopy information from Galaxy Evolution Explorer (GALEX), $Gaia$, Dark Energy Survey (DES), Wise-field Infrared Survey Explorer (WISE), $Spitzer$, Dark Energy Survey (DESI), and Sloan Digital Sky Survey (SDSS), including spectroscopic redshift from public compilations. We investigate the AGN contents of the Q1 fields by applying selection criteria using $Euclid$ colours and WISE-AllWISE cuts finding respectively 292,222 and 65,131 candidates. We also create a high-purity QSO catalogue based on $Gaia$ DR3 information containing 1971 candidates. Furthermore, we utilise the collected spectroscopic information from DESI to perform broad-line and narrow-line AGN selections, leading to a total of 4392 AGN candidates in the Q1 field. We investigate and refine the Q1 probabilistic random forest QSO population, selecting a total of 180,666 candidates. Additionally, we perform SED fitting on a subset of sources with available $z_{\text{spec}}$, and by utilizing the derived AGN fraction, we identify a total of 7766 AGN candidates. We discuss purity and completeness of the selections and define two new colour selection criteria ($JH$_$I_{\text{E}}Y$ and $I_{\text{E}}H$_$gz$) to improve on purity, finding 313,714 and 267,513 candidates respectively in the Q1 data. We find a total of 229,779 AGN candidates equivalent to an AGN surface density of 3641 deg$^{-2}$ for $18<I_{\text{E}}\leq 24.5$, and a subsample of 30,422 candidates corresponding to an AGN surface density of 482 deg$^{-2}$ when limiting the depth to $18<I_{\text{E}}\leq 22$. The surface density of AGN recovered from this work is in line with predictions based on the AGN X-ray luminosity functions.

astro-ph.HE↗

arXiv2024

CircleZ: Reliable Photometric redshifts for AGN computed using only photometry from Legacy Survey Imaging for DESI

(abridged)Photometric redshifts for AGN (galaxies hosting an accreting supermassive black hole in their center) are notoriously challenging and currently better computed via SED fitting, assuming that deep photometry for many wavelengths is available. However, for AGN detected all-sky, the photometry is limited and provided by different projects. This makes the task of homogenising the data challenging and is a dramatic drawback for the millions of AGN that wide surveys like SRG/eROSITA will detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGN using only one dataset that covers a large area: the 10th Data Release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures, thus avoids issues related to the cross-calibration of surveys. We present the results from CircleZ, a machine-learning algorithm based on a Fully Connected Neural Network. CircleZ uses training sample of 14,000 X-ray-detected AGN and utilizes multi-aperture photometry. The accuracy and the fraction of outliers reached in a test sample of 2913 AGN are 0.067 and 11.6%, respectively. The results are comparable to or better than those obtained previously for the same field but with much less effort. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching comparable accuracy as in eFEDS when limiting the magnitude of the counterparts with respect to the depth of LS10. The method applies to fainter samples of AGN using deeper optical data from future surveys (e.g., LSST, Euclid), granted LS10-like information on the light distribution beyond a morphological type is provided. With the paper, we release an updated version of the photometric redshifts (including errors and probability distribution function) for eROSITA/eFEDS.

astro-ph.GA↗

arXiv2023

Optical polarization and spectral properties of the H-poor superluminous supernovae SN 2021bnw and SN 2021fpl

New optical photometric, spectrocopic and imaging polarimetry data are combined with publicly available data to study some of the physical properties of the two H-poor superluminous supernovae (SLSN) SN 2021bnw and SN 2021fpl. For each SLSN, the best-fit parameters obtained from the magnetar model with \texttt{MOSFiT} do not depart from the range of parameter obtained on other SLSNe discussed in the literature. A spectral analysis with \texttt{SYN++} shows that SN 2021bnw is a W Type, Fast evolver, while SN 2021fpl is a 15bn Type, Slow evolver. The analysis of the polarimetry data obtained on SN 2021fpl at four epochs (+1.8, +20.6, +34.1 and +43.0 days, rest-frame) shows $> 3σ$ polarization detections in the range 0.8--1 $\%$. A comparison of the spectroscopy data suggests that SN 2021fpl underwent a spectral transition a bit earlier than SN 2015bn, during which, similarly, it could have underwent a polarization transition. The analysis of the polarimetry data obtained on SN 2021bnw do not show any departure from symmetry of the photosphere at an empirical diffusion timescale of $\approx$ 2 (+81.1 days rest-frame). This result is consistent with those on the sample of W Type SLSN observed at empirical diffusion timescale $\le$ 1 with that technique, even though it is not clear the effect of limited spectral windows varying from one object to the other. Measurements at higher empirical diffusion timescale may be needed to see any departure from symmetry as it is discussed in the literature for SN 2017egm.

astro-ph.HE↗

arXiv2022

LensWatch: I. Resolved HST Observations and Constraints on the Strongly-Lensed Type Ia Supernova 2022qmx ("SN Zwicky")

Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply-imaged Type Ia SN 2022qmx (aka, "SN Zwicky") at $z=0.3544$. SN Zwicky was discovered by the Zwicky Transient Facility (ZTF) in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multi-cycle "LensWatch" program. We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, F814W) but unresolved with WFC3/IR~F160W, and present an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between lens model predicted time delays ($\lesssim1$ day), and delays estimated with the single epoch of HST colors ($\lesssim3.5$ days), including the uncertainty from chromatic microlensing ($\sim1$-$1.5$ days). Our lens models converge to an Einstein radius of $\theta_E=(0.168^{+0.009}_{-0.005})\prime\prime$, the smallest yet seen in a lensed SN system. The "standard candle" nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter than predicted by $\sim1.7^{+0.8}_{-0.6}$mag and $\sim0.9^{+0.8}_{-0.6}$mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

astro-ph.CO↗

arXiv2022

SALT3-NIR: Taking the Open-Source Type Ia Supernova Model to Longer Wavelengths for Next-Generation Cosmological Measurements

A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 ($\sim 2800$--8700$A$ central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 $μ$m with the open-source model-training software SALTShaker, which can easily accommodate future observations. Using simulated data we show that the training process constrains the NIR model to $\sim 2$--3% across the phase range ($-20$ to $50$ days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to $\sim 30$% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to $\sim20%$. For SN Ia observations expected from the \textit{Roman Space Telescope}, SALT3-NIR increases the amount of usable data in the SALT framework by $\sim 20$% at redshift $z\lesssim0.4$ and by $\sim 50$% at $z\lesssim0.15$. The SALT3-NIR model is part of the open-source {\tt SNCosmo} and {\tt SNANA} SN Ia cosmology packages.

astro-ph.CO↗

arXiv2022

The star-formation rates of QSOs

We examine the far-IR properties of a sample of 5391 optically selected QSOs in the 0.5 44.7, using SPIRE data from Herschel-ATLAS. We split the sample in a grid of 74 luminosity-redshift bins and compute the average optical-infrared spectral energy distribution (SED) in each bin. By normalising an intrinsic AGN template to the AGN optical power (at 5100A) we decompose the total infrared emission (L_IR; 8-1000um) into an AGN (L_IR,AGN) and star-forming component (L_IR,SF). We find that the AGN contribution to L_IR increases as a function of AGN power which manifests as a reduction of the `far-IR bump' in the average QSO SEDs. We note that L_IR,SF does not correlate with AGN power; the mean star formation rates (SFRs) of AGN host galaxies are a function of redshift only and they range from ~6 Msun/yr at z~0 to a plateau of <200 Msun/yr at z~2.6. Our results indicate that the accuracy of far-IR emission as a proxy for SFR decreases with increasing AGN luminosity. We show that, at any given redshift, observed trends between infrared luminosity (whether monochromatic or total) and AGN power (in the optical or X-rays) can be explained by a simple model which is the sum of two components: (A) the infrared emission from star-formation, uncorrelated with AGN power and (B) the infrared emission from AGN, directly proportional to AGN power in the optical or X-rays.

astro-ph.GA↗