arXiv subjects

M. Smith

Publications and source records attributed to M. Smith.

At least 163 records · Page 9Linked to original sources

arXiv2022

HyperGal: hyperspectral scene modeling for supernova typing with the Integral Field Spectrograph SEDmachine

Recent developments in time domain astronomy, like the Zwicky Transient Facility, have made possible a daily scan of the entire visible sky, leading to the discovery of hundreds of new transients every night. Among them, 10 to 15 are supernovae (SNe), which have to be classified prior to cosmological use. The Spectral Energy Distribution machine (SEDm), a low resolution Integral Field Spectrograph, has been designed, built, and operated to spectroscopically classify targets detected by the ZTF main camera. The current Pysedm pipeline is limited by contamination when the transient is too close to its host galaxy core; this can lead to an incorrect typing and ultimately bias the cosmological analyses, and affect the SN sample homogeneity in terms of local environment properties. We present a new scene modeler to extract the transient spectrum from its structured background, aiming at improving the typing efficiency of the SEDm. HyperGal is a fully chromatic scene modeler, which uses pre-transient photometric images to generate a hyperspectral model of the host galaxy; it is based on the CIGALE SED fitter used as a physically-motivated spectral interpolator. The galaxy model, complemented by a point source and a diffuse background component, is projected onto the SEDm spectro-spatial observation space and adjusted to observations. The full procedure is validated on 5000 simulated cubes. We introduce the contrast as the transient-to-total flux ratio at SN location. From estimated contrast distribution of real SEDm observations, we show that HyperGal correctly classifies ~95% of SNe Ia. Compared to the standard extraction method, HyperGal correctly classifies 10% more SNe Ia. The false positive rate is less than 2%, half as much as the standard extraction method. Assuming a similar contrast distribution for core-collapse SNe, HyperGal classifies 14% (11%) additional SNe II (Ibc).

astro-ph.CO↗

arXiv2022

Characterising the Intracluster Light over the Redshift Range $0.2 < z < 0.8$ in the DES-ACT Overlap

We characterise the properties and evolution of Bright Central Galaxies (BCGs) and the surrounding intracluster light (ICL) in galaxy clusters identified in overlapping regions of the Dark Energy Survey and Atacama Cosmology Telescope Survey (DES-ACT), covering the redshift range $0.20 $14.4. We also measure the stellar mass - halo mass (SMHM) relation for the BCG+ICL system and find that the slope, $β$, which characterises the dependence of $M_{\rm 200m,SZ}$ on the BCG+ICL stellar mass, increases with radius. The outskirts are more strongly correlated with the halo than the core, which supports that the BCG+ICL system follows a two-phase growth, where recent growth ($z<2$) occurs beyond the BCG's core. Additionally, we compare our observed SMHM relation results to the IllustrisTNG 300-1 cosmological hydrodynamic simulations and find moderate qualitative agreement in the amount of diffuse light. However, the SMHM relation's slope is steeper in TNG300-1 and the intrinsic scatter is lower, likely from the absence of projection effects in TNG300-1. Additionally, we find that the ICL exhibits a colour gradient such that the outskirts are bluer than the core. Moreover, for the lower halo mass clusters (log$_{10}(M_{\rm 200m,SZ}$/M$_{\odot})<$14.59 ), we detect a modest change in the colour gradient's slope with lookback time, which combined with the absence of stellar mass growth may suggest that lower mass clusters have been involved in growth via tidal stripping more recently than their higher mass counterparts.

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arXiv2022

Lessons Learned from the Two Largest Galaxy Morphological Classification Catalogues built by Convolutional Neural Networks

We compare the two largest galaxy morphology catalogues, which separate early and late type galaxies at intermediate redshift. The two catalogues were built by applying supervised deep learning (convolutional neural networks, CNNs) to the Dark Energy Survey data down to a magnitude limit of $\sim$21 mag. The methodologies used for the construction of the catalogues include differences such as the cutout sizes, the labels used for training, and the input to the CNN - monochromatic images versus $gri$-band normalized images. In addition, one catalogue is trained using bright galaxies observed with DES ($i<18$), while the other is trained with bright galaxies ($r<17.5$) and `emulated' galaxies up to $r$-band magnitude $22.5$. Despite the different approaches, the agreement between the two catalogues is excellent up to $i<19$, demonstrating that CNN predictions are reliable for samples at least one magnitude fainter than the training sample limit. It also shows that morphological classifications based on monochromatic images are comparable to those based on $gri$-band images, at least in the bright regime. At fainter magnitudes, $i>19$, the overall agreement is good ($\sim$95\%), but is mostly driven by the large spiral fraction in the two catalogues. In contrast, the agreement within the elliptical population is not as good, especially at faint magnitudes. By studying the mismatched cases we are able to identify lenticular galaxies (at least up to $i<19$), which are difficult to distinguish using standard classification approaches. The synergy of both catalogues provides an unique opportunity to select a population of unusual galaxies.

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arXiv2022

Dwarf AGNs from Optical Variability for the Origins of Seeds (DAVOS): Insights from the Dark Energy Survey Deep Fields

We present a sample of 706, $z < 1.5$ active galactic nuclei (AGNs) selected from optical photometric variability in three of the Dark Energy Survey (DES) deep fields (E2, C3, and X3) over an area of 4.64 deg$^2$. We construct light curves using difference imaging aperture photometry for resolved sources and non-difference imaging PSF photometry for unresolved sources, respectively, and characterize the variability significance. Our DES light curves have a mean cadence of 7 days, a 6 year baseline, and a single-epoch imaging depth of up to $g \sim 24.5$. Using spectral energy distribution (SED) fitting, we find 26 out of total 706 variable galaxies are consistent with dwarf galaxies with a reliable stellar mass estimate ($M_{\ast}<10^{9.5}\ M_\odot$; median photometric redshift of 0.9). We were able to constrain rapid characteristic variability timescales ($\sim$ weeks) using the DES light curves in 15 dwarf AGN candidates (a subset of our variable AGN candidates) at a median photometric redshift of 0.4. This rapid variability is consistent with their low black hole masses. We confirm the low-mass AGN nature of one source with a high S/N optical spectrum. We publish our catalog, optical light curves, and supplementary data, such as X-ray properties and optical spectra, when available. We measure a variable AGN fraction versus stellar mass and compare to results from a forward model. This work demonstrates the feasibility of optical variability to identify AGNs with lower black hole masses in deep fields, which may be more "pristine" analogs of supermassive black hole seeds.

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arXiv2022

Dust grain size evolution in local galaxies: a comparison between observations and simulations

The evolution of the dust grain size distribution has been studied in recent years with great detail in cosmological hydrodynamical simulations taking into account all the channels under which dust evolves in the interstellar medium. We present a systematic analysis of the observed spectral energy distribution of a large sample of galaxies in the local universe in order to derive not only the total dust masses but also the relative mass fraction between small and large dust grains (DS/DL). Simulations reproduce fairly well the observations except for the high stellar mass regime where dust masses tend to be overestimated. We find that ~45% of galaxies exhibit DS/DL consistent with the expectations of simulations, while there is a sub-sample of massive galaxies presenting high DS/DL (log(DS/DL)~-0.5), and deviating from the prediction in simulations. For these galaxies, which also have high molecular gas mass fractions and metallicities, coagulation is not an important mechanism affecting the dust evolution. Including diffusion, transporting large grains from dense regions to a more diffuse medium where they can be easily shattered, would explain the observed high DS/DL values in these galaxies. With this study we reinforce the use of the small-to-large grain mass ratio to study the relative importance of the different mechanisms in the dust life cycle. Multi-phase hydrodynamical simulations with detailed feedback prescriptions and more realistic subgrid models for the dense phase could help to reproduce the evolution of the dust grain size distribution traced by observations.

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arXiv2022

Cosmological Results from the RAISIN Survey: Using Type Ia Supernovae in the Near Infrared as a Novel Path to Measure the Dark Energy Equation of State

Type Ia supernovae (SNe Ia) are more precise standardizable candles when measured in the near-infrared (NIR) than in the optical. With this motivation, from 2012-2017 we embarked on the RAISIN program with the Hubble Space Telescope (HST) to obtain rest-frame NIR light curves for a cosmologically distant sample of 37 SN Ia ($0.2 \lesssim z \lesssim 0.6$) discovered by Pan-STARRS and the Dark Energy Survey. By comparing higher-$z$ HST data with 42 SN Ia at $z<0.1$ observed in the NIR by the Carnegie Supernova Project, we construct a Hubble diagram from NIR observations (with only time of maximum light and some selection cuts from optical data) to pursue a unique avenue to constrain the dark energy equation of state parameter, $w$. We analyze the dependence of the full set of Hubble residuals on the SN Ia host galaxy mass and find Hubble residual steps of size $\sim$0.06-0.1~mag with 1.5- to 2.5-$σ$ significance depending on the method and step location. Combining our NIR sample with CMB constraints, we find $1+w=-0.17\pm0.12$ (stat$+$syst). The largest systematic errors are the redshift-dependent SN selection biases and the properties of the NIR mass step. We also use these data to measure $H_0=75.9\pm 2.2$ km s$^{-1}$ Mpc$^{-1}$ from stars with geometric distance calibration in the hosts of 8 SNe Ia observed in the NIR versus $H_0=71.2\pm3.8$ km s$^{-1}$ Mpc$^{-1}$ using an inverse distance ladder approach tied to Planck. Using optical data we find $1+w=-0.10\pm0.09$ and with optical and NIR data combined, we find $1+w=-0.06\pm0.07$; these shifts of up to 0.11 in $w$ could point to inconsistency in optical versus NIR SN models. There will be many opportunities to improve this NIR measurement and better understand systematic uncertainties through larger low-$z$ samples, new light-curve models, calibration improvements, and by building high-$z$ samples from the Roman Space Telescope.

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arXiv2022

The Dark Energy Survey 5-year photometrically identified Type Ia Supernovae

As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multi-band light-curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNova (SNN; Möller et al. 2019) trained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1,863 SNe Ia from which we select 1,484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically-selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).

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arXiv2022

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey: I. Evidence for thermal energy anisotropy using oriented stacking

The cosmic web contains filamentary structure on a wide range of scales. On the largest scales, superclustering aligns multiple galaxy clusters along inter-cluster bridges, visible through their thermal Sunyaev-Zel'dovich signal in the Cosmic Microwave Background. We demonstrate a new, flexible method to analyze the hot gas signal from multi-scale extended structures. We use a Compton-$y$ map from the Atacama Cosmology Telescope (ACT) stacked on redMaPPer cluster positions from the optical Dark Energy Survey (DES). Cutout images from the $y$ map are oriented with large-scale structure information from DES galaxy data such that the superclustering signal is aligned before being overlaid. We find evidence for an extended quadrupole moment of the stacked $y$ signal at the 3.5$σ$ level, demonstrating that the large-scale thermal energy surrounding galaxy clusters is anisotropically distributed. We compare our ACT$\times$DES results with the Buzzard simulations, finding broad agreement. Using simulations, we highlight the promise of this novel technique for constraining the evolution of anisotropic, non-Gaussian structure using future combinations of microwave and optical surveys.

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arXiv2022

Dark Energy Survey Year 3 results: imprints of cosmic voids and superclusters in the Planck CMB lensing map

The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3 (Y3) data set ($\sim$5,000 deg$^{2}$), expanding on previous measurements that used Y1 catalogues ($\sim$1,300 deg$^{2}$). Given the increased statistical power compared to Y1 data, we report a $6.6σ$ detection of negative CMB convergence ($κ$) imprints using approximately 3,600 voids detected from a redMaGiC luminous red galaxy sample. However, the measured signal is lower than expected from the MICE N-body simulation that is based on the $Λ$CDM model (parameters $Ω_{\rm m} = 0.25$, $σ_8 = 0.8$), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_κ=κ_{\rm DES}/κ_{\rm MICE}$ to a simulation-based template with fixed shape and found a moderate $2σ$ deviation in the signal with $A_κ\approx0.79\pm0.12$. We also examined the WebSky simulation that is based on a Planck 2018 $Λ$CDM cosmology, but the results were even less consistent given the slightly higher matter density fluctuations than in MICE. We then identified superclusters in the DES and the MICE catalogues, and detected their imprints at the $8.4σ$ level; again with a lower-than-expected $A_κ=0.84\pm0.10$ amplitude. The combination of voids and superclusters yields a $10.3σ$ detection with an $A_κ=0.82\pm0.08$ constraint on the CMB lensing amplitude, thus the overall signal is $2.3σ$ weaker than expected from MICE.

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arXiv2022

A galaxy-driven model of type Ia supernova luminosity variations

Type Ia supernovae (SNe Ia) are used as standardisable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame $U-R$ colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-year SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio $(R_V)$ between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy $U-R$. Modelling the $R_V$ step as a function of galaxy age provides a better match overall. Additional age vs. luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width vs. luminosity coefficient $α$. Furthermore, we find no evidence that $α$ varies with SN age.

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arXiv2022

Gaia Data Release 3: Properties of the line broadening parameter derived with the Radial Velocity Spectrometer (RVS)

The third release of the Gaia catalogue contains the radial velocities for 33,812,183 stars having effective temperatures ranging from 3100 K to 14,500 K. The measurements are based on the comparison of the observed RVS spectrum (wavelength coverage: 846--870 nm, median resolving power: 11,500) to synthetic data broadened to the adequate Along-Scan Line Spread Function. The additional line-broadening, fitted as it would only be due to axial rotation, is also produced by the pipeline and is available in the catalogue (field name gaia_source:vbroad). To describe the properties of the line-broadening information extracted from the RVS and published in the catalogue, as well as to analyse the limitations imposed by the adopted method, wavelength range, and instrument. We use simulations to express the link existing between the line broadening measurement provided in Gaia Data Release 3 and Vsin(i). We then compare the observed values to the measurements published by various catalogues and surveys (GALAH, APOGEE, LAMOST, ...). While we recommend being cautious in the interpretation of the vbroad measurement, we also find a reasonable global agreement between the Gaia Data Release 3 line broadening values and those found in the other catalogues. We discuss and establish the validity domain of the published vbroad values. The estimate tends to be overestimated at the lower vsini end, and at $T_\mathrm{eff}>7500\,\mathrm{K}$ its quality and significance degrade rapidly when $G_\mathrm{RVS}>10$. Despite all the known and reported limitations, the Gaia Data Release 3 line broadening catalogue contains the measurements obtained for 3,524,677 stars with $T_\mathrm{eff}$\ ranging from 3500 to 14,500 K, and $G_\mathrm{RVS}<12$. It gathers the largest stellar sample ever considered for the purpose, and allows a first mapping of the \Gaia\ line broadening parameter across the HR diagram.

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arXiv2022

Gaia Data Release 3 Properties and validation of the radial velocities

Gaia Data Release 3 (Gaia DR3) contains the second release of the combined radial velocities. It is based on the spectra collected during the first 34 months of the nominal mission. The longer time baseline and the improvements of the pipeline made it possible to push the processing limit, from Grvs = 12 in Gaia DR2, to Grvs = 14 mag. In this article, we describe the new functionalities implemented for Gaia DR3, the quality filters applied during processing and post-processing and the properties and performance of the published velocities. For Gaia DR3, several functionalities were upgraded or added. (Abridged) Gaia DR3 contains the combined radial velocities of 33 812 183 stars. With respect to Gaia DR2, the interval of temperature has been expanded from Teff \in [3600, 6750] K to Teff \in [3100, 14500] K for the bright stars ( Grvs \leq 12 mag) and [3100, 6750] K for the fainter stars. The radial velocities sample a significant part of the Milky Way: they reach a few kilo-parsecs beyond the Galactic centre in the disc and up to about 10-15 kpc vertically into the inner halo. The median formal precision of the velocities is of 1.3 km/s at Grvs = 12 and 6.4 km/s at Grvs = 14 mag. The velocity zero point exhibits a small systematic trend with magnitude starting around Grvs = 11 mag and reaching about 400 m/s at Grvs = 14 mag. A correction formula is provided, which can be applied to the published data. The Gaia DR3 velocity scale is in satisfactory agreement with APOGEE, GALAH, GES and RAVE, with systematic differences that mostly do not exceed a few hundreds m/s. The properties of the radial velocities are also illustrated with specific objects: open clusters, globular clusters as well as the Large Magellanic Cloud (LMC). For example, the precision of the data allows to map the line-of-sight rotational velocities of the globular cluster 47 Tuc and of the LMC.

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arXiv2022

Gaia Data Release 3: G_RVS photometry from the RVS spectra

Gaia Data Release 3 (DR3) contains the first release of magnitudes estimated from the integration of Radial Velocity Spectrometer (RVS) spectra for a sample of about 32.2 million stars brighter than G_RVS~14 mag (or G~15 mag). In this paper, we describe the data used and the approach adopted to derive and validate the G_RVS magnitudes published in DR3. We also provide estimates of the G_RVS passband and associated G_RVS zero-point. We derived G_RVS photometry from the integration of RVS spectra over the wavelength range from 846 to 870 nm. We processed these spectra following a procedure similar to that used for DR2, but incorporating several improvements that allow a better estimation of G_RVS. These improvements pertain to the stray-light background estimation, the line spread function calibration, and the detection of spectra contaminated by nearby relatively bright sources. We calibrated the G_RVS zero-point every 30 hours based on the reference magnitudes of constant stars from the Hipparcos catalogue, and used them to transform the integrated flux of the cleaned and calibrated spectra into epoch magnitudes. The G_RVS magnitude of a star published in DR3 is the median of the epoch magnitudes for that star. We estimated the G_RVS passband by comparing the RVS spectra of 108 bright stars with their flux-calibrated spectra from external spectrophotometric libraries. The G_RVS magnitude provides information that is complementary to that obtained from the G, G_BP, and G_RP magnitudes, which is useful for constraining stellar metallicity and interstellar extinction. The median precision of G_RVS measurements ranges from about 0.006 mag for the brighter stars (i.e. with 3.5 < G_RVS < 6.5 mag) to 0.125 mag at the faint end. The derived G_RVS passband shows that the effective transmittance of the RVS is approximately 1.23 times better than the pre-launch estimate.

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arXiv2022

Gaia Data Release 3: Hot-star radial velocities

The second Gaia data release, DR2, contained radial velocities of stars with effective temperatures up to Teff = 6900 K. The third data release, Gaia DR3, extends this up to Teff = 14,500 K. We derive the radial velocities for hot stars (i.e. in the Teff = 6900 - 14,500 K range) from data obtained with the Radial Velocity Spectrometer (RVS) on board Gaia. The radial velocities were determined by the standard technique of measuring the Doppler shift of a template spectrum that was compared to the observed spectrum. The RVS wavelength range is very limited. The proximity to and systematic blueward offset of the calcium infrared triplet to the hydrogen Paschen lines in hot stars can result in a systematic offset in radial velocity. For the hot stars, we developed a specific code to improve the selection of the template spectrum, thereby avoiding this systematic offset. With the improved code, and with the correction we propose to the DR3 archive radial velocities, we obtain values that agree with reference values to within 3 km/s (in median). Because of the required S/N for applying the improved code, the hot star radial velocities in DR3 are mostly limited to stars with a magnitude in the RVS wavelength band <= 12 mag.

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arXiv2022

Velocity Dispersions of Clusters in the Dark Energy Survey Y3 redMaPPer Catalog

We measure the velocity dispersions of clusters of galaxies selected by the redMaPPer algorithm in the first three years of data from the Dark Energy Survey (DES), allowing us to probe cluster selection and richness estimation, $λ$, in light of cluster dynamics. Our sample consists of 126 clusters with sufficient spectroscopy for individual velocity dispersion estimates. We examine the correlations between cluster velocity dispersion, richness, X-ray temperature and luminosity as well as central galaxy velocity offsets. The velocity dispersion-richness relation exhibits a bimodal distribution. The majority of clusters follow scaling relations between velocity dispersion, richness, and X-ray properties similar to those found for previous samples; however, there is a significant population of clusters with velocity dispersions which are high for their richness. These clusters account for roughly 22\% of the $λ< 70$ systems in our sample, but more than half (55\%) of $λ< 70$ clusters at $z>0.5$. A couple of these systems are hot and X-ray bright as expected for massive clusters with richnesses that appear to have been underestimated, but most appear to have high velocity dispersions for their X-ray properties likely due to line-of-sight structure. These results suggest that projection effects contribute significantly to redMaPPer selection, particularly at higher redshifts and lower richnesses. The redMaPPer determined richnesses for the velocity dispersion outliers are consistent with their X-ray properties, but several are X-ray undetected and deeper data is needed to understand their nature.

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arXiv2022

STRIDES: Automated uniform models for 30 quadruply imaged quasars

Gravitational time delays provide a powerful one step measurement of $H_0$, independent of all other probes. One key ingredient in time delay cosmography are high accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (10$^{5-6}$ CPU hours and $\sim$ 0.5-1 year, respectively). Major improvements in modeling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, building on the work by Shajib et al. (2019), we develop an automated modeling pipeline and apply it to a sample of 30 quadruply imaged quasars and one lensed compact galaxy, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in Fermat potential (proportional to time delay) w.r.t. modeling choices. We find that for 10/30 lenses our models are cosmography or nearly cosmography grade (<3% and 3-5% variations). For 6/30 lenses the models are close to cosmography grade (5-10%). These results are based on informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modeling sequence and options. In conclusion, we show that uniform cosmography grade modeling of large strong lens samples is within reach.

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arXiv2022

Dark Energy Survey Year 3 Results: Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS

We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors due to the galaxy clustering bias, finding our method to be generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for eleven different photometrically-selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift to be below $|Δz|=0.01$ in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9\%. We discuss how these results calibrate the photometric redshift distributions used in companion DES Year 3 Results papers.

astro-ph.CO↗

arXiv2022

Optical Variability of Quasars with 20-Year Photometric Light Curves

We study the optical $gri$ photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during $\sim 1998-2020$ with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average $\sim 200$ nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10-15 yr baselines and $\lesssim 100$ epochs. We find that the average damping timescale $τ_{\rm DRW}$ continues to rise with increased baseline, reaching a median value of $\sim 750$ days ($g$ band) in the rest-frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained $τ_{\rm DRW}$ (less than 20\% of the baseline), we confirm a weak wavelength dependence of $τ_{\rm DRW}\propto λ^{0.51\pm0.20}$. We further quantify optical variability of these quasars over days to decades timescales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping timescales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on timescales less than $\sim$ a month for these luminous quasars, and this second break point correlates with the longer DRW damping timescale.

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