Reverberation mapping measurements have been used to constrain the relationship between the size of the broad-line region and luminosity of active galactic nuclei (AGN). This $R-L$ relation is used to estimate single-epoch virial black hole masses, and has been proposed for use to standardise AGN to determine cosmological distances. We present reverberation measurements made with H$\beta$ from the six-year Australian Dark Energy Survey (OzDES) Reverberation Mapping Program. We successfully recover reverberation lags for eight AGN at $0.12

The correlation between the broad line region radius and continuum luminosity ($R-L$ relation) of active galactic nuclei (AGN) is critical for single-epoch mass estimates of supermassive black holes (SMBHs). At $z \sim 1-2$, where AGN activity peaks, the $R-L$ relation is constrained by the reverberation mapping (RM) lags of the Mg II line. We present 25 Mg II lags from the Australian Dark Energy Survey (OzDES) RM project based on six years of monitoring. We define quantitative criteria to select good lag measurements and verify their reliability with simulations based on both the damped random walk stochastic model and the re-scaled, re-sampled versions of the observed lightcurves of local, well-measured AGN. Our sample significantly increases the number of Mg II lags and extends the $R-L$ relation to higher redshifts and luminosities. The relative iron line strength $\mathcal{R}_{\rm Fe}$ has little impact on the $R-L$ relation. The best-fit Mg II $R-L$ relation has a slope $\alpha = 0.39 \pm 0.08$ with an intrinsic scatter $\sigma_{\rm rl} = 0.15^{+0.03}_{-0.02}$. The slope is consistent with previous measurements and shallower than the H$\beta$ $R-L$ relation. The intrinsic scatter of the new $R-L$ relation is substantially smaller than previous studies and comparable to the intrinsic scatter of the H$\beta$ $R-L$ relation. Our new $R-L$ relation will enable more precise single-epoch mass estimates and SMBH demographic studies at cosmic noon.

Type Ia supernovae (SNe Ia) are explosions of white dwarf stars that facilitate exquisite measurements of cosmological expansion history, but improvements in accuracy and precision are hindered by observational biases. Of particular concern is the apparent difference in the corrected brightnesses of SNe Ia in different host galaxy environments. SNe Ia in more massive, passive, older environments appear brighter after having been standardized by their light-curve properties. The luminosity difference commonly takes the form of a step function. Recent works imply that environmental characteristics that trace the age of the stellar population in the vicinity of SNe show the largest steps. Here we use simulations of SN Ia populations to test the impact of using different tracers and investigate promising new models of the step. We test models with a total-to-selective dust extinction ratio RV that changes between young and old SN Ia host galaxies, as well as an intrinsic luminosity difference between SNe from young and old progenitors. The data are well replicated by a model driven by a galaxy-age varying RV and no intrinsic SN luminosity difference, and we find that specific star-formation rate measured locally to the SN is a relatively pure tracer of this galaxy age difference. We cannot rule out an intrinsic difference causing part of the observed step and show that if luminosity differences are caused by multiple drivers then no single environmental measurement is able to accurately trace them. We encourage the use of multiple tracers in luminosity corrections to negate this issue.

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 $\tau_{\rm DRW}$ 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 $\tau_{\rm DRW}$ (less than 20\% of the baseline), we confirm a weak wavelength dependence of $\tau_{\rm DRW}\propto \lambda^{0.51\pm0.20}$. 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.

In the new era of time-domain surveys Type Ia supernovae are being caught sooner after explosion, which has exposed significant variation in their early light curves. Two driving factors for early time evolution are the distribution of nickel in the ejecta and the presence of flux excesses of various causes. We perform an analysis of the largest young SN Ia sample to date. We compare 115 SN Ia light curves from the Zwicky Transient Facility to the turtls model grid containing light curves of Chandrasekhar-mass explosions with a range of nickel masses, nickel distributions and explosion energies. We find that the majority of our observed light curves are well reproduced by Chandrasekhar-mass explosion models with a preference for highly extended nickel distributions. We identify six SNe Ia with an early-time flux excess in our g- and r-band data (four `blue' and two `red' flux excesses). We find an intrinsic rate of 18+/-11 per cent of early flux excesses in SNe Ia at z < 0.07, based on three detected flux excesses out of 30 (10 per cent) observed SNe Ia with a simulated efficiency of 57 per cent. This is comparable to rates of flux excesses in the literature but also accounts for detection efficiencies. Two of these events are mostly consistent with CSM interaction, while the other four have longer lifetimes in agreement with companion interaction and nickel-clump models. We find a higher frequency of flux excesses in 91T/99aa-like events (44+/-13 per cent).

Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential astrophysical dependencies may bias cosmological measurements if not properly accounted for. The dependency of the intrinsic luminosity of SNe Ia with their host-galaxy environment is often used to standardize SNe Ia luminosity and is commonly parameterized as a step function. This functional form implicitly assumes two-populations of SNe Ia. In the literature, multiple environmental indicators have been considered, finding different, sometimes incompatible, step function amplitudes. We compare these indicators in the context of a two-populations model, based on their ability to distinguish the two populations. We show that local H$\alpha$-based specific star formation rate (lsSFR) and global stellar mass are better tracers than, for instance, host galaxy morphology. We show that tracer accuracy can explain the discrepancy between the observed SNe Ia step amplitudes found in the literature. Using lsSFR or global mass to distinguish the two populations can explain all other observations, though lsSFR is favoured. As lsSFR is strongly connected to age, our results favour a prompt and delayed population model. In any case, there exists two populations that differ in standardized magnitude by at least $0.121\pm0.010\,\mathrm{mag}$.

ABSTRACT 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 (∼5000 deg2), expanding on previous measurements that used Y1 catalogues (∼1300 deg2). Given the increased statistical power compared to Y1 data, we report a 6.6σ detection of negative CMB convergence (κ) imprints using approximately 3600 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 ΛCDM model (parameters Ωm = 0.25, σ8 = 0.8), and the discrepancy is associated mostly with the void centre region. Considering the full void lensing profile, we fit an amplitude $A_{\kappa }=\kappa _{{\rm DES}}/\kappa _{{\rm MICE}}$ to a simulation-based template with fixed shape and found a moderate 2σ deviation in the signal with Aκ ≈ 0.79 ± 0.12. We also examined the WebSky simulation that is based on a Planck 2018 ΛCDM 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 Aκ = 0.84 ± 0.10 amplitude. The combination of voids and superclusters yields a 10.3σ detection with an Aκ = 0.82 ± 0.08 constraint on the CMB lensing amplitude, thus the overall signal is 2.3σ weaker than expected from MICE.

We study a phenomenological class of models where dark matter converts to dark radiation in the low redshift epoch. This class of models, dubbed DMDR, characterizes the evolution of comoving dark-matter density with two extra parameters, and may be able to help alleviate the observed discrepancies between early and late-time probes of the Universe. We investigate how the conversion affects key cosmological observables such as the cosmic microwave background (CMB) temperature and matter power spectra. Combining 3x2pt data from Year 1 of the Dark Energy Survey, Planck-2018 CMB temperature and polarization data, supernovae (SN) Type Ia data from Pantheon, and baryon acoustic oscillation (BAO) data from BOSS DR12, MGS and 6dFGS, we place new constraints on the amount of dark matter that has converted to dark radiation and the rate of this conversion. The fraction of the dark matter that has converted since the beginning of the Universe in units of the current amount of dark matter, zeta, is constrained at 68% confidence level to be <0.32 for DES-Y1 3x2pt data, < 0.030 for CMB + SN + BAO data, and <0.037 for the combined dataset. The probability that the DES and CMB+SN+BAO datasets are concordant increases from 4% for the Lambda CDM model to 8% (less tension) for DMDR. The tension in S-8 = sigma(8)root Omega(m)/0.3 between DES-Y1 3x2pt and CMB + SN + BAO is slightly reduced from 2.3 sigma to 1.9 sigma. We find no reduction in the Hubble tension when the combined data is compared to distance-ladder measurements in the DMDR model. The maximum-posterior goodness-of-fit statistics of DMDR and Lambda CDM model are comparable, indicating no preference for the DMDR cosmology over Lambda CDM.

This paper details the modeling pipeline and validates the baseline analysis choices of the DES Year 3 joint analysis of galaxy clustering and weak lensing (a so-called "3$\times$2pt" analysis). These analysis choices include the specific combination of cosmological probes, priors on cosmological and systematics parameters, model parameterizations for systematic effects and related approximations, and angular scales where the model assumptions are validated. We run a large number of simulated likelihood analyses using synthetic data vectors to test the robustness of our baseline analysis. We demonstrate that the DES Year 3 modeling pipeline, including the calibrated scale cuts, is sufficiently accurate relative to the constraining power of the DES Year 3 analyses. Our systematics mitigation strategy accounts for astrophysical systematics, such as galaxy bias, intrinsic alignments, source and lens magnification, baryonic effects, and source clustering, as well as for uncertainties in modeling the matter power spectrum, reduced shear, and estimator effects. We further demonstrate excellent agreement between two independently-developed modeling pipelines, and thus rule out any residual uncertainties due to the numerical implementation.

We report the results of a systematic search for ultra-faint Milky Way satellite galaxies using data from the Dark Energy Survey (DES) and Pan-STARRS1 (PS1). Together, DES and PS1 provide multi-band photometry in optical/near-infrared wavelengths over ∼80% of the sky. Our search for satellite galaxies targets ∼25,000 deg2 of the high-Galactic-latitude sky reaching a 10σ point-source depth of ≳22.5 mag in the g and r bands. While satellite galaxy searches have been performed independently on DES and PS1 before, this is the first time that a self-consistent search is performed across both data sets. We do not detect any new high-significance satellite galaxy candidates, recovering the majority of satellites previously detected in surveys of comparable depth. We characterize the sensitivity of our search using a large set of simulated satellites injected into the survey data. We use these simulations to derive both analytic and machine-learning models that accurately predict the detectability of Milky Way satellites as a function of their distance, size, luminosity, and location on the sky. To demonstrate the utility of this observational selection function, we calculate the luminosity function of Milky Way satellite galaxies, assuming that the known population of satellite galaxies is representative of the underlying distribution. We provide access to our observational selection function to facilitate comparisons with cosmological models of galaxy formation and evolution.

We present the results from a search for the electromagnetic counterpart of the LIGO/Virgo event S190510g using the Dark Energy Camera (DECam). S190510g is a binary neutron star (BNS) merger candidate of moderate significance detected at a distance of 227 ± 92 Mpc and localized within an area of 31 (1166) square degrees at 50% (90%) confidence. While this event was later classified as likely nonastrophysical in nature within 30 hours of the event, our short latency search and discovery pipeline identified 11 counterpart candidates, all of which appear consistent with supernovae following offline analysis and spectroscopy by other instruments. Later reprocessing of the images enabled the recovery of six more candidates. Additionally, we implement our candidate selection procedure on simulated kilonovae and supernovae under DECam observing conditions (e.g., seeing and exposure time) with the intent of quantifying our search efficiency and making informed decisions on observing strategy for future similar events. This is the first BNS counterpart search to employ a comprehensive simulation-based efficiency study. We find that using the current follow-up strategy, there would need to be 19 events similar to S190510g for us to have a 99% chance of detecting an optical counterpart, assuming a GW170817-like kilonova. We further conclude that optimization of observing plans, which should include preference for deeper images over multiple color information, could result in up to a factor of 1.5 reduction in the total number of follow-ups needed for discovery.

We present Magellan/IMACS spectroscopy of three recently discovered ultra-faint Milky Way satellites, Grus.II, Tucana.IV, and Tucana.V. We measure systemic velocities of vhel = -110.0. 0.5 km s-1, = v 15.9+ hel 1.71.8 km s-1, and = - v 36.2+ hel 2.22.5 km s-1 for the three objects, respectively. Their large relative velocities demonstrate that the satellites are unrelated despite their close physical proximity. We determine a velocity dispersion for Tuc.IV of s = 4.3+ 1.01.7 km s-1, but we cannot resolve the velocity dispersions of the other two systems. For Gru.II, we place an upper limit (90%.confidence) on the dispersion of s.<.1.9 km s-1, and for Tuc.V, we do not obtain any useful limits. All three satellites have metallicities below[Fe H] = -2.1, but none has a detectable metallicity spread. We determine proper motions for each satellite based on Gaia astrometry and compute their orbits around the Milky Way. Gru.II is on a tightly bound orbit with a pericenter of 25+ 76 kpc and orbital eccentricity of 0.45+ 0.050.08. Tuc.V likely has an apocenter beyond 100.kpc and could be approaching the Milky Way for the first time. The current orbit of Tuc.IV is similar to that of Gru.II, with a pericenter of 25+ 811 kpc and an eccentricity of 0.36+ 0.060.13. However, a backward integration of the position of Tuc.IV demonstrates that it collided with the Large Magellanic Cloud at an impact parameter of 4. kpc 120.Myr ago, deflecting its trajectory and possibly altering its internal kinematics. Based on their sizes, masses, and metallicities, we classify Gru.II and Tuc.IV as likely dwarf galaxies, but the nature of Tuc.V remains uncertain.

We present the discovery of 255 binary and six multiple system candidates with wide (> 5") separation composed by L or T dwarfs companions to stars, plus nine double brown dwarf systems. The sample of brown dwarf candidates was found in the Dark Energy Survey and the possible stellar companions are from Gaia DR2 and DES data. Our search is based in a common distance criterion with no proper motion information. For the Gaia DR2 stars we estimate distances based on their parallaxes and photometry, using the StarHorse code, while for DES stars, the StarHorse distances were purely photometric for the majority of cases, with a fraction having parallax measurement from Gaia DR2. L and T dwarfs distances are based on empirical templates ranging from L0 to T9. We also compute chance alignment probabilities in order to assess the physical nature of each pair. We find 174 possible pairs with Gaia DR2 primaries with chance alignment probabilities < 5%. We also find 85 binary pair candidates with a DES star as a primary, 81 of them with chance alignment probabilities < 5%. Only nine candidate systems composed of two brown dwarfs were identified. The sample of multiple systems is made up of five triple systems and one quadruple system. We determine that the typical wide binary fraction over the L and T spectral types is 2-4%. The significant leap provided by this sample will enable constraints on the formation and evolution of L and T dwarfs.

We report the results of the STRong lensing Insights from the Dark Energy Survey (STRIDES) follow-up campaign of the late 2017/early 2018 season. We obtained spectra of 65 lensed quasar candidates either with EFOSC2 on the NTT or ESI on Keck, which confirm 10 new gravitationally lensed quasars and 10 quasar pairs with similar spectra, but which do not show a lensing galaxy in DES images. Eight lensed quasars are doubly imaged with source redshifts between 0.99 and 2.90, one is triply imaged by a group (DESJ0345-2545, $z=1.68$), and one is quadruply imaged (quad: DESJ0053-2012, $z=3.8$). Singular isothermal ellipsoid models for the doubles, based on high-resolution imaging from SAMI on SOAR or NIRC2 on Keck, give total magnifications between 3.2 and 5.6, and Einstein radii between 0.49 and 1.97 arcseconds. After spectroscopic follow-up, we extract multi-epoch $grizY$ photometry of confirmed lensed quasars and contaminant quasar+star pairs from the first 4 years of DES data using parametric multi-band modelling, and compare variability in each system's components. By measuring the reduced ${\chi}^2$ associated with fitting all epochs to the same magnitude, we find a simple cut on the less variable component that retains all confirmed lensed quasars, while removing 94 per cent of contaminant systems with stellar components. Based on our spectroscopic follow-up, this variability information can improve selection of lensed quasars and quasar pairs from 34-45 per cent to 51-70 per cent, with the majority of remaining contaminants being compact star-forming galaxies. Using mock lensed quasar lightcurves we demonstrate that selection based only on variability will over-represent the quad fraction by 10 per cent over a complete DES magnitude-limited sample (excluding microlensing differences), explained by the magnification bias and hence lower luminosity (more variable) sources in quads.

For ground-based optical imaging with current CCD technology, the Poisson fluctuations in source and sky background photon arrivals dominate the noise budget and are readily estimated. Another component of noise, however, is the signal from the undetected population of stars and galaxies. Using injection of artificial galaxies into images, we demonstrate that the measured variance of galaxy moments (used for weak gravitational lensing measurements) in Dark Energy Survey (DES) images is significantly in excess of the Poisson predictions, by up to 30\%, and that the background sky levels are overestimated by current software. By cross-correlating distinct images of "empty" sky regions, we establish that there is a significant image noise contribution from undetected static sources (US), which on average are mildly resolved at DES resolution. Treating these US as a stationary noise source, we compute a correction to the moment covariance matrix expected from Poisson noise. The corrected covariance matrix matches the moment variances measured on the injected DES images to within 5\%. Thus we have an empirical method to statistically account for US in weak lensing measurements, rather than requiring extremely deep sky simulations. We also find that local sky determinations can remove the bias in flux measurements, at a small penalty in additional, but quantifiable, noise.

Weak lensing source galaxy catalogues used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study, we test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift P(z) of source galaxies into contaminating and background components. We perform a full scale mock analysis on a simulated sky survey approximately mirroring the observational properties of the Dark Energy Survey Year One observations (DES Y1), and find excellent agreement between the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. We further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of weak lensing source galaxies. We find indications that the correlation based estimates are biased by the selection of the weak lensing sources in the cluster vicinity, which does not strongly impact the P(z) decomposition method. Collectively, these benchmarks demonstrate the strength of the P(z) decomposition method in alleviating membership contamination and enabling highly accurate cluster weak lensing studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing.

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogues from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multiband deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalogue created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of sigma(Delta z) = 0.007, which is a 60 per cent improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.