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Abstract We present the discovery of DELVE 6, an ultra-faint stellar system identified in the second data release of the DECam Local Volume Exploration (DELVE) survey. Based on a maximum-likelihood fit to its structure and stellar population, we find that DELVE 6 is an old ( τ > 9.8 Gyr at 95% confidence) and metal-poor ([Fe/H] < −1.17 dex at 95% confidence) stellar system with an absolute magnitude of M V = − 1.5 − 0.6 + 0.4 mag and an azimuthally averaged half-light radius of r 1 / 2 = 10 − 3 + 4 pc. These properties are consistent with the population of ultra-faint star clusters uncovered by recent surveys. Interestingly, DELVE 6 is located at an angular separation of ∼10° from the center of the Small Magellanic Cloud (SMC), corresponding to a 3D physical separation of ∼20 kpc given the system’s observed distance ( D ⊙ = 80 kpc). This also places the system ∼35 kpc from the center of the Large Magellanic Cloud (LMC), lying within recent constraints on the size of the LMC’s dark matter halo. We tentatively measure the proper motion of DELVE 6 using data from Gaia, which we find supports a potentialmore »association between the system and the LMC/SMC. Although future kinematic measurements will be necessary to determine its origins, we highlight that DELVE 6 may represent only the second or third ancient ( τ > 9 Gyr) star cluster associated with the SMC, or one of fewer than two dozen ancient clusters associated with the LMC. Nonetheless, we cannot currently rule out the possibility that the system is a distant Milky Way halo star cluster.« less

The fiducial cosmological analyses of imaging surveys like DES typically probe the Universe at redshifts z < 1. We present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around z ∼ 0.9, 1.2, and 1.5, which extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times higher than those in the DES Year 3 fiducial case. We characterize the redshift uncertainties of the samples, including the usage of various spectroscopic and high-quality redshift samples, and we develop a machine-learning method to correct for correlations between galaxy density and survey observing conditions. The analysis of galaxy clustering measurements, with a total signal to noise S/N ∼ 70 after scale cuts, yields robust cosmological constraints on a combination of the fraction of matter in the Universe Ωm and the Hubble parameter h, $\Omega _m h = 0.195^{+0.023}_{-0.018}$, andmore »2–3  per cent measurements of the amplitude of the galaxy clustering signals, probing galaxy bias and the amplitude of matter fluctuations, bσ8. A companion paper (in preparation) will present the cross-correlations of these high-z samples with cosmic microwave background lensing from Planck and South Pole Telescope, and the cosmological analysis of those measurements in combination with the galaxy clustering presented in this work.

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We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1σformal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with theP= 15.785 90 ± 0.00005 day sidereal period of Dysnomia’s orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris’s brightness with respect to illumination phase averaged acrossg,V, andrbands, intermediate between Pluto’s and Charon’s values. Variations of 0.3 mag are detected in Dysnomia’s brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.

We present a sample of 19 583 ultracool dwarf candidates brighter than z ≤23 selected from the Dark Energy Survey DR2 coadd data matched to VHS DR6, VIKING DR5, and AllWISE covering ∼ 480 deg2. The ultracool candidates were first pre-selected based on their (i–z), (z–Y), and (Y–J) colours. They were further classified using a method that compares their optical, near-infrared, and mid-infrared colours against templates of M, L, and T dwarfs. 14 099 objects are presented as new L and T candidates and the remaining objects are from the literature, including 5342 candidates from our previous work. Using this new and deeper sample of ultracool dwarf candidates we also present: 20 new candidate members to nearby young moving groups and associations, variable candidate sources and four new wide binary systems composed of two ultracool dwarfs. Finally, we also show the spectra of 12 new ultracool dwarfs discovered by our group and presented here for the first time. These spectroscopically confirmed objects are a sanity check of our selection of ultracool dwarfs and photometric classification method.

We cross-match and compare characteristics of galaxy clusters identified in observations from two sky surveys using two completely different techniques. One sample is optically selected from the analysis of 3 years of Dark Energy Survey observations using the redMaPPer cluster detection algorithm. The second is X-ray selected from XMM observations analysed by the XMM Cluster Survey. The samples comprise a total area of 57.4 deg2, bounded by the area of four contiguous XMM survey regions that overlap the DES footprint. We find that the X-ray-selected sample is fully matched with entries in the redMaPPer catalogue, above λ > 20 and within 0.1 <$z$ <0.9. Conversely, only 38 per cent of the redMaPPer catalogue is matched to an X-ray extended source. Next, using 120 optically clusters and 184 X-ray-selected clusters, we investigate the form of the X-ray luminosity–temperature (LX –TX ), luminosity–richness (LX –λ), and temperature–richness (TX –λ) scaling relations. We find that the fitted forms of the LX –TX relations are consistent between the two selection methods and also with other studies in the literature. However, we find tentative evidence for a steepening of the slope of the relation for low richness systems in the X-ray-selected sample. When considering the scalingmore »of richness with X-ray properties, we again find consistency in the relations (i.e. LX –λ and TX –λ) between the optical and X-ray-selected samples. This is contrary to previous similar works that find a significant increase in the scatter of the luminosity scaling relation for X-ray-selected samples compared to optically selected samples.

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We present direct constraints on galaxy intrinsic alignments (IAs) using the Dark Energy Survey Year 3 (DES Y3), the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and its precursor, the Baryon Oscillation Spectroscopic Survey (BOSS). Our measurements incorporate photometric red sequence (redMaGiC) galaxies from DES with median redshift z ∼ 0.2–1.0, luminous red galaxies from eBOSS at z ∼ 0.8, and also an SDSS-III BOSS CMASS sample at z ∼ 0.5. We measure two-point IA correlations, which we fit using a model that includes lensing, magnification, and photometric redshift error. Fitting on scales 6 Mpc h−1 < rp < 70 Mpc h−1, we make a detection of IAs in each sample, at 5σ–22σ (assuming a simple one-parameter model for IAs). Using these red samples, we measure the IA–luminosity relation. Our results are statistically consistent with previous results, but offer a significant improvement in constraining power, particularly at low luminosity. With this improved precision, we see detectable dependence on colour between broadly defined red samples. It is likely that a more sophisticated approach than a binary red/blue split, which jointly considers colour and luminosity dependence in the IA signal, will be needed in future. We also compare the various signal components at themore »best-fitting point in parameter space for each sample, and find that magnification and lensing contribute $\sim 2\!-\!18~{{\ \rm per\ cent}}$ of the total signal. As precision continues to improve, it will certainly be necessary to account for these effects in future direct IA measurements. Finally, we make equivalent measurements on a sample of emission-line galaxies from eBOSS at z ∼ 0.8. We constrain the non-linear alignment amplitude to be $A_1=0.07^{+0.32}_{-0.42}$ (|A1| < 0.78 at 95 per cent CL).

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We study the effect of magnification in the Dark Energy Survey Year 3 analysis of galaxy clustering and galaxy–galaxy lensing, using two different lens samples: a sample of luminous red galaxies, redMaGiC, and a sample with a redshift-dependent magnitude limit, MagLim. We account for the effect of magnification on both the flux and size selection of galaxies, accounting for systematic effects using the Balrog image simulations. We estimate the impact of magnification on the galaxy clustering and galaxy–galaxy lensing cosmology analysis, finding it to be a significant systematic for the MagLim sample. We show cosmological constraints from the galaxy clustering autocorrelation and galaxy–galaxy lensing signal with different magnifications priors, finding broad consistency in cosmological parameters in ΛCDM and wCDM. However, when magnification bias amplitude is allowed to be free, we find the two-point correlation functions prefer a different amplitude to the fiducial input derived from the image simulations. We validate the magnification analysis by comparing the cross-clustering between lens bins with the prediction from the baseline analysis, which uses only the autocorrelation of the lens bins, indicating that systematics other than magnification may be the cause of the discrepancy. We show that adding the cross-clustering between lens redshift binsmore »to the fit significantly improves the constraints on lens magnification parameters and allows uninformative priors to be used on magnification coefficients, without any loss of constraining power or prior volume concerns.

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We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ∼520 million astronomical sources covering ∼4000 deg²of the southern sky to a 5σpoint–source depth ofg= 24.3,r= 23.9,i= 23.3, andz= 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ∼11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap (b> 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprintmore »does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

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Recent analyses have found intriguing correlations between the colour (c) of type Ia supernovae (SNe Ia) and the size of their ‘mass-step’, the relationship between SN Ia host galaxy stellar mass (Mstellar) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically classified SNe Ia from the Dark Energy Survey 5-yr sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a 3σ difference in the mass-step when comparing blue (c < 0) and red (c > 0) SNe. We observe the lowest r.m.s. scatter (∼0.14 mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for c-dependent relationships between Hubble residuals and Mstellar, approximating existing dust models, we remove the mass-step from the data and find tentative ∼2σ residual steps in rest-frame galaxy U − R colour. This indicates that dust modelling based on Mstellar may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a c-dependent relationship between Hubble residuals and globalmore »U − R, results in ≤1σ residual steps in Mstellar and local U − R, suggesting that U − R provides different information about the environment of SNe Ia compared to Mstellar, and motivating the inclusion of galaxy U − R colour in SN Ia distance bias correction.

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Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program’s 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameterswand Ω_m. We useg−icolors of Type Ia supernovae to quantify astrometric offsets caused by DCR and simulate point-spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of +0.2 mmag and −0.3 mmag, respectively, with standard deviations of 0.7 mmag and 2.7 mmag across all DES observing bands (griz) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find thatwand Ω_mare lower by less than 0.004 ± 0.02 and 0.001 ± 0.01, respectively, with 0.02 and 0.01 being the 1σstatistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much highermore »statistics, lower systematics, and especially those that observe in theuband will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

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