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L. N. da Costa

Publications and source records attributed to L. N. da Costa.

At least 145 records · Page 8Linked to original sources

Active Galactic Nuclei signatures in Red Geyser galaxies from Gemini GMOS-IFU observations

Red Geysers are quiescent galaxies with galactic scale ionised outflows, likely due to low-luminosity Active Galactic Nuclei (AGN). We used Gemini GMOS-IFU observations of the inner $\sim 1.0-3.0$ kpc of nine Red Geysers selected from the MaNGA survey to study the gas ionisation and kinematics. The emission-line ratios suggest the presence of Seyfert/LINER (Low Ionisation Nuclear Emission Region) nuclei in all sources. Two galaxies show H$α$ equivalent width (H$α$ EW) larger than 3 Å(indicative of AGN ionisation) within an aperture 2.5 arcsec of diameter ($1.3-3.7$ kpc at the distance of galaxies) for MaNGA data, while with the higher resolution GMOS data, four galaxies present H$α$ EW$>3$ Åwithin an aperture equal to the angular resolution ($0.3-0.9$ kpc). For two objects with GMOS-IFU data, the H$α$ EW is lower than 3 Åbut larger than 1.5 Å, most probably due to a faint AGN. The spatially resolved electron density maps show values between $100-3000$ cm$^{-3}$ and are consistent with those determined in other studies. The large (MaNGA) and the nuclear scale (GMOS-IFU) gas velocity fields are misaligned, with a kinematic position angle difference between 12$^{\circ}$ and 60$^{\circ}$. The [NII]$λ$6583 emission-line profiles are asymmetrical, with blue wings on the redshifted side of the velocity field and red wings on the blueshifted side. Our results support previous indications that the gas in Red Geysers is ionised by an AGN, at least in their central region, with the presence of outflows, likely originating in a precessing accretion disc.

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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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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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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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Dark Energy Survey Year 3 Results: Three-Point Shear Correlations and Mass Aperture Moments

We present high signal-to-noise measurements of three-point shear correlations and the third moment of the mass aperture statistic using the first 3 years of data from the Dark Energy Survey. We additionally obtain the first measurements of the configuration and scale dependence of the four three-point shear correlations which carry cosmological information. With the third-order mass aperture statistic, we present tomographic measurements over angular scales of 4 to 60 arcminutes with a combined statistical significance of 15.0$σ$. Using the tomographic information and measuring also the second-order mass aperture, we additionally obtain a skewness parameter and its redshift evolution. We find that the amplitudes and scale-dependence of these shear 3pt functions are in qualitative agreement with measurements in a mock galaxy catalog based on N-body simulations, indicating promise for including them in future cosmological analyses. We validate our measurements by showing that B-modes, parity-violating contributions and PSF modeling uncertainties are negligible, and determine that the measured signals are likely to be of astrophysical and gravitational origin.

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Joint analysis of DES Year 3 data and CMB lensing from SPT and Planck III: Combined cosmological constraints

We present cosmological constraints from the analysis of two-point correlation functions between galaxy positions and galaxy lensing measured in Dark Energy Survey (DES) Year 3 data and measurements of cosmic microwave background (CMB) lensing from the South Pole Telescope (SPT) and Planck. When jointly analyzing the DES-only two-point functions and the DES cross-correlations with SPT+Planck CMB lensing, we find $Ω_{\rm m} = 0.344\pm 0.030$ and $S_8 \equiv σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.773\pm 0.016$, assuming $Λ$CDM. When additionally combining with measurements of the CMB lensing autospectrum, we find $Ω_{\rm m} = 0.306^{+0.018}_{-0.021}$ and $S_8 = 0.792\pm 0.012$. The high signal-to-noise of the CMB lensing cross-correlations enables several powerful consistency tests of these results, including comparisons with constraints derived from cross-correlations only, and comparisons designed to test the robustness of the galaxy lensing and clustering measurements from DES. Applying these tests to our measurements, we find no evidence of significant biases in the baseline cosmological constraints from the DES-only analyses or from the joint analyses with CMB lensing cross-correlations. However, the CMB lensing cross-correlations suggest possible problems with the correlation function measurements using alternative lens galaxy samples, in particular the redMaGiC galaxies and high-redshift MagLim galaxies, consistent with the findings of previous studies. We use the CMB lensing cross-correlations to identify directions for further investigating these problems.

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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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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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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.

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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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DeepZipper II: Searching for Lensed Supernovae in Dark Energy Survey Data with Deep Learning

Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain and 5-10 LSNe in total while next-generation experiments are expected to contain several hundreds to a few thousands of these systems. We search for these systems in observed Dark Energy Survey (DES) 5-year SN fields -- 10 3-sq. deg. regions of sky imaged in the $griz$ bands approximately every six nights over five years. To perform the search, we utilize the DeepZipper approach: a multi-branch deep learning architecture trained on image-level simulations of LSNe that simultaneously learns spatial and temporal relationships from time series of images. We find that our method obtains a LSN recall of 61.13% and a false positive rate of 0.02% on the DES SN field data. DeepZipper selected 2,245 candidates from a magnitude-limited ($m_i$ $<$ 22.5) catalog of 3,459,186 systems. We employ human visual inspection to review systems selected by the network and find three candidate LSNe in the DES SN fields.

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Constraints on the Physical Properties of GW190814 through Simulations based on DECam Follow-up Observations by the Dark Energy Survey

On 14 August 2019, the LIGO and Virgo Collaborations detected gravitational waves from a black hole and a 2.6 solar mass compact object, possibly the first neutron star -- black hole (NSBH) merger. In search of an optical counterpart, the Dark Energy Survey (DES) obtained deep imaging of the entire 90 percent confidence level localization area with Blanco/DECam 0, 1, 2, 3, 6, and 16 nights after the merger. Objects with varying brightness were detected by the DES Pipeline and we systematically reduced the candidate counterparts through catalog matching, light curve properties, host-galaxy photometric redshifts, SOAR spectroscopic follow-up observations, and machine-learning-based photometric classification. All candidates were rejected as counterparts to the merger. To quantify the sensitivity of our search, we applied our selection criteria to full light curve simulations of supernovae and kilonovae as they would appear in the DECam observations. Since the source class of the merger was uncertain, we utilized an agnostic, three-component kilonova model based on tidally-disrupted NS ejecta properties to quantify our detection efficiency of a counterpart if the merger included a NS. We find that if a kilonova occurred during this merger, configurations where the ejected matter is greater than 0.07 solar masses, has lanthanide abundance less than $10^{-8.56}$, and has a velocity between $0.18c$ and $0.21c$ are disfavored at the $2σ$ level. Furthermore, we estimate that our background reduction methods are capable of associating gravitational wave signals with a detected electromagnetic counterpart at the $4σ$ level in $95\%$ of future follow-up observations.

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DeepZipper: A Novel Deep Learning Architecture for Lensed Supernovae Identification

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey datasets, we designed ZipperNet, a multi-branch deep neural network that combines convolutional layers (traditionally used for images) with long short-term memory (LSTM) layers (traditionally used for time series). We tested ZipperNet on the task of classifying objects from four categories -- no lens, galaxy-galaxy lens, lensed type Ia supernova, lensed core-collapse supernova -- within high-fidelity simulations of three cosmic survey data sets -- the Dark Energy Survey (DES), Rubin Observatory's Legacy Survey of Space and Time (LSST), and a Dark Energy Spectroscopic Instrument (DESI) imaging survey. Among our results, we find that for the LSST-like dataset, ZipperNet classifies LSNe with a receiver operating characteristic area under the curve of 0.97, predicts the spectroscopic type of the lensed supernovae with 79\% accuracy, and demonstrates similarly high performance for LSNe 1-2 epochs after first detection. We anticipate that a model like ZipperNet, which simultaneously incorporates spatial and temporal information, can play a significant role in the rapid identification of lensed transient systems in cosmic survey experiments.

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Dark Energy Survey Year 3 Results: High-precision measurement and modeling of galaxy-galaxy lensing

We present and characterize the galaxy-galaxy lensing signal measured using the first three years of data from the Dark Energy Survey (DES Y3) covering 4132 deg$^2$. These galaxy-galaxy measurements are used in the DES Y3 3$\times$2pt cosmological analysis, which combines weak lensing and galaxy clustering information. We use two lens samples: a magnitude-limited sample and the redMaGic sample, which span the redshift range $\sim 0.2-1$ with 10.7 M and 2.6 M galaxies respectively. For the source catalog, we use the Metacalibration shape sample, consisting of $\simeq$100 M galaxies separated into 4 tomographic bins. Our galaxy-galaxy lensing estimator is the mean tangential shear, for which we obtain a total S/N of $\sim$148 for MagLim ($\sim$120 for redMaGic), and $\sim$67 ($\sim$55) after applying the scale cuts of 6 Mpc/$h$. Thus we reach percent-level statistical precision, which requires that our modeling and systematic-error control be of comparable accuracy. The tangential shear model used in the 3$\times$2pt cosmological analysis includes lens magnification, a five-parameter intrinsic alignment model (TATT), marginalization over a point-mass to remove information from small scales and a linear galaxy bias model validated with higher-order terms. We explore the impact of these choices on the tangential shear observable and study the significance of effects not included in our model, such as reduced shear, source magnification and source clustering. We also test the robustness of our measurements to various observational and systematics effects, such as the impact of observing conditions, lens-source clustering, random-point subtraction, scale-dependent Metacalibration responses, PSF residuals, and B-modes.

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Dark Energy Survey Year 3 Results: Exploiting small-scale information with lensing shear ratios

Using the first three years of data from the Dark Energy Survey, we use ratios of small-scale galaxy-galaxy lensing measurements around the same lens sample to constrain source redshift uncertainties, intrinsic alignments and other nuisance parameters of our model. Instead of using a simple geometric approach for the ratios, we use the full modeling of the galaxy-galaxy lensing measurements, including the corresponding integration over the power spectrum and the contributions from intrinsic alignments and lens magnification. We perform extensive testing of the small-scale shear ratio (SR) modeling by studying the impact of different effects such as the inclusion of baryonic physics, non-linear biasing, halo occupation distribution descriptions and lens magnification, among others, and using realistic $N$-body simulations. We validate the robustness of our constraints in the data by using two independent lens samples, and by deriving constraints using the corresponding large-scale ratios for which the modeling is simpler. The DES Y3 results demonstrate how the ratios provide significant improvements in constraining power for several nuisance parameters in our model, especially on source redshift calibration and intrinsic alignments (IA). For source redshifts, SR improves the constraints from the prior by up to 38\% in some redshift bins. Such improvements, and especially the constraints it provides on IA, translate to tighter cosmological constraints when SR is combined with cosmic shear and other 2pt functions. In particular, for the DES Y3 data, SR improves $S_8$ constraints from cosmic shear by up to 31\%, and for the full combination of probes (3$\times$2pt) by up to 10\%. The shear ratios presented in this work are used as an additional likelihood for cosmic shear, 2$\times$2pt and the full 3$\times$2pt in the fiducial DES Y3 cosmological analysis.

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Joint analysis of DES Year 3 data and CMB lensing from SPT and Planck II: Cross-correlation measurements and cosmological constraints

Cross-correlations of galaxy positions and galaxy shears with maps of gravitational lensing of the cosmic microwave background (CMB) are sensitive to the distribution of large-scale structure in the Universe. Such cross-correlations are also expected to be immune to some of the systematic effects that complicate correlation measurements internal to galaxy surveys. We present measurements and modeling of the cross-correlations between galaxy positions and galaxy lensing measured in the first three years of data from the Dark Energy Survey with CMB lensing maps derived from a combination of data from the 2500 deg$^2$ SPT-SZ survey conducted with the South Pole Telescope and full-sky data from the Planck satellite. The CMB lensing maps used in this analysis have been constructed in a way that minimizes biases from the thermal Sunyaev Zel'dovich effect, making them well suited for cross-correlation studies. The total signal-to-noise of the cross-correlation measurements is 23.9 (25.7) when using a choice of angular scales optimized for a linear (nonlinear) galaxy bias model. We use the cross-correlation measurements to obtain constraints on cosmological parameters. For our fiducial galaxy sample, which consist of four bins of magnitude-selected galaxies, we find constraints of $Ω_{m} = 0.272^{+0.032}_{-0.052}$ and $S_{8} \equiv σ_8 \sqrt{Ω_{m}/0.3}= 0.736^{+0.032}_{-0.028}$ ($Ω_{m} = 0.245^{+0.026}_{-0.044}$ and $S_{8} = 0.734^{+0.035}_{-0.028}$) when assuming linear (nonlinear) galaxy bias in our modeling. Considering only the cross-correlation of galaxy shear with CMB lensing, we find $Ω_{m} = 0.270^{+0.043}_{-0.061}$ and $S_{8} = 0.740^{+0.034}_{-0.029}$. Our constraints on $S_8$ are consistent with recent cosmic shear measurements, but lower than the values preferred by primary CMB measurements from Planck.

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The DECam Local Volume Exploration Survey Data Release 2

We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ~160,000 exposures that cover >21,000 deg^2 of the high Galactic latitude (|b| > 10 deg) sky in four broadband optical/near-infrared filters (g, r, i, z). DELVE DR2 provides point-source and automatic aperture photometry for ~2.5 billion astronomical sources with a median 5σ point-source depth of g=24.3, r=23.9, i=23.5, and z=22.8 mag. A region of ~17,000 deg^2 has been imaged in all four filters, providing four-band photometric measurements for ~618 million astronomical sources. DELVE DR2 covers more than four times the area of the previous DELVE data release and contains roughly five times as many astronomical objects. DELVE DR2 is publicly available via the NOIRLab Astro Data Lab science platform.

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Joint analysis of DES Year 3 data and CMB lensing from SPT and Planck I: Construction of CMB Lensing Maps and Modeling Choices

Joint analyses of cross-correlations between measurements of galaxy positions, galaxy lensing, and lensing of the cosmic microwave background (CMB) offer powerful constraints on the large-scale structure of the Universe. In a forthcoming analysis, we will present cosmological constraints from the analysis of such cross-correlations measured using Year 3 data from the Dark Energy Survey (DES), and CMB data from the South Pole Telescope (SPT) and Planck. Here we present two key ingredients of this analysis: (1) an improved CMB lensing map in the SPT-SZ survey footprint, and (2) the analysis methodology that will be used to extract cosmological information from the cross-correlation measurements. Relative to previous lensing maps made from the same CMB observations, we have implemented techniques to remove contamination from the thermal Sunyaev Zel'dovich effect, enabling the extraction of cosmological information from smaller angular scales of the cross-correlation measurements than in previous analyses with DES Year 1 data. We describe our model for the cross-correlations between these maps and DES data, and validate our modeling choices to demonstrate the robustness of our analysis. We then forecast the expected cosmological constraints from the galaxy survey-CMB lensing auto and cross-correlations. We find that the galaxy-CMB lensing and galaxy shear-CMB lensing correlations will on their own provide a constraint on $S_8=σ_8 \sqrt{Ω_{\rm m}/0.3}$ at the few percent level, providing a powerful consistency check for the DES-only constraints. We explore scenarios where external priors on shear calibration are removed, finding that the joint analysis of CMB lensing cross-correlations can provide constraints on the shear calibration amplitude at the 5 to 10% level.

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