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The present state of cosmology is facing a crisis where there is a fundamental disagreement in measurements of the Hubble constant ($H_{0}$), with significant tension between the early and late Universe methods. Type Ia supernovae (SNe Ia) are important to measuring $H_{0}$ through the astronomical distance ladder. However, there remains potential to better standardize SN Ia light curves by using known dependencies on host galaxy properties after the standard light curve width and colour corrections have been applied to the peak SN Ia luminosities. To explore this, we use the 5-yr photometrically identified SNe Ia sample obtained by the Dark Energy Survey, along with host galaxy spectra obtained by the Australian Dark Energy Survey. Using host galaxy spectroscopy, we find a significant trend with the equivalent width (EW) of the [O ii] $\lambda \lambda$ 3727, 29 doublet, a proxy for specific star formation rate, and Hubble residuals. We find that the correlation with [O ii] EW is a powerful alternative to the commonly used mass step after initial light-curve corrections. Applying this [O ii] EW correction to 20 SNe Ia in calibrator galaxies observed with WiFeS, we examined the impact on SN Ia absolute magnitudes and $H_{0}$. Our [O ii] EW corrections result in $H_{0}$ values ranging between 73.04 and 73.51 $\mathrm{km \, s^{-1} \, Mpc^{-1}}$, with a combined statistical and systematic uncertainty of $\sim 1.31 \, \mathrm{km \, s^{-1} \, Mpc^{-1}}$. However, even with this additional correction, the impact of host galaxy properties in standardizing SNe Ia appears limited in reducing the current tension ($\sim 5\sigma$) with the cosmic microwave background result for $H_{0}$.

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range $0.20 \lt z \lt 0.60$, we characterize the hierarchical assembly of bright central galaxies (BCGs) and the surrounding intracluster light (ICL). To quantify hierarchical formation we use the stellar mass–halo mass (SMHM) relation, comparing the halo mass, estimated via the mass–richness relation, to the stellar mass within the BCG + ICL system. Moreover, we incorporate the magnitude gap (M14), the difference in brightness between the BCG (measured within 30 kpc) and fourth brightest cluster member galaxy within 0.5 $R_{200,c}$, as a third parameter in this linear relation. The inclusion of M14, which traces BCG hierarchical growth, increases the slope and decreases the intrinsic scatter, highlighting that it is a latent variable within the BCG + ICL SMHM relation. Moreover, the correlation with M14 decreases at large radii. However, the stellar light within the BCG + ICL transition region (30 –80 kpc) most strongly correlates with halo mass and has a statistically significant correlation with M14. Since the transition region and M14 are independent measurements, the transition region may grow due to the BCG’s hierarchical formation. Additionally, as M14 and ICL result from hierarchical growth, we use a stacked sample and find that clusters with large M14 values are characterized by larger ICL and BCG + ICL fractions, which illustrates that the merger processes that build the BCG stellar mass also grow the ICL. Furthermore, this may suggest that M14 combined with the ICL fraction can identify dynamically relaxed clusters.

Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-yr Dark Energy Survey (DES) data set using the SuperNNova classifier. Our approach, which does not rely on any information from the SN host-galaxy, recovers SNe Ia that might otherwise be lost due to a lack of an identifiable host. We select $2{,}298$ high-quality SNe Ia from the DES 5-yr data set an almost complete sample of detected SNe Ia. More than 700 of these have no spectroscopic host redshift and are potentially new SNIa compared to the DES-SN5YR cosmology analysis. To analyse these SNe Ia, we derive their redshifts and properties using only their light curves with a modified version of the SALT2 light-curve fitter. Compared to other DES SN Ia samples with spectroscopic redshifts, our new sample has in average higher redshift, bluer and broader light curves, and fainter host-galaxies. Future surveys such as LSST will also face an additional challenge, the scarcity of spectroscopic resources for follow-up. When applying our novel method to DES data, we reduce the need for follow-up by a factor of four and three for host-galaxy and live SN, respectively, compared to earlier approaches. Our novel method thus leads to better optimization of spectroscopic resources for follow-up.

Context.The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches is machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs.

Aims.The goal of this work is to calculate the photo-zsfor the Year 3 (Y3) Dark Energy Survey (DES) Deep Fields catalogue using the Directional Neighborhood Fitting (DNF) machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained by DNF on the Y3 DES Deep Fields catalogue with that of the EAzY template fitting approach.

Methods.We emulated – at a brighter magnitude – the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We used a principal component analysis to graphically assess the incompleteness and relate it with the performance parameters provided by DNF. Finally, we applied the results on the incompleteness to the photo-zcomputation on the Y3 DES Deep Fields with DNF and estimated its performance.

Results.The photo-zsof the galaxies in the DES deep fields were computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. We have developed some techniques to evaluate the performance in the absence of “true” redshift and to assess the completeness. We have studied the tradeoff in the training sample between the highest spectroscopic redshift quality versus completeness. We found some advantages in relaxing the highest-quality spectroscopic redshift requirements at fainter magnitudes in favour of completeness. The results achieved by DNF on the Y3 Deep Fields are competitive with the ones provided by EAzY, showing notable stability at high redshifts. It should be noted that the good results obtained by DNF in the estimation of photo-zsin deep field catalogues make DNF suitable for the future Legacy Survey of Space and Time (LSST) andEucliddata, which will have similar depths to the Y3 DES Deep Fields.

We present the full Hubble diagram of photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7000 host galaxies. Based on the light-curve quality, we select 1635 photometrically identified SNe Ia with spectroscopic redshift 0.10 <z< 1.13, which is the largest sample of supernovae from any single survey and increases the number of knownz> 0.5 supernovae by a factor of 5. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are${\sigma }_{{\mathrm{\Omega }}_M,\mathrm{stat}+\mathrm{sys}}^{\mathrm{\Lambda }\mathrm{CDM}}=$0.017 in a flat ΛCDM model, and$({\sigma }_{{\mathrm{\Omega }}_M},{\sigma }_w{)}_{\mathrm{stat}+\mathrm{sys}}^{w\mathrm{CDM}}$= (0.082, 0.152) in a flatwCDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

Reverberation mapping is the leading technique used to measure direct black hole masses outside of the local Universe. Additionally, reverberation measurements calibrate secondary mass-scaling relations used to estimate single-epoch virial black hole masses. The Australian Dark Energy Survey (OzDES) conducted one of the first multi-object reverberation mapping surveys, monitoring 735 AGN up to z ∼ 4, over 6 years. The limited temporal coverage of the OzDES data has hindered recovery of individual measurements for some classes of sources, particularly those with shorter reverberation lags or lags that fall within campaign season gaps. To alleviate this limitation, we perform a stacking analysis of the cross-correlation functions of sources with similar intrinsic properties to recover average composite reverberation lags. This analysis leads to the recovery of average lags in each redshift-luminosity bin across our sample. We present the average lags recovered for the Hβ, Mg ii, and C iv samples, as well as multiline measurements for redshift bins where two lines are accessible. The stacking analysis is consistent with the Radius–Luminosity relations for each line. Our results for the Hβ sample demonstrate that stacking has the potential to improve upon constraints on the R–L relation, which have been derived only from individual source measurements until now.

We present an extension to a Sunyaev–Zel’dovich Effect (SZE) selected cluster catalogue based on observations from the South Pole Telescope (SPT); this catalogue extends to lower signal to noise than the previous SPT–SZ catalogue and therefore includes lower mass clusters. Optically derived redshifts, centres, richnesses, and morphological parameters together with catalogue contamination and completeness statistics are extracted using the multicomponent matched filter (MCMF) algorithm applied to the S/N > 4 SPT–SZ candidate list and the Dark Energy Survey (DES) photometric galaxy catalogue. The main catalogue contains 811 sources above S/N = 4, has 91  per cent purity, and is 95 per cent complete with respect to the original SZE selection. It contains in total 50 per cent more clusters and twice as many clusters above z = 0.8 in comparison to the original SPT-SZ sample. The MCMF algorithm allows us to define subsamples of the desired purity with traceable impact on catalogue completeness. As an example, we provide two subsamples with S/N > 4.25 and S/N > 4.5 for which the sample contamination and cleaning-induced incompleteness are both as low as the expected Poisson noise for samples of their size. The subsample with S/N > 4.5 has 98 per cent purity and 96 per cent completeness and is part of our new combined SPT cluster and DES weak-lensing cosmological analysis. We measure the number of false detections in the SPT-SZ candidate list as function of S/N, finding that it follows that expected from assuming Gaussian noise, but with a lower amplitude compared to previous estimates from simulations.

We present a flare star catalog from 4 yr of nontargeted millimeter-wave survey data from the South Pole Telescope (SPT). The data were taken with the SPT-3G camera and cover a 1500 deg²region of the sky from 20^h40^m0^sto 3^h20^m0^sin right ascension and from −42° to −70° in declination. This region was observed on a nearly daily cadence from 2019 to 2022 and chosen to avoid the plane of the galaxy. A short-duration transient search of this survey yields 111 flaring events from 66 stars, increasing the number of both flaring events and detected flare stars by an order of magnitude from the previous SPT-3G data release. We provide cross-matching to Gaia DR3, as well as matches to X-ray point sources found in the second ROSAT all-sky survey. We have detected flaring stars across the main sequence, from early-type A stars to M dwarfs, as well as a large population of evolved stars. These stars are mostly nearby, spanning 10–1000 pc in distance. Most of the flare spectral indices are constant or gently rising as a function of frequency at 95/150/220 GHz. The timescale of these events can range from minutes to hours, and the peakνL_νluminosities range from 10²⁷to 10³¹erg s⁻¹in the SPT-3G frequency bands.