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We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadencer-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σdepth of the combined exposures typically reaches the 27^thmagnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed inHubbleSpace Telescope imaging. This was made possible thanks to a new photometric pipeline,lightcurver, and the forward modelling methodSTARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal. 

We present Magellan/IMACS and Magellan/MIKE spectroscopy of the ultra-faint dwarf (UFD) galaxy Pictor~II (Pic~II) that is located only 12 kpc from the Large Magellanic Cloud (LMC). From the IMACS spectroscopy, we identify 13 member stars and measure a mean heliocentric velocity of , a velocity dispersion of , a mean metallicity of , and an upper limit on the metallicity dispersion of . We measure detailed elemental abundances for the brightest star, finding $\text{[Fe/H]}=-3.3$, high [ $\alpha$/Fe] ratios, and no detectable neutron capture elements, similar to stars in other UFDs. However, this star has an unusually high [Sc/Fe] ratio. The dynamical mass-to-light ratio ( $M/L={760}_{-420}^{+910}{M}_{\odot }{L}_{\odot }^{-1}$), size, and chemical abundances confirms that Pic~II is a dark matter-dominated dwarf galaxy. We perform detailed orbit modeling of Pic~II in a combined Milky Way (MW) and LMC potential and find that Pic~II is highly likely to be a long-term LMC satellite. Furthermore, we find that Pic II is likely still bound to the LMC today. Pic~II is the seventh LMC-associated UFD and among the most metal-poor UFDs known. We further update the morphological parameters with deeper Dark Energy Camera (DECam) photometry, compute the dark matter properties for dark matter indirect detection searches, verify the extremely low metallicity with narrowband CaHK imaging, and briefly discuss tidal influences of the LMC and MW. 

We present a study of the weak lensing inferred matter profiles ΔΣ(R) of 698 South Pole Telescope (SPT) thermal Sunyaev-Zel’dovich effect (tSZE) selected and MCMF optically confirmed galaxy clusters in the redshift range 0.25 <  z <  0.94 that have associated weak gravitational lensing shear profiles from the Dark Energy Survey (DES). Rescaling these profiles to account for the mass dependent size and the redshift dependent density produces average rescaled matter profiles ΔΣ(R/R_200c)/(ρ_critR_200c) with a lower dispersion than the unscaled ΔΣ(R) versions, indicating a significant degree of self-similarity. Galaxy clusters from hydrodynamical simulations also exhibit matter profiles that suggest a high degree of self-similarity, with RMS variation among the average rescaled matter profiles with redshift and mass falling by a factor of approximately six and 23, respectively, compared to the unscaled average matter profiles. We employed this regularity in a new Bayesian method for weak lensing mass calibration that employs the so-called cluster mass posteriorP(M₂₀₀|ζ̂, λ̂,z), which describes the individual cluster masses given their tSZE (ζ̂) and optical (λ̂,z) observables. This method enables simultaneous constraints on richnessλ-mass and tSZE detection significanceζ-mass relations using average rescaled cluster matter profiles. We validated the method using realistic mock datasets and present observable-mass relation constraints for the SPT×DES sample, where we constrained the amplitude, mass trend, redshift trend, and intrinsic scatter. Our observable-mass relation results are in agreement with the mass calibration derived from the recent cosmological analysis of the SPT×DES data based on a cluster-by-cluster lensing calibration. Our new mass calibration technique offers a higher efficiency when compared to the single cluster calibration technique. We present new validation tests of the observable-mass relation that indicate the underlying power-law form and scatter are adequate to describe the real cluster sample but that also suggest a redshift variation in the intrinsic scatter of theλ-mass relation may offer a better description. In addition, the average rescaled matter profiles offer high signal-to-noise ratio (S/N) constraints on the shape of real cluster matter profiles, which are in good agreement with available hydrodynamical ΛCDM simulations. This high S/N profile contains information about baryon feedback, the collisional nature of dark matter, and potential deviations from general relativity. 

We use galaxy cluster abundance measurements from the South Pole Telescope enhanced by multicomponent matched filter confirmation and complemented with mass information obtained using weak-lensing data from Dark Energy Survey Year 3 (DES Y3) and targeted Hubble Space Telescope observations for probing deviations from the cold dark matter paradigm. Concretely, we consider a class of dark sector models featuring interactions between dark matter (DM) and a dark radiation (DR) component within the framework of the effective theory of structure formation (ETHOS). We focus on scenarios that lead to power suppression over a wide range of scales, and thus can be tested with data sensitive to large scales, as realized, for example, for DM–DR interactions following from an unbroken non-Abelian $SU\left(N\right)$gauge theory (interaction rate with power-law index $n=0$within the ETHOS parametrization). Cluster abundance measurements are mostly sensitive to the amount of DR interacting with DM, parametrized by the ratio of DR temperature to the cosmic microwave background (CMB) temperature, ${\xi }_{\mathrm{DR}}=T_{\mathrm{DR}}/T_{\mathrm{CMB}}$. We find an upper limit ${\xi }_{\mathrm{DR}}<17\%$at 95% credibility. When the cluster data are combined with Planck 2018 CMB data along with baryon acoustic oscillation (BAO) measurements we find ${\xi }_{\mathrm{DR}}<10\%$, corresponding to a limit on the abundance of interacting DR that is around 3 times tighter than that from CMB + BAO data alone. We also discuss the complementarity of weak lensing informed cluster abundance studies with probes sensitive to smaller scales, explore the impact on our analysis of massive neutrinos, and comment on a slight preference for the presence of a nonzero interacting DR abundance, which enables a physical solution to the $S_8$tension. Published by the American Physical Society2025 

We present constraints on the $f\left(R\right)$gravity model using a sample of 1005 galaxy clusters in the redshift range 0.25–1.78 that have been selected through the thermal Sunyaev-Zel’dovich effect from South Pole Telescope data and subjected to optical and near-infrared confirmation with the multicomponent matched filter algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey Year 3 data for 688 clusters at $z<0.95$and from the Hubble Space Telescope for 39 clusters with $0.6<z<1.7$. Our cluster sample is a powerful probe of $f\left(R\right)$gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semianalytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background temperature and polarization anisotropy measurements from the Planck 2018 release, we derive robust constraints on the $f\left(R\right)$parameter $f_{R0}$. Our results, ${\log }_{10}\left|f_{R0}\right|<-5.32$at the 95% credible level, are the tightest current constraints on $f\left(R\right)$gravity from cosmological scales. This upper limit rules out $f\left(R\right)$-like deviations from general relativity that result in more than a $\sim 20\%$enhancement of the cluster population on mass scales $M_{200\mathrm{c}}>3\times {10}^{14}{M}_{\odot }$. Published by the American Physical Society2025 

ABSTRACT 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. 

The importance of alternative methods for measuring the Hubble constant, such as time-delay cosmography, is highlighted by the recent Hubble tension. It is paramount to thoroughly investigate and rule out systematic biases in all measurement methods before we can accept new physics as the source of this tension. In this study, we perform a check for systematic biases in the lens modelling procedure of time-delay cosmography by comparing independent and blind time-delay predictions of the system WGD 2038−4008 from two teams using two different software programs:GLEEandLENSTRONOMY. The predicted time delays from the two teams incorporate the stellar kinematics of the deflector and the external convergence from line-of-sight structures. The un-blinded time-delay predictions from the two teams agree within 1.2σ, implying that once the time delay is measured the inferred Hubble constant will also be mutually consistent. However, there is a ∼4σdiscrepancy between the power-law model slope and external shear, which is a significant discrepancy at the level of lens models before the stellar kinematics and the external convergence are incorporated. We identify the difference in the reconstructed point spread function (PSF) to be the source of this discrepancy. When the same reconstructed PSF was used by both teams, we achieved excellent agreement, within ∼0.6σ, indicating that potential systematics stemming from source reconstruction algorithms and investigator choices are well under control. We recommend that future studies supersample the PSF as needed and marginalize over multiple algorithms or realizations for the PSF reconstruction to mitigate the systematics associated with the PSF. A future study will measure the time delays of the system WGD 2038−4008 and infer the Hubble constant based on our mass models. 

Abstract 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.