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Computing systems, including real-time embedded systems, are becoming increasingly connected to allow for more advanced and safer operation. Such embedded systems are resource-constrained, such as lower processing capabilities, as compared to general purpose computing systems like desktops or servers. However, allowing external interfaces to such embedded systems increases their exposure to attackers. With an increase in attacks against embedded systems ranging from home appliances to industrial control systems operating critical equipment that have hard real-time requirements, it is imperative that defense mechanisms be created that explicitly consider such resource and real-time constraints constraints. Control-flow integrity (CFI) is a family of defense mechanisms that prevent attackers from modifying the flow of execution. We survey CFI techniques, ranging from the basic to state-of-the-art, that are built for embedded systems and real-time embedded systems and find that there is a dearth, especially for real-time embedded systems, of CFI mechanisms. We then present open challenges to the community to help drive research in this domain.

Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on state-of-the-art simulations of photometrically identified SN Ia samples and determine cosmological biases due to such 'non-Ia' contamination in the Dark Energy Survey (DES) 5-year SN sample. As part of the analysis, we test on our DES simulations the performance of SuperNNova, a photometric SN classifier based on recurrent neural networks. Depending on the choice of non-Ia SN models in both the simulated data sample and training sample, contamination ranges from 0.8-3.5 %, with the efficiency of the classification from 97.7-99.5 %. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension 'BEAMS with Bias Correction' (BBC), we produce a redshift-binned Hubble diagram marginalised over contamination and corrected for selection effects and we use it to constrain the dark energy equation-of-state, $w$. Assuming a flat universe with Gaussian $\Omega_M$ prior of $0.311\pm0.010$, we show that biases on $w$ are $<0.008$ when using SuperNNova and accounting for a wide range of non-Ia SN models in the simulations. Systematic uncertainties associated with contamination are estimated to be at most $\sigma_{w, \mathrm{syst}}=0.004$. This compares to an expected statistical uncertainty of $\sigma_{w,\mathrm{stat}}=0.039$ for the DES-SN sample, thus showing that contamination is not a limiting uncertainty in our analysis. We also measure biases due to contamination on $w_0$ and $w_a$ (assuming a flat universe), and find these to be $<$0.009 in $w_0$ and $<$0.108 in $w_a$, hence 5 to 10 times smaller than the statistical uncertainties expected from the DES-SN sample.

We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the Metacalibration catalogue and perform a likelihood analysis within the framework of CosmoSIS. We set scale cuts based on baryonic effects contamination and model redshift and shear calibration uncertainties as well as intrinsic alignments. We adopt as fiducial covariance matrix an analytical computation accounting for the mask geometry in the Gaussian term, including non-Gaussian contributions. A suite of 1200 lognormal simulations is used to validate the harmonic space pipeline and the covariance matrix. We perform a series of stress tests to gauge the robustness of the harmonic space analysis. Finally, we use the DES-Y1 pipeline in configuration space to perform a similar likelihood analysis and compare both results, demonstrating their compatibility in estimating the cosmological parameters $S_8$, $\sigma_8$ and $\Omega_m$. The methods implemented and validated in this paper will allow us to perform a consistent harmonic space analysis in the upcoming DES data., Comment: 16 pages, 11 figures. This version matches the published one

There has been a rapid growth in the deployment of Unmanned Aerial Vehicles (UAVs) in various applications ranging from vital safety-of-life such as surveillance and reconnaissance at nuclear power plants to entertainment and hobby applications. While popular, drones can pose serious security threats that can be unintentional or intentional. Thus, there is an urgent need for real-time accurate detection and classification of drones. In this article, we perform a survey of drone detection approaches presenting their advantages and limitations. We analyze detection techniques that employ radars, acoustic and optical sensors, and emitted radio frequency (RF) signals. We compare their performance, accuracy, and cost, concluding that combining multiple sensing modalities might be the path forward., Comment: 7 pages, 2 figures, 1 table

We constrain the matter density $\Omega_{\mathrm{m}}$ and the amplitude of density fluctuations $\sigma_8$ within the $\Lambda$CDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv~\sigma_8\sqrt{\Omega_{\mathrm{m}}/0.3}~=~0.797_{-0.013}^{+0.015}$ (68% confidence limits), with a precision of 1.8%, an improvement of ~38% compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in $S_8$ is recorded. We find a mild tension of $1.5 \thinspace \sigma$ between our study and the results from Planck 2018, with our analysis yielding a lower $S_8$. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment $A_{\mathrm{IA}}$ and $S_8$, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.

We use six years of data from the Dark Energy Survey to perform a detailed photometric characterization of the Phoenix stellar stream, a 15-degree long, thin, dynamically cold, low-metallicity stellar system in the southern hemisphere. We use natural splines, a non-parametric modeling technique, to simultaneously fit the stream track, width, and linear density. This updated stream model allows us to improve measurements of the heliocentric distance ($17.4 \pm 0.1\,{\rm (stat.)} \pm 0.8\,{\rm (sys.)}$ kpc) and distance gradient ($-0.009 \pm 0.006$ kpc deg$^{-1}$) of Phoenix, which corresponds to a small change of $0.13 \pm 0.09$ kpc in heliocentric distance along the length of the stream. We measure linear intensity variations on degree scales, as well as deviations in the stream track on $\sim 2$-degree scales, suggesting that the stream may have been disturbed during its formation and/or evolution. We recover three peaks and one gap in linear intensity along with fluctuations in the stream track. Compared to other thin streams, the Phoenix stream shows more fluctuations and, consequently, the study of Phoenix offers a unique perspective on gravitational perturbations of stellar streams. We discuss possible sources of perturbations to Phoenix including baryonic structures in the Galaxy and dark matter subhalos., Comment: 18 Pages, 7 Figures, Matches published version

We report the combined results of eight searches for strong gravitational lens systems in the full 5,000 sq. deg. of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in 5 filters (grizY), with an $i-$band limiting magnitude (at $10\sigma$) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color-coadd "tiles" created from the full DES six-season data set. A short list of the most promising strong lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported. This catalog will be of use for selecting interesting systems for detailed follow-up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong lens searches., Comment: 38 pages, 17 figures, 4 tables, accepted by ApJS

On 2019 August 14 at 21:10:39 UTC, the LIGO/Virgo Collaboration (LVC) detected a possible neutron star-black hole merger (NSBH), the first ever identified. An extensive search for an optical counterpart of this event, designated GW190814, was undertaken using the Dark Energy Camera (DECam) on the 4m Victor M. Blanco Telescope at the Cerro Tololo Inter-American Observatory. Target of Opportunity interrupts were issued on 8 separate nights to observe 11 candidates using the 4.1m Southern Astrophysical Research (SOAR) telescope's Goodman High Throughput Spectrograph in order to assess whether any of these transients was likely to be an optical counterpart of the possible NSBH merger. Here, we describe the process of observing with SOAR, the analysis of our spectra, our spectroscopic typing methodology, and our resultant conclusion that none of the candidates corresponded to the gravitational wave merger event but were all instead other transients. Finally, we describe the lessons learned from this effort. Application of these lessons will be critical for a successful community spectroscopic follow-up program for LVC observing run 4 (O4) and beyond., Comment: 32 pages, 18 figures, accepted for publication by ApJ

C/2014 UN271 (Bernardinelli-Bernstein) is a comet incoming from the Oort cloud which is remarkable in having the brightest (and presumably largest) nucleus of any well-measured comet, and having been discovered at heliocentric distance $r_h\approx29$ au farther than any Oort-cloud member. We describe the properties that can be inferred from images recorded until the first reports of activity in June 2021. The orbit has $i=95^\circ,$ with perihelion of 10.97 au to be reached in 2031, and previous aphelion at $40,400\pm260$ au. Backwards integration of the orbit under a standard Galactic tidal model and known stellar encounters suggests this is a pristine new comet, with a perihelion of $q\approx18$ au on its previous perihelion passage 3.5 Myr ago. The photometric data show an unresolved nucleus with absolute magnitude $H_r=8.0,$ colors that are typical of comet nuclei or Damocloids, and no secular trend as it traversed the range 34--23 au. For $r$-band geometric albedo $p_r,$ this implies a diameter of $150 (p_r/0.04)^{-0.5}$ km. There is strong evidence of brightness fluctuations at $\pm0.2$ mag level, but no rotation period can be discerned. A coma consistent with a ``stationary' $1/\rho$ surface-brightness distribution grew in scattering cross-section at an exponential rate from $A f \rho\approx1$ m to $\approx150$ m as the comet approached from 28 to 20 au. The activity is consistent with a simple model of sublimation of a surface species in radiative equilibrium with the Sun. The inferred enthalpy of sublimation matches those of $CO_2$ and $NH_3$. More-volatile species -- $N_2,$ $CH_4,$ and $CO$ -- must be far less abundant on the sublimating surfaces., Comment: 19 pages, submitted to ApJ Letters

Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky -- only a few tens are known to date -- and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic "needle in a haystack" problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range 0.86 to 0.89. Recall is close to 100% down to total magnitude i~21 indicating high completeness, while precision declines from 85% to 70% in the range i~17-21. The methods are extremely fast: training on 2 million samples takes 20 hours on a GPU machine, and 10^8 multi-band cutouts can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads., Comment: 17 pages, 14 figures, submitted to MNRAS

Cosmological information from weak lensing surveys is maximised by dividing source galaxies into tomographic sub-samples for which the redshift distributions are estimated. Uncertainties on these redshift distributions must be correctly propagated into the cosmological results. We present hyperrank, a new method for marginalising over redshift distribution uncertainties in cosmological analyses, using discrete samples from the space of all possible redshift distributions. This is demonstrated in contrast to previous highly simplified parametric models of the redshift distribution uncertainty. In hyperrank the set of proposed redshift distributions is ranked according to a small (in this work between one and four) number of summary values, which are then sampled along with other nuisance parameters and cosmological parameters in the Monte Carlo chain used for inference. This can be regarded as a general method for marginalising over discrete realisations of data vector variation with nuisance parameters, which can consequently be sampled separately to the main parameters of interest, allowing for increased computational efficiency. We focus on the case of weak lensing cosmic shear analyses and demonstrate our method using simulations made for the Dark Energy Survey (DES). We show the method can correctly and efficiently marginalise over a range of models for the redshift distribution uncertainty. Finally, we compare hyperrank to the common mean-shifting method of marginalising over redshift uncertainty, validating that this simpler model is sufficient for use in the DES Year 3 cosmology results presented in companion papers., Comment: Accepted for publication in MNRAS. 17 pages, 12 figures, comments welcome Replacement: Added small comments suggested by referee

Accurate and complete terrain maps enhance the awareness of autonomous robots and enable safe and optimal path planning. Rocks and topography often create occlusions and lead to missing elevation information in the Digital Elevation Map (DEM). Currently, these occluded areas are either fully avoided during motion planning or the missing values in the elevation map are filled-in using traditional interpolation, diffusion or patch-matching techniques. These methods cannot leverage the high-level terrain characteristics and the geometric constraints of line of sight we humans use intuitively to predict occluded areas. We introduce a self-supervised learning approach capable of training on real-world data without a need for ground-truth information to reconstruct the occluded areas in the DEMs. We accomplish this by adding artificial occlusion to the incomplete elevation maps constructed on a real robot by performing ray casting. We first evaluate a supervised learning approach on synthetic data for which we have the full ground-truth available and subsequently move to several real-world datasets. These real-world datasets were recorded during exploration of both structured and unstructured terrain with a legged robot, and additionally in a planetary scenario on Lunar analogue terrain. We state a significant improvement compared to the baseline methods both on synthetic terrain and for the real-world datasets. Our neural network is able to run in real-time on both CPU and GPU with suitable sampling rates for autonomous ground robots. We motivate the applicability of reconstructing occlusion in elevation maps with preliminary motion planning experiments., Comment: 8 pages, 4 figures, accepted with IEEE Robotics and Automation Letters (RA-L)

We present the results of a search for outer Solar System objects in the full six years of data (Y6) from the Dark Energy Survey (DES). The DES covered a contiguous $5000$ deg$^2$ of the southern sky with $\approx 80,000$ $3$ deg$^2$ exposures in the $grizY$ optical/IR filters between 2013 and 2019. This search yielded 815 trans-Neptunian objects (TNOs), one Centaur and one Oort cloud comet, with 461 objects reported for the first time in this paper. We present methodology that builds upon our previous search carried out on the first four years of data. Here, all DES images were reprocessed with an improved detection pipeline that leads to an average completeness gain of 0.47 mag per exposure, as well as an improved transient catalog production and optimized algorithms for linkage of detections into orbits. All objects were verified by visual inspection and by computing the sub-threshold significance, the total signal-to-noise ratio in the stack of images in which the object's presence is indicated by the orbit fit, but no detection was reported. This yields a highly pure catalog of TNOs complete to $r \approx 23.8$ mag and distances $29150$ au, $q>30$ au) are consistent with the null hypothesis of azimuthal isotropy; and non-resonant TNOs with $q>38$ au, $a>50$ au show a highly significant tendency to be sunward of the major mean motion resonances, whereas this tendency is not present for $q<38$ au., Comment: 29 pages, submitted to AAS journals. Survey simulation software and table of objects will be made available post peer review. Abstract abridged

We present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zeldovich (tSZ) maps from ${\it Planck}$ and the Atacama Cosmology Telescope (ACT) and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey (DES Y3). This correlation is sensitive to the thermal energy in baryons over a wide redshift range, and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of $21\sigma$, the highest significance to date. We examine the tSZ maps for potential contaminants, including cosmic infrared background (CIB) and radio sources, finding that CIB has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the tSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalises over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalise over $\Omega_{\rm m}$ and $\sigma_8$ using ${\it Planck}$ or DES priors. We find that the data prefers the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong AGN feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions., Comment: submitted to PRD

Hot, ionized gas leaves an imprint on the cosmic microwave background via the thermal Sunyaev Zel'dovich (tSZ) effect. The cross-correlation of gravitational lensing (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) is a powerful probe of the thermal state of ionized baryons throughout the Universe, and is sensitive to effects such as baryonic feedback. In a companion paper (Gatti et al. 2021), we present tomographic measurements and validation tests of the cross-correlation between galaxy shear measurements from the first three years of observations of the Dark Energy Survey, and tSZ measurements from a combination of Atacama Cosmology Telescope and ${\it Planck}$ observations. In this work, we use the same measurements to constrain models for the pressure profiles of halos across a wide range of halo mass and redshift. We find evidence for reduced pressure in low mass halos, consistent with predictions for the effects of feedback from active galactic nuclei. We infer the hydrostatic mass bias ($B \equiv M_{500c}/M_{\rm SZ}$) from our measurements, finding $B = 1.8\pm0.1$ when adopting the ${\it Planck}$-preferred cosmological parameters. We additionally find that our measurements are consistent with a non-zero redshift evolution of $B$, with the correct sign and sufficient magnitude to explain the mass bias necessary to reconcile cluster count measurements with the ${\it Planck}$-preferred cosmology. Our analysis introduces a model for the impact of intrinsic alignments (IA) of galaxy shapes on the shear-tSZ correlation. We show that IA can have a significant impact on these correlations at current noise levels., Comment: 22 pages, 13 figures. Comments welcome

We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3 data based on Convolutional Neural Networks (CNN). Monochromatic $i$-band DES images with linear, logarithmic, and gradient scales, matched with debiased visual classifications from the Galaxy Zoo 1 (GZ1) catalogue, are used to train our CNN models. With a training set including bright galaxies ($16\le{i}<18$) at low redshift ($z<0.25$), we furthermore investigate the limit of the accuracy of our predictions applied to galaxies at fainter magnitude and at higher redshifts. Our final catalogue covers magnitudes $16\le{i}<21$, and redshifts $z<1.0$, and provides predicted probabilities to two galaxy types -- Ellipticals and Spirals (disk galaxies). Our CNN classifications reveal an accuracy of over 99\% for bright galaxies when comparing with the GZ1 classifications ($i<18$). For fainter galaxies, the visual classification carried out by three of the co-authors shows that the CNN classifier correctly categorises disky galaxies with rounder and blurred features, which humans often incorrectly visually classify as Ellipticals. As a part of the validation, we carry out one of the largest examination of non-parametric methods, including $\sim$100,000 galaxies with the same coverage of magnitude and redshift as the training set from our catalogue. We find that the Gini coefficient is the best single parameter discriminator between Ellipticals and Spirals for this data set., Comment: 23 pages, 15 figures. Accepted by MNRAS

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$\sigma$ 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., Comment: 37 pages, 23 figures, 4 tables. Added explanatory figure, table, covariance matrix equations, discussion of CIB impact. Matches the version published in ApJ

In this paper we present and validate the galaxy sample used for the analysis of the Baryon Acoustic Oscillation signal (BAO) in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high quality photometric redshift determination. The sample covers $\approx 4100$ square degrees to a depth of $i = 22.3 \ (AB)$ at $10\sigma$. It contains 7,031,993 galaxies in the redshift range from $z$= 0.6 to 1.1, with a mean effective redshift of 0.835. Photometric redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of $z_{\mathrm{bias}} \approx 0.01$ and a mean uncertainty, in units of $1+z$, of $\sigma_{68} \approx 0.03$. We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of $\lesssim 4\%$. We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics. We apply it to the DES Y3 BAO sample and calculate sample weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in the DES Y3 data. In the companion papers, Ferrero et al. (2021) and DES Collaboration (2021), we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale, respectively. The galaxy sample, masks and additional material will be released in the public DES data repository upon acceptance., Comment: Accepted for publication in MNRAS. 24 pages, 24 figures

We present angular diameter measurements obtained by measuring the position of Baryon Acoustic Oscillations (BAO) in an optimised sample of galaxies from the first three years of Dark Energy Survey data (DES Y3). The sample consists of 7 million galaxies distributed over a footprint of 4100 deg$^2$ with $0.6 < z_{\rm photo} < 1.1$ and a typical redshift uncertainty of $0.03(1+z)$. The sample selection is the same as in the BAO measurement with the first year of DES data, but the analysis presented here uses three times the area, extends to higher redshift and makes a number of improvements, including a fully analytical BAO template, the use of covariances from both theory and simulations, and an extensive pre-unblinding protocol. We used two different statistics: angular correlation function and power spectrum, and validate our pipeline with an ensemble of over 1500 realistic simulations. Both statistics yield compatible results. We combine the likelihoods derived from angular correlations and spherical harmonics to constrain the ratio of comoving angular diameter distance $D_M$ at the effective redshift of our sample to the sound horizon scale at the drag epoch. We obtain $D_M(z_{\rm eff}=0.835)/r_{\rm d} = 18.92 \pm 0.51$, which is consistent with, but smaller than, the Planck prediction assuming flat \lcdm, at the level of $2.3 \sigma$. The analysis was performed blind and is robust to changes in a number of analysis choices. It represents the most precise BAO distance measurement from imaging data to date, and is competitive with the latest transverse ones from spectroscopic samples at $z>0.75$. When combined with DES 3x2pt + SNIa, they lead to improvements in $H_0$ and $\Omega_m$ constraints by $\sim 20\%$, Comment: 24 pages, 10 figures, matches version accepted by PRD

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey (DES) Year 3 BAO sample over its full photometric redshift range $0.6

We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $0.03 \le z \le 0.60$. The precision on inferred SMHM parameters is improved by including the magnitude gap ($\rm m_{gap}$) between the BCG and fourth brightest cluster member (M14) as a third parameter in the SMHM relation. At fixed halo mass, accounting for $\rm m_{gap}$, through a stretch parameter, reduces the SMHM relation's intrinsic scatter. To explore this redshift range, we use clusters, BCGs, and cluster members identified using the Sloan Digital Sky Survey C4 and redMaPPer cluster catalogs and the Dark Energy Survey redMaPPer catalog. Through this joint analysis, we detect no systematic differences in BCG stellar mass, $\rm m_{gap}$, and cluster mass (inferred from richness) between the datsets. We utilize the Pareto function to quantify each parameter's evolution. We confirm prior findings of negative evolution in the SMHM relation's slope (3.5$\sigma$) and detect negative evolution in the stretch parameter (4.0$\sigma$) and positive evolution in the offset parameter (5.8$\sigma$). This observed evolution, combined with the absence of BCG growth, when stellar mass is measured within 50kpc, suggests that this evolution results from changes in the cluster's $\rm m_{gap}$. For this to occur, late-term growth must be in the intra-cluster light surrounding the BCG. We also compare the observed results to Illustris TNG 300-1 cosmological hydrodynamic simulations and find modest qualitative agreement. However, the simulations lack the evolutionary features detected in the real data., Comment: 21 pages, 12 Figures, 3 Tables. Submitted to ApJ on July 1

In [5] Soare and Stob prove that if $A$ is an r.e. set which isn't computable then there is a set of the form $A \oplus W^A_e$ which isn't of r.e. Turing degree. If we define a properly $n+1$-REA set to be an $n+1$-REA set which isn't Turing equivalent to any $n$-REA set this result shows that every properly 1-REA set can be extended to a properly 2-REA set. This result was extended in [1] by Cholak and Hinman who proved that every 2-REA set can be extended to a properly 3-REA set. This leads naturally to the hypothesis that every properly $n$-REA set can be extended to a properly $n+1$-REA set. In this paper, we show this hypothesis is false and that there is a properly $3$-REA set which can't be extended to a properly $4$-REA set.

We present the first cosmology results from large-scale structure in the Dark Energy Survey (DES) spanning 5000 deg$^2$. We perform an analysis combining three two-point correlation functions (3$\times$2pt): (i) cosmic shear using 100 million source galaxies, (ii) galaxy clustering, and (iii) the cross-correlation of source galaxy shear with lens galaxy positions. The analysis was designed to mitigate confirmation or observer bias; we describe specific changes made to the lens galaxy sample following unblinding of the results. We model the data within the flat $\Lambda$CDM and $w$CDM cosmological models. We find consistent cosmological results between the three two-point correlation functions; their combination yields clustering amplitude $S_8=0.776^{+0.017}_{-0.017}$ and matter density $\Omega_{\mathrm{m}} = 0.339^{+0.032}_{-0.031}$ in $\Lambda$CDM, mean with 68% confidence limits; $S_8=0.775^{+0.026}_{-0.024}$, $\Omega_{\mathrm{m}} = 0.352^{+0.035}_{-0.041}$, and dark energy equation-of-state parameter $w=-0.98^{+0.32}_{-0.20}$ in $w$CDM. This combination of DES data is consistent with the prediction of the model favored by the Planck 2018 cosmic microwave background (CMB) primary anisotropy data, which is quantified with a probability-to-exceed $p=0.13$ to $0.48$. When combining DES 3$\times$2pt data with available baryon acoustic oscillation, redshift-space distortion, and type Ia supernovae data, we find $p=0.34$. Combining all of these data sets with Planck CMB lensing yields joint parameter constraints of $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.306^{+0.004}_{-0.005}$, $h=0.680^{+0.004}_{-0.003}$, and $\sum m_{\nu}<0.13 \;\mathrm{eV\; (95\% \;CL)}$ in $\Lambda$CDM; $S_8 = 0.812^{+0.008}_{-0.008}$, $\Omega_{\mathrm{m}} = 0.302^{+0.006}_{-0.006}$, $h=0.687^{+0.006}_{-0.007}$, and $w=-1.031^{+0.030}_{-0.027}$ in $w$CDM. (abridged), Comment: See https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 3x2pt cosmology release. Matches version accepted in PRD

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., Comment: 29 pages, 17 figures, accepted by PRD. This version matches the published version

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., Comment: 33 pages, 18 figures, accepted by PRD

This work, together with its companion paper, Secco and Samuroff et al. (2021), presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the data spanning 4143 deg$^2$ on the sky, divided into four redshift bins, we produce the highest significance measurement of cosmic shear to date, with a signal-to-noise of 40. We conduct a blind analysis in the context of the $\Lambda$CDM model and find a 3% constraint of the clustering amplitude, $S_8\equiv \sigma_8 (\Omega_{\rm m}/0.3)^{0.5} = 0.759^{+0.025}_{-0.023}$. A $\Lambda$CDM-Optimized analysis, which safely includes smaller scale information, yields a 2% precision measurement of $S_8= 0.772^{+0.018}_{-0.017}$ that is consistent with the fiducial case. The two low-redshift measurements are statistically consistent with the Planck Cosmic Microwave Background result, however, both recovered $S_8$ values are lower than the high-redshift prediction by $2.3\sigma$ and $2.1\sigma$ ($p$-values of 0.02 and 0.05), respectively. The measurements are shown to be internally consistent across redshift bins, angular scales and correlation functions. The analysis is demonstrated to be robust to calibration systematics, with the $S_8$ posterior consistent when varying the choice of redshift calibration sample, the modeling of redshift uncertainty and methodology. Similarly, we find that the corrections included to account for the blending of galaxies shifts our best-fit $S_8$ by $0.5\sigma$ without incurring a substantial increase in uncertainty. We examine the limiting factors for the precision of the cosmological constraints and find observational systematics to be subdominant to the modeling of astrophysics. Specifically, we identify the uncertainties in modeling baryonic effects and intrinsic alignments as the limiting systematics., Comment: 42 pages, 19 figures

We present reconstructed convergence maps, \textit{mass maps}, from the Dark Energy Survey (DES) third year (Y3) weak gravitational lensing data set. The mass maps are weighted projections of the density field (primarily dark matter) in the foreground of the observed galaxies. We use four reconstruction methods, each is a \textit{maximum a posteriori} estimate with a different model for the prior probability of the map: Kaiser-Squires, null B-mode prior, Gaussian prior, and a sparsity prior. All methods are implemented on the celestial sphere to accommodate the large sky coverage of the DES Y3 data. We compare the methods using realistic $\Lambda$CDM simulations with mock data that are closely matched to the DES Y3 data. We quantify the performance of the methods at the map level and then apply the reconstruction methods to the DES Y3 data, performing tests for systematic error effects. The maps are compared with optical foreground cosmic-web structures and are used to evaluate the lensing signal from cosmic-void profiles. The recovered dark matter map covers the largest sky fraction of any galaxy weak lensing map to date., Comment: Final updates matching published MNRAS version

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., Comment: part of the DES year-3 combined 2-point function analysis; see https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release

Two of the most sensitive probes of the large scale structure of the universe are the clustering of galaxies and the tangential shear of background galaxy shapes produced by those foreground galaxies, so-called galaxy-galaxy lensing. Combining the measurements of these two two-point functions leads to cosmological constraints that are independent of the galaxy bias factor. The optimal choice of foreground, or lens, galaxies is governed by the joint, but conflicting requirements to obtain accurate redshift information and large statistics. We present cosmological results from the full 5000 sq. deg. of the Dark Energy Survey first three years of observations (Y3) combining those two-point functions, using for the first time a magnitude-limited lens sample (MagLim) of 11 million galaxies especially selected to optimize such combination, and 100 million background shapes. We consider two cosmological models, flat $\Lambda$CDM and $w$CDM. In $\Lambda$CDM we obtain for the matter density $\Omega_m = 0.320^{+0.041}_{-0.034}$ and for the clustering amplitude $S_8 = 0.778^{+0.037}_{-0.031}$, at 68% C.L. The latter is only 1$\sigma$ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In $w$CDM we find $\Omega_m = 0.32^{+0.044}_{-0.046}$, $S_8=0.777^{+0.049}_{-0.051}$, and dark energy equation of state $w=-1.031^{+0.218}_{-0.379}$. We find that including smaller scales while marginalizing over non-linear galaxy bias improves the constraining power in the $\Omega_m-S_8$ plane by $31$% and in the $\Omega_m-w$ plane by $41$% while yielding consistent cosmological parameters from those in the linear bias case. These results are combined with those from cosmic shear in a companion paper to present full DES-Y3 constraints from the three two-point functions (3x2pt)., Comment: 27 pages, 17 figures, matches the version accepted in PRD. See https://www.darkenergysurvey.org/des-year-3-cosmology-results-papers/ for the full DES Y3 cosmology release

We constrain cosmological and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework, and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy bias model and redMaGiC galaxy sample, we obtain constraints on the matter density to be $\Omega_{\rm m} = 0.325^{+0.033}_{-0.034}$. We also implement a non-linear galaxy bias model to probe smaller scales that includes parameterization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate the stability of the constraints to changes in the theoretical model. Using the redMaGiC galaxy sample as foreground lens galaxies, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to de-correlation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the $S_8$ parameter. We find that a scale-, redshift- and sky-area-independent phenomenological de-correlation parameter can effectively capture the impact of this systematic error. We trace the source of this de-correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the $S_8$ parameter are consistent with previous studies, and we find a small shift in the $\Omega_{\rm m}$ constraints compared to the fiducial redMaGiC sample. We constrain the mean host halo mass of the redMaGiC galaxies in this new sample to be approximately $1.6 \times 10^{13} M_{\odot}/h$., Comment: 34 pages, 23 figures, includes the updated results from a new redmagic sample giving S8 consistent with the cosmic shear results (and also prefers Xlens=1)