Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z_s= 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is ~10^(14.2) M⊙. We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro–Frenk–White profile—with a free parameter for the inner density slope—we find that the break radius is 270^(+48)_(-76) kpc, and that the inner density falls with radius to the power −0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as r^(-1). The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as r^(-0.8) and r^(-1.0)) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them

Early dark energy constraints with late-time expansion marginalization

Early dark energy (EDE) is an extension to the $\Lambda$CDM model, proposed to reduce the tension between the measurements of the Hubble constant $H_0$ from the cosmic microwave background (CMB) and from the local cosmic distance ladder. However, this model increases the $S_8$ tension between CMB and large scale structure measurements. Analyses of galaxy clustering and lensing correlation functions report a decreased preference for EDE and its effect on the Hubble tension. Smooth dark energy models affect growth of structure through the background expansion. In this work, we study the inclusion of a general, smooth late-time dark energy modification in combination with EDE and obtain constraints on EDE marginalized over the late-time expansion. We assess the impact on the $S_8$ and Hubble tensions. In order to generalize the late expansion, we use a late dark energy fluid model with a piecewise constant equation of state $w(z)$ over 3, 5 and 10 redshift bins in the window $z \in [0,3]$. We show that, when analyzing ACT and Planck CMB data combined with Pantheon supernovae, BAO from 6dF, SDSS and BOSS, Planck 2018 CMB lensing and Dark Energy Survey cosmic shear and clustering data, the inclusion of a general smooth dark energy modification at late times has no significant effect on $S_8$ and EDE parameter constraints. Using the aforementioned datasets, the EDE fraction constraint with late-time expansion marginalization is $f_\mathrm{EDE} = 0.067^{+0.019}_{-0.027}$ using 3 redshift bins, with similar results for 5 and 10 redshift bins. This work shows that in order to solve simultaneously the Hubble and $S_8$ tensions, one needs a mechanism for increasing the clustering of matter at late times different from a simple change in the background evolution of late dark energy. [Abridged]Comment: 22 pages, 9 figure

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.Comment: 32 pages + 60 pages of appendices. This is v1 of the DESC SRD, an internal collaboration document that is being made public and is not planned for submission to a journal. Data products for reproducing key plots are available at the LSST DESC Zenodo community, https://zenodo.org/communities/lsst-desc; see "Executive Summary and User Guide" for instructions on how to use and cite those product

Host galaxy identification for supernova surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey

Constraints on dark matter to dark radiation conversion in the late universe with DES-Y1 and external data

84siWe study a class of decaying dark matter models as a possible resolution to the observed discrepancies between early- and late-time probes of the universe. This class of models, dubbed DDM, characterizes the evolution of comoving dark matter density with two extra parameters. We investigate how DDM affects key cosmological observables such as the CMB temperature and matter power spectra. Combining 3x2pt data from Year 1 of the Dark Energy Survey,Planck-2018 CMB temperature and polarization data, Supernova (SN) Type Ia data from Pantheon, and BAO data from BOSS DR12, MGS and 6dFGS, we place new constraints on the amount of dark matter that has decayed and the rate with which it converts to dark radiation. The fraction of the decayed dark matter in units of the current amount of dark matter, $zeta$, is constrained at 68% confidence level to be <0.32 for DES-Y1 3x2pt data, <0.030 for CMB+SN+BAO data, and <0.037 for the combined dataset. The probability that the DES and CMB+SN+BAO datasets are concordant increases from 4% for the $Lambda$CDM model to 8% (less tension) for DDM. Moreover, tension in $S_8=sigma_8sqrt{Omega_m/0.3}$ between DES-Y1 3x2pt and CMB+SN+BAO is reduced from 2.3$sigma$ to 1.9$sigma$. We find no reduction in the Hubble tension when the combined data is compared to distance-ladder measurements in the DDM model. The maximum-posterior goodness-of-fit statistics of DDM and $Lambda$CDM are comparable, indicating no preference for the DDM cosmology over $Lambda$CDM....partially_openopenChen, Angela; Huterer, Dragan; Lee, Sujeong; Ferté, Agnès; Weaverdyck, Noah; Alonso Alves, Otavio; Leonard, C. Danielle; MacCrann, Niall; Raveri, Marco; Porredon, Anna; Di Valentino, Eleonora; Muir, Jessica; Lemos, Pablo; Liddle, Andrew; Blazek, Jonathan; Campos, Andresa; Cawthon, Ross; Choi, Ami; Dodelson, Scott; Elvin-Poole, Jack; Gruen, Daniel; Ross, Ashley; Secco, Lucas F.; Sevilla, Ignacio; Sheldon, Erin; Troxel, Michael A.; Zuntz, Joe; Abbott, Tim; Aguena, Michel; Allam, Sahar; Annis, James; Avila, Santiago; Bertin, Emmanuel; Bhargava, Sunayana; Bridle, Sarah; Brooks, David; Carnero Rosell, Aurelio; Carrasco Kind, Matias; Carretero, Jorge; Costanzi, Matteo; Crocce, Martin; da Costa, Luiz; Elidaiana da Silva Pereira, Maria; Davis, Tamara; Doel, Peter; Eifler, Tim; Ferrero, Ismael; Fosalba, Pablo; Frieman, Josh; Garcia-Bellido, Juan; Gaztanaga, Enrique; Gerdes, David; Gruendl, Robert; Gschwend, Julia; Gutierrez, Gaston; Hinton, Samuel; Hollowood, Devon L.; Honscheid, Klaus; Hoyle, Ben; James, David; Jarvis, Mike; Kuehn, Kyler; Lahav, Ofer; Maia, Marcio; Marshall, Jennifer; Menanteau, Felipe; Miquel, Ramon; Morgan, Robert; Palmese, Antonella; Paz-Chinchon, Francisco; Plazas Malagón, Andrés; Roodman, Aaron; Sanchez, Eusebio; Scarpine, Vic; Schubnell, Michael; Serrano, Santiago; Smith, Mathew; Suchyta, Eric; Tarle, Gregory; Thomas, Daniel; To, Chun-Hao; Varga, Tamas Norbert; Weller, Jochen; Wilkinson, ReeseChen, Angela; Huterer, Dragan; Lee, Sujeong; Ferté, Agnès; Weaverdyck, Noah; Alonso Alves, Otavio; Leonard, C. Danielle; Maccrann, Niall; Raveri, Marco; Porredon, Anna; Di Valentino, Eleonora; Muir, Jessica; Lemos, Pablo; Liddle, Andrew; Blazek, Jonathan; Campos, Andresa; Cawthon, Ross; Choi, Ami; Dodelson, Scott; Elvin-Poole, Jack; Gruen, Daniel; Ross, Ashley; Secco, Lucas F.; Sevilla, Ignacio; Sheldon, Erin; Troxel, Michael A.; Zuntz, Joe; Abbott, Tim; Aguena, Michel; Allam, Sahar; Annis, James; Avila, Santiago; Bertin, Emmanuel; Bhargava, Sunayana; Bridle, Sarah; Brooks, David; Carnero Rosell, Aurelio; Carrasco Kind, Matias; Carretero, Jorge; Costanzi, Matteo; Crocce, Martin; da Costa, Luiz; Elidaiana da Silva Pereira, Maria; Davis, Tamara; Doel, Peter; Eifler, Tim; Ferrero, Ismael; Fosalba, Pablo; Frieman, Josh; Garcia-Bellido, Juan; Gaztanaga, Enrique; Gerdes, David; Gruendl, Robert; Gschwend, Julia; Gutierrez, Gaston; Hinton, Samuel; Hollowood, Devon L.; Honscheid, Klaus; Hoyle, Ben; James, David; Jarvis, Mike; Kuehn, Kyler; Lahav, Ofer; Maia, Marcio; Marshall, Jennifer; Menanteau, Felipe; Miquel, Ramon; Morgan, Robert; Palmese, Antonella; Paz-Chinchon, Francisco; Plazas Malagón, Andrés; Roodman, Aaron; Sanchez, Eusebio; Scarpine, Vic; Schubnell, Michael; Serrano, Santiago; Smith, Mathew; Suchyta, Eric; Tarle, Gregory; Thomas, Daniel; Chun-Hao, To; Varga, Tamas Norbert; Weller, Jochen; Wilkinson, Rees

Discovery of a z = 0.65 post-starburst BAL quasar in the DES supernova fields

We present the discovery of a z = 0.65 low-ionization broad absorption line (LoBAL) quasar in a post-starburst galaxy in data from the Dark Energy Survey (DES) and spectroscopy from the Australian Dark Energy Survey (OzDES). LoBAL quasars are a minority of all BALs, and rarer still is that this object also exhibits broad Fe II (an FeLoBAL) and Balmer absorption. This is the first BAL quasar that has signatures of recently truncated star formation, which we estimate ended about 40 Myr ago. The characteristic signatures of an FeLoBAL require high column densities, which could be explained by the emergence of a young quasar from an early, dust-enshrouded phase, or by clouds compressed by a blast wave. The age of the starburst component is comparable to estimates of the lifetime of quasars, so if we assume the quasar activity is related to the truncation of the star formation, this object is better explained by the blast wave scenario

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ¼ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties δz ≲ 0.05 in the mean of the fiducial SKYNET photo-z nðzÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, Σcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nðzÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis

OzDES reverberation mapping program: lag recovery reliability for 6-yr C IV analysis

We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius-Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R-L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R-L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN