Eduardo Rozo

Interests

Research

Cosmology

Teaching

Physics, Astronomy

Courses

Scholarly Contributions

Journals/Publications

• Bonnett, C., Troxel, M. A., Hartley, W., Amara, A., Leistedt, B., Becker, M. R., Bernstein, G. M., Bridle, S., Bruderer, C., Busha, M. T., Kind, C. M., Childress, M. J., Castander, F. J., Chang, C., Crocce, M., Davis, T. M., Eifler, T. F., Frieman, J., Gangkofner, C., , Gaztanaga, E., et al. (2023). Redshift distributions of galaxies in the DES Science Verification shear catalogue and implications for weak lensing. Phys. Rev. D.
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  We present photometric redshift estimates for galaxies used in the weaklensing 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 analysed.For training, calibration, and testing of these methods, we construct acatalogue of spectroscopically confirmed galaxies matched against DES SV data.The performance of the methods is evaluated against the matched spectroscopiccatalogue, focusing on metrics relevant for weak lensing analyses, withadditional validation against COSMOS photo-zs. From the galaxies in the DES SVshear catalogue, which have mean redshift $0.72\pm0.01$ over the range$0.3
• Chang, C., Baxter, E., Jain, B., Sánchez, C., Adhikari, S., Varga, T. N., Fang, Y., Rozo, E., Rykoff, E. S., Kravtsov, A., Gruen, D., Huff, E. M., Jarvis, M., Kim, A. G., Prat, J., MacCrann, N., McClintock, T., Palmese, A., Rapetti, D., , Rollins, R. P., et al. (2023). The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles.
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  Splashback refers to the process of matter that is accreting onto a darkmatter halo reaching its first orbital apocenter and turning around in itsorbit. The cluster-centric radius at which this process occurs, r_sp, defines ahalo boundary that is connected to the dynamics of the cluster. A rapid declinein the halo profile is expected near r_sp. We measure the galaxy number densityand weak lensing mass profiles around redMaPPer galaxy clusters in the firstyear Dark Energy Survey (DES) data. For a cluster sample with mean M_200m mass~2.5 x 10^14 M_sun, we find strong evidence of a splashback-like steepening ofthe galaxy density profile and measure r_sp=1.13 +/- 0.07 Mpc/h, consistentwith earlier SDSS measurements of More et al. (2016) and Baxter et al. (2017).Moreover, our weak lensing measurement demonstrates for the first time theexistence of a splashback-like steepening of the matter profile of galaxyclusters. We measure r_sp=1.34 +/- 0.21 Mpc/h from the weak lensing data, ingood agreement with our galaxy density measurements. For different cluster andgalaxy samples, we find that consistent with LCDM simulations, r_sp scales withR_200m and does not evolve with redshift over the redshift range of 0.3--0.6.We also find that potential systematic effects associated with the redMaPPeralgorithm may impact the location of r_sp. We discuss progress needed tounderstand the systematic uncertainties and fully exploit forthcoming data fromDES and future surveys, emphasizing the importance of more realistic mockcatalogs and independent cluster samples.[Journal_ref: ]
• Chang, C., Vikram, V., Jain, B., Bacon, D., Amara, A., Becker, M. R., Bernstein, G., Bonnett, C., Bridle, S., Brout, D., Busha, M., Frieman, J., Gaztanaga, E., Hartley, W., Jarvis, M., Kacprzak, T., Kovacs, A., Lahav, O., Lin, H., , Melchior, P., et al. (2023). Wide-Field Lensing Mass Maps from DES Science Verification Data. Phys. Rev. Lett..
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  We present a mass map reconstructed from weak gravitational lensing shearmeasurements over 139 sq. deg from the Dark Energy Survey (DES) ScienceVerification data. The mass map probes both luminous and dark matter, thusproviding a tool for studying cosmology. We find good agreement between themass map and the distribution of massive galaxy clusters identified using ared-sequence cluster finder. Potential candidates for super-clusters and voidsare identified using these maps. We measure the cross-correlation between themass map and a magnitude-limited foreground galaxy sample and find a detectionat the 5-7 sigma level on a large range of scales. These measurements areconsistent with simulated galaxy catalogs based on LCDM N-body simulations,suggesting low systematics uncertainties in the map. We summarize our keyfindings in this letter; the detailed methodology and tests for systematics arepresented in a companion paper.[Journal_ref: Phys. Rev. Lett. 115, 051301 (2015)]
• Clampitt, J., Sánchez, C., Kwan, J., Krause, E., MacCrann, N., Park, Y., Troxel, M. A., Jain, B., Rozo, E., Rykoff, E. S., Wechsler, R. H., Blazek, J., Bonnett, C., Crocce, M., Fang, Y., Gaztanaga, E., Gruen, D., Jarvis, M., Miquel, R., , Prat, J., et al. (2023). Galaxy-Galaxy Lensing in the DES Science Verification Data.
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  We present galaxy-galaxy lensing results from 139 square degrees of DarkEnergy Survey (DES) Science Verification (SV) data. Our lens sample consists ofred galaxies, known as redMaGiC, which are specifically selected to have a lowphotometric redshift error and outlier rate. The lensing measurement has atotal signal-to-noise of 29 over scales $0.09 < R < 15$ Mpc/$h$, including alllenses over a wide redshift range $0.2 < z < 0.8$. Dividing the lenses intothree redshift bins for this constant moving number density sample, we find noevidence for evolution in the halo mass with redshift. We obtain consistentresults for the lensing measurement with two independent shear pipelines, ngmixand im3shape. We perform a number of null tests on the shear and photometricredshift catalogs and quantify resulting systematic uncertainties. Covariancesfrom jackknife subsamples of the data are validated with a suite of 50 mocksurveys. The results and systematics checks in this work provide a criticalinput for future cosmological and galaxy evolution studies with the DES dataand redMaGiC galaxy samples. We fit a Halo Occupation Distribution (HOD) model,and demonstrate that our data constrains the mean halo mass of the lensgalaxies, despite strong degeneracies between individual HOD parameters.[Journal_ref: ]
• Collaboration, T. D., Bechtol, K., Drlica-Wagner, A., Balbinot, E., Pieres, A., Simon, J. D., Yanny, B., Santiago, B., Wechsler, R. H., Frieman, J., Walker, A. R., Williams, P., Rozo, E., Rykoff, E. S., Queiroz, A., Luque, E., Benoit-Levy, A., Tucker, D., Sevilla, I., , Gruendl, R. A., et al. (2023). Eight New Milky Way Companions Discovered in First-Year Dark Energy Survey Data.
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  We report the discovery of eight new Milky Way companions in ~1,800 deg^2 ofoptical imaging data collected during the first year of the Dark Energy Survey(DES). Each system is identified as a statistically significant over-density ofindividual stars consistent with the expected isochrone and luminosity functionof an old and metal-poor stellar population. The objects span a wide range ofabsolute magnitudes (M_V from -2.2 mag to -7.4 mag), physical sizes (10 pc to170 pc), and heliocentric distances (30 kpc to 330 kpc). Based on the lowsurface brightnesses, large physical sizes, and/or large Galactocentricdistances of these objects, several are likely to be new ultra-faint satellitegalaxies of the Milky Way and/or Magellanic Clouds. We introduce alikelihood-based algorithm to search for and characterize stellarover-densities, as well as identify stars with high satellite membershipprobabilities. We also present completeness estimates for detecting ultra-faintgalaxies of varying luminosities, sizes, and heliocentric distances in thefirst-year DES data.[Journal_ref: ]
• Costanzi, M., Rozo, E., Rykoff, E. S., Farahi, A., Jeltema, T., Evrard, A. E., Mantz, A., Gruen, D., Mandelbaum, R., DeRose, J., McClintock, T., Varga, T. N., Zhang, Y., Weller, J., Wechsler, R. H., & Aguena, M. (2023). Modeling projection effects in optically-selected cluster catalogues.
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  The cosmological utility of galaxy cluster catalogues is primarily limited byour ability to calibrate the relation between halo mass and observable massproxies such as cluster richness, X-ray luminosity or the Sunyaev-Zeldovichsignal. Projection effects are a particularly pernicious systematic effect thatcan impact observable mass proxies; structure along the line of sight can bothbias and increase the scatter of the observable mass proxies used in clusterabundance studies. In this work, we develop an empirical method to characterizethe impact of projection effects on redMaPPer cluster catalogues. We usenumerical simulations to validate our method and illustrate its robustness. Wedemonstrate that modeling of projection effects is a necessary component forcluster abundance studies capable of reaching $\approx 5\%$ mass calibrationuncertainties (e.g. the Dark Energy Survey Year 1 sample). Specifically,ignoring the impact of projection effects in the observable--mass relation ---i.e. marginalizing over a log-normal model only --- biases the posterior of thecluster normalization condition $S_8 \equiv \sigma_8 (\Omega_{\rmm}/0.3)^{1/2}$ by $\Delta S_8 =0.05$, more than twice the uncertainty in theposterior for such an analysis.[Journal_ref: ]
• Farahi, A., Chen, X., Evrard, A. E., Hollowood, D. L., Wilkinson, R., Bhargava, S., Giles, P., Romer, A. K., Jeltema, T., Hilton, M., Bermeo, A., Mayers, J., Cervantes, V. C., Rozo, E., Rykoff, E. S., Collins, C., Costanzi, M., Everett, S., Liddle, A. R., , Mann, R. G., et al. (2023). Mass Variance from Archival X-ray Properties of Dark Energy Survey Year-1 Galaxy Clusters.
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  Using archival X-ray observations and a log-normal population model, weestimate constraints on the intrinsic scatter in halo mass at fixed opticalrichness for a galaxy cluster sample identified in Dark Energy Survey Year-One(DES-Y1) data with the redMaPPer algorithm. We examine the scaling behavior ofX-ray temperatures, $T_X$, with optical richness, $\lambda_{RM}$, for clustersin the redshift range $0.2 130$. Regression analysis on the two samplesproduces consistent posterior scaling parameters, from which we derive acombined constraint on the residual scatter, $\sigma_{\ln Tx | \lambda} = 0.275\pm 0.019$. Joined with constraints for $T_X$ scaling with halo mass from theWeighing the Giants program and richness--temperature covariance estimates fromthe LoCuSS sample, we derive the richness-conditioned scatter in mass,$\sigma_{\ln M | \lambda} = 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rmsys})}$, at an optical richness of approximately 70. Uncertainties in externalparameters, particularly the slope and variance of the $T_X$--mass relation andthe covariance of $T_X$ and $\lambda_{RM}$ at fixed mass, dominate thesystematic error. The $95\%$ confidence region from joint sample analysis isrelatively broad, $\sigma_{\ln M | \lambda} \in [0.14, \, 0.55]$, or a factorten in variance.[Journal_ref: ]
• Geach, J. E., More, A., Verma, A., Marshall, P. J., Jackson, N., Belles, P. -., Beswick, R., Baeten, E., Chavez, M., Cornen, C., Cox, B. E., Erben, T., Erickson, N. J., Garrington, S., Harrison, P. A., Harrington, K., Hughes, D. H., Ivison, R. J., Jordan, C., , Lin, Y. -., et al. (2023). The Red Radio Ring: a gravitationally lensed hyperluminous infrared radio galaxy at z=2.553 discovered through citizen science.
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  We report the discovery of a gravitationally lensed hyperluminous infraredgalaxy (L_IR~10^13 L_sun) with strong radio emission (L_1.4GHz~10^25 W/Hz) atz=2.553. The source was identified in the citizen science project SpaceWarpsthrough the visual inspection of tens of thousands of iJKs colour compositeimages of Luminous Red Galaxies (LRGs), groups and clusters of galaxies andquasars. Appearing as a partial Einstein ring (r_e~3") around an LRG at z=0.2,the galaxy is extremely bright in the sub-millimetre for a cosmological source,with the thermal dust emission approaching 1 Jy at peak. The redshift of thelensed galaxy is determined through the detection of the CO(3-2) molecularemission line with the Large Millimetre Telescope's Redshift Search Receiverand through [OIII] and H-alpha line detections in the near-infrared fromSubaru/IRCS. We have resolved the radio emission with high resolution (300-400mas) eMERLIN L-band and JVLA C-band imaging. These observations are used incombination with the near-infrared imaging to construct a lens model, whichindicates a lensing magnification of ~10x. The source reconstruction appears tosupport a radio morphology comprised of a compact (
• Gruen, D., Friedrich, O., Amara, A., Bacon, D., Bonnett, C., Hartley, W., Jain, B., Jarvis, M., Kacprzak, T., Krause, E., Mana, A., Rozo, E., Rykoff, E. S., Seitz, S., Sheldon, E., Troxel, M. A., Vikram, V., Abbott, T., Abdalla, F. B., , Allam, S., et al. (2023). Weak lensing by galaxy troughs in DES Science Verification data.
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  We measure the weak lensing shear around galaxy troughs, i.e. the radialalignment of background galaxies relative to underdensities in projections ofthe foreground galaxy field over a wide range of redshift in ScienceVerification data from the Dark Energy Survey. Our detection of the shearsignal is highly significant (10 to 15$\sigma$ for the smallest angular scales)for troughs with the redshift range z in [0.2,0.5] of the projected galaxyfield and angular diameters of 10 arcmin...1{\deg}. These measurements probethe connection between the galaxy, matter density, and convergence fields. Byassuming galaxies are biased tracers of the matter density with Poissoniannoise, we find agreement of our measurements with predictions in a fiducialLambda cold dark matter model. The prediction for the lensing signal on largetrough scales is virtually independent of the details of the underlying modelfor the connection of galaxies and matter. Our comparison of the shear aroundtroughs with that around cylinders with large galaxy counts is consistent witha symmetry between galaxy and matter over- and underdensities. In addition, wemeasure the two-point angular correlation of troughs with galaxies which, incontrast to the lensing signal, is sensitive to galaxy bias on all scales. Thelensing signal of troughs and their clustering with galaxies is therefore apromising probe of the statistical properties of matter underdensities andtheir connection to the galaxy field.[Journal_ref: ]
• Gruen, D., Zhang, Y., Palmese, A., Yanny, B., Busti, V., Hoyle, B., Melchior, P., Miller, C. J., Rozo, E., Rykoff, E. S., Varga, T. N., Abdalla, F. B., Allam, S., Annis, J., Avila, S., Brooks, D., Burke, D. L., Rosell, C. A., Kind, C. M., , Carretero, J., et al. (2023). Dark Energy Survey Year 1 Results: The effect of intracluster light on photometric redshifts for weak gravitational lensing.
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  We study the effect of diffuse intracluster light on the critical surfacemass density estimated from photometric redshifts of lensing source galaxies,and the resulting bias in a weak lensing measurement of galaxy cluster mass.Under conservative assumptions, we find the bias to be negligible for imagingsurveys like the Dark Energy Survey (DES) with a recommended scale cut of >=200kpc distance from cluster centers. For significantly deeper source catalogsfrom present and future surveys like the Large Synoptic Survey Telescope (LSST)program, more conservative scale and source magnitude cuts or a correction ofthe effect may be necessary to achieve per-cent level lensing measurementaccuracy, especially at the massive end of the cluster population.[Journal_ref: ]
• Hennig, C., Mohr, J. J., Zenteno, A., Desai, S., Dietrich, J. P., Bocquet, S., Strazzullo, V., Saro, A., Abbott, T. M., Abdalla, F. B., Bayliss, M., Benoit-Levy, A., Bernstein, R. A., Bertin, E., Brooks, D., Capasso, R., Capozzi, D., Carnero, A., Kind, C. M., , Carretero, J., et al. (2023). Galaxy Populations in Massive Galaxy Clusters to z=1.1: Color Distribution, Concentration, Halo Occupation Number and Red Sequence Fraction.
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  We study the galaxy populations in 74 Sunyaev Zeldovich Effect (SZE) selectedclusters from the South Pole Telescope (SPT) survey that have been imaged inthe science verification phase of the Dark Energy Survey (DES). The sampleextends up to $z\sim 1.1$ with $4 \times 10^{14} M_{\odot}\le M_{200}\le3\times 10^{15} M_{\odot}$. Using the band containing the 4000~\AA\ break andits redward neighbor, we study the color-magnitude distributions of clustergalaxies to $\sim m_*+2$, finding: (1) the intrinsic rest frame $g-r$ colorwidth of the red sequence (RS) population is $\sim$0.03 out to $z\sim0.85$ witha preference for an increase to $\sim0.07$ at $z=1$ and (2) the prominence ofthe RS declines beyond $z\sim0.6$. The spatial distribution of cluster galaxiesis well described by the NFW profile out to $4R_{200}$ with a concentration of$c_{\mathrm{g}} = 3.59^{+0.20}_{-0.18}$, $5.37^{+0.27}_{-0.24}$ and$1.38^{+0.21}_{-0.19}$ for the full, the RS and the blue non-RS populations,respectively, but with $\sim40$\% to 55\% cluster to cluster variation and nostatistically significant redshift or mass trends. The number of galaxieswithin the virial region $N_{200}$ exhibits a mass trend indicating that thenumber of galaxies per unit total mass is lower in the most massive clusters,and shows no significant redshift trend. The red sequence (RS) fraction within$R_{200}$ is $(68\pm3)$\% at $z=0.46$, varies from $\sim$55\% at $z=1$ to$\sim$80\% at $z=0.1$, and exhibits intrinsic variation among clusters of$\sim14$\%. We discuss a model that suggests the observed redshift trend in RSfraction favors a transformation timescale for infalling field galaxies tobecome RS galaxies of 2 to 3~Gyr.[Journal_ref: ]
• Kirk, D., Omori, Y., Benoit-Lévy, A., Cawthon, R., Chang, C., Larsen, P., Amara, A., Bacon, D., Crawford, T. M., Dodelson, S., Fosalba, P., Giannantonio, T., Holder, G., Jain, B., Kacprzak, T., Lahav, O., MacCrann, N., Nicola, A., Refregier, A., , Sheldon, E., et al. (2023). Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing.
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  We measure the cross-correlation between weak lensing of galaxy images and ofthe cosmic microwave background (CMB). The effects of gravitational lensing ondifferent sources will be correlated if the lensing is caused by the same massfluctuations. We use galaxy shape measurements from 139 deg$^{2}$ of the DarkEnergy Survey (DES) Science Verification data and overlapping CMB lensing fromthe South Pole Telescope (SPT) and Planck. The DES source galaxies have amedian redshift of $z_{\rm med} {\sim} 0.7$, while the CMB lensing kernel isbroad and peaks at $z{\sim}2$. The resulting cross-correlation is maximallysensitive to mass fluctuations at $z{\sim}0.44$. Assuming the Planck 2015best-fit cosmology, the amplitude of the DES$\times$SPT cross-power is found tobe $A = 0.88 \pm 0.30$ and that from DES$\times$Planck to be $A = 0.86 \pm0.39$, where $A=1$ corresponds to the theoretical prediction. These areconsistent with the expected signal and correspond to significances of $2.9\sigma$ and $2.2 \sigma$ respectively. We demonstrate that our results arerobust to a number of important systematic effects including the shearmeasurement method, estimator choice, photometric redshift uncertainty and CMBlensing systematics. Significant intrinsic alignment of galaxy shapes wouldincrease the cross-correlation signal inferred from the data; we calculate avalue of $A = 1.08 \pm 0.36$ for DES$\times$SPT when we correct theobservations with a simple IA model. With three measurements of thiscross-correlation now existing in the literature, there is not yet reliableevidence for any deviation from the expected LCDM level of cross-correlation,given the size of the statistical uncertainties and the significant impact ofsystematic errors, particularly IAs. We provide forecasts for the expectedsignal-to-noise of the combination of the five-year DES survey and SPT-3G.[Journal_ref: ]
• Leistedt, B., Peiris, H. V., Elsner, F., Benoit-Lévy, A., Amara, A., Bauer, A. H., Becker, M. R., Bonnett, C., Bruderer, C., Busha, M. T., Kind, C. M., Chang, C., Crocce, M., Costa, D. L., Gaztanaga, E., Huff, E. M., Lahav, O., Palmese, A., Percival, W. J., , Refregier, A., et al. (2023). Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data.
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  Spatially-varying depth and characteristics of observing conditions, such asseeing, airmass, or sky background, are major sources of systematicuncertainties in modern galaxy survey analyses, in particular in deepmulti-epoch surveys. We present a framework to extract and project thesesources of systematics onto the sky, and apply it to the Dark Energy Survey(DES) to map the observing conditions of the Science Verification (SV) data.The resulting distributions and maps of sources of systematics are used inseveral analyses of DES SV to perform detailed null tests with the data, andalso to incorporate systematics in survey simulations. We illustrate thecomplementarity of these two approaches by comparing the SV data with theBCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DESSV images. We analyse the BCC-UFig simulation to construct galaxy samplesmimicking those used in SV galaxy clustering studies. We show that thespatially-varying survey depth imprinted in the observed galaxy densities andthe redshift distributions of the SV data are successfully reproduced by thesimulation and well-captured by the maps of observing conditions. The combineduse of the maps, the SV data and the BCC-UFig simulation allows us to quantifythe impact of spatial systematics on $N(z)$, the redshift distributionsinferred using photometric redshifts. We conclude that spatial systematics inthe SV data are mainly due to seeing fluctuations and are under control incurrent clustering and weak lensing analyses. The framework presented here isrelevant to all multi-epoch surveys, and will be essential for exploitingfuture surveys such as the Large Synoptic Survey Telescope (LSST), which willrequire detailed null-tests and realistic end-to-end image simulations tocorrectly interpret the deep, high-cadence observations of the sky.[Journal_ref: ]
• Old, L., Wojtak, R., Mamon, G. A., Skibba, R. A., Pearce, F. R., Croton, D., Bamford, S., Behroozi, P., Carvalho, D. R., Muñoz-Cuartas, J. C., Gifford, D., Gray, M. E., der Linden, V. A., Merrifield, M. R., Muldrew, S. I., Müller, V., Pearson, R. J., Ponman, T. J., Rozo, E., , Rykoff, E., et al. (2023). Galaxy Cluster Mass Reconstruction Project: II. Quantifying scatter and bias using contrasting mock catalogues.
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  This article is the second in a series in which we perform an extensivecomparison of various galaxy-based cluster mass estimation techniques thatutilise the positions, velocities and colours of galaxies. Our aim is toquantify the scatter, systematic bias and completeness of cluster massesderived from a diverse set of 25 galaxy-based methods using two contrastingmock galaxy catalogues based on a sophisticated halo occupation model and asemi-analytic model. Analysing 968 clusters, we find a wide range in the RMSerrors in log M200c delivered by the different methods (0.18 to 1.08 dex, i.e.,a factor of ~1.5 to 12), with abundance matching and richness methods providingthe best results, irrespective of the input model assumptions. In addition,certain methods produce a significant number of catastrophic cases where themass is under- or over-estimated by a factor greater than 10. Given the steeplyfalling high-mass end of the cluster mass function, we recommend that richnessor abundance matching-based methods are used in conjunction with these methodsas a sanity check for studies selecting high mass clusters. We see a strongercorrelation of the recovered to input number of galaxies for both catalogues incomparison with the group/cluster mass, however, this does not guarantee thatthe correct member galaxies are being selected. We do not observe significantlyhigher scatter for either mock galaxy catalogues. Our results have implicationsfor cosmological analyses that utilise the masses, richnesses, or abundances ofclusters, which have different uncertainties when different methods are used.[Journal_ref: ]
• Palmese, A., Annis, J., Burgad, J., Farahi, A., Soares-Santos, M., Welch, B., Pereira, D. S., Lin, H., Bhargava, S., Hollowood, D. L., Wilkinson, R., Giles, P., Jeltema, T., Romer, A. K., Evrard, A. E., Hilton, M., Cervantes, V. C., Bermeo, A., Mayers, J., , DeRose, J., et al. (2023). Stellar mass as a galaxy cluster mass proxy: application to the Dark Energy Survey redMaPPer clusters.
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  We introduce a galaxy cluster mass observable, $\mu_\star$, based on thestellar masses of cluster members, and we present results for the Dark EnergySurvey (DES) Year 1 observations. Stellar masses are computed using a BayesianModel Averaging method, and are validated for DES data using simulations andCOSMOS data. We show that $\mu_\star$ works as a promising mass proxy bycomparing our predictions to X-ray measurements. We measure the X-raytemperature-$\mu_\star$ relation for a total of 150 clusters matched betweenthe wide-field DES Year 1 redMaPPer catalogue, and Chandra and XMM archivalobservations, spanning the redshift range $0.1
• Palmese, A., Lahav, O., Banerji, M., Gruen, D., Jouvel, S., Melchior, P., Aleksić, J., Annis, J., Diehl, H. T., Jeltema, T., Romer, K., Rozo, E., Rykoff, E. S., Seitz, S., Suchyta, E., Zhang, Y., Abbott, T. M., Abdalla, F. B., Allam, S., , Benoit-Lévy, A., et al. (2023). Comparing Dark Energy Survey and HST-CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter.
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  We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431observed with the Dark Energy Survey (DES) during the Science Verificationperiod. We compare the stellar mass results from DES (five filters) with thosefrom the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17filters). When the cluster spectroscopic redshift is assumed, we show thatstellar masses from DES can be estimated within 25% of CLASH values. We computethe stellar mass contribution coming from red and blue galaxies, and study therelation between stellar mass and the underlying dark matter using weak lensingstudies with DES and CLASH. An analysis of the radial profiles of the DES totaland stellar mass yields a stellar-to-total fraction of f*=(6.8+-1.7)x10^-3within a radius of r_200c~2 Mpc. Our analysis also includes a comparison ofphotometric redshifts and star/galaxy separation efficiency for both data sets.We conclude that space-based small field imaging can be used to calibrate thegalaxy properties in DES for the much wider field of view. The techniquedeveloped to derive the stellar mass fraction in galaxy clusters can be appliedto the ~100 000 clusters that will be observed within this survey and yieldimportant information about galaxy evolution.[Journal_ref: ]
• Pierre, M., Pacaud, F., Adami, C., Alis, S., Altieri, B., Baran, B., Benoist, C., Birkinshaw, M., Bongiorno, A., Bremer, M. N., Brusa, M., Butler, A., Ciliegi, P., Chiappetti, L., Clerc, N., Corasaniti, P. S., Coupon, J., Breuck, D. C., Democles, J., , Desai, S., et al. (2023). The XXL Survey: I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme.
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  We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms todate and involving an international consortium of roughly 100 members. The XXLSurvey covers two extragalactic areas of 25 deg2 each at a point-sourcesensitivity of ~ 5E-15 erg/sec/cm2 in the [0.5-2] keV band (completenesslimit). The survey's main goals are to provide constraints on the dark energyequation of state from the space-time distribution of clusters of galaxies andto serve as a pathfinder for future, wide-area X-ray missions. We reviewscience objectives, including cluster studies, AGN evolution, and large-scalestructure, that are being conducted with the support of approximately 30follow-up programmes. We describe the 542 XMM observations along with theassociated multi-lambda and numerical simulation programmes. We give a detailedaccount of the X-ray processing steps and describe innovative tools beingdeveloped for the cosmological analysis. The paper provides a thoroughevaluation of the X-ray data, including quality controls, photon statistics,exposure and background maps, and sky coverage. Source catalogue constructionand multi-lambda associations are briefly described. This material will be thebasis for the calculation of the cluster and AGN selection functions, criticalelements of the cosmological and science analyses. The XXL multi-lambda dataset will have a unique lasting legacy value for cosmological and extragalacticstudies and will serve as a calibration resource for future dark energy studieswith clusters and other X-ray selected sources. With the present article, werelease the XMM XXL photon and smoothed images along with the correspondingexposure maps. The XMM XXL observation list (Table B.1) is available inelectronic form at the CDS. The present paper is the first in a seriesreporting results of the XXL-XMM survey.[Journal_ref: ]
• Rozo, E., Rykoff, E. S., Abate, A., Bonnett, C., Crocce, M., Davis, C., Hoyle, B., Leistedt, B., Peiris, H. V., Wechsler, R. H., Abbott, T., Abdalla, F. B., Banerji, M., Bauer, A. H., Benoit-Lévy, A., Bernstein, G. M., Bertin, E., Brooks, D., Buckley-Geer, E., , Burke, D. L., et al. (2023). redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data.
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  We introduce redMaGiC, an automated algorithm for selecting Luminous RedGalaxies (LRGs). The algorithm was specifically developed to minimizephotometric redshift uncertainties in photometric large-scale structurestudies. redMaGiC achieves this by self-training the color-cuts necessary toproduce a luminosity-thresholded LRG sample of constant comoving density. Wedemonstrate that redMaGiC photozs are very nearly as accurate as the bestmachine-learning based methods, yet they require minimal spectroscopictraining, do not suffer from extrapolation biases, and are very nearlyGaussian. We apply our algorithm to Dark Energy Survey (DES) ScienceVerification (SV) data to produce a redMaGiC catalog sampling the redshiftrange $z\in[0.2,0.8]$. Our fiducial sample has a comoving space density of$10^{-3}\ (h^{-1} Mpc)^{-3}$, and a median photoz bias ($z_{spec}-z_{photo}$)and scatter $(\sigma_z/(1+z))$ of 0.005 and 0.017 respectively. Thecorresponding $5\sigma$ outlier fraction is 1.4%. We also test our algorithmwith Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8) and Stripe 82 data,and discuss how spectroscopic training can be used to control photoz biases atthe 0.1% level.[Journal_ref: ]
• Sánchez, C., Clampitt, J., Kovacs, A., Jain, B., García-Bellido, J., Nadathur, S., Gruen, D., Hamaus, N., Huterer, D., Vielzeuf, P., Amara, A., Bonnett, C., DeRose, J., Hartley, W. G., Jarvis, M., Lahav, O., Miquel, R., Rozo, E., Rykoff, E. S., , Sheldon, E., et al. (2023). Cosmic Voids and Void Lensing in the Dark Energy Survey Science Verification Data.
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  Galaxies and their dark matter halos populate a complicated filamentarynetwork around large, nearly empty regions known as cosmic voids. Cosmic voidsare usually identified in spectroscopic galaxy surveys, where 3D informationabout the large-scale structure of the Universe is available. Although anincreasing amount of photometric data is being produced, its potential for voidstudies is limited since photometric redshifts induce line-of-sight positionerrors of $\sim50$ Mpc/$h$ or more that can render many voids undetectable. Inthis paper we present a new void finder designed for photometric surveys,validate it using simulations, and apply it to the high-quality photo-$z$redMaGiC galaxy sample of the Dark Energy Survey Science Verification (DES-SV)data. The algorithm works by projecting galaxies into 2D slices and findingvoids in the smoothed 2D galaxy density field of the slice. Fixing theline-of-sight size of the slices to be at least twice the photo-$z$ scatter,the number of voids found in these projected slices of simulated spectroscopicand photometric galaxy catalogs is within 20% for all transverse void sizes,and indistinguishable for the largest voids of radius $\sim 70$ Mpc/$h$ andlarger. The positions, radii, and projected galaxy profiles of photometricvoids also accurately match the spectroscopic void sample. Applying thealgorithm to the DES-SV data in the redshift range $0.2
• Varga, T. N., Gruen, D., Seitz, S., MacCrann, N., Sheldon, E., Hartley, W. G., Amon, A., Choi, A., Palmese, A., Zhang, Y., Becker, M. R., McCullough, J., Rozo, E., Rykoff, E. S., To, C., Grandis, S., Bernstein, G. M., Dodelson, S., Eckert, K., , Everett, S., et al. (2023). Synthetic Galaxy Clusters and Observations Based on Dark Energy Survey Year 3 Data.
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  We develop a novel data-driven method for generating synthetic opticalobservations of galaxy clusters. In cluster weak lensing, the interplay betweenanalysis choices and systematic effects related to source galaxy selection,shape measurement and photometric redshift estimation can be best characterizedin end-to-end tests going from mock observations to recovered cluster masses.To create such test scenarios, we measure and model the photometric propertiesof galaxy clusters and their sky environments from the Dark Energy Survey Year3 (DES Y3) data in two bins of cluster richness $\lambda\in[30;\,45)$,$\lambda\in[45;\,60)$ and three bins in cluster redshift ($z\in[0.3;\,0.35)$,$z\in[0.45;\,0.5)$ and $z\in[0.6;\,0.65)$. Using deep-field imaging data weextrapolate galaxy populations beyond the limiting magnitude of DES Y3 andcalculate the properties of cluster member galaxies via statistical backgroundsubtraction. We construct mock galaxy clusters as random draws from adistribution function, and render mock clusters and line-of-sight catalogs intosynthetic images in the same format as actual survey observations. Syntheticgalaxy clusters are generated from real observational data, and thus areindependent from the assumptions inherent to cosmological simulations. Therecipe can be straightforwardly modified to incorporate extra information, andcorrect for survey incompleteness. New realizations of synthetic clusters canbe created at minimal cost, which will allow future analyses to generate thelarge number of images needed to characterize systematic uncertainties incluster mass measurements.[Journal_ref: ]
• Vikram, V., Chang, C., Jain, B., Bacon, D., Amara, A., Becker, M. R., Bernstein, G., Bonnett, C., Bridle, S., Brout, D., Busha, M., Frieman, J., Gaztanaga, E., Hartley, W., Jarvis, M., Kacprzak, T., Kovacs, A., Lahav, O., Leistedt, B., , Lin, H., et al. (2023). Wide-Field Lensing Mass Maps from DES Science Verification Data: Methodology and Detailed Analysis.
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  Weak gravitational lensing allows one to reconstruct the spatial distributionof the projected mass density across the sky. These "mass maps" provide apowerful tool for studying cosmology as they probe both luminous and darkmatter. In this paper, we present a weak lensing mass map reconstructed fromshear measurements in a 139 sq. deg area from the Dark Energy Survey (DES)Science Verification (SV) data. We compare the distribution of mass with thatof the foreground distribution of galaxies and clusters. The overdensities inthe reconstructed map correlate well with the distribution of opticallydetected clusters. We demonstrate that candidate superclusters and voids alongthe line of sight can be identified, exploiting the tight scatter of thecluster photometric redshifts. We cross-correlate the mass map with aforeground magnitude-limited galaxy sample from the same data. Our measurementgives results consistent with mock catalogs from N-body simulations thatinclude the primary sources of statistical uncertainties in the galaxy,lensing, and photo-z catalogs. The statistical significance of thecross-correlation is at the 6.8-sigma level with 20 arcminute smoothing. Amajor goal of this study is to investigate systematic effects arising from avariety of sources, including PSF and photo-z uncertainties. We make mapsderived from twenty variables that may characterize systematics and find theprincipal components. We find that the contribution of systematics to thelensing mass maps is generally within measurement uncertainties. In this work,we analyze less than 3% of the final area that will be mapped by the DES; thetools and analysis techniques developed in this paper can be applied toforthcoming larger datasets from the survey.[Journal_ref: ]
• Yuan, F., Lidman, C., Davis, T. M., Childress, M., Abdalla, F. B., Banerji, M., Buckley-Geer, E., Rosell, C. A., Carollo, D., Castander, F. J., D'Andrea, C. B., Diehl, H. T., Cunha, C. E., Foley, R. J., Frieman, J., Glazebrook, K., Gschwend, J., Hinton, S., Jouvel, S., , Kessler, R., et al. (2023). OzDES multi-fibre spectroscopy for the Dark Energy Survey: first-year operation and results.
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  OzDES is a five-year, 100-night, spectroscopic survey on the Anglo-AustralianTelescope, whose primary aim is to measure redshifts of approximately 2,500Type Ia supernovae host galaxies over the redshift range 0.1 < z < 1.2, andderive reverberation-mapped black hole masses for approximately 500 activegalactic nuclei and quasars over 0.3 < z < 4.5. This treasure trove of dataforms a major part of the spectroscopic follow-up for the Dark Energy Surveyfor which we are also targeting cluster galaxies, radio galaxies, stronglenses, and unidentified transients, as well as measuring luminous red galaxiesand emission line galaxies to help calibrate photometric redshifts. Here we present an overview of the OzDES program and our first-year results.Between Dec 2012 and Dec 2013, we observed over 10,000 objects and measuredmore than 6,000 redshifts. Our strategy of retargeting faint objects acrossmany observing runs has allowed us to measure redshifts for galaxies as faintas m_r=25 mag. We outline our target selection and observing strategy, quantifythe redshift success rate for different types of targets, and discuss theimplications for our main science goals. Finally, we highlight a fewinteresting objects as examples of the fortuitous yet not totally unexpecteddiscoveries that can come from such a large spectroscopic survey.[Journal_ref: ]
• Zhou, C., Tong, A., Troxel, M. A., Blazek, J., Lin, C., Bacon, D., Bleem, L., Rosell, C. A., Chang, C., Costanzi, M., DeRose, J., Dietrich, J. P., Drlica-Wagner, A., Gruen, D., Gruendl, R. A., Hoyle, B., Jarvis, M., MacCrann, N., Mawdsley, B., , McClintock, T., et al. (2023). The Intrinsic Alignment of Red Galaxies in DES Y1 redMaPPer Galaxy Clusters.
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  Clusters of galaxies are sensitive to the most nonlinear peaks in the cosmicdensity field. The weak gravitational lensing of background galaxies byclusters can allow us to infer their masses. However, galaxies associated withthe local environment of the cluster can also be intrinsically aligned due tothe local tidal gradient, contaminating any cosmology derived from the lensingsignal. We measure this intrinsic alignment in Dark Energy Survey (DES) Year 1redMaPPer clusters. We find evidence of a non-zero mean radial alignment ofgalaxies within clusters between redshift 0.1-0.7. We find a significantsystematic in the measured ellipticities of cluster satellite galaxies that weattribute to the central galaxy flux and other intracluster light. We attemptto correct this signal, and fit a simple model for intrinsic alignmentamplitude ($A_{\textrm{IA}}$) to the measurement, finding$A_{\textrm{IA}}=0.15\pm 0.04$, when excluding data near the edge of thecluster. We find a significantly stronger alignment of the central galaxy withthe cluster dark matter halo at low redshift and with higher richness andcentral galaxy absolute magnitude (proxies for cluster mass). This is animportant demonstration of the ability of large photometric data sets like DESto provide direct constraints on the intrinsic alignment of galaxies withinclusters. These measurements can inform improvements to small-scale modelingand simulation of the intrinsic alignment of galaxies to help improve theseparation of the intrinsic alignment signal in weak lensing studies.[Journal_ref: ]
• Chen, R., Scolnic, D., Rozo, E., Rykoff, E. S., Popovic, B., Kessler, R., Vincenzi, M., Davis, T. M., Armstrong, P., Brout, D., Galbany, L., Kelsey, L., Lidman, C., Möller, A., Rose, B., Sako, M., Sullivan, M., Taylor, G., Wiseman, P., , Asorey, J., et al. (2022). Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC galaxies. ApJ.
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  Current and future cosmological analyses with Type Ia Supernovae (SNe Ia)face three critical challenges: i) measuring redshifts from the supernova orits host galaxy; ii) classifying SNe without spectra; and iii) accounting forcorrelations between the properties of SNe Ia and their host galaxies. Wepresent here a novel approach that addresses each challenge. In the context ofthe Dark Energy Survey (DES), we analyze a SNIa sample with host galaxies inthe redMaGiC galaxy catalog, a selection of Luminous Red Galaxies. Photo-$z$estimates for these galaxies are expected to be accurate to $\sigma_{\Deltaz/(1+z)}\sim0.02$. The DES-5YR photometrically classified SNIa sample containsapproximately 1600 SNe and 125 of these SNe are in redMaGiC galaxies. Wedemonstrate that redMaGiC galaxies almost exclusively host SNe Ia, reducingconcerns with classification uncertainties. With this subsample, we findsimilar Hubble scatter (to within $\sim0.01$ mag) using photometric redshiftsin place of spectroscopic redshifts. With detailed simulations, we show thebias due to using photo-$z$s from redMaGiC host galaxies on the measurement ofthe dark energy equation-of-state $w$ is up to $\Delta w \sim 0.01-0.02$. Withreal data, we measure a difference in $w$ when using redMaGiC photometricredshifts versus spectroscopic redshifts of $\Delta w = 0.005$. Finally, wediscuss how SNe in redMaGiC galaxies appear to be a more standardizablepopulation due to a weaker relation between color and luminosity ($\beta$)compared to the DES-3YR population by $\sim5\sigma$; this finding is consistentwith predictions that redMaGiC galaxies exhibit lower reddening ratios($\textrm{R}_\textrm{V}$) than the general population of SN host galaxies.These results establish the feasibility of performing redMaGiC SN cosmologywith photometric survey data in the absence of spectroscopic data.[Journal_ref: ApJ 938 62 (2022)]
• Abbott}, T., Allam, S., Andersen, P., Angus, C., Asorey, J., Avelino, A., Avila, S., Bassett, B., Bechtol, K., Bernstein, G., Bertin, E., Brooks, D., Brout, D., Brown, P., Burke, D., Calcino, J., Carnero Rosell, A., Carollo, D., Carrasco Kind, M., , Carretero, J., et al. (2019). First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters. \apj, 872, L30.
• Costanzi, M., Rozo, E., Rykoff, E., Farahi, A., Jeltema, T., Evrard, A., Mantz, A., Gruen, D., Mandelbaum, R., DeRose, J., McClintock, T., Varga, T., Zhang, Y., Weller, J., Wechsler, R., & Aguena, M. (2019). Modelling projection effects in optically selected cluster catalogues. \mnras, 482, 490-505.
• Garcia, R., & Rozo, E. (2019). Halo Exclusion Criteria Impacts Halo Statistics. arXiv e-prints, arXiv:1903.01709.
• Ge, C., Sun, M., Rozo, E., Sehgal, N., Vikhlinin, A., Forman, W., Jones, C., & Nagai, D. (2019). X-ray scaling relations from a complete sample of the richest maxBCG clusters. \mnras, 484, 1946-1971.
• McClintock, T., Rozo, E., Becker, M. R., DeRose, J., Mao, Y., McLaughlin, S., Tinker, J. L., Wechsler, R. H., & Zhai, Z. (2019). The Aemulus Project. II. Emulating the Halo Mass Function. \apj, 872, 53.
• McClintock, T., Varga, T., Gruen, D., Rozo, E., Rykoff, E., Shin, T., Melchior, P., DeRose, J., Seitz, S., Dietrich, J., Sheldon, E., Zhang, Y., Linden, A., Jeltema, T., Mantz, A., Romer, A., Allen, S., Becker, M., Bermeo, A., , Bhargava, S., et al. (2019). Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters. \mnras, 482, 1352-1378.
• Raghunathan, S., Patil, S., Baxter, E., Benson, B., Bleem, L., Chou, T., Crawford, T., Holder, G., McClintock, T., Reichardt, C., Rozo, E., Varga, T., Abbott, T., Ade, P., Allam, S., Anderson, A., Annis, J., Austermann, J., Avila, S., , Beall, J., et al. (2019). Mass Calibration of Optically Selected DES Clusters Using a Measurement of CMB-cluster Lensing with SPTpol Data. \apj, 872, 170.
• Wang, Y., Bean, R., Behroozi, P., Chuang, C., Dell'antonio, I., Dickinson, M., Dore, O., Eisenstein, D., Foley, R., Glazebrook, K., Guzzo, L., Hirata, C., Ho, S., Hudson, M., Jain, B., Natarajan, P., Newman, J., Orsi, A., Padmanabhan, N., , Peacock, J., et al. (2019). Illuminating the dark universe with a very high density galaxy redshift survey over a wide area. arXiv e-prints, arXiv:1903.06034.
• Zhang, Y., Jeltema, T., Hollowood, D., Everett, S., Rozo, E., Farahi, A., Bermeo, A., Bhargava, S., Giles, P., Romer, A., Wilkinson, R., Rykoff, E., Mantz, A., Diehl, H., Evrard, A., Stern, C., Gruen, D., Linden, A., Splettstoesser, M., , Chen, X., et al. (2019). Dark Energy Survey Year 1 Results: Calibration of Cluster Mis-centering in the redMaPPer Catalogs. arXiv e-prints, arXiv:1901.07119.
• , C. C., , E. B., , B. J., , C. S., , S. A., , T. N., , Y. F., , E. R., , E. S., , A. K., , D. G., , E. M., , M. J., , A. G., , J. P., , N. M., , T. M., , A. P., , D. R., , , R. P., et al. (2018). The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles.
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  Splashback refers to the process of matter that is accreting onto a darkmatter halo reaching its first orbital apocenter and turning around in itsorbit. The cluster-centric radius at which this process occurs, r_sp, defines ahalo boundary that is connected to the dynamics of the cluster, in contrastwith other common halo boundary definitions such as R_200. A rapid decline inthe matter density profile of the halo is expected near r_sp. We measure thegalaxy number density and weak lensing mass profiles around RedMapper galaxyclusters in the first year Dark Energy Survey (DES) data. For a cluster samplewith mean mass ~2.5 x 10^14 solar masses, we find strong evidence of asplashback-like steepening of the galaxy density profile and measure r_sp=1.16+/- 0.08 Mpc/h, consistent with earlier SDSS measurements of More et al. (2016)and Baxter et al. (2017). Moreover, our weak lensing measurement demonstratesfor the first time the existence of a splashback-like steepening of the matterprofile of galaxy clusters. We measure r_sp=1.28 +/- 0.18 Mpc/h from the weaklensing data, in good agreement with our galaxy density measurements. Applyingour analysis to different cluster and galaxy samples, we find that consistentwith LambdaCDM simulations, r_sp scales with R_200m and does not evolve withredshift over the redshift range of 0.3--0.6. We also find that potentialsystematic effects associated with the RedMapper algorithm may impact thelocation of r_sp, in particular the choice of scale used to estimate clusterrichness. We discuss progress needed to understand the systematic uncertaintiesand fully exploit forthcoming data from DES and future surveys, emphasizing theimportance of more realistic mock catalogs and independent cluster samples.[Journal_ref: ]
• , C. D., , M. G., , P. V., , R. C., , E. R., , A. A., , G. M., , C. B., , A. C., , F. J., , C. C., , L. N., , T. M., , J. D., , J. D., , A. D., , J. E., , E. G., , D. G., , , J. G., et al. (2018). Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts in the DES -- Calibration of the Weak Lensing Source Redshift Distributions.
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  We present the calibration of the Dark Energy Survey Year 1 (DES Y1) weaklensing source galaxy redshift distributions from clustering measurements. Bycross-correlating the positions of source galaxies with luminous red galaxiesselected by the redMaGiC algorithm we measure the redshift distributions of thesource galaxies as placed into different tomographic bins. These measurementsconstrain any such shifts to an accuracy of $\sim0.02$ and can be computed evenwhen the clustering measurements do not span the full redshift range. Thehighest-redshift source bin is not constrained by the clustering measurementsbecause of the minimal redshift overlap with the redMaGiC galaxies. We compareour constraints with those obtained from $\texttt{COSMOS}$ 30-band photometryand find that our two very different methods produce consistent constraints.[Journal_ref: ]
• , D. C., , T. M., , F. B., , J. A., , K. B., , B. A., , R. A., , G. M., , E. B., , D. B., , D. L., , A. C., , M. C., , J. C., , F. J., , C. L., , T. M., , C. E., , C. B., , , L. N., et al. (2018). Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data.
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  We combine Dark Energy Survey Year 1 clustering and weak lensing data withBaryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN)experiments to constrain the Hubble constant. Assuming a flat $\Lambda$CDMmodel with minimal neutrino mass ($\sum m_\nu = 0.06$ eV) we find$H_0=67.2^{+1.2}_{-1.0}$ km/s/Mpc (68% CL). This result is completelyindependent of Hubble constant measurements based on the distance ladder,Cosmic Microwave Background (CMB) anisotropies (both temperature andpolarization), and strong lensing constraints. There are now five data setsthat: a) have no shared observational systematics; and b) each constrain theHubble constant with a few percent level precision. We compare these fiveindependent measurements, and find that, as a set, the differences between themare significant at the $2.1\sigma$ level ($\chi^2/dof=20.1/11$, probability toexceed=4%). This difference is low enough that we consider the data setsstatistically consistent with each other. The best fit Hubble constant obtainedby combining all five data sets is $H_0 = 69.1^{+0.4}_{-0.6}$ km/s/Mpc.[Journal_ref: ]
• , D. G., , O. F., , E. K., , J. D., , R. C., , C. D., , J. E., , E. S., , R. H., , A. A., , G. M., , J. B., , C. C., , J. C., , M. C., , J. D., , M. G., , M. S., , W. G., , , S. H., et al. (2018). Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS.
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  We derive cosmological constraints from the probability distribution function(PDF) of evolved large-scale matter density fluctuations. We do this bysplitting lines of sight by density based on their count of tracer galaxies,and by measuring both gravitational shear around and counts-in-cells inoverdense and underdense lines of sight, in Dark Energy Survey (DES) First Yearand Sloan Digital Sky Survey (SDSS) data. Our analysis uses a perturbationtheory model (see companion paper Friedrich at al.) and is validated usingN-body simulation realizations and log-normal mocks. It allows us to constraincosmology, bias and stochasticity of galaxies w.r.t. matter density and, inaddition, the skewness of the matter density field. From a Bayesian model comparison, we find that the data weakly prefer aconnection of galaxies and matter that is stochastic beyond Poissonfluctuations on
• , J. E., , M. C., , A. J., , T. G., , E. R., , E. S., , S. A., , N. B., , J. B., , S. L., , R. C., , A. D., , O. F., , N. K., , E. K., , N. M., , J. P., , C. S., , L. F., , , I. S., et al. (2018). Dark Energy Survey Year 1 Results: Galaxy clustering for combined probes.
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  We measure the clustering of DES Year 1 galaxies that are intended to becombined with weak lensing samples in order to produce precise cosmologicalconstraints from the joint analysis of large-scale structure and lensingcorrelations. Two-point correlation functions are measured for a sample of $6.6\times 10^{5}$ luminous red galaxies selected using the \textsc{redMaGiC}algorithm over an area of $1321$ square degrees, in the redshift range $0.15
• , J. P., , C. S., , Y. F., , D. G., , J. E., , N. K., , L. F., , B. J., , R. M., , N. M., , M. A., , A. A., , D. B., , G. M., , J. B., , R. C., , C. C., , M. C., , C. D., , , J. D., et al. (2018). Dark Energy Survey Year 1 Results: Galaxy-Galaxy Lensing.
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  We present galaxy-galaxy lensing measurements from 1321 sq. deg. of the DarkEnergy Survey (DES) Year 1 (Y1) data. The lens sample consists of a selectionof 660,000 red galaxies with high-precision photometric redshifts, known asredMaGiC, split into five tomographic bins in the redshift range $0.15 < z
• , M. A., , N. M., , J. Z., , T. F., , E. K., , S. D., , D. G., , J. B., , O. F., , S. S., , J. P., , L. F., , C. D., , A. F., , J. D., , A. A., , A. A., , E. B., , M. R., , , G. M., et al. (2018). Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear.
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  We use 26 million galaxies from the Dark Energy Survey (DES) Year 1 shapecatalogs over 1321 deg$^2$ of the sky to produce the most significantmeasurement of cosmic shear in a galaxy survey to date. We constraincosmological parameters in both the flat $\Lambda$CDM and $w$CDM models, whilealso varying the neutrino mass density. These results are shown to be robustusing two independent shape catalogs, two independent photo-$z$ calibrationmethods, and two independent analysis pipelines in a blind analysis. We find a3% fractional uncertainty on $\sigma_8(\Omega_m/0.3)^{0.5} =0.789^{+0.024}_{-0.026}$ at 68% CL, which is a factor of three improvement overthe fractional constraining power of our DES Science Verification results and afactor 1.5 tighter than the previous state-of-the-art cosmic shear results. In$w$CDM, we find a 5% fractional uncertainty on $\sigma_8(\Omega_m/0.3)^{0.5} =0.789^{+0.036}_{-0.038}$ and a dark energy equation-of-state$w=-0.82^{+0.26}_{-0.48}$. Though we find results that are consistent withprevious cosmic shear constraints in $\sigma_8$ - $\Omega_m$, we neverthelesssee no evidence for disagreement of our weak lensing data with data from theCMB. Finally, we find no evidence preferring a $w$CDM model allowing $w\ne -1$.We expect further significant improvements with subsequent years of DES data,which will more than triple the sky coverage of our shape catalogs and doublethe effective integrated exposure time per galaxy.[Journal_ref: ]
• , M. G., , P. V., , C. D., , R. C., , M. M., , J. D., , J. D., , A. A., , E. R., , E. G., , B. H., , R. M., , G. M., , C. B., , A. C., , F. J., , C. C., , L. N., , D. G., , , J. G., et al. (2018). Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization.
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  We use numerical simulations to characterize the performance of aclustering-based method to calibrate photometric redshift biases. Inparticular, we cross-correlate the weak lensing (WL) source galaxies from theDark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous redgalaxies with secure photometric redshifts) to estimate the redshiftdistribution of the former sample. The recovered redshift distributions areused to calibrate the photometric redshift bias of standard photo-$z$ methodsapplied to the same source galaxy sample. We apply the method to threephoto-$z$ codes run in our simulated data: Bayesian Photometric Redshift (BPZ),Directional Neighborhood Fitting (DNF), and Random Forest-based photo-$z$ (RF).We characterize the systematic uncertainties of our calibration procedure, andfind that these systematic uncertainties dominate our error budget. Thedominant systematics are due to our assumption of unevolving bias andclustering across each redshift bin, and to differences between the shapes ofthe redshift distributions derived by clustering vs photo-$z$'s. The systematicuncertainty in the mean redshift bias of the source galaxy sample is $\Delta z\lesssim 0.02$, though the precise value depends on the redshift bin underconsideration. We discuss possible ways to mitigate the impact of our dominantsystematics in future analyses.[Journal_ref: ]
• , R. C., , C. D., , M. G., , P. V., , J. E., , E. R., , J. F., , E. S., , A. A., , G. M., , C. B., , A. C., , F. J., , C. C., , L. N., , J. D., , J. D., , A. D., , E. G., , , T. G., et al. (2018). Dark Energy Survey Year 1 Results: Calibration of redMaGiC Redshift Distributions in DES and SDSS from Cross-Correlations.
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  We present calibrations of the redshift distributions of redMaGiC galaxies inthe Dark Energy Survey Year 1 (DES Y1) and Sloan Digital Sky Survey (SDSS) DR8data. These results determine the priors of the redshift distribution ofredMaGiC galaxies, which were used for galaxy clustering measurements and aslenses for galaxy-galaxy lensing measurements in DES Y1 cosmological analyses.We empirically determine the bias in redMaGiC photometric redshift estimatesusing angular cross-correlations with Baryon Oscillation Spectroscopic Survey(BOSS) galaxies. For DES, we calibrate a single parameter redshift bias inthree photometric redshift bins: $z \in[0.15,0.3]$, [0.3,0.45], and [0.45,0.6].Our best fit results in each bin give photometric redshift biases of $|\Deltaz|
• , T. D., , T. M., , F. B., , A. A., , S. A., , F. A., , J. A., , S. A., , M. B., , N. B., , K. B., , G. M., , R. A., , E. B., , D. B., , E. B., , D. L., , H. C., , A. C., , , M. C., et al. (2018). Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation scale in the distribution of galaxies to redshift 1.
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  We present angular diameter distance measurements obtained by locating theBAO scale in the distribution of galaxies selected from the first year of DarkEnergy Survey data. We consider a sample of over 1.3 million galaxiesdistributed over a footprint of 1318 deg$^2$ with $0.6 < z_{\rm photo} < 1$ anda typical redshift uncertainty of $0.03(1+z)$. This sample was selected, asfully described in a companion paper, using a color/magnitude selection thatoptimizes trade-offs between number density and redshift uncertainty. Weinvestigate the BAO signal in the projected clustering using three conventions,the angular separation, the co-moving transverse separation, and sphericalharmonics. Further, we compare results obtained from template based and machinelearning photometric redshift determinations. We use 1800 simulations thatapproximate our sample in order to produce covariance matrices and allow us tovalidate our distance scale measurement methodology. We measure the angulardiameter distance, $D_A$, at the effective redshift of our sample divided bythe true physical scale of the BAO feature, $r_{\rm d}$. We obtain close to a 4per cent distance measurement of $D_A(z_{\rm eff}=0.81)/r_{\rm d} = 10.75\pm0.43 $. These results are consistent with the flat $\Lambda$CDM concordancecosmological model supported by numerous other recent experimental results.[Journal_ref: ]
• Abbott, T., Abdalla, F., Alarcon, A., Allam, S., Andrade-Oliveira, F. .., Annis, J., Avila, S., Banerji, M., Banik, N., Bechtol, K., Bernstein, R., Bernstein, G., Bertin, E., Brooks, D., Buckley-Geer, E. .., Burke, D., Camacho, H., Carnero Rosell, A., Carrasco Kind, M., , Carretero, J., et al. (2018). Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation scale in the distribution of galaxies to redshift 1. \mnras, 3191.
• Abbott, T., Abdalla, F., Alarcon, A., Allam, S., Annis, J., Avila, S., Aylor, K., Banerji, M., Banik, N., Baxter, E., Bechtol, K., Becker, M., Benson, B., Bernstein, G., Bertin, E., Bianchini, F., Blazek, J., Bleem, L., Bleem, L., , Bridle, S., et al. (2018). Dark Energy Survey Year 1 Results: Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions. arXiv e-prints, arXiv:1810.02322.
• Abbott, T., Abdalla, F., Annis, J., Bechtol, K., Blazek, J., Benson, B., Bernstein, R., Bernstein, G., Bertin, E., Brooks, D., Burke, D., Carnero Rosell, A., Carrasco Kind, M., Carretero, J., Castander, F., Chang, C., Crawford, T., Cunha, C., D'Andrea, C., , Costa, L., et al. (2018). Dark Energy Survey Year 1 Results: A Precise H$_0$ Estimate from DES Y1, BAO, and D/H Data. \mnras, 480, 3879-3888.
• Baxter, E., Raghunathan, S., Crawford, T., Fosalba, P., Hou, Z., Holder, G., Omori, Y., Patil, S., Rozo, E., Abbott, T., Annis, J., Aylor, K., Benoit-L{\'evy}, A., Benson, B., Bertin, E., Bleem, L., Buckley-Geer, E. .., Burke, D., Carlstrom, J., , Carnero Rosell, A., et al. (2018). A measurement of CMB cluster lensing with SPT and DES year 1 data. \mnras, 476, 2674-2688.
• Cawthon}, R., Davis, C., Gatti, M., Vielzeuf, P., Elvin-Poole, J. .., Rozo, E., Frieman, J., Rykoff, E., Alarcon, A., Bernstein, G., Bonnett, C., Carnero Rosell, A., Castander, F., Chang, C., Costa, L., De Vicente, J., DeRose, J., Drlica-Wagner, A. .., Gaztanaga, E., , Giannantonio, T., et al. (2018). Dark Energy Survey Year 1 Results: calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations. \mnras, 481, 2427-2443.
• Chang, C., Pujol, A., Mawdsley, B., Bacon, D., Elvin-Poole, J. .., Melchior, P., Kov{\'acs}, A., Jain, B., Leistedt, B., Giannantonio, T., Alarcon, A., Baxter, E., Bechtol, K., Becker, M., Benoit-L{\'evy}, A., Bernstein, G., Bonnett, C., Busha, M., Rosell, A. C., , Castander, F., et al. (2018). Dark Energy Survey Year 1 results: curved-sky weak lensing mass map. \mnras, 475, 3165-3190.
• Chang}, C., Baxter, E., Jain, B., S{\'anchez}, C., Adhikari, S., Varga, T., Fang, Y., Rozo, E., Rykoff, E., Kravtsov, A., Gruen, D., Hartley, W., Huff, E., Jarvis, M., Kim, A., Prat, J., MacCrann, N., McClintock, T., Palmese, A., , Rapetti, D., et al. (2018). The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles. \apj, 864, 83.
• Collaboration, D., Abbott, T., Allam, S., Andersen, P., Angus, C., Asorey, J., Avelino, A., Avila, S., Bassett, B., Bechtol, K., Bernstein, G., Bertin, E., Brooks, D., Brout, D., Brown, P., Burke, D., Calcino, J., Carnero Rosell, A., Carollo, D., , Carrasco Kind, M., et al. (2018). First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters. arXiv e-prints, arXiv:1811.02374.
• Costanzi, M., Rozo, E., Simet, M., Zhang, Y., Evrard, A., Mantz, A., Rykoff, E., Jeltema, T., Gruen, D., McClintock, S., Romer, A., Linden, A., Farahi, A., DeRose, J., Varga, T., Weller, J., Giles, P., Hollowood, D., Bhargava, S., , Bermeo-Hernandez, A. .., et al. (2018). Dark Energy Survey Year 1 Results: Methods for Cluster Cosmology and Application to the SDSS. arXiv e-prints, arXiv:1810.09456.
• Davis, C., Rozo, E., Roodman, A., Alarcon, A., Cawthon, R., Gatti, M., Lin, H., Miquel, R., Rykoff, E., Troxel, M., Vielzeuf, P., Abbott, T., Abdalla, F., Allam, S., Annis, J., Bechtol, K., Benoit-L{\'evy}, A., Bertin, E., Brooks, D., , Buckley-Geer, E. .., et al. (2018). Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data. \mnras, 477, 2196-2208.
• Dor{\'e}, O., Hirata, C., Wang, Y., Weinberg, D., Baronchelli, I., Benson, A., Capak, P., Choi, A., Eifler, T., Hemmati, S., Ho, S., Izard, A., Jain, B., Jarvis, M., Kiessling, A., Krause, E., Massara, E., Masters, D., Merson, A., , Miyatake, H., et al. (2018). WFIRST Science Investigation Team ''Cosmology with the High Latitude Survey'' Annual Report 2017. arXiv e-prints, arXiv:1804.03628.
• Elvin-Poole}, J., Crocce, M., Ross, A., Giannantonio, T., Rozo, E., Rykoff, E., Avila, S., Banik, N., Blazek, J., Bridle, S., Cawthon, R., Drlica-Wagner, A. .., Friedrich, O., Kokron, N., Krause, E., MacCrann, N., Prat, J., S{\'anchez}, C., Secco, L., , Sevilla-Noarbe, I. .., et al. (2018). Dark Energy Survey year 1 results: Galaxy clustering for combined probes. \prd, 98, 042006.
• Gatti, M., Vielzeuf, P., Davis, C., Cawthon, R., Rau, M., DeRose, J., De Vicente, J., Alarcon, A., Rozo, E., Gaztanaga, E., Hoyle, B., Miquel, R., Bernstein, G., Bonnett, C., Carnero Rosell, A., {Castand, e. F., Chang, C., Costa, L., Gruen, D., , Gschwend, J., et al. (2018). Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization. \mnras, 477, 1664-1682.
• Gruen, D., Zhang, Y., Palmese, A., Yanny, B., Busti, V., Hoyle, B., Melchior, P., Miller, C., Rozo, E., Rykoff, E., Varga, T., Abdalla, F., Allam, S., Annis, J., Avila, S., Brooks, D., Burke, D., Carnero Rosell, A., Carrasco Kind, M., , Carretero, J., et al. (2018). Dark Energy Survey Year 1 Results: The effect of intra-cluster light on photometric redshifts for weak gravitational lensing. arXiv e-prints, arXiv:1809.04599.
• Gruen}, D., Friedrich, O., Krause, E., DeRose, J., Cawthon, R., Davis, C., Elvin-Poole, J. .., Rykoff, E., Wechsler, R., Alarcon, A., Bernstein, G., Blazek, J., Chang, C., Clampitt, J., Crocce, M., De Vicente, J., Gatti, M., Gill, M., Hartley, W., , Hilbert, S., et al. (2018). Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data. \prd, 98, 023507.
• Hikage, C., Mandelbaum, R., Leauthaud, A., Rozo, E., & Rykoff, E. S. (2018). Testing redMaPPer centring probabilities using galaxy clustering and galaxy-galaxy lensing. \mnras, 480, 2689-2697.
• Hollowood, D. L., Jeltema, T., Chen, X., Farahi, A., Evrard, A., Everett, S., Rozo, E., Rykoff, E., Bernstein, R., Bermeo, A., Eiger, L., Giles, P., Israel, H., Michel, R., Noorali, R., Romer, K., Rooney, P., & Splettstoesser, M. (2018). Chandra Follow-Up of the SDSS DR8 redMaPPer Catalog Using the MATCha Pipeline. arXiv e-prints, arXiv:1808.06637.
• Hoyle, B., Gruen, D., Bernstein, G., Rau, M., De Vicente, J., Hartley, W., Gaztanaga, E., DeRose, J., Troxel, M., Davis, C., Alarcon, A., MacCrann, N., Prat, J., S{\'anchez}, C., Sheldon, E., Wechsler, R., Asorey, J., Becker, M., Bonnett, C., , Carnero Rosell, A., et al. (2018). Dark Energy Survey Year 1 Results: redshift distributions of the weak-lensing source galaxies. \mnras, 478, 592-610.
• Huang, H., Mandelbaum, R., Freeman, P. E., Chen, Y., Rozo, E., & Rykoff, E. (2018). Intrinsic alignment in redMaPPer clusters - II. Radial alignment of satellites towards cluster centres. \mnras, 474, 4772-4794.
• Omori, Y., Baxter, E., Chang, C., Kirk, D., Alarcon, A., Bernstein, G., Bleem, L., Cawthon, R., Choi, A., Chown, R., Crawford, T., Davis, C., De Vicente, J., DeRose, J., Dodelson, S., Eifler, T., Fosalba, P., Friedrich, O., Gatti, M., , Gaztanaga, E., et al. (2018). Dark Energy Survey Year 1 Results: Cross-correlation between DES Y1 galaxy weak lensing and SPT+Planck CMB weak lensing. arXiv e-prints, arXiv:1810.02441.
• Shin, T., Adhikari, S., Baxter, E., Chang, C., Jain, B., Battaglia, N., Bleem, L., Bocquet, S., DeRose, J., Gruen, D., Hilton, M., Kravtsov, A., McClintock, T., Rozo, E., Rykoff, E., Varga, T., Wechsler, R., Wu, H., Aiola, S., , Allam, S., et al. (2018). Measurement of the Splashback Feature around SZ-selected Galaxy Clusters with DES, SPT and ACT. arXiv e-prints, arXiv:1811.06081.
• Shin, T., Clampitt, J., Jain, B., Bernstein, G., Neil, A., Rozo, E., & Rykoff, E. (2018). The ellipticity of galaxy cluster haloes from satellite galaxies and weak lensing. \mnras, 475, 2421-2437.
• Simet, M., McClintock, T., Mandelbaum, R., Rozo, E., Rykoff, E., Sheldon, E., & Wechsler, R. H. (2018). Erratum: Weak Lensing Measurement of the Mass-Richness Relation of SDSS redMaPPer Clusters. \mnras, 480, 5385-5385.
• Troxel}, M., MacCrann, N., Zuntz, J., Eifler, T., Krause, E., Dodelson, S., Gruen, D., Blazek, J., Friedrich, O., Samuroff, S., Prat, J., Secco, L., Davis, C., Fert{\'e}, A., DeRose, J., Alarcon, A., Amara, A., Baxter, E., Becker, M., , Bernstein, G., et al. (2018). Dark Energy Survey Year 1 results: Cosmological constraints from cosmic shear. \prd, 98, 043528.
• Varga, T., DeRose, J., Gruen, D., McClintock, T., Seitz, S., Rozo, E., Costanzi, M., Hoyle, B., MacCrann, N., Plazas, A., Rykoff, E., Simet, M., Linden, A., Wechsler, R., Annis, J., Avila, S., Bertin, E., Brooks, D., Buckley-Geer, E. .., , Burke, D., et al. (2018). Dark Energy Survey Year 1 results: Validation of weak lensing cluster member contamination estimates from P(z) decomposition. arXiv e-prints, arXiv:1812.05116.
• Wojtak, R., Old, L., Mamon, G. A., Pearce, F. R., Carvalho, D. R., Sifón, C., Gray, M. E., Skibba, R. A., Croton, D., Bamford, S., Gifford, D., der Linden, V. A., Muñoz-Cuartas, J. C., Müller, V., Pearson, R. J., Rozo, E., Rykoff, E., Saro, A., Sepp, T., & Tempel, E. (2018). Galaxy Cluster Mass Reconstruction Project - IV. Understanding the effects of imperfect membership on cluster mass estimation. MNRAS,.
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  The primary difficulty in measuring dynamical masses of galaxy clusters fromgalaxy data lies in the separation between true cluster members frominterloping galaxies along the line of sight. We study the impact of membershipcontamination and incompleteness on cluster mass estimates obtained with 25commonly used techniques applied to nearly 1000 mock clusters. We show that allmethods overestimate or underestimate cluster masses when applied tocontaminated or incomplete galaxy samples respectively. This appears to be themain source of the intrinsic scatter in the mass scaling relation. Applyingcorrections based on a prior knowledge of contamination and incompleteness canreduce the scatter to the level of shot noise expected for poorly sampledclusters. We establish an empirical model quantifying the effect of imperfectmembership on cluster mass estimation and discuss its universal andmethod-dependent features. We find that both imperfect membership and theresponse of the mass estimators depend on cluster mass, effectively causing aflattening of the estimated - true mass relation. Imperfect membership thusalters cluster counts determined from spectroscopic surveys, hence thecosmological parameters that depend on such counts.[Journal_ref: MNRAS, 481, 324 (2018)]
• Wojtak, R., Old, L., Mamon, G., Pearce, F., Carvalho, R., Sif{\'on}, C., Gray, M., Skibba, R., Croton, D., Bamford, S., Gifford, D., Linden, A., Mu{\~noz-Cuartas}, J., M{\"uller}, V., Pearson, R., Rozo, E., Rykoff, E., Saro, A., Sepp, T., & Tempel, E. (2018). Galaxy Cluster Mass Reconstruction Project - IV. Understanding the effects of imperfect membership on cluster mass estimation. \mnras, 481, 324-340.
• Zhai, Z., Tinker, J. L., Becker, M. R., DeRose, J., Mao, Y., McClintock, T., McLaughlin, S., Rozo, E., & Wechsler, R. H. (2018). The Aemulus Project III: Emulation of the Galaxy Correlation Function. arXiv e-prints, arXiv:1804.05867.
• , C. H., , R. M., , A. L., , E. R., & , E. S. (2017). Testing redMaPPer Centering Probabilities using Galaxy Clustering and Galaxy-Galaxy Lensing.
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  Galaxy cluster centering is one of the key issues for precision cosmologystudies using galaxy surveys. The red-sequence Matched-filter ProbabilisticPercolation (redMaPPer) estimates the centering probability of member galaxiesfrom photometric information; however, the centering algorithm has notpreviously been well-tested. We test the centering probabilities of redMaPPercluster catalog using the projected cross correlation between redMaPPerclusters with photometric red galaxies and galaxy-galaxy lensing. We focus onthe subsample of redMaPPer clusters in which the redMaPPer central galaxies(RMCGs) are not the brightest member galaxies (BMEM) and both of them havespectroscopic redshift. This subsample represents nearly 10% of the wholecluster sample. We also make a "High Pcen" sample where the central probabilityof RMCGs is larger than 99% to be used as a reference sample of centralgalaxies. We find a clear difference in the cross-correlation measurementsbetween RMCGs and BMEMs, and the estimated centering probability is 74$\pm$10%for RMCGs and 13$\pm$4% for BMEMs in the sample. These values are in agreementwith the central probability values reported by redMaPPer (75% for RMCG and 10%for BMEMs) within 1$\sigma$. Our analysis provides a strong consistency test ofthe redMaPPer centering probabilities. Our results suggest that redMaPPercentering probabilities are reliably estimated, and that the brightest galaxyin the cluster is not always the central galaxy.[Journal_ref: ]
• , D. C., , A. A., , J. A., , S. A., , S. A., , L. E., , C. A., , J. A., , S. B., , C. B., , O. B., , C. B., , L. B., , C. B., , T. C., , E. F., , J. L., , R. B., , F. B., , , C. B., et al. (2017). The DESI Experiment Part II: Instrument Design.
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  DESI (Dark Energy Spectropic Instrument) is a Stage IV ground-based darkenergy experiment that will study baryon acoustic oscillations and the growthof structure through redshift-space distortions with a wide-area galaxy andquasar redshift survey. The DESI instrument is a robotically-actuated,fiber-fed spectrograph capable of taking up to 5,000 simultaneous spectra overa wavelength range from 360 nm to 980 nm. The fibers feed ten three-armspectrographs with resolution $R= \lambda/\Delta\lambda$ between 2000 and 5500,depending on wavelength. The DESI instrument will be used to conduct afive-year survey designed to cover 14,000 deg$^2$. This powerful instrumentwill be installed at prime focus on the 4-m Mayall telescope in Kitt Peak,Arizona, along with a new optical corrector, which will provide a three-degreediameter field of view. The DESI collaboration will also deliver aspectroscopic pipeline and data management system to reduce and archive alldata for eventual public use.[Journal_ref: ]
• , E. B., , C. C., , B. J., , S. A., , N. D., , A. K., , S. M., , E. R., , E. R., & , R. K. (2017). The Halo Boundary of Galaxy Clusters in the SDSS.
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  Mass around dark matter halos can be divided into "infalling" material and"collapsed" material that has passed through at least one pericenter.Analytical models and simulations predict a rapid drop in the halo densityprofile associated with the transition between these two regimes. Using datafrom SDSS, we explore the evidence for such a feature in the density profilesof galaxy clusters and investigate the connection between this feature and apossible phase space boundary. We first estimate the steepening of the outergalaxy density profile around clusters: the profiles show an abrupt steepening,providing evidence for truncation of the halo profile. Next, we measure thegalaxy density profile around clusters using two sets of galaxies selectedbased on color. We find evidence of an abrupt change in the galaxy colors thatcoincides with the location of the steepening of the density profile. Sincegalaxies are likely to be quenched of star formation and turn red inside ofclusters, this change in the galaxy color distribution can be interpreted asthe transition from an infalling regime to a collapsed regime. We also measurethis transition using a model comparison approach which has been used recentlyin studies of the "splashback" phenomenon, but find that this approach is not arobust way to quantify the significance of detecting a splashback-like feature.Finally, we perform measurements using an independent cluster catalog to testfor potential systematic errors associated with cluster selection. We identifyseveral avenues for future work: improved understanding of the small-scalegalaxy profile, lensing measurements, identification of proxies for the haloaccretion rate, and other tests. With upcoming data from the DES, KiDS and HSCsurveys, we can expect significant improvements in the study of haloboundaries.[Journal_ref: ]
• , E. J., , E. R., , B. J., , E. R., & , R. H. (2017). Constraining the Mass-Richness Relationship of redMaPPer Clusters with Angular Clustering.
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  The potential of using cluster clustering for calibrating the mass-observablerelation of galaxy clusters has been recognized theoretically for over adecade. Here, we demonstrate the feasibility of this technique to achieve highprecision mass calibration using redMaPPer clusters in the Sloan Digital SkySurvey North Galactic Cap. By including cross-correlations between severalrichness bins in our analysis we significantly improve the statisticalprecision of our mass constraints. The amplitude of the mass-richness relationis constrained to 7% statistical precision. However, the error budget issystematics dominated, reaching an 18% total error that is dominated bytheoretical uncertainty in the bias-mass relation for dark matter halos. Weperform a detailed treatment of the effects of assembly bias on our analysis,finding that the contribution of such effects to our parameter uncertainties issomewhat greater than that of measurement noise. We confirm the results fromMiyatake et al. (2015) that the clustering amplitude of redMaPPer clustersdepends on galaxy concentration, and provide additional evidence in support ofthis effect being due to some form of assembly bias. The results presented heredemonstrate the power of cluster clustering for mass calibration and cosmologyprovided the current theoretical systematics can be ameliorated.[Journal_ref: ]
• , H. H., , R. M., , P. E., , Y. C., , E. R., , E. R., & , E. J. (2017). Intrinsic alignments in redMaPPer clusters -- I. Central galaxy alignments and angular segregation of satellites.
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  The shapes of cluster central galaxies are not randomly oriented, but ratherexhibit coherent alignments with the shapes of their parent clusters as well aswith the surrounding large-scale structures. In this work, we aim to identifythe galaxy and cluster quantities that most strongly predict the central galaxyalignment phenomenon among a large parameter space with a sample of 8237clusters and 94817 members within 0.1
• , J. K., , C. S., , J. C., , J. B., , M. C., , B. J., , J. Z., , A. A., , M. B., , G. B., , C. B., , J. D., , S. D., , T. E., , E. G., , T. G., , D. G., , W. H., , T. K., , , D. K., et al. (2017). Cosmology from large scale galaxy clustering and galaxy-galaxy lensing with Dark Energy Survey Science Verification data.
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  We present cosmological constraints from the Dark Energy Survey (DES) using acombined analysis of angular clustering of red galaxies and theircross-correlation with weak gravitational lensing of background galaxies. Weuse a 139 square degree contiguous patch of DES data from the ScienceVerification (SV) period of observations. Using large scale measurements, weconstrain the matter density of the Universe as Omega_m = 0.31 +/- 0.09 and theclustering amplitude of the matter power spectrum as sigma_8 = 0.74 +/- 0.13after marginalizing over seven nuisance parameters and three additionalcosmological parameters. This translates into S_8 = sigma_8(Omega_m/0.3)^{0.16}= 0.74 +/- 0.12 for our fiducial lens redshift bin at 0.35
• , N. C., , A. M., , Y. Z., , A. F., , T. D., , K. N., , C. A., , K. D., , J. K., , E. R., , E. R., , T. S., , J. R., , Y. L., , J. R., , M. S., , A. S., , M. S., , H. S., & , J. T. (2017). SPIDERS: the spectroscopic follow-up of X-ray selected clusters of galaxies in SDSS-IV.
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  SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a programdedicated to the homogeneous and complete spectroscopic follow-up of X-ray AGNand galaxy clusters over a large area ($\sim$7500 deg$^2$) of the extragalacticsky. SPIDERS is part of the SDSS-IV project, together with the Extended BaryonOscillation Spectroscopic Survey (eBOSS) and the Time-Domain SpectroscopicSurvey (TDSS). This paper describes the largest project within SPIDERS beforethe launch of eROSITA: an optical spectroscopic survey of X-ray selected,massive ($\sim 10^{14}$ to $10^{15}~M_{\odot}$) galaxy clusters discovered inROSAT and XMM-Newton imaging. The immediate aim is to determine precise($\Delta_z \sim 0.001$) redshifts for 4,000-5,000 of these systems out to $z\sim 0.6$. The scientific goal of the program is precision cosmology, usingclusters as probes of large-scale structure in the expanding Universe. Wepresent the cluster samples, target selection algorithms and observationstrategies. We demonstrate the efficiency of selecting targets using acombination of SDSS imaging data, a robust red-sequence finder and a dedicatedprioritization scheme. We describe a set of algorithms and work-flow developedto collate spectra and assign cluster membership, and to deliver catalogues ofspectroscopically confirmed clusters. We discuss the relevance of line-of-sightvelocity dispersion estimators for the richer systems. We illustrate ourtechniques by constructing a catalogue of 230 spectroscopically validatedclusters ($0.031 < z < 0.658$), found in pilot observations. We discuss twopotential science applications of the SPIDERS sample: the study of the X-rayluminosity-velocity dispersion ($L_X-\sigma$) relation and the building ofstacked phase-space diagrams.[Journal_ref: ]
• , Y. F., , J. C., , N. D., , B. J., , E. R., , J. M., & , E. R. (2017). Tidal stripping as a test of satellite quenching in redMaPPer clusters.
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  When dark matter halos are accreted by massive host clusters, stronggravitational tidal forces begin stripping mass from the accreted subhalos.This stripping eventually removes all mass beyond a subhalo's tidal radius, butthe unbound mass remains in the vicinity of the satellite for at least adynamical time t_dyn. The N-body subhalo study of Chamberlain et al. verifiedthis picture and pointed out a useful observational consequence: measurementsof subhalo correlations beyond the tidal radius are sensitive to the infalltime, t_infall, of the subhalo onto its host. We perform this cross-correlationmeasurement using ~ 160,000 red satellite galaxies in SDSS redMaPPer clustersand find evidence that subhalo correlations do persist well beyond the tidalradius, suggesting that many of the observed satellites fell into their currenthost less than a dynamical time ago, t_infall < t_dyn. Combined with estimateddynamical times t_dyn ~ 3-5 Gyr and SED fitting results for the time at whichsatellites stopped forming stars, t_quench ~ 6 Gyr, we infer that for asignificant fraction of the satellites, star formation quenched before thosesatellites entered their current hosts. The result holds for red satellitesover a large range of cluster-centric distances 0.1 - 0.6 Mpc/h. We discuss theimplications of this result for models of galaxy formation.[Journal_ref: ]
• , Y. Z., , R. M., , M. S., , E. R., & , E. S. (2017). On the Level of Cluster Assembly Bias in SDSS.
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  Recently, several studies have discovered a strong discrepancy between thelarge-scale clustering biases of two subsamples of galaxy clusters at the samehalo mass, split by their average projected membership distances$R_{\mathrm{mem}}$. The level of this discrepancy significantly exceeds themaximum halo assembly bias signal predicted by LCDM. In this study, we explorewhether some of the clustering bias differences could be caused by biases in$R_{\mathrm{mem}}$ due to projection effects from other systems along theline-of-sight. We thoroughly investigate the halo assembly bias of thephotometrically-detected redMaPPer clusters in SDSS, by defining a new variantof the average membership distance estimator $\tilde{R}_{\mathrm{mem}}$ that ismore robust against projection effects in the cluster membershipidentification. Using the angular mark correlation functions of clusters, weshow that the large-scale bias differences when splitting by $R_{\mathrm{mem}}$can be largely attributed to such projection effects. After splitting by$\tilde{R}_{\mathrm{mem}}$, the anomalously large signal is reduced, giving aratio of $1.02\pm0.14$ between the two clustering biases as measured from weaklensing. Using a realistic mock cluster catalog, we predict that the bias ratiobetween two $\tilde{R}_{\mathrm{mem}}$-split subsamples should be $
• Collaboration}, {. E., {Abbott}, T., {Abdalla}, F., {Allam}, S., {Aleksic}, J., {Amara}, A., {Bacon}, D., {Balbinot}, E., {Banerji}, M., {Bechtol}, K., {Benoit-Levy}, A., {Bernstein}, G., {Bertin}, E., {Blazek}, J., {Dodelson}, S., {Bonnett}, C., {Brooks}, D., {Bridle}, S., {Brunner}, R., , {Buckley-Geer}, E., et al. (2016). The Dark Energy Survey: more than dark energy - an overview. ArXiv e-prints.
• Skielboe, A., Wojtak, R., Pedersen, K., Rozo, E., & Rykoff, E. S. (2016). SPATIAL ANISOTROPY OF GALAXY KINEMATICS IN SLOAN DIGITAL SKY SURVEY GALAXY CLUSTERS. ASTROPHYSICAL JOURNAL LETTERS, 758(1).
• {Becker}, M., , E. (2016). Fourier band-power E/B-mode estimators for cosmic shear. \mnras, 457, 304-312.
• {Farahi}, A., {Evrard}, A., {Rozo}, E., {Rykoff}, E., , R. (2016). Galaxy Cluster Mass Estimation from Stacked Spectroscopic Analysis. ArXiv e-prints.
• {Gruen}, D., {Friedrich}, O., {Amara}, A., {Bacon}, D., {Bonnett}, C., {Hartley}, W., {Jain}, B., {Jarvis}, M., {Kacprzak}, T., {Krause}, E., {Mana}, A., {Rozo}, E., {Rykoff}, E., {Seitz}, S., {Sheldon}, E., {Troxel}, M., {Vikram}, V., {Abbott}, T., {Abdalla}, F., , {Allam}, S., et al. (2016). Weak lensing by galaxy troughs in DES Science Verification data. \mnras, 455, 3367-3380.
• {Miyatake}, H., {More}, S., {Takada}, M., {Spergel}, D., {Mandelbaum}, R., {Rykoff}, E., , E. (2016). Evidence of Halo Assembly Bias in Massive Clusters. Physical Review Letters, 116, 041301.
• {More}, S., {Miyatake}, H., {Takada}, M., {Diemer}, B., {Kravtsov}, A., {Dalal}, N., {More}, A., {Murata}, R., {Mandelbaum}, R., {Rozo}, E., {Rykoff}, E., {Oguri}, M., , D. (2016). Detection of the Splashback Radius and Halo Assembly bias of Massive Galaxy Clusters. ArXiv e-prints.
• {Palmese}, A., {Lahav}, O., {Banerji}, M., {Gruen}, D., {Jouvel}, S., {Melchior}, P., {Aleksi{\'c}}, J., {Annis}, J., {Diehl}, H., {Jeltema}, T., {Romer}, K., {Rozo}, E., {Rykoff}, E., {Seitz}, S., {Suchyta}, E., {Zhang}, Y., {Abbott}, T., {Abdalla}, F., {Allam}, S., , {Benoit-L{\'e}vy}, A., et al. (2016). Comparing Dark Energy Survey and HST-CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter. ArXiv e-prints.
• {Rykoff}, E., {Rozo}, E., {Hollowood}, D., {Bermeo-Hernandez}, A., {Jeltema}, T., {Mayers}, J., {Romer}, A., {Rooney}, P., {Saro}, A., {Vergara Cervantes}, C., {Wilcox}, H., {Abbott}, T., {Abdalla}, F., {Allam}, S., {Annis}, J., {Benoit-L{\'e}vy}, A., {Bernstein}, G., {Bertin}, E., {Brooks}, D., , {Burke}, D., et al. (2016). The redMaPPer Galaxy Cluster Catalog From DES Science Verification Data. ArXiv e-prints.
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• Hao, J., McKay, T. A., Koester, B. P., Rykoff, E. S., Rozo, E., Annis, J., Wechsler, R. H., Evrard, A., Siegel, S. R., Becker, M., Busha, M., Gerdes, D., Johnston, D. E., & Sheldon, E. (2015). A GMBCG GALAXY CLUSTER CATALOG OF 55,424 RICH CLUSTERS FROM SDSS DR7. ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 191(2), 254-274.
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• {Hoshino}, H., {Leauthaud}, A., {Lackner}, C., {Hikage}, C., {Rozo}, E., {Rykoff}, E., {Mandelbaum}, R., {More}, S., {More}, A., {Saito}, S., , B. (2015). Luminous red galaxies in clusters: central occupation, spatial distributions and miscentring. \mnras, 452, 998-1013.
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• {Kirk}, D., {Omori}, Y., {Benoit-L{\'e}vy}, A., {Cawthon}, R., {Chang}, C., {Larsen}, P., {Amara}, A., {Bacon}, D., {Crawford}, T., {Dodelson}, S., {Fosalba}, P., {Giannantonio}, T., {Holder}, G., {Jain}, B., {Kacprzak}, T., {Lahav}, O., {MacCrann}, N., {Nicola}, A., {Refregier}, A., , {Sheldon}, E., et al. (2015). Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing. ArXiv e-prints.
• {Kosyra}, R., {Gruen}, D., {Seitz}, S., {Mana}, A., {Rozo}, E., {Rykoff}, E., {Sanchez}, A., , R. (2015). Environment-based selection effects of Planck clusters. \mnras, 452, 2353-2366.
• {Leistedt}, B., {Peiris}, H., {Elsner}, F., {Benoit-L{\'e}vy}, A., {Amara}, A., {Bauer}, A., {Becker}, M., {Bonnett}, C., {Bruderer}, C., {Busha}, M., {Carrasco Kind}, M., {Chang}, C., {Crocce}, M., {da Costa}, L., {Gaztanaga}, E., {Huff}, E., {Lahav}, O., {Palmese}, A., {Percival}, W., , {Refregier}, A., et al. (2015). Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data. ArXiv e-prints.
• {Li}, R., {Shan}, H., {Kneib}, J., {Mo}, H., {Rozo}, E., {Leauthaud}, A., {Moustakas}, J., {Xie}, L., {Erben}, T., {Van Waerbeke}, L., {Makler}, M., {Rykoff}, E., , B. (2015). Measuring subhalo mass in redMaPPer clusters with CFHT Stripe 82 Survey. ArXiv e-prints.
• {Old}, L., {Wojtak}, R., {Mamon}, G., {Skibba}, R., {Pearce}, F., {Croton}, D., {Bamford}, S., {Behroozi}, P., {de Carvalho}, R., {Mu{\~n}oz-Cuartas}, J., {Gifford}, D., {Gray}, M., {der Linden}, A., {Merrifield}, M., {Muldrew}, S., {M{\"u}ller}, V., {Pearson}, R., {Ponman}, T., {Rozo}, E., , {Rykoff}, E., et al. (2015). Galaxy Cluster Mass Reconstruction Project - II. Quantifying scatter and bias using contrasting mock catalogues. \mnras, 449, 1897-1920.
• {Park}, Y., {Krause}, E., {Dodelson}, S., {Jain}, B., {Amara}, A., {Becker}, M., {Bridle}, S., {Clampitt}, J., {Crocce}, M., {Fosalba}, P., {Gaztanaga}, E., {Honscheid}, K., {Rozo}, E., {Sobreira}, F., {S{\'a}nchez}, C., {Wechsler}, R., {Abbott}, T., {Abdalla}, F., {Allam}, S., , {Benoit-L{\'e}vy}, A., et al. (2015). Joint Analysis of Galaxy-Galaxy Lensing and Galaxy Clustering: Methodology and Forecasts for DES. ArXiv e-prints.
• {Pierre}, M., {Pacaud}, F., {Adami}, C., {Alis}, S., {Altieri}, B., {Baran}, B., {Benoist}, C., {Birkinshaw}, M., {Bongiorno}, A., {Bremer}, M., {Brusa}, M., {Butler}, A., {Ciliegi}, P., {Chiappetti}, L., {Clerc}, N., {Corasaniti}, P., {Coupon}, J., {De Breuck}, C., {Democles}, J., , {Desai}, S., et al. (2015). The XXL Survey: I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme. ArXiv e-prints.
• {Rhodes}, J., {Allen}, S., {Benson}, B., {Chang}, T., {de Putter}, R., {Dodelson}, S., {Dor{\'e}}, O., {Honscheid}, K., {Linder}, E., {M{\'e}nard}, B., {Newman}, J., {Nord}, B., {Rozo}, E., {Rykoff}, E., {Vallinotto}, A., , D. (2015). Exploiting cross correlations and joint analyses. Astroparticle Physics, 63, 42-54.
• {Rozo}, E., {Rykoff}, E., {Abate}, A., {Bonnett}, C., {Crocce}, M., {Davis}, C., {Hoyle}, B., {Leistedt}, B., {Peiris}, H., {Wechsler}, R., {Abbott}, T., {Abdalla}, F., {Banerji}, M., {Bauer}, A., {Benoit-L{\'e}vy}, A., {Bernstein}, G., {Bertin}, E., {Brooks}, D., {Buckley-Geer}, E., , {Burke}, D., et al. (2015). redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data. ArXiv e-prints.
• {Rozo}, E., {Rykoff}, E., {Bartlett}, J., , J. (2015). redMaPPer - III. A detailed comparison of the Planck 2013 and SDSS DR8 redMaPPer cluster catalogues. \mnras, 450, 592-605.
• {Rozo}, E., {Rykoff}, E., {Becker}, M., {Reddick}, R., , R. (2015). redMaPPer - IV. Photometric membership identification of red cluster galaxies with 1 per cent precision. \mnras, 453, 38-52.
• {Rykoff}, E., {Rozo}, E., , R. (2015). Assessing Galaxy Limiting Magnitudes in Large Optical Surveys. ArXiv e-prints.
• {Saro}, A., {Bocquet}, S., {Rozo}, E., {Benson}, B., {Mohr}, J., {Rykoff}, E., {Soares-Santos}, M., {Bleem}, L., {Dodelson}, S., {Melchior}, P., {Sobreira}, F., {Upadhyay}, V., {Weller}, J., {Abbott}, T., {Abdalla}, F., {Allam}, S., {Armstrong}, R., {Banerji}, M., {Bauer}, A., , {Bayliss}, M., et al. (2015). Constraints on the richness-mass relation and the optical-SZE positional offset distribution for SZE-selected clusters. \mnras, 454, 2305-2319.
• {Vikram}, V., {Chang}, C., {Jain}, B., {Bacon}, D., {Amara}, A., {Becker}, M., {Bernstein}, G., {Bonnett}, C., {Bridle}, S., {Brout}, D., {Busha}, M., {Frieman}, J., {Gaztanaga}, E., {Hartley}, W., {Jarvis}, M., {Kacprzak}, T., {Kov{\'a}cs}, A., {Lahav}, O., {Leistedt}, B., , {Lin}, H., et al. (2015). Wide-field lensing mass maps from Dark Energy Survey science verification data: Methodology and detailed analysis. \prd, 92, 022006.
• {Yuan}, F., {Lidman}, C., {Davis}, T., {Childress}, M., {Abdalla}, F., {Banerji}, M., {Buckley-Geer}, E., {Carnero Rosell}, A., {Carollo}, D., {Castander}, F., {D'Andrea}, C., {Diehl}, H., {Cunha}, C., {Foley}, R., {Frieman}, J., {Glazebrook}, K., {Gschwend}, J., {Hinton}, S., {Jouvel}, S., , {Kessler}, R., et al. (2015). OzDES multifibre spectroscopy for the Dark Energy Survey: first-year operation and results. \mnras, 452, 3047-3063.
• Hoshino, H., Leauthaud, A., Lackner, C., Hikage, C., Rozo, E., Rykoff, E., Mandelbaum, R., More, S., More, A., Saito, S., & Vulcani, B. (2014). Luminous red galaxies in clusters: central occupation, spatial distributions and miscentring. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 452(1), 998-1013.
• Miyatake, H., More, S., Takada, M., Spergel, D. N., Mandelbaum, R., Rykoff, E. S., & Rozo, E. (2014). Evidence of Halo Assembly Bias in Massive Clusters. PHYSICAL REVIEW LETTERS, 116(4).
• Dietrich, J. P., Zhang, Y., Song, J., Davis, C. P., McKay, T. A., Baruah, L., Becker, M., Benoist, C., Busha, M., da Costa, L. A., Hao, J., Maia, M. A., Miller, C. J., Ogando, R., Romer, A. K., Rozo, E., Rykoff, E., & Wechsler, R. (2013). Orientation bias of optically selected galaxy clusters and its impact on stacked weak-lensing analyses. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 443(2), 1713-1722.
• Rozo, E., Rykoff, E. S., Koester, B. P., McKay, T., Hao, J., Evrard, A., Wechsler, R. H., Hansen, S., Sheldon, E., Johnston, D., Becker, M., Annis, J., Bleem, L., & Scranton, R. (2013). IMPROVEMENT OF THE RICHNESS ESTIMATES OF maxBCG CLUSTERS. ASTROPHYSICAL JOURNAL, 703(1), 601-613.
• Chen, J., Rozo, E., Dalal, N., & Taylor, J. E. (2012). Astrometric perturbations in substructure lensing. ASTROPHYSICAL JOURNAL, 659(1), 52-68.
• Draper, P., Dodelson, S., Hao, J., & Rozo, E. (2012). Sunyaev-Zel'dovich signal of the maxBCG SDSS galaxy clusters in WMAP. PHYSICAL REVIEW D, 85(2).
• Rozo, E., Vikhlinin, A., & More, S. (2012). THE Y-SZ-Y-X SCALING RELATION AS DETERMINED FROM PLANCK AND CHANDRA. ASTROPHYSICAL JOURNAL, 760(1).
• Wu, H., Rozo, E., & Wechsler, R. H. (2012). THE EFFECTS OF HALO ASSEMBLY BIAS ON SELF-CALIBRATION IN GALAXY CLUSTER SURVEYS. ASTROPHYSICAL JOURNAL, 688(2), 729-741.
• Rozo, E., Wu, H., & Schmidt, F. (2011). STACKED WEAK LENSING MASS CALIBRATION: ESTIMATORS, SYSTEMATICS, AND IMPACT ON COSMOLOGICAL PARAMETER CONSTRAINTS. ASTROPHYSICAL JOURNAL, 735(2).
• Schmidt, F., Rozo, E., Dodelson, S., Hui, L., & Sheldon, E. (2011). LENSING BIAS IN COSMIC SHEAR. ASTROPHYSICAL JOURNAL, 702(1), 593-602.
• Schmidt, F., Rozo, E., Dodelson, S., Hui, L., & Sheldon, E. (2011). Size Bias in Galaxy Surveys. PHYSICAL REVIEW LETTERS, 103(5).
• Schmidt, F., & Rozo, E. (2010). WEAK-LENSING PEAK FINDING: ESTIMATORS, FILTERS, AND BIASES. ASTROPHYSICAL JOURNAL, 735(2).
• Tinker, J. L., Sheldon, E. S., Wechsler, R. H., Becker, M. R., Rozo, E., Zu, Y., Weinberg, D. H., Zehavi, I., Blanton, M. R., Busha, M. T., & Koester, B. P. (2010). COSMOLOGICAL CONSTRAINTS FROM GALAXY CLUSTERING AND THE MASS-TO-NUMBER RATIO OF GALAXY CLUSTERS. ASTROPHYSICAL JOURNAL, 745(1).
• Baxter, E. J., & Rozo, E. (2009). A MAXIMUM LIKELIHOOD APPROACH TO ESTIMATING CORRELATION FUNCTIONS. ASTROPHYSICAL JOURNAL, 779(1).
• Huterer, D., Kirkby, D., Bean, R., Connolly, A., Dawson, K., Dodelson, S., Evrard, A., Jain, B., Jarvis, M., Linder, E., Mandelbaum, R., May, M., Raccanelli, A., Reid, B., Rozo, E., Schmidt, F., Sehgal, N., Slosar, A., van Engelen, A., , Wu, H., et al. (2009). Growth of cosmic structure: Probing dark energy beyond expansion. ASTROPARTICLE PHYSICS, 63, 23-41.
• Rozo, E., Nagai, D., Keeton, C., & Kravtsov, A. (2009). THE IMPACT OF BARYONIC COOLING ON GIANT ARC ABUNDANCES. ASTROPHYSICAL JOURNAL, 687(1), 22-38.
• Rozo, E., Rykoff, E. S., Evrard, A., Becker, M., McKay, T., Wechsler, R. H., Koester, B. P., Hao, J., Hansen, S., Sheldon, E., Johnston, D., Annis, J., & Frieman, J. (2009). CONSTRAINING THE SCATTER IN THE MASS-RICHNESS RELATION OF maxBCG CLUSTERS WITH WEAK LENSING AND X-RAY DATA. ASTROPHYSICAL JOURNAL, 699(1), 768-781.
• Wu, H., Rozo, E., & Wechsler, R. H. (2009). ANNEALING A FOLLOW-UP PROGRAM: IMPROVEMENT OF THE DARK ENERGY FIGURE OF MERIT FOR OPTICAL GALAXY CLUSTER SURVEYS. ASTROPHYSICAL JOURNAL, 713(2), 1207-1218.
• Rozo, E., Rykoff, E., Koester, B., Nord, B., Wu, H., Evrard, A., & Wechsler, R. (2008). EXTRINSIC SOURCES OF SCATTER IN THE RICHNESS-MASS RELATION OF GALAXY CLUSTERS. ASTROPHYSICAL JOURNAL, 740(2).
• Zu, Y., Weinberg, D. H., Rozo, E., Sheldon, E. S., Tinker, J. L., & Becker, M. R. (2008). Cosmological constraints from the large-scale weak lensing of SDSS MaxBCG clusters. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 439(2), 1628-1647.
• Hao, J., Koester, B. P., Mckay, T. A., Rykoff, E. S., Rozo, E., Evrard, A., Annis, J., Becker, M., Busha, M., Gerdes, D., Johnston, D. E., Sheldon, E., & Wechsler, R. H. (2007). PRECISION MEASUREMENTS OF THE CLUSTER RED SEQUENCE USING AN ERROR-CORRECTED GAUSSIAN MIXTURE MODEL. ASTROPHYSICAL JOURNAL, 702(1), 745-758.
• Rozo, E., Wechsler, R. H., Rykoff, E. S., Annis, J. T., Becker, M. R., Evrard, A. E., Frieman, J. A., Hansen, S. M., Hao, J., Johnston, D. E., Koester, B. P., McKay, T. A., Sheldon, E. S., & Weinberg, D. H. (2007). COSMOLOGICAL CONSTRAINTS FROM THE SLOAN DIGITAL SKY SURVEY MaxBCG CLUSTER CATALOG. ASTROPHYSICAL JOURNAL, 708(1), 645-660.

Proceedings Publications

• McCall, H., Scolnic, D., Rozo, E., Rykoff, E., & Kessler, R. (2019, Jan). Supernova Cosmology with Luminous Red Galaxies. In American Astronomical Society Meeting Abstracts \#233, 233.
• Hayden, B., Aldering, G., Amanullah, R., Barbary, K., Bohringer, H., Boone, K. R., Brodwin, M., Cunha, C., Currie, M., Deustua, S., Dixon, S., Eisenhardt, P., Fassbender, R., Fruchter, A., Gladders, M., Gonzalez, A., Goobar, A., Hildebrandt, H., Hilton, M., , Hoekstra, H., et al. (2018, Jan). See Change: Cosmology Analysis Update for the Supernova Cosmology Project High-z Cluster Supernova Survey. In American Astronomical Society Meeting Abstracts \#231, 231.
• Johnson, E., Scolnic, D., Kessler, R., Rykoff, E., & Rozo, E. (2018, Jan). Supernova Cosmology Without Spectroscopy. In American Astronomical Society Meeting Abstracts \#231, 231.
• Shin, T., Clampitt, J., Jain, B., Bernstein, G., Neil, A., Rozo, E., & Rykoff, E. (2018, Jan). The ellipticity of galaxy cluster halos from satellite galaxies and weak lensing. In APS April Meeting Abstracts, 2018.

Presentations

• Rozo, E. (2015, February). Lessons from redmapper in DES. LSST DESC Collaboration Meeting.
• Rozo, E. (2015, February). redmagic. LSST DESC Collaboration Meeting.
• Rozo, E. (2015, January). DESI C3 Science Readiness. DESI Collaboration Meeting.
• Rozo, E. (2014, December). redmapper and redmagic. University of Michigan Physics Colloquium.
• Rozo, E. (2014, November). Cosmology with Optical Cluster Surveys. Madrid Cluster Conference.
• Rozo, E. (2014, November). redmagic. DESI Collaboration Meeting.
• Rozo, E. (2014, October). redmagic. DES Sussex Collaboration Meeting.
• Rozo, E. (2014, October). redmapper Membership Probabilities. Sussex DES Collaboration Meeting.
• Rozo, E. (2014, September). Planck Cosmology and Galaxy Clusters. Brazil Web Seminar.

Reviews

• Koester, B. P., McKay, T. A., Annis, J., Wechsler, R. H., Evrard, A. E., Rozo, E., Bleem, L., Sheldon, E. S., & Johnston, D. (2015. MaxBCG: A red-sequence galaxy cluster finder(pp 221-238).
• Weinberg, D. H., Mortonson, M. J., Eisenstein, D. J., Hirata, C., Riess, A. G., & Rozo, E. (2010. Observational probes of cosmic acceleration(pp 87-255).