arXiv subjects

M. T. Busha

Publications and source records attributed to M. T. Busha.

15 recordsLinked to original sources

arXiv2019

Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

We present cosmological results from a combined analysis of galaxy clustering and weak gravitational lensing, using 1321 deg$^2$ of $griz$ imaging data from the first year of the Dark Energy Survey (DES Y1). We combine three two-point functions: (i) the cosmic shear correlation function of 26 million source galaxies in four redshift bins, (ii) the galaxy angular autocorrelation function of 650,000 luminous red galaxies in five redshift bins, and (iii) the galaxy-shear cross-correlation of luminous red galaxy positions and source galaxy shears. To demonstrate the robustness of these results, we use independent pairs of galaxy shape, photometric redshift estimation and validation, and likelihood analysis pipelines. To prevent confirmation bias, the bulk of the analysis was carried out while blind to the true results; we describe an extensive suite of systematics checks performed and passed during this blinded phase. The data are modeled in flat $Λ$CDM and $w$CDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for $Λ$CDM) or 7 (for $w$CDM) cosmological parameters including the neutrino mass density and including the 457 $\times$ 457 element analytic covariance matrix. We find consistent cosmological results from these three two-point functions, and from their combination obtain $S_8 \equiv σ_8 (Ω_m/0.3)^{0.5} = 0.783^{+0.021}_{-0.025}$ and $Ω_m = 0.264^{+0.032}_{-0.019}$ for $Λ$CDM for $w$CDM, we find $S_8 = 0.794^{+0.029}_{-0.027}$, $Ω_m = 0.279^{+0.043}_{-0.022}$, and $w=-0.80^{+0.20}_{-0.22}$ at 68% CL. The precision of these DES Y1 results rivals that from the Planck cosmic microwave background measurements, allowing a comparison of structure in the very early and late Universe on equal terms. Although the DES Y1 best-fit values for $S_8$ and $Ω_m$ are lower than the central values from Planck ...

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arXiv2018

DES Y1 Results: Validating cosmological parameter estimation using simulated Dark Energy Surveys

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input cosmology is consistent with the combined constraints from multiple simulated DES Y1 realizations in the $Ω_m-σ_8$ plane. For one of the suites, we are able to show with high confidence that any biases in the inferred $S_8=σ_8(Ω_m/0.3)^{0.5}$ and $Ω_m$ are smaller than the DES Y1 $1-σ$ uncertainties. For the other suite, for which we have fewer realizations, we are unable to be this conclusive; we infer a roughly 70% probability that systematic biases in the recovered $Ω_m$ and $S_8$ are sub-dominant to the DES Y1 uncertainty. As cosmological analyses of this kind become increasingly more precise, validation of parameter inference using survey simulations will be essential to demonstrate robustness.

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arXiv2018

Dark Energy Survey Year 1 Results: Redshift distributions of the weak lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the galaxies used as weak lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z=0.2 and 1.3, and to produce initial estimates of the lensing-weighted redshift distributions $n^i_{PZ}(z)$ for bin i. Accurate determination of cosmological parameters depends critically on knowledge of $n^i$ but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts $n^i(z)=n^i_{PZ}(z-Δz^i)$ to correct the mean redshift of $n^i(z)$ for biases in $n^i_{\rm PZ}$. The $Δz^i$ are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the COSMOS field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the $Δz^i$ are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15<z<0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the $n^i(z)$ beyond the choice of $Δz^i$. The clustering and COSMOS validation methods produce consistent estimates of $Δz^i$, with combined uncertainties of $σ_{Δz^i}=$0.015, 0.013, 0.011, and 0.022 in the four bins. We marginalize over these in all analyses to follow, which does not diminish the constraining power significantly. Repeating the photo-z procedure using the Directional Neighborhood Fitting (DNF) algorithm instead of BPZ, or using the $n^i(z)$ directly estimated from COSMOS, yields no discernible difference in cosmological inferences.

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arXiv2017

Dark Energy Survey Year 1 Results: Curved-Sky Weak Lensing Mass Map

We construct the largest curved-sky galaxy weak lensing mass map to date from the DES first-year (DES Y1) data. The map, about 10 times larger than previous work, is constructed over a contiguous $\approx1,500 $deg$^2$, covering a comoving volume of $\approx10 $Gpc$^3$. The effects of masking, sampling, and noise are tested using simulations. We generate weak lensing maps from two DES Y1 shear catalogs, Metacalibration and Im3shape, with sources at redshift $0.2<z<1.3,$ and in each of four bins in this range. In the highest signal-to-noise map, the ratio between the mean signal-to-noise in the E-mode and the B-mode map is $\sim$1.5 ($\sim$2) when smoothed with a Gaussian filter of $σ_{G}=30$ (80) arcminutes. The second and third moments of the convergence $κ$ in the maps are in agreement with simulations. We also find no significant correlation of $κ$ with maps of potential systematic contaminants. Finally, we demonstrate two applications of the mass maps: (1) cross-correlation with different foreground tracers of mass and (2) exploration of the largest peaks and voids in the maps.

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arXiv2017

Cosmology from Cosmic Shear with DES Science Verification Data

We present the first constraints on cosmology from the Dark Energy Survey (DES), using weak lensing measurements from the preliminary Science Verification (SV) data. We use 139 square degrees of SV data, which is less than 3\% of the full DES survey area. Using cosmic shear 2-point measurements over three redshift bins we find $σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.81 \pm 0.06$ (68\% confidence), after marginalising over 7 systematics parameters and 3 other cosmological parameters. We examine the robustness of our results to the choice of data vector and systematics assumed, and find them to be stable. About $20$\% of our error bar comes from marginalising over shear and photometric redshift calibration uncertainties. The current state-of-the-art cosmic shear measurements from CFHTLenS are mildly discrepant with the cosmological constraints from Planck CMB data; our results are consistent with both datasets. Our uncertainties are $\sim$30\% larger than those from CFHTLenS when we carry out a comparable analysis of the two datasets, which we attribute largely to the lower number density of our shear catalogue. We investigate constraints on dark energy and find that, with this small fraction of the full survey, the DES SV constraints make negligible impact on the Planck constraints. The moderate disagreement between the CFHTLenS and Planck values of $σ_8 (Ω_{\rm m}/0.3)^{0.5}$ is present regardless of the value of $w$.

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arXiv2016

Cosmic Shear Measurements with DES Science Verification Data

We present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix or im3shape, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our results pass a suite of null tests including tests for B-mode contamination and direct tests for any dependence of the two-point functions on a set of 16 observing conditions and galaxy properties, such as seeing, airmass, galaxy color, galaxy magnitude, etc. We furthermore use a large suite of simulations to compute the covariance matrix of the cosmic shear measurements and assign statistical significance to our null tests. We find that our covariance matrix is consistent with the halo model prediction, indicating that it has the appropriate level of halo sample variance. We compare the same jackknife procedure applied to the data and the simulations in order to search for additional sources of noise not captured by the simulations. We find no statistically significant extra sources of noise in the data. The overall detection significance with tomography for our highest source density catalog is 9.7sigma. Cosmological constraints from the measurements in this work are presented in a companion paper (DES et al. 2015).

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arXiv2015

Redshift distributions of galaxies in the DES Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods -- ANNZ2, BPZ calibrated against BCC-Ufig simulations, SkyNet, and TPZ -- are analysed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-zs. From the galaxies in the DES SV shear catalogue, which have mean redshift $0.72\pm0.01$ over the range $0.3<z<1.3$, we construct three tomographic bins with means of $z=\{0.45, 0.67, 1.00\}$. These bins each have systematic uncertainties $δz \lesssim 0.05$ in the mean of the fiducial SkyNet photo-z $n(z)$. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of $σ_8$ of approx. 3%. This shift is within the one sigma statistical errors on $σ_8$ for the DES SV shear catalog. We further study the potential impact of systematic differences on the critical surface density, $Σ_{\mathrm{crit}}$, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of $n(z)$ of width $0.05$ for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis.

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arXiv2015

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources 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 in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.

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arXiv2015

Star/galaxy separation at faint magnitudes: Application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the Gravitational Weak Lensing and Large Scale Structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by Point Spread Function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper. We first use Principal Component Analysis to outline the correlations between the objects parameters and extract from it the most relevant information. We then use the reduced set of parameters as input to an Artificial Neural Network. This multi-parameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SExtractor), especially at faint magnitudes: it increases the purity by up to 20% for stars and by up to 12% for galaxies, at i-magnitude fainter than 23.

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arXiv2015

Modelling the Transfer Function for the Dark Energy Survey

We present a forward-modelling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function -- a mapping from cosmological and astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator, Berge et al. 2013) and catalogs representative of the DES data. In this work we simulate the 244 sq. deg coadd images and catalogs in 5 bands for the DES Science Verification (SV) data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples, star/galaxy classification and proximity effects on object detection, are then used to demonstrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modelling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies which is sufficiently realistic and highly controllable.

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arXiv2014

redMaPPer I: Algorithm and SDSS DR8 Catalog

We describe redMaPPer, a new red-sequence cluster finder specifically designed to make optimal use of ongoing and near-future large photometric surveys. The algorithm has multiple attractive features: (1) It can iteratively self-train the red-sequence model based on minimal spectroscopic training sample, an important feature for high redshift surveys; (2) It can handle complex masks with varying depth; (3) It produces cluster-appropriate random points to enable large-scale structure studies; (4) All clusters are assigned a full redshift probability distribution P(z); (5) Similarly, clusters can have multiple candidate central galaxies, each with corresponding centering probabilities; (6) The algorithm is parallel and numerically efficient: it can run a Dark Energy Survey-like catalog in ~500 CPU hours; (7) The algorithm exhibits excellent photometric redshift performance, the richness estimates are tightly correlated with external mass proxies, and the completeness and purity of the corresponding catalogs is superb. We apply the redMaPPer algorithm to ~10,000 deg^2 of SDSS DR8 data, and present the resulting catalog of ~25,000 clusters over the redshift range 0.08<z<0.55. The redMaPPer photometric redshifts are nearly Gaussian, with a scatter σ_z ~ 0.006 at z~0.1, increasing to σ_z~0.02 at z~0.5 due to increased photometric noise near the survey limit. The median value for |Δz|/(1+z) for the full sample is 0.006. The incidence of projection effects is low (<=5%). Detailed performance comparisons of the redMaPPer DR8 cluster catalog to X-ray and SZ catalogs are presented in a companion paper (Rozo & Rykoff 2014).

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arXiv2014

The Blanco Cosmology Survey: An Optically-Selected Galaxy Cluster Catalog and a Public Release of Optical Data Products

The Blanco Cosmology Survey is 4-band (griz) optical-imaging survey that covers ~80 square degrees of the southern sky. The survey consists of two fields roughly centered at (RA,DEC) = (23h,-55d) and (5h30m,-53d) with imaging designed to reach depths sufficient for the detection of L* galaxies out to a redshift of one. In this paper we describe the reduction of the survey data, the creation of calibrated source catalogs and a new method for the separation of stars and galaxies. We search these catalogs for galaxy clusters at z< 0.75 by identifying spatial over-densities of red-sequence galaxies. We report the coordinates, redshift, and optical richness, Lambda, for 764 detected galaxy clusters at z < 0.75. This sample, >85% of which are new discoveries, has a median redshift of 0.52 and median richness Lambda(0.4L*) of 16.4. Accompanying this paper we also release data products including the reduced images and calibrated source catalogs. These products are available at http://data.rcc.uchicago.edu/dataset/blanco-cosmology-survey .

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arXiv2013

Detecting Massive Galaxies at High Redshift using the Dark Energy Survey

The Dark Energy Survey (DES) will be unprecedented in its ability to probe exceptionally large cosmic volumes to relatively faint optical limits. Primarily designed for the study of comparatively low redshift (z<2) galaxies with the aim of constraining dark energy, an intriguing byproduct of the survey will be the identification of massive (>10^(12.0) M_sun) galaxies at z>~4. This will greatly improve our understanding of how galaxies form and evolve. By both passively evolving the low redshift mass function and extrapolating the observed high redshift mass function, we find that such galaxies should be rare but nonetheless present at early times, with predicted number densities of ~0.02 deg^-2. The unique combination of depth and coverage that DES provides will allow the identification of such galaxies should they exist - potentially identifying hundreds of such sources. We then model possible high redshift galaxies and determine their detectability using the DES filter sets and depths. We model sources with a broad range stellar properties and find that for these galaxies to be detected they must be either sufficiently young, high mass and/or relatively dust free (E(B-V)<0.45) - with these parameters jointly affecting each galaxy's detectability. We also propose colour-colour selection criteria for the identification of both pristine and dusty sources and find that, although contamination fractions will be high, the most reliable candidate massive high redshift galaxies are likely to be identifiable in the DES data through prioritisation of colour-selected sources.

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arXiv2012

A Measurement of the Correlation of Galaxy Surveys with CMB Lensing Convergence Maps from the South Pole Telescope

We compare cosmic microwave background lensing convergence maps derived from South Pole Telescope (SPT) data with galaxy survey data from the Blanco Cosmology Survey, the Wide-field Infrared Survey Explorer, and a new large Spitzer/IRAC field designed to overlap with the SPT survey. Using optical and infrared catalogs covering between 17 and 68 square degrees of sky, we detect correlation between the SPT convergence maps and each of the galaxy density maps at >4 sigma, with zero cross-correlation robustly ruled out in all cases. The amplitude and shape of the cross-power spectra are in good agreement with theoretical expectations and the measured galaxy bias is consistent with previous work. The detections reported here utilize a small fraction of the full 2500 square degree SPT survey data and serve as both a proof of principle of the technique and an illustration of the potential of this emerging cosmological probe.

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arXiv2011

A theoretical framework for combining techniques that probe the link between galaxies and dark matter

We develop a theoretical framework that combines measurements of galaxy-galaxy lensing, galaxy clustering, and the galaxy stellar mass function in a self-consistent manner. While considerable effort has been invested in exploring each of these probes individually, attempts to combine them are still in their infancy despite the potential of such combinations to elucidate the galaxy-dark matter connection, to constrain cosmological parameters, and to test the nature of gravity. In this paper, we focus on a theoretical model that describes the galaxy-dark matter connection based on standard halo occupation distribution techniques. Several key modifications enable us to extract additional parameters that determine the stellar-to-halo mass relation and to simultaneously fit data from multiple probes while allowing for independent binning schemes for each probe. In a companion paper, we demonstrate that the model presented here provides an excellent fit to galaxy-galaxy lensing, galaxy clustering, and stellar mass functions measured in the COSMOS survey from z=0.2 to z=1.0. We construct mock catalogs from numerical simulations to investigate the effects of sample variance and covariance on each of the three probes. Finally, we analyze and discuss how trends in each of the three observables impact the derived parameters of the model. In particular, we investigate the various features of the observed galaxy stellar mass function (low-mass slope, plateau, knee, and high-mass cut-off) and show how each feature is related to the underlying relationship between stellar and halo mass. We demonstrate that the observed plateau feature in the stellar mass function at Mstellar~2x10^10 Msun is due to the transition that occurs in the stellar-to-halo mass relation at Mhalo ~ 10^12 Msun from a low-mass power-law regime to a sub-exponential function at higher stellar mass.

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