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B. Hoyle

Publications and source records attributed to B. Hoyle.

104 records · Page 6Linked to original sources

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear

We use 26 million galaxies from the Dark Energy Survey (DES) Year 1 shape catalogs over 1321 deg$^2$ of the sky to produce the most significant measurement of cosmic shear in a galaxy survey to date. We constrain cosmological parameters in both the flat $Λ$CDM and $w$CDM models, while also varying the neutrino mass density. These results are shown to be robust using two independent shape catalogs, two independent \photoz\ calibration methods, and two independent analysis pipelines in a blind analysis. We find a 3.5\% fractional uncertainty on $σ_8(Ω_m/0.3)^{0.5} = 0.782^{+0.027}_{-0.027}$ at 68\% CL, which is a factor of 2.5 improvement over the fractional constraining power of our DES Science Verification results. In $w$CDM, we find a 4.8\% fractional uncertainty on $σ_8(Ω_m/0.3)^{0.5} = 0.777^{+0.036}_{-0.038}$ and a dark energy equation-of-state $w=-0.95^{+0.33}_{-0.39}$. We find results that are consistent with previous cosmic shear constraints in $σ_8$ -- $Ω_m$, and see no evidence for disagreement of our weak lensing data with data from the CMB. 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 double the effective integrated exposure time per galaxy.

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Weak lensing magnification in the Dark Energy Survey Science Verification Data

In this paper the effect of weak lensing magnification on galaxy number counts is studied by cross-correlating the positions of two galaxy samples, separated by redshift, using data from the Dark Energy Survey Science Verification dataset. The analysis is carried out for two photometrically-selected galaxy samples, with mean photometric redshifts in the $0.2 < z < 0.4$ and $0.7 < z < 1.0$ ranges, in the riz bands. A signal is detected with a $3.5σ$ significance level in each of the bands tested, and is compatible with the magnification predicted by the $Λ$CDM model. After an extensive analysis, it cannot be attributed to any known systematic effect. The detection of the magnification signal is robust to estimated uncertainties in the outlier rate of the pho- tometric redshifts, but this will be an important issue for use of photometric redshifts in magnification mesurements from larger samples. In addition to the detection of the magnification signal, a method to select the sample with the maximum signal-to-noise is proposed and validated with data.

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Stellar Streams Discovered in the Dark Energy Survey

We perform a search for stellar streams around the Milky Way using the first three years of multi-band optical imaging data from the Dark Energy Survey (DES). We use DES data covering $\sim 5000$ sq. deg. to a depth of $g > 23.5$ with a relative photometric calibration uncertainty of $< 1 \%$. This data set yields unprecedented sensitivity to the stellar density field in the southern celestial hemisphere, enabling the detection of faint stellar streams to a heliocentric distance of $\sim 50$ kpc. We search for stellar streams using a matched-filter in color-magnitude space derived from a synthetic isochrone of an old, metal-poor stellar population. Our detection technique recovers four previously known thin stellar streams: Phoenix, ATLAS, Tucana III, and a possible extension of Molonglo. In addition, we report the discovery of eleven new stellar streams. In general, the new streams detected by DES are fainter, more distant, and lower surface brightness than streams detected by similar techniques in previous photometric surveys. As a by-product of our stellar stream search, we find evidence for extra-tidal stellar structure associated with four globular clusters: NGC 288, NGC 1261, NGC 1851, and NGC 1904. The ever-growing sample of stellar streams will provide insight into the formation of the Galactic stellar halo, the Milky Way gravitational potential, as well as the large- and small-scale distribution of dark matter around the Milky Way.

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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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Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data

We combine Dark Energy Survey Year 1 clustering and weak lensing data with Baryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN) experiments to constrain the Hubble constant. Assuming a flat $Λ$CDM model with minimal neutrino mass ($\sum m_ν= 0.06$ eV) we find $H_0=67.2^{+1.2}_{-1.0}$ km/s/Mpc (68% CL). This result is completely independent of Hubble constant measurements based on the distance ladder, Cosmic Microwave Background (CMB) anisotropies (both temperature and polarization), and strong lensing constraints. There are now five data sets that: a) have no shared observational systematics; and b) each constrain the Hubble constant with a few percent level precision. We compare these five independent measurements, and find that, as a set, the differences between them are significant at the $2.1σ$ level ($χ^2/dof=20.1/11$, probability to exceed=4%). This difference is low enough that we consider the data sets statistically consistent with each other. The best fit Hubble constant obtained by combining all five data sets is $H_0 = 69.1^{+0.4}_{-0.6}$ km/s/Mpc.

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Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts in the DES -- Calibration of the Weak Lensing Source Redshift Distributions

We present the calibration of the Dark Energy Survey Year 1 (DES Y1) weak lensing source galaxy redshift distributions from clustering measurements. By cross-correlating the positions of source galaxies with luminous red galaxies selected by the redMaGiC algorithm we measure the redshift distributions of the source galaxies as placed into different tomographic bins. These measurements constrain any such shifts to an accuracy of $\sim0.02$ and can be computed even when the clustering measurements do not span the full redshift range. The highest-redshift source bin is not constrained by the clustering measurements because of the minimal redshift overlap with the redMaGiC galaxies. We compare our constraints with those obtained from $\texttt{COSMOS}$ 30-band photometry and find that our two very different methods produce consistent constraints.

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Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-$z$ methods applied to the same source galaxy sample. We apply the method to three photo-$z$ 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, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-$z$'s. The systematic uncertainty in the mean redshift bias of the source galaxy sample is $Δz \lesssim 0.02$, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

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The redMaPPer Galaxy Cluster Catalog From DES Science Verification Data

We describe updates to the \redmapper{} algorithm, a photometric red-sequence cluster finder specifically designed for large photometric surveys. The updated algorithm is applied to $150\,\mathrm{deg}^2$ of Science Verification (SV) data from the Dark Energy Survey (DES), and to the Sloan Digital Sky Survey (SDSS) DR8 photometric data set. The DES SV catalog is locally volume limited, and contains 786 clusters with richness $λ>20$ (roughly equivalent to $M_{\rm{500c}}\gtrsim10^{14}\,h_{70}^{-1}\,M_{\odot}$) and $0.2<z<0.9$. The DR8 catalog consists of 26311 clusters with $0.08<z<0.6$, with a sharply increasing richness threshold as a function of redshift for $z\gtrsim 0.35$. The photometric redshift performance of both catalogs is shown to be excellent, with photometric redshift uncertainties controlled at the $σ_z/(1+z)\sim 0.01$ level for $z\lesssim0.7$, rising to $\sim0.02$ at $z\sim0.9$ in DES SV. We make use of \emph{Chandra} and \emph{XMM} X-ray and South Pole Telescope Sunyaev-Zeldovich data to show that the centering performance and mass--richness scatter are consistent with expectations based on prior runs of \redmapper{} on SDSS data. We also show how the \redmapper{} \photoz{} and richness estimates are relatively insensitive to imperfect star/galaxy separation and small-scale star masks.

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Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data I: Stellar Mass Growth of Bright Central Galaxies Since z~1.2

Using the science verification data of the Dark Energy Survey (DES) for a new sample of 106 X-Ray selected clusters and groups, we study the stellar mass growth of Bright Central Galaxies (BCGs) since redshift 1.2. Compared with the expectation in a semi-analytical model applied to the Millennium Simulation, the observed BCGs become under-massive/under-luminous with decreasing redshift. We incorporate the uncertainties associated with cluster mass, redshift, and BCG stellar mass measurements into analysis of a redshift-dependent BCG-cluster mass relation, $m_{*}\propto(\frac{M_{200}}{1.5\times 10^{14}M_{\odot}})^{0.24\pm 0.08}(1+z)^{-0.19\pm0.34}$, and compare the observed relation to the model prediction. We estimate the average growth rate since $z = 1.0$ for BCGs hosted by clusters of $M_{200, z}=10^{13.8}M_{\odot}$, at $z=1.0$: $m_{*, BCG}$ appears to have grown by $0.13\pm0.11$ dex, in tension at $\sim 2.5 σ$ significance level with the $0.40$ dex growth rate expected from the semi-analytic model. We show that the buildup of extended intra-cluster light after $z=1.0$ may alleviate this tension in BCG growth rates.

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redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the color-cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photozs are very nearly as accurate as the best machine-learning based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalog sampling the redshift range $z\in[0.2,0.8]$. 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 $(σ_z/(1+z))$ of 0.005 and 0.017 respectively. The corresponding $5σ$ outlier fraction is 1.4%. We also test our algorithm with 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 at the 0.1% level.

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Optical Confirmation and Redshift Estimation of the Planck Cluster Candidates overlapping the Pan-STARRS Survey

We report results of a study of Planck Sunyaev-Zel'dovich effect (SZE) selected galaxy cluster candidates using the Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) imaging data. We first examine 150 Planck confirmed galaxy clusters with spectroscopic redshifts to test our algorithm for identifying optical counterparts and measuring their redshifts; our redshifts have a typical accuracy of $σ_{z/(1+z)} \sim 0.022$ for this sample. Using 60 random sky locations, we estimate that our chance of contamination through a random superposition is ~ 3 per cent. We then examine an additional 237 Planck galaxy cluster candidates that have no redshift in the source catalogue. Of these 237 unconfirmed cluster candidates we are able to confirm 60 galaxy clusters and measure their redshifts. A further 83 candidates are so heavily contaminated by stars due to their location near the Galactic plane that we do not attempt to identify counterparts. For the remaining 94 candidates we find no optical counterpart but use the depth of the Pan-STARRS1 data to estimate a redshift lower limit $z_{\text{lim}(10^{15})}$ beyond which we would not have expected to detect enough galaxies for confirmation. Scaling from the already published Planck sample, we expect that $\sim$12 of these unconfirmed candidates may be real clusters.

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Galaxy And Mass Assembly (GAMA): Spectroscopic analysis

The Galaxy And Mass Assembly (GAMA) survey is a multiwavelength photometric and spectroscopic survey, using the AAOmega spectrograph on the Anglo-Australian Telescope to obtain spectra for up to ~300000 galaxies over 280 square degrees, to a limiting magnitude of r_pet < 19.8 mag. The target galaxies are distributed over 0<z<0.5 with a median redshift of z~0.2, although the redshift distribution includes a small number of systems, primarily quasars, at higher redshifts, up to and beyond z=1. The redshift accuracy ranges from sigma_v~50km/s to sigma_v~100km/s depending on the signal-to-noise of the spectrum. Here we describe the GAMA spectroscopic reduction and analysis pipeline. We present the steps involved in taking the raw two-dimensional spectroscopic images through to flux-calibrated one-dimensional spectra. The resulting GAMA spectra cover an observed wavelength range of 3750<lambda<8850 A at a resolution of R~1300. The final flux calibration is typically accurate to 10-20%, although the reliability is worse at the extreme wavelength ends, and poorer in the blue than the red. We present details of the measurement of emission and absorption features in the GAMA spectra. These measurements are characterised through a variety of quality control analyses detailing the robustness and reliability of the measurements. We illustrate the quality of the measurements with a brief exploration of elementary emission line properties of the galaxies in the GAMA sample. We demonstrate the luminosity dependence of the Balmer decrement, consistent with previously published results, and explore further how Balmer decrement varies with galaxy mass and redshift. We also investigate the mass and redshift dependencies of the [NII]/Halpha vs [OIII]/Hbeta spectral diagnostic diagram, commonly used to discriminate between star forming and nuclear activity in galaxies.

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The XMM Cluster Survey: The build up of stellar mass in Brightest Cluster Galaxies at high redshift

We present deep J and Ks band photometry of 20 high redshift galaxy clusters between z=0.8-1.5, 19 of which are observed with the MOIRCS instrument on the Subaru Telescope. By using near-infrared light as a proxy for stellar mass we find the surprising result that the average stellar mass of Brightest Cluster Galaxies (BCGs) has remained constant at ~9e11MSol since z~1.5. We investigate the effect on this result of differing star formation histories generated by three well known and independent stellar population codes and find it to be robust for reasonable, physically motivated choices of age and metallicity. By performing Monte Carlo simulations we find that the result is unaffected by any correlation between BCG mass and cluster mass in either the observed or model clusters. The large stellar masses imply that the assemblage of these galaxies took place at the same time as the initial burst of star formation. This result leads us to conclude that dry merging has had little effect on the average stellar mass of BCGs over the last 9-10 Gyr in stark contrast to the predictions of semi-analytic models, based on the hierarchical merging of dark matter haloes, which predict a more protracted mass build up over a Hubble time. We discuss however that there is potential for reconciliation between observation and theory if there is a significant growth of material in the intracluster light over the same period.

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Radio Weak Gravitational Lensing with VLA and MERLIN

We carry out an exploratory weak gravitational lensing analysis on a combined VLA and MERLIN radio data set: a deep (3.3 micro-Jy beam^-1 rms noise) 1.4 GHz image of the Hubble Deep Field North. We measure the shear estimator distribution at this radio sensitivity for the first time, finding a similar distribution to that of optical shear estimators for HST ACS data in this field. We examine the residual systematics in shear estimation for the radio data, and give cosmological constraints from radio-optical shear cross-correlation functions. We emphasize the utility of cross-correlating shear estimators from radio and optical data in order to reduce the impact of systematics. Unexpectedly we find no evidence of correlation between optical and radio intrinsic ellipticities of matched objects; this result improves the properties of optical-radio lensing cross-correlations. We explore the ellipticity distribution of the radio counterparts to optical sources statistically, confirming the lack of correlation; as a result we suggest a connected statistical approach to radio shear measurements.

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