arXiv subjects

Rachel Mandelbaum

Publications and source records attributed to Rachel Mandelbaum.

At least 145 records · Page 8Linked to original sources

arXiv2017

Two- and three-dimensional wide-field weak lensing mass maps from the Hyper Suprime-Cam Subaru Strategic Program S16A data

We present wide-field (167 deg$^2$) weak lensing mass maps from the Hyper Supreme-Cam Subaru Strategic Program (HSC-SSP). We compare these weak lensing based dark matter maps with maps of the distribution of the stellar mass associated with luminous red galaxies. We find a strong correlation between these two maps with a correlation coefficient of $ρ=0.54\pm0.03$ (for a smoothing size of $8'$). This correlation is detected even with a smaller smoothing scale of $2'$ ($ρ=0.34\pm 0.01$). This detection is made uniquely possible because of the high source density of the HSC-SSP weak lensing survey ($\bar{n}\sim 25$ arcmin$^{-2}$). We also present a variety of tests to demonstrate that our maps are not significantly affected by systematic effects. By using the photometric redshift information associated with source galaxies, we reconstruct a three-dimensional mass map. This three-dimensional mass map is also found to correlate with the three-dimensional galaxy mass map. Cross-correlation tests presented in this paper demonstrate that the HSC-SSP weak lensing mass maps are ready for further science analyses.

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arXiv2017

On the Level of Cluster Assembly Bias in SDSS

Recently, several studies have discovered a strong discrepancy between the large-scale clustering biases of two subsamples of galaxy clusters at the same halo mass, split by their average projected membership distances $R_{\mathrm{mem}}$. The level of this discrepancy significantly exceeds the maximum halo assembly bias signal predicted by LCDM. In this study, we explore whether some of the clustering bias differences could be caused by biases in $R_{\mathrm{mem}}$ due to projection effects from other systems along the line-of-sight. We thoroughly investigate the halo assembly bias of the photometrically-detected redMaPPer clusters in SDSS, by defining a new variant of the average membership distance estimator $\tilde{R}_{\mathrm{mem}}$ that is more robust against projection effects in the cluster membership identification. Using the angular mark correlation functions of clusters, we show 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 a ratio of $1.02\pm0.14$ between the two clustering biases as measured from weak lensing. Using a realistic mock cluster catalog, we predict that the bias ratio between two $\tilde{R}_{\mathrm{mem}}$-split subsamples should be $<1.10$, which is at least 60% weaker than the maximum halo assembly bias signal (1.24) when split by halo concentration. Therefore, our results demonstrate that the level of halo assembly bias exhibited by redMaPPer clusters in SDSS is consistent with the LCDM prediction. With a ten-fold increase in cluster numbers, deeper ongoing surveys will enable a more robust detection of halo assembly bias. Our findings also have important implications for how projection effects and their impact on cluster cosmology can be quantified in photometric cluster catalogs.

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arXiv2017

The Hyper Suprime-Cam Software Pipeline

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

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arXiv2017

Characterization and Photometric Performance of the Hyper Suprime-Cam Software Pipeline

The Subaru Strategic Program (SSP) is an ambitious multi-band survey using the Hyper Suprime-Cam (HSC) on the Subaru telescope. The Wide layer of the SSP is both wide and deep, reaching a detection limit of i~26.0 mag. At these depths, it is challenging to achieve accurate, unbiased, and consistent photometry across all five bands. The HSC data are reduced using a pipeline that builds on the prototype pipeline for the Large Synoptic Survey Telescope. We have developed a Python-based, flexible framework to inject synthetic galaxies into real HSC images called SynPipe. Here we explain the design and implementation of SynPipe and generate a sample of synthetic galaxies to examine the photometric performance of the HSC pipeline. For stars, we achieve 1% photometric precision at i~19.0 mag and 6% precision at i~25.0 in the i-band. For synthetic galaxies with single-Sersic profiles, forced CModel photometry achieves 13% photometric precision at i~20.0 mag and 18% precision at i~25.0 in the i-band. We show that both forced PSF and CModel photometry yield unbiased color estimates that are robust to seeing conditions. We identify several caveats that apply to the version of HSC pipeline used for the first public HSC data release (DR1) that need to be taking into consideration. First, the degree to which an object is blended with other objects impacts the overall photometric performance. This is especially true for point sources. Highly blended objects tend to have larger photometric uncertainties, systematically underestimated fluxes and slightly biased colors. Second, >20% of stars at 22.5< i < 25.0 mag can be misclassified as extended objects. Third, the current CModel algorithm tends to strongly underestimate the half-light radius and ellipticity of galaxy with i>21.5 mag.

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arXiv2017

Mapping stellar content to dark matter halos - III.Environmental dependence and conformity of galaxy colours

Recent studies suggest that the quenching properties of galaxies are correlated over several mega-parsecs. The large-scale "galactic conformity" phenomenon around central galaxies has been regarded as a potential signature of "galaxy assembly bias" or "pre-heating", both of which interpret conformity as a result of direct environmental effects acting on galaxy formation. Building on the iHOD halo quenching framework developed in Zu & Mandelbaum (2015, 2016), we discover that our fiducial halo mass quenching model, without any galaxy assembly bias, can successfully explain the overall environmental dependence and the conformity of galaxy colours in SDSS, as measured by the mark correlation functions of galaxy colours and the red galaxy fractions around isolated primaries, respectively. Our fiducial iHOD halo quenching mock also correctly predicts the differences in the spatial clustering and galaxy-galaxy lensing signals between the more vs. less red galaxy subsamples, split by the red-sequence ridge-line at fixed stellar mass. Meanwhile, models that tie galaxy colours fully or partially to halo assembly bias have difficulties in matching all these observables simultaneously. Therefore, we demonstrate that the observed environmental dependence of galaxy colours can be naturally explained by the combination of 1) halo quenching and 2) the variation of halo mass function with environment --- an indirect environmental effect mediated by two separate physical processes.

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arXiv2017

Weak Lensing Measurement of the Mass--Richness Relation of SDSS redMaPPer Clusters

We perform a measurement of the mass--richness relation of the redMaPPer galaxy cluster catalogue using weak lensing data from the Sloan Digital Sky Survey. We have carefully characterized a broad range of systematic uncertainties, including shear calibration errors, photo-$z$ biases, dilution by member galaxies, source obscuration, magnification bias, incorrect assumptions about cluster mass profiles, cluster centering, halo triaxiality, and projection effects. We also compare measurements of the lensing signal from two independently-produced shear and photometric redshift catalogues to characterize systematic errors in the lensing signal itself. Using a sample of 5,570 clusters from $0.1\le z\le 0.33$, the normalization of our power-law mass vs.\ $λ$ relation is $\log_{10}[M_{200m}/h^{-1}\ M_{\odot}]$ = $14.344 \pm 0.021$ (statistical) $\pm 0.023$ (systematic) at a richness $λ=40$, a 7 per cent calibration uncertainty, with a power-law index of $1.33^{+0.09}_{-0.10}$ ($1σ$). The detailed systematics characterization in this work renders it the definitive weak lensing mass calibration for SDSS redMaPPer clusters at this time.

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arXiv2017

Weak lensing calibration of mass bias in the REFLEX+BCS X-ray galaxy cluster catalogue

The use of large, X-ray selected galaxy cluster catalogues for cosmological analyses requires a thorough understanding of the X-ray mass estimates. Weak gravitational lensing is an ideal method to shed light on such issues, due to its insensitivity to the cluster dynamical state. We perform a weak lensing calibration of 166 galaxy clusters from the REFLEX and BCS cluster catalogue and compare our results to the X-ray masses based on scaled luminosities from that catalogue. To interpret the weak lensing signal in terms of cluster masses, we compare the lensing signal to simple theoretical Navarro-Frenk-White models and to simulated cluster lensing profiles, including complications such as cluster substructure, projected large-scale structure, and Eddington bias. We find evidence of underestimation in the X-ray masses, as expected, with $\langle M_{\mathrm{X}}/M_{\mathrm{WL}}\rangle = 0.75 \pm 0.07$ stat. $\pm 0.05$ sys. for our best-fit model. The biases in cosmological parameters in a typical cluster abundance measurement that ignores this mass bias will typically exceed the statistical errors.

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arXiv2017

CMU DeepLens: Deep Learning For Automatic Image-based Galaxy-Galaxy Strong Lens Finding

Galaxy-scale strong gravitational lensing is not only a valuable probe of the dark matter distribution of massive galaxies, but can also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as LSST, Euclid, and WFIRST. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on Deep Learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20,000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99%, a completeness of 90% can be achieved for lenses with Einstein radii larger than 1.4" and S/N larger than 20 on individual $g$-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens .

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arXiv2017

Metacalibration: Direct Self-Calibration of Biases in Shear Measurement

One of the primary limiting sources of systematic uncertainty in forthcoming weak lensing measurements is systematic uncertainty in the quantitative relationship between the distortions due to gravitational lensing and the measurable properties of galaxy images. We present a statistically principled, general solution to this problem. Our technique infers multiplicative shear calibration parameters by modifying the actual survey data to simulate the effects of a known shear. It can be applied to any shear estimation method based on weighted averages of galaxy shape measurements, which includes all methods used to date for shear estimation with real data. Use of the real images mitigates uncertainty due to unknown galaxy morphology, which is a serious concern for calibration of shear estimates based on image simulations. We test our results on simulated images from the GREAT3 challenge, and show that the method eliminates calibration biases for several different shape measurement techniques at the level of precision measurable with the GREAT3 simulations (a few tenths of a percent).

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arXiv2017

Detecting Effects of Filaments on Galaxy Properties in the Sloan Digital Sky Survey III

We study the effects of filaments on galaxy properties in the Sloan Digital Sky Survey (SDSS) Data Release 12 using filaments from the `Cosmic Web Reconstruction' catalogue (Chen et al. 2016), a publicly available filament catalogue for SDSS. Since filaments are tracers of medium-to-high density regions, we expect that galaxy properties associated with the environment are dependent on the distance to the nearest filament. Our analysis demonstrates that a red galaxy or a high-mass galaxy tend to reside closer to filaments than a blue or low-mass galaxy. After adjusting the effect from stellar mass, on average, early-forming galaxies or large galaxies have a shorter distance to filaments than late-forming galaxies or small galaxies. For the Main galaxy sample (MGS), all signals are very significant ($>6σ$). For the LOWZ and CMASS sample, the stellar mass and size are significant ($>2 σ$). The filament effects we observe persist until $z = 0.7$ (the edge of the CMASS sample). Comparing our results to those using the galaxy distances from redMaPPer galaxy clusters as a reference, we find a similar result between filaments and clusters. Moreover, we find that the effect of clusters on the stellar mass of nearby galaxies depends on the galaxy's filamentary environment. Our findings illustrate the strong correlation of galaxy properties with proximity to density ridges, strongly supporting the claim that density ridges are good tracers of filaments.

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arXiv2016

Testing gravity on large scales by combining weak lensing with galaxy clustering using CFHTLenS and BOSS CMASS

We measure a combination of gravitational lensing, galaxy clustering, and redshift-space distortions called $E_G$. The quantity $E_G$ probes both parts of metric potential and is insensitive to galaxy bias and $σ_8$. These properties make it an attractive statistic to test $Λ$CDM, General Relativity and its alternate theories. We have combined CMASS DR11 with CFHTLenS and recent measurements of $β$ from RSD analysis, and find $E_G(z = 0.57) = 0.42 \pm 0.056$, an 13\% measurement in agreement with the prediction of general relativity $E_G(z = 0.57) = 0.396 \pm 0.011$ using the Planck 2015 cosmological parameters. We have corrected our measurement for various observational and theoretical systematics. Our measurement is consistent with the first measurement of $E_G$ using CMB lensing in place of galaxy lensing (Pullen et. al. 2015a) at small scales, but shows 2.8$σ$ tension when compared with their final results including large scales. This analysis with future surveys will provide improved statistical error and better control over systematics to test General Relativity and its alternate theories.

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arXiv2016

Enabling Dark Energy Science with Deep Generative Models of Galaxy Images

Understanding the nature of dark energy, the mysterious force driving the accelerated expansion of the Universe, is a major challenge of modern cosmology. The next generation of cosmological surveys, specifically designed to address this issue, rely on accurate measurements of the apparent shapes of distant galaxies. However, shape measurement methods suffer from various unavoidable biases and therefore will rely on a precise calibration to meet the accuracy requirements of the science analysis. This calibration process remains an open challenge as it requires large sets of high quality galaxy images. To this end, we study the application of deep conditional generative models in generating realistic galaxy images. In particular we consider variations on conditional variational autoencoder and introduce a new adversarial objective for training of conditional generative networks. Our results suggest a reliable alternative to the acquisition of expensive high quality observations for generating the calibration data needed by the next generation of cosmological surveys.

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arXiv2016

Lensing is Low: Cosmology, Galaxy Formation, or New Physics?

We present high signal-to-noise galaxy-galaxy lensing measurements of the BOSS CMASS sample using 250 square degrees of weak lensing data from CFHTLenS and CS82. We compare this signal with predictions from mock catalogs trained to match observables including the stellar mass function and the projected and two dimensional clustering of CMASS. We show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40% larger than observed. Detailed tests show that our results are robust to a variety of systematic effects. Lowering the value of $S_{\rm 8}=σ_{\rm 8} \sqrt{Ω_{\rm m}/0.3}$ compared to Planck2015 reconciles the lensing with clustering. However, given the scale of our measurement ($r<10$ $h^{-1}$ Mpc), other effects may also be at play and need to be taken into consideration. We explore the impact of baryon physics, assembly bias, massive neutrinos, and modifications to general relativity on $ΔΣ$ and show that several of these effects may be non-negligible given the precision of our measurement. Disentangling cosmological effects from the details of the galaxy-halo connection, the effects of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy samples from Baryon Acoustic Oscillation surveys with precise measurements but complex selection functions.

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arXiv2016

Maximizing Science in the Era of LSST: A Community-Based Study of Needed US Capabilities

The Large Synoptic Survey Telescope (LSST) will be a discovery machine for the astronomy and physics communities, revealing astrophysical phenomena from the Solar System to the outer reaches of the observable Universe. While many discoveries will be made using LSST data alone, taking full scientific advantage of LSST will require ground-based optical-infrared (OIR) supporting capabilities, e.g., observing time on telescopes, instrumentation, computing resources, and other infrastructure. This community-based study identifies, from a science-driven perspective, capabilities that are needed to maximize LSST science. Expanding on the initial steps taken in the 2015 OIR System Report, the study takes a detailed, quantitative look at the capabilities needed to accomplish six representative LSST-enabled science programs that connect closely with scientific priorities from the 2010 decadal surveys. The study prioritizes the resources needed to accomplish the science programs and highlights ways that existing, planned, and future resources could be positioned to accomplish the science goals.

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arXiv2016

Cross-correlating Planck CMB lensing with SDSS: Lensing-lensing and galaxy-lensing cross-correlations

We present results from cross-correlating Planck CMB lensing maps with the Sloan Digital Sky Survey (SDSS) galaxy lensing shape catalog and BOSS galaxy catalogs. For galaxy position vs. CMB lensing cross-correlations, we measure the convergence signal around the galaxies in configuration space, using the BOSS LOWZ ($z\sim0.30$) and CMASS ($z\sim0.57$) samples. With fixed Planck 2015 cosmology, doing a joint fit with the galaxy clustering measurement, for the LOWZ (CMASS) sample we find a galaxy bias $b_g=1.75\pm0.04$ ($1.95\pm 0.02$) and galaxy-matter cross-correlation coefficient $r_{cc}=1.0\pm0.2$ ($0.8\pm 0.1$) using $20<r_p<70h^{-1}$Mpc, consistent with results from galaxy-galaxy lensing. Using the same scales and including the galaxy-galaxy lensing measurements, we constrain $Ω_m=0.284\pm0.024$ and relative calibration bias between the CMB lensing and galaxy lensing to be $b_γ=0.82^{+0.15}_{-0.14}$. The combination of galaxy lensing and CMB lensing also allows us to measure the cosmological distance ratios (with $z_l\sim0.3$, $z_s\sim0.5$) $\mathcal R=\frac{D_s D_{l,*}}{D_* D_{l,s}}=2.68\pm0.29$, consistent with predictions from the Planck 2015 cosmology ($\mathcal R=2.35$). We detect the galaxy position-CMB convergence cross-correlation at small scales, $r_p<1h^{-1}$Mpc, and find consistency with lensing by NFW halos of mass $M_h\sim10^{13}h^{-1}M_\odot$. Finally, we measure the CMB lensing-galaxy shear cross-correlation, finding an amplitude of $A=0.76\pm0.23$ ($z_\text{eff}=0.35$, $θ<2^\circ$) with respect to Planck 2015 $Λ$CDM predictions ($1σ$-level consistency). We do not find evidence for relative systematics between the CMB and SDSS galaxy lensing.

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arXiv2016

Intrinsic alignments in redMaPPer clusters -- I. Central galaxy alignments and angular segregation of satellites

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94817 members within 0.1<z<0.35, based on the redMaPPer cluster catalog constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centering probability, and redder color. Satellites with redder color, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation toward their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

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arXiv2016

Intrinsic alignments of disk and elliptical galaxies in the MassiveBlack-II and Illustris simulations

We study the shapes and intrinsic alignments of disks and elliptical galaxies in the MassiveBlack-II (MBII) and Illustris cosmological hydrodynamic simulations, with volumes of $(100h^{-1}Mpc)^{3}$ and $(75h^{-1}Mpc)^{3}$ respectively. We find that simulated disk galaxies are more oblate in shape and more misaligned with the shape of their host dark matter subhalo when compared with ellipticals. The disk major axis is found to be oriented towards the location of nearby elliptical galaxies. We also find that the disks are thinner in MBII and misalignments with dark matter halo orientations are smaller in both disks and ellipticals when compared with Illustris. As a result, the intrinsic alignment correlation functions at fixed mass have a higher amplitude in MBII than in Illustris. Finally, at scales above $\sim 0.1$\hmpc, the intrinsic alignment two-point correlation functions for disk galaxies in both simulations are consistent with a null detection, unlike those for ellipticals. Despite significant differences in the treatments of hydrodynamics and baryonic physics in the simulations, we find that the $w_{δ+}$ correlation function scales similarly with transverse separation. However, the less massive galaxies show different scale dependence in the ED correlation. This result indicates that, while hydrodynamic simulations are a promising tool to study intrinsic alignments, further study is needed to understand the impact of differences in the implementations of hydrodynamics and baryonic feedback.

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arXiv2016

The Impact of Interpixel Capacitance in CMOS Detectors on PSF shapes and Implications for WFIRST

Unlike optical CCDs, near-infrared detectors, which are based on CMOS hybrid readout technology, typically suffer from electrical crosstalk between the pixels. The interpixel capacitance (IPC) responsible for the crosstalk affects the point-spread function (PSF) of the telescope, increasing the size and modifying the shape of all objects in the images while correlating the Poisson noise. Upcoming weak lensing surveys that use these detectors, such as WFIRST, place stringent requirements on the PSF size and shape (and the level at which these are known), which in turn must be translated into requirements on IPC. To facilitate this process, we present a first study of the effect of IPC on WFIRST PSF sizes and shapes. Realistic PSFs are forward-simulated from physical principles for each WFIRST bandpass. We explore how the PSF size and shape depends on the range of IPC coupling with pixels that are connected along an edge or corner; for the expected level of IPC in WFIRST, IPC increases the PSF sizes by $\sim$5\%. We present a linear fitting formula that describes the uncertainty in the PSF size or shape due to uncertainty in the IPC, which could arise for example due to unknown time evolution of IPC as the detectors age or due to spatial variation of IPC across the detector. We also study of the effect of a small anisotropy in the IPC, which further modifies the PSF shapes. Our results are a first, critical step in determining the hardware and characterization requirements for the detectors used in the WFIRST survey.

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