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Jeremy Tinker

Publications and source records attributed to Jeremy Tinker.

At least 19 recordsLinked to original sources

Aemulus $\nu$: Precision halo mass functions in w$\nu$CDM cosmologies

Precise and accurate predictions of the halo mass function for cluster mass scales in $w\nu{\rm CDM}$ cosmologies are crucial for extracting robust and unbiased cosmological information from upcoming galaxy cluster surveys. Here, we present a halo mass function emulator for cluster mass scales ($\gtrsim 10^{13}M_\odot /h$) up to redshift $z=2$ with comprehensive support for the parameter space of $w\nu{\rm CDM}$ cosmologies allowed by current data. Based on the Aemulus $\nu$ suite of simulations, the emulator marks a significant improvement in the precision of halo mass function predictions by incorporating both massive neutrinos and non-standard dark energy equation of state models. This allows for accurate modeling of the cosmology dependence in large-scale structure and galaxy cluster studies. We show that the emulator, designed using Gaussian Process Regression, has negligible theoretical uncertainties compared to dominant sources of error in future cluster abundance studies. Our emulator is publicly available, providing the community with a crucial tool for upcoming cosmological surveys such as LSST and Euclid.

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Aemulus $\nu$: Precise Predictions for Matter and Biased Tracer Power Spectra in the Presence of Neutrinos

We present the Aemulus $\nu$ simulations: a suite of 150 $(1.05 h^{-1}\rm Gpc)^3$ $N$-body simulations with a mass resolution of $3.51\times 10^{10} \frac{\Omega_{cb}}{0.3} ~ h^{-1} M_{\odot}$ in a $w\nu$CDM cosmological parameter space. The simulations have been explicitly designed to span a broad range in $\sigma_8$ to facilitate investigations of tension between large scale structure and cosmic microwave background cosmological probes. Neutrinos are treated as a second particle species to ensure accuracy to $0.5\, \rm eV$, the maximum neutrino mass that we have simulated. By employing Zel'dovich control variates, we increase the effective volume of our simulations by factors of $10-10^5$ depending on the statistic in question. As a first application of these simulations, we build new hybrid effective field theory and matter power spectrum surrogate models, demonstrating that they achieve $\le 1\%$ accuracy for $k\le 1\, h\,\rm Mpc^{-1}$ and $0\le z \le 3$, and $\le 2\%$ accuracy for $k\le 4\, h\,\rm Mpc^{-1}$ for the matter power spectrum. We publicly release the trained surrogate models, and estimates of the surrogate model errors in the hope that they will be broadly applicable to a range of cosmological analyses for many years to come.

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The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints

There is untapped cosmological information in galaxy redshift surveys in the non-linear regime. In this work, we use the AEMULUS suite of cosmological $N$-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales ($0.1-50 \: h^{-1}\,\mathrm{Mpc}$) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics -- the projected correlation function $w_\mathrm{p}(r_\mathrm{p})$, the redshift-space monopole of the correlation function $\xi_0(s)$, and the quadrupole $\xi_2(s)$ -- we emulate statistics that include information about the local environment, namely the underdensity probability function $P_\mathrm{U}(s)$ and the density-marked correlation function $M(s)$. This extends the model of AEMULUS III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including $P_\mathrm{U}(s)$ and $M(s)$ improves the precision of our constraints on $\Omega_m$ by 27%, $\sigma_8$ by 19%, and the growth of structure parameter, $f \sigma_8$, by 12% compared to standard statistics. We additionally find that scales below $\sim6 \: h^{-1}\,\mathrm{Mpc}$ contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy-halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

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Super-resolving Dark Matter Halos using Generative Deep Learning

Generative deep learning methods built upon Convolutional Neural Networks (CNNs) provide a great tool for predicting non-linear structure in cosmology. In this work we predict high resolution dark matter halos from large scale, low resolution dark matter only simulations. This is achieved by mapping lower resolution to higher resolution density fields of simulations sharing the same cosmology, initial conditions and box-sizes. To resolve structure down to a factor of 8 increase in mass resolution, we use a variation of U-Net with a conditional GAN, generating output that visually and statistically matches the high resolution target extremely well. This suggests that our method can be used to create high resolution density output over Gpc/h box-sizes from low resolution simulations with negligible computational effort.

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dm2gal: Mapping Dark Matter to Galaxies with Neural Networks

Maps of cosmic structure produced by galaxy surveys are one of the key tools for answering fundamental questions about the Universe. Accurate theoretical predictions for these quantities are needed to maximize the scientific return of these programs. Simulating the Universe by including gravity and hydrodynamics is one of the most powerful techniques to accomplish this; unfortunately, these simulations are very expensive computationally. Alternatively, gravity-only simulations are cheaper, but do not predict the locations and properties of galaxies in the cosmic web. In this work, we use convolutional neural networks to paint galaxy stellar masses on top of the dark matter field generated by gravity-only simulations. Stellar mass of galaxies are important for galaxy selection in surveys and thus an important quantity that needs to be predicted. Our model outperforms the state-of-the-art benchmark model and allows the generation of fast and accurate models of the observed galaxy distribution.

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The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 LRG sample: structure growth rate measurement from the anisotropic LRG correlation function in the redshift range 0.6 < z < 1.0

We analyze the anisotropic clustering of the Sloan Digital Sky Survey-IV Extended Baryon Oscillation Spectroscopic Survey (eBOSS) Luminous Red Galaxy Data Release 14 (DR14) sample combined with Baryon Oscillation Spectroscopic Survey (BOSS) CMASS sample of galaxies in the redshift range 0.6$<z<$1.0, which consists of 80,118 galaxies from eBOSS and 46,439 galaxies from the BOSS-CMASS sample. The eBOSS-CMASS Luminous Red Galaxy sample has a sky coverage of 1,844 deg$^2$, with an effective volume of 0.9 Gpc$^3$. The analysis was made in configuration space using a Legendre multipole expansion. The Redshift Space Distortion signal is modeled as a combination of the Convolution Lagrangian Perturbation Model and the Gaussian Streaming Model. We constrain the logarithmic growth of structure times the amplitude of dark matter density fluctuations, $f (z_{\rm eff})\sigma_8(z_{\rm eff})=0.454 \pm0.139 $, and the Alcock-Paczynski dilation scales which constraints the angular diameter distance $D_A(z_{eff})=1466.5 \pm 136.6 (r_s/r_s^{\rm fid})$ and $H(z_{\rm eff})=105.8 \pm 16 (r_s^{\rm fid}/r_s) \mathrm{km\,s^{-1}\,Mpc^{-1}}$, where $r_s$ is the sound horizon at the end of the baryon drag epoch and $r_s^{\rm fid}$ is its value in the fiducial cosmology at an effective redshift $z_{\rm eff}=0.72$. These results are in full agreement with the current $\Lambda$-Cold Dark Matter ($\Lambda$-CDM) cosmological model inferred from Planck measurements. This study is the first eBOSS LRG full-shape analysis i.e. including Redshift-Space Distortions (RSD) simultaneously with the Alcock-Paczynski (AP) effect and the Baryon Acoustic Oscillation (BAO) scale.

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Probing Galaxy Assembly Bias in BOSS Galaxies Using Void Probabilities

We measure the void probability function (VPF) of galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS). The VPF provides complementary information to standard two-point statistics in that it is sensitive to galaxy bias in the most extreme underdensities in the cosmic web. Thus the VPF is ideal for testing whether halo occupation of galaxies depends on large-scale density, an effect known as galaxy assembly bias. We find that standard HOD model---one parameterized by halo mass only---fit only to the two-point function, accurately predicts the VPF. Additionally, for HOD models where density dependence is explicitly incorporated, the best-fit models fit to the combination of the correlation function and the VPF have zero density dependence. Thus galaxy assembly bias is not a strong source of systematic uncertaintiy when modeling the clustering of massive galaxies.

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Astro2020: Empirically Constraining Galaxy Evolution

Over the past decade, empirical constraints on the galaxy-dark matter halo connection have significantly advanced our understanding of galaxy evolution. Past techniques have focused on connections between halo properties and galaxy stellar mass and/or star formation rates. Empirical techniques in the next decade will link halo assembly histories with galaxies' circumgalactic media, supermassive black holes, morphologies, kinematics, sizes, colors, metallicities, and transient rates. Uncovering these links will resolve many critical uncertainties in galaxy formation and will enable much higher-fidelity mock catalogs essential for interpreting observations. Achieving these results will require broader and deeper spectroscopic coverage of galaxies and their circumgalactic media; survey teams will also need to meet several criteria (cross-comparisons, public access, and covariance matrices) to facilitate combining data across different surveys. Acting on these recommendations will continue enabling dramatic progress in both empirical modeling and galaxy evolution for the next decade.

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The SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations at redshift of 0.72 with the DR14 Luminous Red Galaxy Sample

The extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 14 sample includes 80,118 Luminous Red Galaxies. By combining these galaxies with the high-redshift tail of the BOSS galaxy sample, we form a sample of LRGs at an effective redshift $z=0.72$, covering an effective volume of 0.9~Gpc$^3$. We introduce new techniques to account for spurious fluctuations caused by targeting and by redshift failures which were validated on a set of mock catalogs. This analysis is sufficient to provide a $2.6$\% measurement of spherically averaged BAO, $D_V(z=0.72) = 2353^{+63}_{-61} (r_d/r_{d,\rm{fid}}) h^{-1}$Mpc, at 2.8$\sigma$ of significance. Together with the recent quasar-based BAO measurement at $z=1.5$, and forthcoming Emission Line Galaxy-based measurements, this measurement demonstrates that eBOSS is fulfilling its remit of extending the range of redshifts covered by such measurements, laying the ground work for forthcoming surveys such as the Dark Energy Spectroscopic Survey and Euclid.

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Emulating galaxy clustering and galaxy-galaxy lensing into the deeply nonlinear regime: methodology, information, and forecasts

The combination of galaxy-galaxy lensing (GGL) with galaxy clustering is one of the most promising routes to determining the amplitude of matter clustering at low redshifts. We show that extending clustering+GGL analyses from the linear regime down to $\sim 0.5 \, h^{-1}$ Mpc scales increases their constraining power considerably, even after marginalizing over a flexible model of non-linear galaxy bias. Using a grid of cosmological N-body simulations, we construct a Taylor-expansion emulator that predicts the galaxy autocorrelation $\xi_{\text{gg}}(r)$ and galaxy-matter cross-correlation $\xi_{\text{gm}}(r)$ as a function of $\sigma_8$, $\Omega_m$, and halo occupation distribution (HOD) parameters, which are allowed to vary with large scale environment to represent possible effects of galaxy assembly bias. We present forecasts for a fiducial case that corresponds to BOSS LOWZ galaxy clustering and SDSS-depth weak lensing (effective source density $\sim 0.3$ arcmin$^{-2}$). Using tangential shear and projected correlation function measurements over $0.5 \leq r_p \leq 30 \, h^{-1}$ Mpc yields a 1.8% constraint on the parameter combination $\sigma_8\Omega_m^{0.58}$, a factor of two better than a constraint that excludes non-linear scales ($r_p > 2 \, h^{-1}$ Mpc, $4 \, h^{-1}$ Mpc for $\gamma_t,w_p$). Much of this improvement comes from the non-linear clustering information, which breaks degeneracies among HOD parameters that would otherwise degrade the inference of matter clustering from GGL. Increasing the effective source density to $3$ arcmin$^{-2}$ sharpens the constraint on $\sigma_8\Omega_m^{0.58}$ by a further factor of two. With robust modeling into the non-linear regime, low-redshift measurements of matter clustering at the 1-percent level with clustering+GGL alone are well within reach of current data sets such as those provided by the Dark Energy Survey.

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The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing S/N, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on i-band absolute magnitude ($M_i$), or, for a small subset of our sample, $M_i$ and color (NUV-i). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to $M_i$ and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (Re), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color-magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range $5\times10^8 \leq M_* \leq 3\times10^{11} M_{\odot}$ and are sampled at median physical resolutions of 1.37 kpc and 2.5 kpc for the Primary and Secondary samples respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume limited sample.

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The Time-Domain Spectroscopic Survey: Target Selection for Repeat Spectroscopy

As astronomers increasingly exploit the information available in the time domain, spectroscopic variability in particular opens broad new channels of investigation. Here we describe the selection algorithms for all targets intended for repeat spectroscopy in the Time Domain Spectroscopic Survey (TDSS), part of the extended Baryon Oscillation Spectroscopic Survey within the Sloan Digital Sky Survey-IV. Also discussed are the scientific rationale and technical constraints leading to these target selections. The TDSS includes a large "Repeat Quasar Spectroscopy" (RQS) program delivering ~13,000 repeat spectra of confirmed SDSS quasars, and several smaller "Few-Epoch Spectroscopy" (FES) programs targeting specific classes of quasars as well as stars. The RQS program aims to provide a large and diverse quasar data set for studying variations in quasar spectra on timescales of years, a comparison sample for the FES quasar programs, and opportunity for discovering rare, serendipitous events. The FES programs cover a wide variety of phenomena in both quasars and stars. Quasar FES programs target broad absorption line quasars, high signal-to-noise ratio normal broad line quasars, quasars with double-peaked or very asymmetric broad emission line profiles, binary supermassive black hole candidates, and the most photometrically variable quasars. Strongly variable stars are also targeted for repeat spectroscopy, encompassing many types of eclipsing binary systems, and classical pulsators like RR Lyrae. Other stellar FES programs allow spectroscopic variability studies of active ultracool dwarf stars, dwarf carbon stars, and white dwarf/M dwarf spectroscopic binaries. We present example TDSS spectra and describe anticipated sample sizes and results.

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An evaluation of cosmological models from expansion and growth of structure measurements

We compare a large suite of theoretical cosmological models to observational data from the cosmic microwave background, baryon acoustic oscillation measurements of expansion, Type Ia SNe measurements of expansion, redshift space distortion measurements of the growth of structure, and the local Hubble constant. Our theoretical models include parametrizations of dark energy as well as physical models of dark energy and modified gravity. We determine the constraints on the model parameters, incorporating the redshift space distortion data directly in the analysis. To determine whether models can be ruled out, we evaluate the $p$ value (the probability under the model of obtaining data as bad or worse than the observed data). In our comparison, we find the well known tension of H$_0$ with the other data; no model resolves this tension successfully. Among the models we consider, the large scale growth of structure data does not affect the modified gravity models as a category particularly differently than dark energy models; it matters for some modified gravity models but not others, and the same is true for dark energy models. We compute predicted observables for each model under current observational constraints, and identify models for which future observational constraints will be particularly informative.

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Clustering of quasars in SDSS-IV eBOSS : study of potential systematics and bias determination

We study the first year of the eBOSS quasar sample in the redshift range $0.9<z<2.2$ which includes 68,772 homogeneously selected quasars. We show that the main source of systematics in the evaluation of the correlation function arises from inhomogeneities in the quasar target selection, particularly related to the extinction and depth of the imaging data used for targeting. We propose a weighting scheme that mitigates these systematics. We measure the quasar correlation function and provide the most accurate measurement to date of the quasar bias in this redshift range, $b_Q = 2.45 \pm 0.05$ at $\bar z=1.55$, together with its evolution with redshift. We use this information to determine the minimum mass of the halo hosting the quasars and the characteristic halo mass, which we find to be both independent of redshift within statistical error. Using a recently-measured quasar-luminosity-function we also determine the quasar duty cycle. The size of this first year sample is insufficient to detect any luminosity dependence to quasar clustering and this issue should be further studied with the final $\sim$500,000 eBOSS quasar sample.

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Exploring cosmic homogeneity with the BOSS DR12 galaxy sample

In this study, we probe the transition to cosmic homogeneity in the Large Scale Structure (LSS) of the Universe using the CMASS galaxy sample of BOSS spectroscopic survey which covers the largest effective volume to date, $3\ h^{-3}\ \mathrm{Gpc}^3$ at $0.43 \leq z \leq 0.7$. We study the scaled counts-in-spheres, $\mathcal{N}( 2.97$ for $r>\mathcal{R}_H$, we find $\mathcal{R}_H = (63.3\pm0.7) \ h^{-1}\ \mathrm{Mpc}$, in agreement at the percentage level with the predictions of the $\Lambda$CDM model $\mathcal{R}_H=62.0\ h^{-1}\ \mathrm{Mpc}$. Thanks to the large cosmic depth of the survey, we investigate the redshift evolution of the transition to homogeneity scale and find agreement with the $\Lambda$CDM prediction. Finally, we find that $\mathcal{D}_2$ is compatible with $3$ at scales larger than $300\ h^{-1}\ $Mpc in all redshift bins. These results consolidate the Cosmological Principle and represent a precise consistency test of the $\Lambda CDM$ model.

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Halo Histories vs. Galaxy Properties at z=0, I: The Quenching of Star Formation

We test whether halo age and galaxy age are correlated at fixed halo and galaxy mass. The formation histories, and thus ages, of dark matter halos correlate with their large-scale density $\rho$, an effect known as assembly bias. We test whether this correlation extends to galaxies by measuring the dependence of galaxy stellar age on $\rho$. To clarify the comparison between theory and observation, and to remove the strong environmental effects on satellites, we use galaxy group catalogs to identify central galaxies and measure their quenched fraction, $f_Q$, as a function of large-scale environment. Models that match halo age to central galaxy age predict a strong positive correlation between $f_Q$ and $\rho$. However, we show that the amplitude of this effect depends on the definition of halo age: assembly bias is significantly reduced when removing the effects of splashback halos---those halos that are central but have passed through a larger halo or experienced strong tidal encounters. Defining age using halo mass at its peak value rather than current mass removes these effects. In SDSS data, at M$_{\rm gal}\gtrsim 10^{10.0}$ M_sol/h$^2$, there is a $\sim 5\%$ increase in $f_Q$ from low to high densities, which is in agreement with predictions of dark matter halos using peak halo mass. At lower stellar mass there is little to no correlation of $f_Q$ with $\rho$. For these galaxies, age-matching is inconsistent with the data across the wide range the halo formation metrics that we tested. This implies that halo formation history has a small but statistically significant impact on quenching of star formation at high masses, while the quenching process in low-mass central galaxies is uncorrelated with halo formation history.

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SPIDERS: the spectroscopic follow-up of X-ray selected clusters of galaxies in SDSS-IV

SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a program dedicated to the homogeneous and complete spectroscopic follow-up of X-ray AGN and galaxy clusters over a large area ($\sim$7500 deg$^2$) of the extragalactic sky. SPIDERS is part of the SDSS-IV project, together with the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the Time-Domain Spectroscopic Survey (TDSS). This paper describes the largest project within SPIDERS before the launch of eROSITA: an optical spectroscopic survey of X-ray selected, massive ($\sim 10^{14}$ to $10^{15}~M_{\odot}$) galaxy clusters discovered in ROSAT 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, using clusters as probes of large-scale structure in the expanding Universe. We present the cluster samples, target selection algorithms and observation strategies. We demonstrate the efficiency of selecting targets using a combination of SDSS imaging data, a robust red-sequence finder and a dedicated prioritization scheme. We describe a set of algorithms and work-flow developed to collate spectra and assign cluster membership, and to deliver catalogues of spectroscopically confirmed clusters. We discuss the relevance of line-of-sight velocity dispersion estimators for the richer systems. We illustrate our techniques by constructing a catalogue of 230 spectroscopically validated clusters ($0.031 < z < 0.658$), found in pilot observations. We discuss two potential science applications of the SPIDERS sample: the study of the X-ray luminosity-velocity dispersion ($L_X-\sigma$) relation and the building of stacked phase-space diagrams.

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SDSS-IV MaNGA IFS Galaxy Survey --- Survey Design, Execution, and Initial Data Quality

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy (IFS) for 10K nearby galaxies at a spectral resolution of R~2000 from 3,622-10,354A. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (Re) while maximizing spatial resolution. About 2/3 of the sample is covered out to 1.5Re (Primary sample), and 1/3 of the sample is covered to 2.5Re (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically, the point spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r-band signal-to-noise ratio is ~73 per 1.4A pixel for spectra stacked between 1-1.5 Re. Measurements of various galaxy properties from the first year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

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