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E. Gaztanaga

Publications and source records attributed to E. Gaztanaga.

At least 289 records · Page 16Linked to original sources

Detection of the kinematic Sunyaev-Zel'dovich effect with DES Year 1 and SPT

We detect the kinematic Sunyaev-Zel'dovich (kSZ) effect with a statistical significance of $4.2 σ$ by combining a cluster catalogue derived from the first year data of the Dark Energy Survey (DES) with CMB temperature maps from the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) Survey. This measurement is performed with a differential statistic that isolates the pairwise kSZ signal, providing the first detection of the large-scale, pairwise motion of clusters using redshifts derived from photometric data. By fitting the pairwise kSZ signal to a theoretical template we measure the average central optical depth of the cluster sample, $\barτ_e = (3.75 \pm 0.89)\cdot 10^{-3}$. We compare the extracted signal to realistic simulations and find good agreement with respect to the signal-to-noise, the constraint on $\barτ_e$, and the corresponding gas fraction. High-precision measurements of the pairwise kSZ signal with future data will be able to place constraints on the baryonic physics of galaxy clusters, and could be used to probe gravity on scales $ \gtrsim 100$ Mpc.

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SDSS-IV eBOSS emission-line galaxy pilot survey

The Sloan Digital Sky Survey IV extended Baryonic Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) will observe 195,000 emission-line galaxies (ELGs) to measure the Baryonic Acoustic Oscillation standard ruler (BAO) at redshift 0.9. To test different ELG selection algorithms, 9,000 spectra were observed with the SDSS spectrograph as a pilot survey based on data from several imaging surveys. First, using visual inspection and redshift quality flags, we show that the automated spectroscopic redshifts assigned by the pipeline meet the quality requirements for a reliable BAO measurement. We also show the correlations between sky emission, signal-to-noise ratio in the emission lines, and redshift error. Then we provide a detailed description of each target selection algorithm we tested and compare them with the requirements of the eBOSS experiment. As a result, we provide reliable redshift distributions for the different target selection schemes we tested. Finally, we determine an target selection algorithms that is best suited to be applied on DECam photometry because they fulfill the eBOSS survey efficiency requirements.

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Optical-SZE Scaling Relations for DES Optically Selected Clusters within the SPT-SZ Survey

We study the Sunyaev-Zel'dovich effect (SZE) signature in South Pole Telescope (SPT) data for an ensemble of 719 optically identified galaxy clusters selected from 124.6 deg$^2$ of the Dark Energy Survey (DES) science verification data, detecting a stacked SZE signal down to richness $λ\sim20$. The SZE signature is measured using matched-filtered maps of the 2500 deg$^2$ SPT-SZ survey at the positions of the DES clusters, and the degeneracy between SZE observable and matched-filter size is broken by adopting as priors SZE and optical mass-observable relations that are either calibrated using SPT selected clusters or through the Arnaud et al. (2010, A10) X-ray analysis. We measure the SPT signal to noise $ζ$-$λ$, relation and two integrated Compton-$y$ $Y_\textrm{500}$-$λ$ relations for the DES-selected clusters and compare these to model expectations accounting for the SZE-optical center offset distribution. For clusters with $λ> 80$, the two SPT calibrated scaling relations are consistent with the measurements, while for the A10-calibrated relation the measured SZE signal is smaller by a factor of $0.61 \pm 0.12$ compared to the prediction. For clusters at $20 < λ< 80$, the measured SZE signal is smaller by a factor of $\sim$0.20-0.80 (between 2.3 and 10~$σ$ significance) compared to the prediction, with the SPT calibrated scaling relations and larger $λ$ clusters showing generally better agreement. We quantify the required corrections to achieve consistency, showing that there is a richness dependent bias that can be explained by some combination of contamination of the observables and biases in the estimated masses. We discuss possible physical effects, as contamination from line-of-sight projections or from point sources, larger offsets in the SZE-optical centering or larger scatter in the $λ$-mass relation at lower richnesses.

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Crowdsourcing quality control for Dark Energy Survey images

We have developed a crowdsourcing web application for image quality control employed by the Dark Energy Survey. Dubbed the "DES exposure checker", it renders science-grade images directly to a web browser and allows users to mark problematic features from a set of predefined classes. Users can also generate custom labels and thus help identify previously unknown problem classes. User reports are fed back to hardware and software experts to help mitigate and eliminate recognized issues. We report on the implementation of the application and our experience with its over 100 users, the majority of which are professional or prospective astronomers but not data management experts. We discuss aspects of user training and engagement, and demonstrate how problem reports have been pivotal to rapidly correct artifacts which would likely have been too subtle or infrequent to be recognized otherwise. We conclude with a number of important lessons learned, suggest possible improvements, and recommend this collective exploratory approach for future astronomical surveys or other extensive data sets with a sufficiently large user base. We also release open-source code of the web application and host an online demo version at http://des-exp-checker.pmelchior.net

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Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a $\sim$116 deg$^{2}$ area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al. 2016) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i$<$22.5 galaxy sample. We find the galaxy bias and 1$σ$ error bars in 4 photometric redshift bins to be 1.12$\pm$0.19 (z=0.2-0.4), 0.97$\pm$0.15 (z=0.4-0.6), 1.38$\pm$0.39 (z=0.6-0.8)), and 1.45$\pm$0.56 (z=0.8-1.0). These measurements are consistent at the 2$σ$ level with measurements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only $σ_8$-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

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The DES Science Verification Weak Lensing Shear Catalogues

We present weak lensing shear catalogues for 139 square degrees of data taken during the Science Verification (SV) time for the new Dark Energy Camera (DECam) being used for the Dark Energy Survey (DES). We describe our object selection, point spread function estimation and shear measurement procedures using two independent shear pipelines, IM3SHAPE and NGMIX, which produce catalogues of 2.12 million and 3.44 million galaxies respectively. We detail a set of null tests for the shear measurements and find that they pass the requirements for systematic errors at the level necessary for weak lensing science applications using the SV data. We also discuss some of the planned algorithmic improvements that will be necessary to produce sufficiently accurate shear catalogues for the full 5-year DES, which is expected to cover 5000 square degrees.

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Assessment of Systematic Chromatic Errors that Impact Sub-1% Photometric Precision in Large-Area Sky Surveys

Meeting the science goals for many current and future ground-based optical large-area sky surveys requires that the calibrated broadband photometry is stable in time and uniform over the sky to 1% precision or better. Past surveys have achieved photometric precision of 1-2% by calibrating the survey's stellar photometry with repeated measurements of a large number of stars observed in multiple epochs. The calibration techniques employed by these surveys only consider the relative frame-by-frame photometric zeropoint offset and the focal plane position-dependent illumination corrections, which are independent of the source color. However, variations in the wavelength dependence of the atmospheric transmission and the instrumental throughput induce source color-dependent systematic errors. These systematic errors must also be considered to achieve the most precise photometric measurements. In this paper, we examine such systematic chromatic errors using photometry from the Dark Energy Survey (DES) as an example. We define a natural magnitude system for DES and calculate the systematic errors on stellar magnitudes, when the atmospheric transmission and instrumental throughput deviate from the natural system. We conclude that the systematic chromatic errors caused by the change of airmass in each exposure, the change of the precipitable water vapor and aerosol in the atmosphere over time, and the non-uniformity of instrumental throughput over the focal plane, can be up to 2% in some bandpasses. We compare the calculated systematic chromatic errors with the observed DES data. For the test sample data, we correct these errors using measurements of the atmospheric transmission and instrumental throughput. The residual after correction is less than 0.3%. We also find that the errors for non-stellar objects are redshift-dependent and can be larger than those for stars at certain redshifts.

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A Dark Energy Camera Search for an Optical Counterpart to the First Advanced LIGO Gravitational Wave Event GW150914

We report initial results of a deep search for an optical counterpart to the gravitational wave event GW150914, the first trigger from the Advanced LIGO gravitational wave detectors. We used the Dark Energy Camera (DECam) to image a 102 deg$^2$ area, corresponding to 38% of the initial trigger high-probability sky region and to 11% of the revised high-probability region. We observed in i and z bands at 4-5, 7, and 24 days after the trigger. The median $5σ$ point-source limiting magnitudes of our search images are i=22.5 and z=21.8 mag. We processed the images through a difference-imaging pipeline using templates from pre-existing Dark Energy Survey data and publicly available DECam data. Due to missing template observations and other losses, our effective search area subtends 40 deg$^{2}$, corresponding to 12% total probability in the initial map and 3% of the final map. In this area, we search for objects that decline significantly between days 4-5 and day 7, and are undetectable by day 24, finding none to typical magnitude limits of i= 21.5,21.1,20.1 for object colors (i-z)=1,0,-1, respectively. Our search demonstrates the feasibility of a dedicated search program with DECam and bodes well for future research in this emerging field.

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A Dark Energy Camera Search for Missing Supergiants in the LMC After the Advanced LIGO Gravitational Wave Event GW150914

The collapse of the core of a star is expected to produce gravitational radiation. While this process will usually produce a luminous supernova, the optical signatue could be subluminous and a direct collapse to a black hole, with the star just disappearing, is possible. The gravitational wave event GW150914 reported by the LIGO Virgo Collaboration (LVC) on 2015 September 16, was detected by a burst analysis and whose high probability spatial localization included the Large Magellanic Cloud. Shortly after the announcement of the event, we used the Dark Energy Camera to observe 102 deg$^2$ of the localization area, including a 38 deg$^2$ area centered on the LMC. Using a catalog of 152 LMC luminous red supergiants, candidates to undergo a core collapse without a visible supernova, we find that the positions of 144 of these are inside our images, and that all are detected - none have disappeared. There are other classes of candidates: we searched existing catalogs of red supergiants, yellow supergiants, Wolf-Rayet stars, and luminous blue variable stars, recovering all that were inside the imaging area. Based on our observations, we conclude that it is unlikely that GW150914 was caused by the core collapse of a supergiant in the LMC, consistent with the LIGO Collaboration analyses of the gravitational wave form as best described by a binary black hole merger. We discuss how to generalize this search for future very nearby core collapse candidates.

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No galaxy left behind: accurate measurements with the faintest objects in the Dark Energy Survey

Accurate statistical measurement with large imaging surveys has traditionally required throwing away a sizable fraction of the data. This is because most measurements have have relied on selecting nearly complete samples, where variations in the composition of the galaxy population with seeing, depth, or other survey characteristics are small. We introduce a new measurement method that aims to minimize this wastage, allowing precision measurement for any class of stars or galaxies detectable in an imaging survey. We have implemented our proposal in Balrog, a software package which embeds fake objects in real imaging in order to accurately characterize measurement biases. We demonstrate this technique with an angular clustering measurement using Dark Energy Survey (DES) data. We first show that recovery of our injected galaxies depends on a wide variety of survey characteristics in the same way as the real data. We then construct a flux-limited sample of the faintest galaxies in DES, chosen specifically for their sensitivity to depth and seeing variations. Using the synthetic galaxies as randoms in the standard Landy-Szalay correlation function estimator suppresses the effects of variable survey selection by at least two orders of magnitude. With this correction, our measured angular clustering is found to be in excellent agreement with that of a matched sample drawn from much deeper, higher-resolution space-based Cosmological Evolution Survey (COSMOS) imaging; over angular scales of $0.004^{\circ} < θ< 0.2^{\circ}$, we find a best-fit scaling amplitude between the DES and COSMOS measurements of $1.00 \pm 0.09$. We expect this methodology to be broadly useful for extending the statistical reach of measurements in a wide variety of coming imaging surveys.

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CMB lensing tomography with the DES Science Verification galaxies

We measure the cross-correlation between the galaxy density in the Dark Energy Survey (DES) Science Verification data and the lensing of the cosmic microwave background (CMB) as reconstructed with the Planck satellite and the South Pole Telescope (SPT). When using the DES main galaxy sample over the full redshift range $0.2 < z < 1.2$, a cross-correlation signal is detected at $6 σ$ and $4σ$ with SPT and Planck respectively. We then divide the DES galaxies into five photometric redshift bins, finding significant ($>$$2 σ$) detections in all bins. Comparing to the fiducial Planck cosmology, we find the redshift evolution of the signal matches expectations, although the amplitude is consistently lower than predicted across redshift bins. We test for possible systematics that could affect our result and find no evidence for significant contamination. Finally, we demonstrate how these measurements can be used to constrain the growth of structure across cosmic time. We find the data are fit by a model in which the amplitude of structure in the $z<1.2$ universe is $0.73 \pm 0.16$ times as large as predicted in the LCDM Planck cosmology, a $1.7σ$ deviation.

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A Prescription for Galaxy Biasing Evolution as a Nuisance Parameter

There is currently no consistent approach to modelling galaxy bias evolution in cosmological inference. This lack of a common standard makes the rigorous comparison or combination of probes difficult. We show that the choice of biasing model has a significant impact on cosmological parameter constraints for a survey such as the Dark Energy Survey (DES), considering the 2-point correlations of galaxies in five tomographic redshift bins. We find that modelling galaxy bias with a free biasing parameter per redshift bin gives a Figure of Merit (FoM) for Dark Energy equation of state parameters w_0, w_a smaller by a factor of 10 than if a constant bias is assumed. An incorrect bias model will also cause a shift in measured values of cosmological parameters. Motivated by these points and focusing on the redshift evolution of linear bias, we propose the use of a generalised galaxy bias which encompasses a range of bias models from theory, observations and simulations, b(z) = c + (b_0 - c)/D(z)^alpha, where parameters c, b_0 and alpha depend on galaxy properties such as halo mass. For a DES-like galaxy survey we find that this model gives an unbiased estimate of w_0, w_a with the same number or fewer nuisance parameters and a higher FoM than a simple b(z) model allowed to vary in z-bins. We show how the parameters of this model are correlated with cosmological parameters. We fit a range of bias models to two recent datasets, and conclude that this generalised parameterisation is a sensible benchmark expression of galaxy bias on large scales.

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Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data

We study the clustering of galaxies detected at $i<22.5$ in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using $2.3\times 10^6$ galaxies over a contiguous 116 deg$^2$ region in five bins of photometric redshift width $Δz = 0.2$ in the range $0.2 < z < 1.2.$ The impact of photometric redshift errors are assessed by comparing results using a template-based photo-$z$ algorithm (BPZ) to a machine-learning algorithm (TPZ). A companion paper (Leistedt et al 2015) presents maps of several observational variables (e.g. seeing, sky brightness) which could modulate the galaxy density. Here we characterize and mitigate systematic errors on the measured clustering which arise from these observational variables, in addition to others such as Galactic dust and stellar contamination. After correcting for systematic effects we measure galaxy bias over a broad range of linear scales relative to mass clustering predicted from the Planck $Λ$CDM model, finding agreement with CFHTLS measurements with $χ^2$ of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. We test a "linear bias" model, in which the galaxy clustering is a fixed multiple of the predicted non-linear dark-matter clustering. The precision of the data allow us to determine that the linear bias model describes the observed galaxy clustering to $2.5\%$ accuracy down to scales at least $4$ to $10$ times smaller than those on which linear theory is expected to be sufficient.

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Observation and Confirmation of Six Strong Lensing Systems in The Dark Energy Survey Science Verification Data

We report the observation and confirmation of the first group- and cluster-scale strong gravitational lensing systems found in Dark Energy Survey (DES) data. Through visual inspection of data from the Science Verification (SV) season, we identified 53 candidate systems. We then obtained spectroscopic follow-up of 21 candidates using the Gemini Multi-Object Spectrograph (GMOS) at the Gemini South telescope and the Inamori-Magellan Areal Camera and Spectrograph (IMACS) at the Magellan/Baade telescope. With this follow-up, we confirmed six candidates as gravitational lenses: Three of the systems are newly discovered, and the remaining three were previously known. Of the 21 observed candidates, the remaining 15 were either not detected in spectroscopic observations, were observed and did not exhibit continuum emission (or spectral features), or were ruled out as lensing systems. The confirmed sample consists of one group-scale and five galaxy cluster-scale lenses. The lensed sources range in redshift z ~ 0.80-3.2, and in i-band surface brightness i_{SB} ~ 23-25 mag/sq.-arcsec. (2" aperture). For each of the six systems, we estimate the Einstein radius and the enclosed mass, which have ranges ~ 5.0 - 8.6" and ~ 7.5 x 10^{12} - 6.4 x 10^{13} solar masses, respectively.

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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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Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS

We present the results of the first test plates of the extended Baryon Oscillation Spectroscopic Survey. This paper focuses on the emission line galaxies (ELG) population targetted from the Dark Energy Survey (DES) photometry. We analyse the success rate, efficiency, redshift distribution, and clustering properties of the targets. From the 9000 spectroscopic redshifts targetted, 4600 have been selected from the DES photometry. The total success rate for redshifts between 0.6 and 1.2 is 71\% and 68\% respectively for a bright and faint, on average more distant, samples including redshifts measured from a single strong emission line. We find a mean redshift of 0.8 and 0.87, with 15 and 13\% of unknown redshifts respectively for the bright and faint samples. In the redshift range 0.6<z<1.2, for the most secure spectroscopic redshifts, the mean redshift for the bright and faint sample is 0.85 and 0.9 respectively. Star contamination is lower than 2\%. We measure a galaxy bias averaged on scales of 1 and 10~Mpc/h of 1.72 \pm 0.1 for the bright sample and of 1.78 \pm 0.12 for the faint sample. The error on the galaxy bias have been obtained propagating the errors in the correlation function to the fitted parameters. This redshift evolution for the galaxy bias is in agreement with theoretical expectations for a galaxy population with MB-5\log h < -21.0. We note that biasing is derived from the galaxy clustering relative to a model for the mass fluctuations. We investigate the quality of the DES photometric redshifts and find that the outlier fraction can be reduced using a comparison between template fitting and neural network, or using a random forest algorithm.

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Eight Ultra-faint Galaxy Candidates Discovered in Year Two of the Dark Energy Survey

We report the discovery of eight new ultra-faint dwarf galaxy candidates in the second year of optical imaging data from the Dark Energy Survey (DES). Six of these candidates are detected at high confidence, while two lower-confidence candidates are identified in regions of non-uniform survey coverage. The new stellar systems are found by three independent automated search techniques and are identified as overdensities of stars, consistent with the isochrone and luminosity function of an old and metal-poor simple stellar population. The new systems are faint (Mv > -4.7 mag) and span a range of physical sizes (17 pc < $r_{1/2}$ < 181 pc) and heliocentric distances (25 kpc < D < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies (μ< 27.5 mag arcsec$^{-2}$). Roughly half of the DES candidates are more distant, less luminous, and/or have lower surface brightnesses than previously known Milky Way satellite galaxies. Most of the candidates are found in the southern part of the DES footprint close to the Magellanic Clouds. We find that the DES data alone exclude (p < 0.001) a spatially isotropic distribution of Milky Way satellites and that the observed distribution can be well, though not uniquely, described by an association between several of the DES satellites and the Magellanic system. Our model predicts that the full sky may hold ~100 ultra-faint galaxies with physical properties comparable to the DES satellites and that 20-30% of these would be spatially associated with the Magellanic Clouds.

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Joint Analysis of Galaxy-Galaxy Lensing and Galaxy Clustering: Methodology and Forecasts for DES

The joint analysis of galaxy-galaxy lensing and galaxy clustering is a promising method for inferring the growth function of large scale structure. This analysis will be carried out on data from the Dark Energy Survey (DES), with its measurements of both the distribution of galaxies and the tangential shears of background galaxies induced by these foreground lenses. We develop a practical approach to modeling the assumptions and systematic effects affecting small scale lensing, which provides halo masses, and large scale galaxy clustering. Introducing parameters that characterize the halo occupation distribution (HOD), photometric redshift uncertainties, and shear measurement errors, we study how external priors on different subsets of these parameters affect our growth constraints. Degeneracies within the HOD model, as well as between the HOD and the growth function, are identified as the dominant source of complication, with other systematic effects sub-dominant. The impact of HOD parameters and their degeneracies necessitate the detailed joint modeling of the galaxy sample that we employ. We conclude that DES data will provide powerful constraints on the evolution of structure growth in the universe, conservatively/optimistically constraining the growth function to 7.9\%/4.8\% with its first-year data that covered over 1000 square degrees, and to 3.9\%/2.3\% with its full five-year data that will survey 5000 square degrees, including both statistical and systematic uncertainties.

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