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G. Tarle

Publications and source records attributed to G. Tarle.

At least 235 records · Page 13Linked to original sources

An extended catalog of galaxy-galaxy strong gravitational lenses discovered in DES using convolutional neural networks

We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage stamp images of 7.9 million sources from the Dark Energy Survey chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates.

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Identification of RR Lyrae stars in multiband, sparsely-sampled data from the Dark Energy Survey using template fitting and Random Forest classification

Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ~ 23.5 mag) in a single exposure; over 5000 deg$^{2}$) provides a rich opportunity to search for substructures out to the edge of the Milky Way halo. However, the sparse and unevenly sampled multiband light curves from the DES wide-field survey (median 4 observations in each of grizY over the first three years) pose a challenge for traditional techniques used to detect RRL. We present an empirically motivated and computationally efficient template fitting method to identify these variable stars using three years of DES data. When tested on DES light curves of previously classified objects in SDSS stripe 82, our algorithm recovers 89% of RRL periods to within 1% of their true value with 85% purity and 76% completeness. Using this method, we identify 5783 RRL candidates, ~31% of which are previously undiscovered. This method will be useful for identifying RRL in other sparse multiband data sets.

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Steve: A hierarchical Bayesian model for Supernova Cosmology

We present a new Bayesian hierarchical model (BHM) named Steve for performing type Ia supernova (SNIa) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic uncertainty, and increasing numerical efficiency. Given light curve fit parameters, redshifts, and host-galaxy masses, we fit Steve simultaneously for parameters describing cosmology, SNIa populations, and systematic uncertainties. Selection effects are characterised using Monte-Carlo simulations. We demonstrate its implementation by fitting realisations of SNIa datasets where the SNIa model closely follows that used in Steve. Next, we validate on more realistic SNANA simulations of SNIa samples from the Dark Energy Survey and low-redshift surveys. These simulated datasets contain more than $60\,000$ SNeIa, which we use to evaluate biases in the recovery of cosmological parameters, specifically the equation-of-state of dark energy, $w$. This is the most rigorous test of a BHM method applied to SNIa cosmology fitting, and reveals small $w$-biases that depend on the simulated SNIa properties, in particular the intrinsic SNIa scatter model. This $w$-bias is less than $0.03$ on average, less than half the statistical uncertainty on $w$.These simulation test results are a concern for BHM cosmology fitting applications on large upcoming surveys, and therefore future development will focus on minimising the sensitivity of Steve to the SNIa intrinsic scatter model.

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Constraints on the redshift evolution of astrophysical feedback with Sunyaev-Zeldovich effect cross-correlations

An understanding of astrophysical feedback is important for constraining models of galaxy formation and for extracting cosmological information from current and future weak lensing surveys. The thermal Sunyaev-Zel'dovich effect, quantified via the Compton-$y$ parameter, is a powerful tool for studying feedback, because it directly probes the pressure of the hot, ionized gas residing in dark matter halos. Cross-correlations between galaxies and maps of Compton-$y$ obtained from cosmic microwave background surveys are sensitive to the redshift evolution of the gas pressure, and its dependence on halo mass. In this work, we use galaxies identified in year one data from the Dark Energy Survey and Compton-$y$ maps constructed from Planck observations. We find highly significant (roughly $12σ$) detections of galaxy-$y$ cross-correlation in multiple redshift bins. By jointly fitting these measurements as well as measurements of galaxy clustering, we constrain the halo bias-weighted, gas pressure of the Universe as a function of redshift between $0.15 \lesssim z \lesssim 0.75$. We compare these measurements to predictions from hydrodynamical simulations, allowing us to constrain the amount of thermal energy in the halo gas relative to that resulting from gravitational collapse.

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Dark Energy Survey Year 1 results: Detection of Intra-cluster Light at Redshift $\sim$ 0.25

Using data collected by the Dark Energy Survey (DES), we report the detection of intracluster light (ICL) with $\sim300$ galaxy clusters in the redshift range of 0.2-0.3. We design methods to mask detected galaxies and stars in the images and stack the cluster light profiles, while accounting for several systematic effects (sky subtraction, instrumental point-spread function, cluster selection effects and residual light in the ICL raw detection from background and cluster galaxies). The methods allow us to acquire high signal-to-noise measurements of the ICL and central galaxies (CGs), which we separate with radial cuts. The ICL appears as faint and diffuse light extending to at least 1 Mpc from the cluster center, reaching a surface brightness level of 30 mag arcsec$^{-2}$. The ICL and the cluster CG contribute to $44\%\pm17$\% of the total cluster stellar luminosity within 1 Mpc. The ICL color is overall consistent with that of the cluster red sequence galaxies, but displays the trend of becoming bluer with increasing radius. The ICL demonstrates an interesting self-similarity feature -- for clusters in different richness ranges, their ICL radial profiles are similar after scaling with cluster $R_\mathrm{200m}$, and the ICL brightness appears to be a good tracer of the cluster radial mass distribution. These analyses are based on the DES redMaPPer cluster sample identified in the first year of observations.

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A Search for Optical Emission from Binary-Black-Hole Merger GW170814 with the Dark Energy Camera

Binary black hole (BBH) mergers found by the LIGO and Virgo detectors are of immense scientific interest to the astrophysics community, but are considered unlikely to be sources of electromagnetic emission. To test whether they have rapidly fading optical counterparts, we used the Dark Energy Camera to perform an $i$-band search for the BBH merger GW170814, the first gravitational wave detected by three interferometers. The 87-deg$^2$ localization region (at 90\% confidence) centered in the Dark Energy Survey (DES) footprint enabled us to image 86\% of the probable sky area to a depth of $i\sim 23$ mag and provide the most comprehensive dataset to search for EM emission from BBH mergers. To identify candidates, we perform difference imaging with our search images and with templates from pre-existing DES images. The analysis strategy and selection requirements were designed to remove supernovae and to identify transients that decline in the first two epochs. We find two candidates, each of which is spatially coincident with a star or a high-redshift galaxy in the DES catalogs, and they are thus unlikely to be associated with GW170814. Our search finds no candidates associated with GW170814, disfavoring rapidly declining optical emission from BBH mergers brighter than $i\sim 23$ mag ($L_{\rm optical} \sim 5\times10^{41}$ erg/s) 1-2 days after coalescence. In terms of GW sky map coverage, this is the most complete search for optical counterparts to BBH mergers to date

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Brown dwarf census with the Dark Energy Survey year 3 data and the thin disk scale height of early L types

In this paper we present a catalogue of 11,745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field Infrared Survey Explorer (WISE) data, covering approx 2,400 deg2 up to i_AB=22. The classification method follows the same photo-type method previously applied to SDSS-UKIDSS-WISE data. The most significant difference comes from the use of DES data instead of SDSS, which allow us to classify almost an order of magnitude more brown dwarfs than any previous search and reaching distances beyond 400 parsecs for the earliest types. Next, we also present and validate the GalmodBD simulation, which produces brown dwarf number counts as a function of structural parameters with realistic photometric properties of a given survey. We use this simulation to estimate the completeness and purity of our photometric LT catalogue down to i_AB=22, as well as to compare to the observed number of LT types. We put constraints on the thin disk scale height for the early L population to be around 450 parsecs, in agreement with previous findings. For completeness, we also publish in a separate table a catalogue of 20,863 M dwarfs that passed our colour cut with spectral types greater than M6. Both the LT and the late M catalogues are found at https://des.ncsa.illinois.edu/releases/other/y3-mlt

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First measurement of the Hubble constant from a dark standard siren using the Dark Energy Survey galaxies and the LIGO/Virgo binary-black-hole merger GW170814

We present a multi-messenger measurement of the Hubble constant H_0 using the binary-black-hole merger GW170814 as a standard siren, combined with a photometric redshift catalog from the Dark Energy Survey (DES). The luminosity distance is obtained from the gravitational wave signal detected by the LIGO/Virgo Collaboration (LVC) on 2017 August 14, and the redshift information is provided by the DES Year 3 data. Black-hole mergers such as GW170814 are expected to lack bright electromagnetic emission to uniquely identify their host galaxies and build an object-by-object Hubble diagram. However, they are suitable for a statistical measurement, provided that a galaxy catalog of adequate depth and redshift completion is available. Here we present the first Hubble parameter measurement using a black-hole merger. Our analysis results in $H_0 = 75.2^{+39.5}_{-32.4}~{\rm km~s^{-1}~Mpc^{-1}}$, which is consistent with both SN Ia and CMB measurements of the Hubble constant. The quoted 68% credible region comprises 60% of the uniform prior range [20,140] ${\rm km~s^{-1}~Mpc^{-1}}$, and it depends on the assumed prior range. If we take a broader prior of [10,220] ${\rm km~s^{-1}~Mpc^{-1}}$, we find $H_0 = 78^{+ 96}_{-24}~{\rm km~s^{-1}~Mpc^{-1}}$ ($57\%$ of the prior range). Although a weak constraint on the Hubble constant from a single event is expected using the dark siren method, a multifold increase in the LVC event rate is anticipated in the coming years and combinations of many sirens will lead to improved constraints on $H_0$.

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Mass Variance from Archival X-ray Properties of Dark Energy Survey Year-1 Galaxy Clusters

Using archival X-ray observations and a log-normal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behavior of X-ray temperatures, $T_X$, with optical richness, $λ_{RM}$, for clusters in the redshift range $0.2 50\%$ complete for clusters with $λ_{RM} > 130$. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $σ_{\ln Tx | λ} = 0.275 \pm 0.019$. Joined with constraints for $T_X$ scaling with halo mass from the Weighing the Giants program and richness--temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $σ_{\ln M | λ} = 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 70. Uncertainties in external parameters, particularly the slope and variance of the $T_X$--mass relation and the covariance of $T_X$ and $λ_{RM}$ at fixed mass, dominate the systematic error. The $95\%$ confidence region from joint sample analysis is relatively broad, $σ_{\ln M | λ} \in [0.14, \, 0.55]$, or a factor ten in variance.

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The First Tidally Disrupted Ultra-Faint Dwarf Galaxy? - Spectroscopic Analysis of the Tucana III Stream

We present a spectroscopic study of the tidal tails and core of the Milky Way satellite Tucana III, collectively referred to as the Tucana III stream, using the 2dF+AAOmega spectrograph on the Anglo-Australian Telescope and the IMACS spectrograph on the Magellan/Baade Telescope. In addition to recovering the brightest 9 previously known member stars in the Tucana III core, we identify 22 members in the tidal tails. We observe strong evidence for a velocity gradient of 8.0 km/s/deg (or 18.3 km/s/kpc over at least 3$^{\circ}$ (or 1.3 kpc) on the sky. Based on the continuity in velocity we confirm that the Tucana III tails are real tidal extensions of Tucana III. The large velocity gradient of the stream implies that Tucana III is likely on a radial orbit. We successfully obtain metallicities for 4 members in the core and 12 members in the tails. We find that members close to the ends of the stream tend to be more metal-poor than members in the core, indicating a possible metallicity gradient between the center of the progenitor halo and its edge. The spread in metallicity suggests that the progenitor of the Tucana III stream is a dwarf galaxy rather than a star cluster. Furthermore, we find that with the precise photometry of the Dark Energy Survey data, there is a discernible color offset between metal-rich disk stars and metal-poor stream members. This metallicity-dependent color offers a more efficient method to recognize metal-poor targets and will increase the selection efficiency of stream members for future spectroscopic follow-up programs on stellar streams.

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Rediscovery of the Sixth Star Cluster in the Fornax Dwarf Spheroidal Galaxy

Since first noticed by Shapley in 1939, a faint object coincident with the Fornax dwarf spheroidal has long been discussed as a possible sixth globular cluster system. However, debate has continued over whether this overdensity is a statistical artifact or a blended galaxy group. In this Letter we demonstrate, using deep DECam imaging data, that this object is well resolved into stars and is a bona fide star cluster. The stellar overdensity of this cluster is statistically significant at the level of ~ 6 - 6.7 sigma in several different photometric catalogs including Gaia. Therefore, it is highly unlikely to be caused by random fluctuation. We show that Fornax 6 is a star cluster with a peculiarly low surface brightness and irregular shape, which may indicate a strong tidal influence from its host galaxy. The Hess diagram of Fornax 6 is largely consistent with that of Fornax field stars, but it appears to be slightly bluer. However, it is still likely more metal-rich than most of the globular clusters in the system. Faint clusters like Fornax 6 that orbit and potentially get disrupted in the centers of dwarf galaxies can prove crucial for constraining the dark matter distribution in Milky Way satellites.

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More out of less: an excess integrated Sachs-Wolfe signal from supervoids mapped out by the Dark Energy Survey

The largest structures in the cosmic web probe the dynamical nature of dark energy through their integrated Sachs-Wolfe imprints. In the strength of the signal, typical cosmic voids have shown good consistency with expectation $A_{\rm ISW}=ΔT^{\rm data} / ΔT^{\rm theory}=1$, given the substantial cosmic variance. Discordantly, large-scale hills in the gravitational potential, or supervoids, have shown excess signals. In this study, we mapped out 87 new supervoids in the total 5000 deg$^2$ footprint of the Dark Energy Survey at $0.2<z<0.9$ to probe these anomalous claims. We found an excess imprinted profile with $ A_{\rm ISW}\approx4.1\pm2.0$ amplitude. The combination with independent BOSS data reveals an ISW imprint of supervoids at the $3.3σ$ significance level with an enhanced $A_{\rm ISW}\approx5.2\pm1.6$ amplitude. The tension with $Λ$CDM predictions is equivalent to $2.6σ$ and remains unexplained.

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Finding high-redshift strong lenses in DES using convolutional neural networks

We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250,000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 < g - i < 5, 0.6 < g -r < 3, r_mag > 19, g_mag > 20 and i_mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7,301 galaxies. During visual inspection we rate 84 as "probably" or "definitely" lenses. Four of these are previously known lenses or lens candidates. We inspect a further 9,428 candidates with a different score threshold, and identify four new candidates. We present 84 new strong lens candidates, selected after a few hours of visual inspection by astronomers. This catalogue contains a comparable number of high-redshift lenses to that predicted by simulations. Based on simulations we estimate our sample to contain most discoverable lenses in this imaging and at this redshift range.

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Transfer learning for galaxy morphology from one survey to another

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.

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Three new VHS-DES Quasars at 6.7 < z < 6.9 and Emission Line Properties at z > 6.5

We report the results from a search for z > 6.5 quasars using the Dark Energy Survey (DES) Year 3 dataset combined with the VISTA Hemisphere Survey (VHS) and WISE All-Sky Survey. Our photometric selection method is shown to be highly efficient in identifying clean samples of high-redshift quasars leading to spectroscopic confirmation of three new quasars - VDESJ 0244-5008 (z=6.724), VDESJ 0020-3653 (z=6.834) and VDESJ 0246-5219 (z=6.90) - which were selected as the highest priority candidates in the survey data without any need for additional follow-up observations. The new quasars span the full range in luminosity covered by other z>6.5 quasar samples (J AB = 20.2 to 21.3; M1450 = -25.6 to -26.6). We have obtained spectroscopic observations in the near infrared for VDESJ 0244-5008 and VDESJ 0020-3653 as well as our previously identified quasar, VDESJ 0224-4711 at z=6.50 from Reed et al. (2017). We use the near infrared spectra to derive virial black-hole masses from the full-width-half-maximum of the MgII line. These black-hole masses are ~ 1 - 2 x 10$^9$M$_\odot$. Combining with the bolometric luminosities of these quasars of L$_{\rm{bol}}\simeq$ 1 - 3 x 10$^{47}$implies that the Eddington ratios are high - $\simeq$0.6-1.1. We consider the C\textrm{\textsc{IV}} emission line properties of the sample and demonstrate that our high-redshift quasars do not have unusual C\textrm{\textsc{IV}} line properties when compared to carefully matched low-redshift samples. Our new DES+VHS $z>6.5$ quasars now add to the growing census of luminous, rapidly accreting supermassive black-holes seen well into the epoch of reionisation.

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Evidence for Color Dichotomy in the Primordial Neptunian Trojan Population

In the current model of early Solar System evolution, the stable members of the Jovian and Neptunian Trojan populations were captured into resonance from the leftover reservoir of planetesimals during the outward migration of the giant planets. As a result, both Jovian and Neptunian Trojans share a common origin with the primordial disk population, whose other surviving members constitute today's trans-Neptunian object (TNO) populations. The cold classical TNOs are ultra-red, while the dynamically excited "hot" population of TNOs contains a mixture of ultra-red and blue objects. In contrast, Jovian and Neptunian Trojans are observed to be blue. While the absence of ultra-red Jovian Trojans can be readily explained by the sublimation of volatile material from their surfaces due to the high flux of solar radiation at 5AU, the lack of ultra-red Neptunian Trojans presents both a puzzle and a challenge to formation models. In this work we report the discovery by the Dark Energy Survey (DES) of two new dynamically stable L4 Neptunian Trojans,2013 VX30 and 2014 UU240, both with inclinations i >30 degrees, making them the highest-inclination known stable Neptunian Trojans. We have measured the colors of these and three other dynamically stable Neptunian Trojans previously observed by DES, and find that 2013 VX30 is ultra-red, the first such Neptunian Trojan in its class. As such, 2013 VX30 may be a "missing link" between the Trojan and TNO populations. Using a simulation of the DES TNO detection efficiency, we find that there are 162 +/- 73 Trojans with Hr < 10 at the L4 Lagrange point of Neptune. Moreover, the blue-to-red Neptunian Trojan population ratio should be higher than 17:1. Based on this result, we discuss the possible origin of the ultra-red Neptunian Trojan population and its implications for the formation history of Neptunian Trojans.

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Dark Energy Survey Year 1 Results: Galaxy Sample for BAO Measurement

We define and characterise a sample of 1.3 million galaxies extracted from the first year of Dark Energy Survey data, optimised to measure Baryon Acoustic Oscillations in the presence of significant redshift uncertainties. The sample is dominated by luminous red galaxies located at redshifts $z \gtrsim 0.6$. We define the exact selection using color and magnitude cuts that balance the need of high number densities and small photometric redshift uncertainties, using the corresponding forecasted BAO distance error as a figure-of-merit in the process. The typical photo-$z$ uncertainty varies from $2.3\%$ to $3.6\%$ (in units of 1+$z$) from $z=0.6$ to $1$, with number densities from $200$ to $130$ galaxies per deg$^2$ in tomographic bins of width $Δz = 0.1$. Next we summarise the validation of the photometric redshift estimation. We characterise and mitigate observational systematics including stellar contamination, and show that the clustering on large scales is robust in front of those contaminants. We show that the clustering signal in the auto-correlations and cross-correlations is generally consistent with theoretical models, which serves as an additional test of the redshift distributions.

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Dark Energy Survey Year 1 results: Validation of weak lensing cluster member contamination estimates from P(z) decomposition

Weak lensing source galaxy catalogs used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study we test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift $P(z)$ of source galaxies into contaminating and background components. We perform a full scale mock analysis on a simulated sky survey approximately mirroring the observational properties of the Dark Energy Survey Year One observations (DES Y1), and find excellent agreement between the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. We further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of weak lensing source galaxies. We find indications that the correlation based estimates are biased by the selection of the weak lensing sources in the cluster vicinity, which does not strongly impact the $P(z)$ decomposition method. Collectively, these benchmarks demonstrate the strength of the $P(z)$ decomposition method in alleviating membership contamination and enabling highly accurate cluster weak lensing studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing.

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