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N. Kuropatkin

Publications and source records attributed to N. Kuropatkin.

At least 199 records · Page 11Linked 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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A faint halo star cluster discovered in the Blanco Imaging of the Southern Sky Survey

We present the discovery of a faint, resolved stellar system, BLISS J0321+0438 (BLISS 1), found in Dark Energy Camera data from the first observing run of the Blanco Imaging of the Southern Sky (BLISS) Survey. BLISS J0321+0438 (BLISS 1) is located at (RA, Dec) = (177.511, -41.772) deg with a heliocentric distance of D = 23.7$^{+1.9}_{-1.0}$ kpc. It is a faint, Mv = 0.0$^{+1.7}_{-0.7}$ mag, and compact, rh = 4.1 +/- 1 pc, system consistent with previously discovered faint halo star clusters. Using data from the second data release of the Gaia satellite, we measure a proper motion of $(μ_α\cos δ, μ_δ)$ = (-2.37 +/- 0.06, 0.16 +/- 0.04) mas/yr. Combining the available positional and velocity information with simulations of the accreted satellite population of the Large Magellanic Cloud, we find that it is unlikely that BLISS J0321+0438 (BLISS 1) originated with the Large Magellanic Cloud.

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First Cosmology Results using Type Ia Supernova from the Dark Energy Survey: Simulations to Correct Supernova Distance Biases

We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light curve analysis, and to determine bias corrections for SN~Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN~Ia model, incorporates information from observations (PSF, sky noise, zero point), and uses summary information (e.g., detection efficiency vs. signal to noise ratio) based on 10,000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05~mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue color, distance biases can reach 0.4~mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at https://des.ncsa.illinois.edu/releases/sn.

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First Cosmology Results using Type Ia Supernovae from the Dark Energy Survey: Constraints on Cosmological Parameters

We present the first cosmological parameter constraints using measurements of type Ia supernovae (SNe Ia) from the Dark Energy Survey Supernova Program (DES-SN). The analysis uses a subsample of 207 spectroscopically confirmed SNe Ia from the first three years of DES-SN, combined with a low-redshift sample of 122 SNe from the literature. Our "DES-SN3YR" result from these 329 SNe Ia is based on a series of companion analyses and improvements covering SN Ia discovery, spectroscopic selection, photometry, calibration, distance bias corrections, and evaluation of systematic uncertainties. For a flat LCDM model we find a matter density Omega_m = 0.331 +_ 0.038. For a flat wCDM model, and combining our SN Ia constraints with those from the cosmic microwave background (CMB), we find a dark energy equation of state w = -0.978 +_ 0.059, and Omega_m = 0.321 +_ 0.018. For a flat w0waCDM model, and combining probes from SN Ia, CMB and baryon acoustic oscillations, we find w0 = -0.885 +_ 0.114 and wa = -0.387 +_ 0.430. These results are in agreement with a cosmological constant and with previous constraints using SNe Ia (Pantheon, JLA).

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Cosmological Constraints from Multiple Probes in the Dark Energy Survey

The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically--confirmed Type Ia supernova lightcurves; the baryon acoustic oscillation feature; weak gravitational lensing; and galaxy clustering. Here we present combined results from these probes, deriving constraints on the equation of state, $w$, of dark energy and its energy density in the Universe. Independently of other experiments, such as those that measure the cosmic microwave background, the probes from this single photometric survey rule out a Universe with no dark energy, finding $w=-0.80^{+0.09}_{-0.11}$. The geometry is shown to be consistent with a spatially flat Universe, and we obtain a constraint on the baryon density of $Ω_b=0.069^{+0.009}_{-0.012}$ that is independent of early Universe measurements. These results demonstrate the potential power of large multi-probe photometric surveys and pave the way for order of magnitude advances in our constraints on properties of dark energy and cosmology over the next decade.

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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

astro-ph.HE↗

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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Mass Calibration of Optically Selected DES clusters using a Measurement of CMB-Cluster Lensing with SPTpol Data

We use cosmic microwave background (CMB) temperature maps from the 500 deg$^{2}$ SPTpol survey to measure the stacked lensing convergence of galaxy clusters from the Dark Energy Survey (DES) Year-3 redMaPPer (RM) cluster catalog. The lensing signal is extracted through a modified quadratic estimator designed to be unbiased by the thermal Sunyaev-Zel{'}dovich (tSZ) effect. The modified estimator uses a tSZ-free map, constructed from the SPTpol 95 and 150 GHz datasets, to estimate the background CMB gradient. For lensing reconstruction, we employ two versions of the RM catalog: a flux-limited sample containing 4003 clusters and a volume-limited sample with 1741 clusters. We detect lensing at a significance of 8.7$σ$(6.7$σ$) with the flux(volume)-limited sample. By modeling the reconstructed convergence using the Navarro-Frenk-White profile, we find the average lensing masses to be $M_{200m}$ = ($1.62^{+0.32}_{-0.25}$ [stat.] $\pm$ 0.04 [sys.]) and ($1.28^{+0.14}_{-0.18}$ [stat.] $\pm$ 0.03 [sys.]) $\times\ 10^{14}\ M_{\odot}$ for the volume- and flux-limited samples respectively. The systematic error budget is much smaller than the statistical uncertainty and is dominated by the uncertainties in the RM cluster centroids. We use the volume-limited sample to calibrate the normalization of the mass-richness scaling relation, and find a result consistent with the galaxy weak-lensing measurements from DES (Mcclintock et al. 2018).

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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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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.

astro-ph.EP↗