arXiv subjects

V. Vikram

Publications and source records attributed to V. Vikram.

At least 73 records · Page 4Linked to original sources

arXiv2019

Dark Energy Survey Year 1 Results: Calibration of Cluster Mis-centering in the redMaPPer Catalogs

The center determination of a galaxy cluster from an optical cluster finding algorithm can be offset from theoretical prescriptions or $N$-body definitions of its host halo center. These offsets impact the recovered cluster statistics, affecting both richness measurements and the weak lensing shear profile around the clusters. This paper models the centering performance of the \RM~cluster finding algorithm using archival X-ray observations of \RM-selected clusters. Assuming the X-ray emission peaks as the fiducial halo centers, and through analyzing their offsets to the \RM~centers, we find that $\sim 75\pm 8 \%$ of the \RM~clusters are well centered and the mis-centered offset follows a Gamma distribution in normalized, projected distance. These mis-centering offsets cause a systematic underestimation of cluster richness relative to the well-centered clusters, for which we propose a descriptive model. Our results enable the DES Y1 cluster cosmology analysis by characterizing the necessary corrections to both the weak lensing and richness abundance functions of the DES Y1 redMaPPer cluster catalog.

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arXiv2019

Dark Energy Survey Year 1 Results: Wide field mass maps via forward fitting in harmonic space

We present new wide-field weak lensing mass maps for the Year 1 Dark Energy Survey data, generated via a forward fitting approach. This method of producing maps does not impose any prior constraints on the mass distribution to be reconstructed. The technique is found to improve the map reconstruction on the edges of the field compared to the conventional Kaiser-Squires method, which applies a direct inversion on the data; our approach is in good agreement with the previous direct approach in the central regions of the footprint. The mapping technique is assessed and verified with tests on simulations; together with the Kaiser-Squires method, the technique is then applied to data from the Dark Energy Survey Year 1 data and the differences between the two methods are compared. We also produce the first DES measurements of the convergence Minkowski functionals and compare them to those measured in simulations.

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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2019

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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arXiv2018

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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arXiv2018

Dynamical Analysis of Three Distant Trans-Neptunian Objects with Similar Orbits

This paper reports the discovery and orbital characterization of two extreme trans-Neptunian objects (ETNOs), 2016 QV$_{89}$ and 2016 QU$_{89}$, which have orbits that appear similar to that of a previously known object, 2013 UH$_{15}$. All three ETNOs have semi-major axes $a\approx 172$ AU and eccentricities $e\approx0.77$. The angular elements $(i,ω,Ω)$ vary by 6, 15, and 49 deg, respectively between the three objects. The two new objects add to the small number of TNOs currently known to have semi-major axes between 150 and 250 AU, and serve as an interesting dynamical laboratory to study the outer realm of our Solar System. Using a large ensemble of numerical integrations, we find that the orbits are expected to reside in close proximity in the $(a,e)$ phase plane for roughly 100 Myr before diffusing to more separated values. We then explore other scenarios that could influence their orbits. With aphelion distances over 300 AU, the orbits of these ETNOs extend far beyond the classical Kuiper Belt, and an order of magnitude beyond Neptune. As a result, their orbital dynamics can be affected by the proposed new Solar System member, referred to as Planet Nine in this work. With perihelion distances of 35-40 AU, these orbits are also influenced by resonant interactions with Neptune. A full assessment of any possible, new Solar System planets must thus take into account this emerging class of TNOs.

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arXiv2018

Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data

Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using Counts-in-Cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification (SV) data from the Dark Energy Survey (DES). We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, CMB lensing, and shear+clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion $δ_{g} = \sum_{k=0}^{3} (b_{k}/k!) δ^{k}$, finding a non-zero value for $b_2$ at the $3σ$ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large scale regime ($>30$ Mpc $h^{-1}$)

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arXiv2018

A catalogue of structural and morphological measurements for DES Y1

We present a structural and morphological catalogue for 45 million objects selected from the first year of data from the Dark Energy Survey (DES). Single Sersic fits and non-parametric measurements are produced for g, r and i filters. The parameters from the best-fitting Sersic model (total magnitude, half-light radius, Sersic index, axis ratio and position angle) are measured with Galfit; the non-parametric coefficients (concentration, asymmetry, clumpiness, Gini, M20) are provided using the Zurich Estimator of Structural Types (ZEST+). To study the statistical uncertainties, we consider a sample of state-of-the-art image simulations with a realistic distribution in the input parameter space and then process and analyse them as we do with real data: this enables us to quantify the observational biases due to PSF blurring and magnitude effects and correct the measurements as a function of magnitude, galaxy size, Sersic index (concentration for the analysis of the non-parametric measurements) and ellipticity. We present the largest structural catalogue to date: we find that accurate and complete measurements for all the structural parameters are typically obtained for galaxies with SExtractor MAG AUTO I < 21. Indeed, the parameters in the filters i and r can be overall well recovered up to MAG AUTO < 21.5, corresponding to a fitting completeness of ~90% below this threshold, for a total of 25 million galaxies. The combination of parametric and non-parametric structural measurements makes this catalogue an important instrument to explore and understand how galaxies form and evolve. The catalogue described in this paper will be publicly released alongside the Dark Energy Survey collaboration Y1 cosmology data products at the following URL: https://des.ncsa.illinois.edu/releases/y1a1/gold/morphology.

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arXiv2018

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion, not accounting for survey masks or noise. The Wiener filter is well-motivated for Gaussian density fields in a Bayesian framework. GLIMPSE uses sparsity, aiming to reconstruct non-linearities in the density field. We compare these methods with several tests using public Dark Energy Survey (DES) Science Verification (SV) data and realistic DES simulations. The Wiener filter and GLIMPSE offer substantial improvements over smoothed KS with a range of metrics. Both the Wiener filter and GLIMPSE convergence reconstructions show a 12 per cent improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods' abilities to find mass peaks, we measure the difference between peak counts from simulated ΛCDM shear catalogues and catalogues with no mass fluctuations (a standard data vector when inferring cosmology from peak statistics); the maximum signal-to-noise of these peak statistics is increased by a factor of 3.5 for the Wiener filter and 9 for GLIMPSE. With simulations we measure the reconstruction of the harmonic phases; the phase residuals' concentration is improved 17 per cent by GLIMPSE and 18 per cent by the Wiener filter. The correlation between reconstructions from data and foreground redMaPPer clusters is increased 18 per cent by the Wiener filter and 32 per cent by GLIMPSE.

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arXiv2018

Dark Energy Survey Year 1 Results: Weak Lensing Mass Calibration of redMaPPer Galaxy Clusters

We constrain the mass--richness scaling relation of redMaPPer galaxy clusters identified in the Dark Energy Survey Year 1 data using weak gravitational lensing. We split clusters into $4\times3$ bins of richness $λ$ and redshift $z$ for $λ\geq20$ and $0.2 \leq z \leq 0.65$ and measure the mean masses of these bins using their stacked weak lensing signal. By modeling the scaling relation as $\langle M_{\rm 200m}|λ,z\rangle = M_0 (λ/40)^F ((1+z)/1.35)^G$, we constrain the normalization of the scaling relation at the 5.0 per cent level as $M_0 = [3.081 \pm 0.075 ({\rm stat}) \pm 0.133 ({\rm sys})] \cdot 10^{14}\ {\rm M}_\odot$ at $λ=40$ and $z=0.35$. The richness scaling index is constrained to be $F=1.356 \pm 0.051\ ({\rm stat})\pm 0.008\ ({\rm sys})$ and the redshift scaling index $G=-0.30\pm 0.30\ ({\rm stat})\pm 0.06\ ({\rm sys})$. These are the tightest measurements of the normalization and richness scaling index made to date. We use a semi-analytic covariance matrix to characterize the statistical errors in the recovered weak lensing profiles. Our analysis accounts for the following sources of systematic error: shear and photometric redshift errors, cluster miscentering, cluster member dilution of the source sample, systematic uncertainties in the modeling of the halo--mass correlation function, halo triaxiality, and projection effects. We discuss prospects for reducing this systematic error budget, which dominates the uncertainty on $M_0$. Our result is in excellent agreement with, but has significantly smaller uncertainties than, previous measurements in the literature, and augurs well for the power of the DES cluster survey as a tool for precision cosmology and upcoming galaxy surveys such as LSST, Euclid and WFIRST.

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arXiv2018

Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data

We derive cosmological constraints from the probability distribution function (PDF) of evolved large-scale matter density fluctuations. We do this by splitting lines of sight by density based on their count of tracer galaxies, and by measuring both gravitational shear around and counts-in-cells in overdense and underdense lines of sight, in Dark Energy Survey (DES) First Year and Sloan Digital Sky Survey (SDSS) data. Our analysis uses a perturbation theory model (see companion paper Friedrich at al.) and is validated using N-body simulation realizations and log-normal mocks. It allows us to constrain cosmology, bias and stochasticity of galaxies w.r.t. matter density and, in addition, the skewness of the matter density field. From a Bayesian model comparison, we find that the data weakly prefer a connection of galaxies and matter that is stochastic beyond Poisson fluctuations on <=20 arcmin angular smoothing scale. The two stochasticity models we fit yield DES constraints on the matter density $Ω_m=0.26^{+0.04}_{-0.03}$ and $Ω_m=0.28^{+0.05}_{-0.04}$ that are consistent with each other. These values also agree with the DES analysis of galaxy and shear two-point functions (3x2pt) that only uses second moments of the PDF. Constraints on $σ_8$ are model dependent ($σ_8=0.97^{+0.07}_{-0.06}$ and $0.80^{+0.06}_{-0.07}$ for the two stochasticity models), but consistent with each other and with the 3x2pt results if stochasticity is at the low end of the posterior range. As an additional test of gravity, counts and lensing in cells allow to compare the skewness $S_3$ of the matter density PDF to its LCDM prediction. We find no evidence of excess skewness in any model or data set, with better than 25 per cent relative precision in the skewness estimate from DES alone.

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arXiv2018

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

We estimate total mass ($M_{500}$), intracluster medium (ICM) mass ($M_{\mathrm{ICM}}$) and stellar mass ($M_{\star}$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $M_{500}\gtrsim2.5\times10^{14}M_{\odot}$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $M_{500}$ are estimated from the SZE observable, the ICM masses $M_{\mathrm{ICM}}$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $M_{\star}$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $\approx9$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.

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