arXiv subjects

V. Scarpine

Publications and source records attributed to V. Scarpine.

At least 163 records · Page 9Linked to original sources

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

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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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

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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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

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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arXiv2018

Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation scale in the distribution of galaxies to redshift 1

We present angular diameter distance measurements obtained by locating the BAO scale in the distribution of galaxies selected from the first year of Dark Energy Survey data. We consider a sample of over 1.3 million galaxies distributed over a footprint of 1318 deg$^2$ with $0.6 < z_{\rm photo} < 1$ and a typical redshift uncertainty of $0.03(1+z)$. This sample was selected, as fully described in a companion paper, using a color/magnitude selection that optimizes trade-offs between number density and redshift uncertainty. We investigate the BAO signal in the projected clustering using three conventions, the angular separation, the co-moving transverse separation, and spherical harmonics. Further, we compare results obtained from template based and machine learning photometric redshift determinations. We use 1800 simulations that approximate our sample in order to produce covariance matrices and allow us to validate our distance scale measurement methodology. We measure the angular diameter distance, $D_A$, at the effective redshift of our sample divided by the true physical scale of the BAO feature, $r_{\rm d}$. We obtain close to a 4 per cent distance measurement of $D_A(z_{\rm eff}=0.81)/r_{\rm d} = 10.75\pm 0.43 $. These results are consistent with the flat $Λ$CDM concordance cosmological model supported by numerous other recent experimental results. All data products are publicly available here: https://des.ncsa.illinois.edu/releases/y1a1/bao

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arXiv2018

DES Y1 Results: Validating cosmological parameter estimation using simulated Dark Energy Surveys

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input cosmology is consistent with the combined constraints from multiple simulated DES Y1 realizations in the $Ω_m-σ_8$ plane. For one of the suites, we are able to show with high confidence that any biases in the inferred $S_8=σ_8(Ω_m/0.3)^{0.5}$ and $Ω_m$ are smaller than the DES Y1 $1-σ$ uncertainties. For the other suite, for which we have fewer realizations, we are unable to be this conclusive; we infer a roughly 70% probability that systematic biases in the recovered $Ω_m$ and $S_8$ are sub-dominant to the DES Y1 uncertainty. As cosmological analyses of this kind become increasingly more precise, validation of parameter inference using survey simulations will be essential to demonstrate robustness.

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arXiv2018

First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Effects of Chromatic Corrections to Supernova Photometry on Measurements of Cosmological Parameters

Calibration uncertainties have been the leading systematic uncertainty in recent analyses using type Ia Supernovae (SNe Ia) to measure cosmological parameters. To improve the calibration, we present the application of Spectral Energy Distribution (SED)-dependent "chromatic corrections" to the supernova light-curve photometry from the Dark Energy Survey (DES). These corrections depend on the combined atmospheric and instrumental transmission function for each exposure, and they affect photometry at the 0.01 mag (1%) level, comparable to systematic uncertainties in calibration and photometry. Fitting our combined DES and low-z SN Ia sample with Baryon Acoustic Oscillation (BAO) and Cosmic Microwave Background (CMB) priors for the cosmological parameters $Ω_{\rm m}$ (the fraction of the critical density of the universe comprised of matter) and w (the dark energy equation of state parameter), we compare those parameters before and after applying the corrections. We find the change in w and $Ω_{\rm m}$ due to not including chromatic corrections are -0.002 and 0.000, respectively, for the DES-SN3YR sample with BAO and CMB priors, consistent with a larger DES-SN3YR-like simulation, which has a w-change of 0.0005 with an uncertainty of 0.008 and an $Ω_{\rm m}$ change of 0.000 with an uncertainty of 0.002 . However, when considering samples on individual CCDs we find large redshift-dependent biases (approximately 0.02 in distance modulus) for supernova distances.

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arXiv2018

Star-galaxy classification in the Dark Energy Survey Y1 dataset

We perform a comparison of different approaches to star-galaxy classification using the broad-band photometric data from Year 1 of the Dark Energy Survey. This is done by performing a wide range of tests with and without external `truth' information, which can be ported to other similar datasets. We make a broad evaluation of the performance of the classifiers in two science cases with DES data that are most affected by this systematic effect: large-scale structure and Milky Way studies. In general, even though the default morphological classifiers used for DES Y1 cosmology studies are sufficient to maintain a low level of systematic contamination from stellar mis-classification, contamination can be reduced to the O(1%) level by using multi-epoch and infrared information from external datasets. For Milky Way studies the stellar sample can be augmented by ~20% for a given flux limit. Reference catalogs used in this work will be made available upon publication.

astro-ph.IM↗

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

Dark Energy Survey Year 1 Results: Methods for Cluster Cosmology and Application to the SDSS

We perform the first blind analysis of cluster abundance data. Specifically, we derive cosmological constraints from the abundance and weak-lensing signal of \redmapper\ clusters of richness $λ\geq 20$ in the redshift range $z\in[0.1,0.3]$ as measured in the Sloan Digital Sky Survey (SDSS). We simultaneously fit for cosmological parameters and the richness--mass relation of the clusters. For a flat $Λ$CDM cosmological model with massive neutrinos, we find $S_8 \equiv σ_{8}(Ω_m/0.3)^{0.5}=0.79^{+0.05}_{-0.04}$. This value is both consistent and competitive with that derived from cluster catalogues selected in different wavelengths. Our result is also consistent with the combined probes analyses by the Dark Energy Survey (DES) and the Kilo-Degree Survey (KiDS), and with the Cosmic Microwave Background (CMB) anisotropies as measured by \planck. We demonstrate that the cosmological posteriors are robust against variation of the richness--mass relation model and to systematics associated with the calibration of the selection function. In combination with Baryon Acoustic Oscillation (BAO) data and Big-Bang Nucleosynthesis (BBN) data, we constrain the Hubble rate to be $h=0.66\pm 0.02$, independent of the CMB. Future work aimed at improving our understanding of the scatter of the richness--mass relation has the potential to significantly improve the precision of our cosmological posteriors. The methods described in this work were developed for use in the forthcoming analysis of cluster abundances in the DES. Our SDSS analysis constitutes the first part of a staged-unblinding analysis of the full DES data set.

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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

Dark Energy Survey Year 1 Results: Calibration of redMaGiC Redshift Distributions in DES and SDSS from Cross-Correlations

We present calibrations of the redshift distributions of redMaGiC galaxies in the Dark Energy Survey Year 1 (DES Y1) and Sloan Digital Sky Survey (SDSS) DR8 data. These results determine the priors of the redshift distribution of redMaGiC galaxies, which were used for galaxy clustering measurements and as lenses for galaxy-galaxy lensing measurements in DES Y1 cosmological analyses. We empirically determine the bias in redMaGiC photometric redshift estimates using angular cross-correlations with Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. For DES, we calibrate a single parameter redshift bias in three photometric redshift bins: $z \in[0.15,0.3]$, [0.3,0.45], and [0.45,0.6]. Our best fit results in each bin give photometric redshift biases of $|Δz|<0.01$. To further test the redMaGiC algorithm, we apply our calibration procedure to SDSS redMaGiC galaxies, where the statistical precision of the cross-correlation measurement is much higher due to a greater overlap with BOSS galaxies. For SDSS, we also find best fit results of $|Δz|<0.01$. We compare our results to other analyses of redMaGiC photometric redshifts.

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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

The morphology and structure of stellar populations in the Fornax dwarf spheroidal galaxy from Dark Energy Survey Data

Using deep wide-field photometry three-year data (Y3) from the Dark Energy Survey (DES), we present a panoramic study of the Fornax dwarf spheroidal galaxy. The data presented here -- a small subset of the full survey -- uniformly covers a region of 25 square degrees centered on the galaxy to a depth of g ~ 23.5. We use this data to study the structural properties of Fornax, overall stellar population, and its member stars in different evolutionary phases. We also search for possible signs of tidal disturbance. Fornax is found to be significantly more spatially extended than what early studies suggested. No statistically significant distortions or signs of tidal disturbances were found down to a surface brightness limit of ~32.1 mag/arcsec^2. However, there are hints of shell-like features located ~30' - 40' from the center of Fornax that may be stellar debris from past merger events. We also find that intermediate age and young main-sequence populations show different orientation at the galaxy center and have many substructures. The deep DES Y3 data allows us to characterize the age of those substructures with great accuracy, both those previously known and those newly discovered in this work, on the basis of their color-magnitude diagram morphology. We find that the youngest overdensities are all found on the Eastern side of Fornax, where the Fornax field population itself is slightly younger than in the West. The high quality DES Y3 data reveals that Fornax has many rich structures, and provides insights into its complex formation history.

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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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