We derive the structural parameters of the recently discovered very low luminosity Milky Way satellites through a maximum likelihood algorithm applied to SDSS data. For each satellite, even when only ...a few tens of stars are available down to the SDSS flux limit, the algorithm yields robust estimates and errors for the centroid, position angle, ellipticity, exponential half-light radius and number of member stars (within the SDSS). This latter parameter is then used in conjunction with stellar population models of the satellites to derive their absolute magnitudes and stellar masses, accounting for color-magnitude diagram shot noise. Most parameters are in good agreement with previous determinations, but we now properly account for parameter covariances. However, we find that faint satellites are somewhat more elliptical than initially thought, and ascribe this effect to the previous use of smoothed maps, which can be dominated by the smoothing (round) kernel. As a result, the faintest half of the Milky Way dwarf galaxies is significantly (4 capital sigma ) flatter than its brightest half . From our best models, we also investigate whether the seemingly distorted shape of the satellites, often taken to be a sign of tidal distortion, can be quantified. We find that, except for tentative evidence of distortion in Canes Venatici I and Ursa Major II, these can be completely accounted for by Poisson scatter in the sparsely sampled systems. We consider three scenarios that could explain the rather elongated shape of faint satellites: rotation supported systems, stars following the shape of more triaxial dark matter subhalos, or elongation due to tidal interaction with the Milky Way. Although none of these is entirely satisfactory, the last one appears the least problematic, but obviously warrants much deeper observations to track evidence of such tidal interaction.
We map the stellar structure of the Galactic thick disk and halo by applying color-magnitude diagram (CMD) fitting to photometric data from the Sloan Extension for Galactic Understanding and ...Exploration (SEGUE) survey. The SEGUE imaging scans allow, for the first time, a comprehensive analysis of Milky Way structure at both high and low latitudes using uniform Sloan Digital Sky Survey photometry. Incorporating photometry of all relevant stars simultaneously, CMD fitting bypasses the need to choose single tracer populations. Using old stellar populations of differing metallicities as templates, we obtain a sparse three-dimensional map of the stellar mass distribution at |Z|>1 kpc. Fitting a smooth Milky Way model comprising exponential thin and thick disks and an axisymmetric power-law halo allows us to constrain the structural parameters of the thick disk and halo. The thick-disk scale height and length are well constrained at 0.75 {+-} 0.07 kpc and 4.1 {+-} 0.4 kpc, respectively. We find a stellar halo flattening within {approx}25 kpc of c/a = 0.88 {+-} 0.03 and a power-law index of 2.75 {+-} 0.07 (for 7 kpc {approx_lt}R{sub GC} {approx_lt} 30 kpc). The model fits yield thick-disk and stellar halo densities at the solar location of {rho}{sub thick,sun} = 10{sup -2.3{+-}0.1} M{sub sun} pc{sup -3} and {rho}{sub halo,sun} = 10{sup -4.20{+-}0.05} M{sub sun} pc{sup -3}, averaging over any substructures. Our analysis provides the first clear in situ evidence for a radial metallicity gradient in the Milky Way's stellar halo: within R {approx_lt} 15 kpc the stellar halo has a mean metallicity of Fe/H {approx_equal} -1.6, which shifts to Fe/H {approx_equal} -2.2 at larger radii, in line with the two-component halo deduced by Carollo et al. from a local kinematic analysis. Subtraction of the best-fit smooth and symmetric model from the overall density maps reveals a wealth of substructures at all latitudes, some attributable to known streams and overdensities, and some new. A simple warp cannot account for the low latitude substructure, as overdensities occur simultaneously above and below the Galactic plane.
We have used data from the Sloan Digital Sky Survey (SDSS) Data Release 5 to explore the overall structure and substructure of the stellar halo of the Milky Way using image4 million color-selected ...main-sequence turnoff stars with image and image. We fit oblate and triaxial broken power law models to the data, and found a 'best-fit' oblateness of the stellar halo image, and halo stellar masses between galactocentric radii of 1 and 40 kpc of image M sub(image). The density profile of the stellar halo is approximately image, where -image. Yet, we found that all smooth and symmetric models were very poor fits to the distribution of stellar halo stars because the data exhibit a great deal of spatial substructure. We quantified deviations from a smooth oblate/triaxial model using the rms of the data around the model profile on scales image100 pc, after accounting for the (known) contribution of Poisson uncertainties. Within the DR5 area of the SDSS, the fractional rms deviation capital sigma /total of the actual stellar distribution from any smooth, parameterized halo model is image40%: hence, the stellar halo is highly structured. We compared the observations with simulations of galactic stellar halos formed entirely from the accretion of satellites in a cosmological context by analyzing the simulations in the same way as the SDSS data. While the masses, overall profiles, and degree of substructure in the simulated stellar halos show considerable scatter, the properties and degree of substructure in the Milky Way's halo match well the properties of a 'typical' stellar halo built exclusively out of the debris from disrupted satellite galaxies. Our results therefore point toward a picture in which an important fraction of the stellar halo of the Milky Way has been accreted from satellite galaxies.
The Kilo-Degree Survey (KiDS) is a multi-band imaging survey designed for cosmological studies from weak lensing and photometric redshifts. It uses the European Southern Observatory VLT Survey ...Telescope with its wide-field camera OmegaCAM. KiDS images are taken in four filters similar to the Sloan Digital Sky Survey ugri bands. The best seeing time is reserved for deep r-band observations. The median 5σ limiting AB magnitude is 24.9 and the median seeing is below 0.7 arcsec. Initial KiDS observations have concentrated on the Galaxy and Mass Assembly (GAMA) regions near the celestial equator, where extensive, highly complete redshift catalogues are available. A total of 109 survey tiles, 1 square degree each, form the basis of the first set of lensing analyses of halo properties of GAMA galaxies. Nine galaxies per square arcminute enter the lensing analysis, for an effective inverse shear variance of 69 arcmin−2. Accounting for the shape measurement weight, the median redshift of the sources is 0.53. KiDS data processing follows two parallel tracks, one optimized for weak lensing measurement and one for accurate matched-aperture photometry (for photometric redshifts). This technical paper describes the lensing and photometric redshift measurements (including a detailed description of the Gaussian aperture and photometry pipeline), summarizes the data quality and presents extensive tests for systematic errors that might affect the lensing analyses. We also provide first demonstrations of the suitability of the data for cosmological measurements, and describe our blinding procedure for preventing confirmation bias in the scientific analyses. The KiDS catalogues presented in this paper are released to the community through http://kids.strw.leidenuniv.nl.
We present the curation and verification of a new combined optical and near infrared dataset for cosmology and astrophysics, derived by combining ugri-band imaging from the Kilo-Degree Survey (KiDS) ...and ZYJHKs-band imaging from the VISTA Kilo degree Infrared Galaxy (VIKING) survey. This dataset is unrivaled in cosmological imaging surveys due to the combination of its area (458 deg2 before masking), depth (r ≤ 25), and wavelength coverage (ugriZYJHKs). This combination of survey depth, area, and (most importantly) wavelength coverage allows significant reductions in systematic uncertainties (i.e. reductions of between 10% and 60% in bias, outlier rate, and scatter) in photometric-to-spectroscopic redshift comparisons, compared to the optical-only case at photo-z above 0.7. The complementarity between our optical and near infrared surveys means that over 80% of our sources, across all photo-z, have significant detections (i.e. not upper limits) in our eight reddest bands. We have derived photometry, photo-z, and stellar masses for all sources in the survey, and verified these data products against existing spectroscopic galaxy samples. We demonstrate the fidelity of our higher-level data products by constructing the survey stellar mass functions in eight volume-complete redshift bins. We find that these photometrically derived mass functions provide excellent agreement with previous mass evolution studies derived using spectroscopic surveys. The primary data products presented in this paper are made publicly available through the KiDS survey website.
We use the first 100 deg2 of overlap between the Kilo-Degree Survey and the Galaxy And Mass Assembly survey to determine the average galaxy halo mass of ∼10 000 spectroscopically confirmed satellite ...galaxies in massive (M > 1013 h
−1 M⊙) galaxy groups. Separating the sample as a function of projected distance to the group centre, we jointly model the satellites and their host groups with Navarro–Frenk–White density profiles, fully accounting for the data covariance. The probed satellite galaxies in these groups have total masses log 〈M
sub/(h
−1 M⊙)〉 ≈ 11.7–12.2 consistent across group-centric distance within the errorbars. Given their typical stellar masses, log 〈M
⋆, sat/(h
−2 M⊙)〉 ∼ 10.5, such total masses imply stellar mass fractions of 〈M
⋆, sat〉/〈M
sub〉 ≈ 0.04 h
−1. The average subhalo hosting these satellite galaxies has a mass M
sub ∼ 0.015M
host independent of host halo mass, in broad agreement with the expectations of structure formation in a Λ cold dark matter universe.
Based on a deep imaging survey, we present the first homogeneous star formation history (SFH) of the Fornax dwarf spheroidal (dSph) galaxy. We have obtained two-filter photometry to a depth of image ...over the entire surface of Fornax, the brightest dSph associated with the Milky Way, and derived its SFH using a CMD-fitting technique. We show that Fornax has produced the most complex star formation and chemical enrichment histories of all the Milky Way dSphs. This system has supported multiple epochs of star formation. A significant number of stars were formed in the early universe; however, the most dominant population are the intermediate-age stars. This includes a strong burst of star formation approximately 3-4 Gyr ago. Significant population gradients are also evident. Similar to other dSphs, we have found that recent star formation was concentrated toward the center of the system. Furthermore, we show that the central region harbored a faster rate of chemical enrichment than the outer parts of Fornax. At the center, the ancient stars (image Gyr) display a mean metallicity of image, with evidence for three peaks in the metallicity distribution. Overall, enrichment in Fornax has been highly efficient: the most recent star formation burst has produced stars with close to solar metallicity. Our results support a scenario in which Fornax experienced an early phase of rapid chemical enrichment, producing a wide range of abundances. Star formation gradually decreased until image4 Gyr ago, when Fornax experienced a sudden burst of strong star formation activity accompanied by substantial chemical enrichment. Weaker star-forming events followed, and we have found tentative evidence for stars with ages less than 100 Myr.
ABSTRACT In the context of upcoming large-scale surveys like Euclid, the necessity for the automation of strong lens detection is essential. While existing machine learning pipelines heavily rely on ...the classification probability (P), this study intends to address the importance of integrating additional metrics, such as Information Content (IC) and the number of pixels above the segmentation threshold ($\rm {\mathit{n}_{s}}$), to alleviate the false positive rate in unbalanced data-sets. In this work, we introduce a segmentation algorithm (U-Net) as a supplementary step in the established strong gravitational lens identification pipeline (Denselens), which primarily utilizes $\rm {\mathit{P}_{mean}}$ and $\rm {IC_{mean}}$ parameters for the detection and ranking. The results demonstrate that the inclusion of segmentation enables significant reduction of false positives by approximately 25 per cent in the final sample extracted from DenseLens, without compromising the identification of strong lenses. The main objective of this study is to automate the strong lens detection process by integrating these three metrics. To achieve this, a decision tree-based selection process is introduced, applied to the Kilo Degree Survey (KiDS) data. This process involves rank-ordering based on classification scores ($\rm {\mathit{P}_{mean}}$), filtering based on Information Content ($\rm {IC_{mean}}$), and segmentation score ($\rm {n_{s}}$). Additionally, the study presents 14 newly discovered strong lensing candidates identified by the U-Denselens network using the KiDS DR4 data.
The Kilo-Degree Survey de Jong, Jelte T. A.; Verdoes Kleijn, Gijs A.; Kuijken, Konrad H. ...
Experimental astronomy,
2013/1, Letnik:
35, Številka:
1-2
Journal Article
Recenzirano
Odprti dostop
The Kilo Degree Survey (KiDS) is a 1500 square degree optical imaging survey with the recently commissioned OmegaCAM wide-field imager on the VLT Survey Telescope (VST). A suite of data products will ...be delivered to the European Southern Observatory (ESO) and the community by the KiDS survey team. Spread over Europe, the KiDS team uses Astro-WISE as its main tool to collaborate efficiently and pool hardware resources. In Astro-WISE the team shares, calibrates and archives all survey data. The data-centric architectural design realizes a dynamic ‘live archive’ in which new KiDS survey products of improved quality can be shared with the team and eventually the full astronomical community in a flexible and controllable manner.
ABSTRACT
Convolutional neural networks (CNNs) are the state-of-the-art technique for identifying strong gravitational lenses. Although they are highly successful in recovering genuine lens systems ...with a high true-positive rate, the unbalanced nature of the data set (lens systems are rare), still leads to a high false positive rate. For these techniques to be successful in upcoming surveys (e.g. with Euclid) most emphasis should be set on reducing false positives, rather than on reducing false negatives. In this paper, we introduce densely connected neural networks (DenseNets) as the CNN architecture in a new pipeline-ensemble model containing an ensemble of classification CNNs and regression CNNs to classify and rank-order lenses, respectively. We show that DenseNets achieve comparable true positive rates but considerably lower false positive rates (when compared to residual networks; ResNets). Thus, we recommend DenseNets for future missions involving large data sets, such as Euclid, where low false positive rates play a key role in the automated follow-up and analysis of large numbers of strong gravitational lens candidates when human vetting is no longer feasible.
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