Photometric constraints on white dwarfs and the identification of extreme objects

Mortlock, D.; Peiris, Hiranya V.; Ivezić, Željko

doi:10.1111/j.1365-2966.2009.15351.x

Cited by 8 publications

(7 citation statements)

References 64 publications

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“…Typically the best δ 4DCD value is not zero because hydrogen white dwarfs are ten times as numerous as helium white dwarfs. These effects can be elegantly treated using the Bayesian formalism developed by Mortlock et al (2008), hereafter MPI08. Here we follow a simpler approach and, informed by the results shown in Figure 6.23, adopt δ 4DCD = −0.05 for the rest of the analysis presented here.…”

Section: Photometric Separation Of Hydrogen and Helium White Dwarfsmentioning

confidence: 99%

LSST Science Book, Version 2.0

Abell¹,

Burke²,

Hamuy³

et al. 2009

552

653

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Prepared by the LSST Science Collaborations, with contributions from the LSST Project. PrefaceMajor advances in our understanding of the Universe over the history of astronomy have often arisen from dramatic improvements in our ability to observe the sky to greater depth, in previously unexplored wavebands, with higher precision, or with improved spatial, spectral, or temporal resolution. Aided by rapid progress in information technology, current sky surveys are again changing the way we view and study the Universe, and the next-generation instruments, and the surveys that will be made with them, will maintain this revolutionary progress. Substantial progress in the important scientific problems of the next decade (determining the nature of dark energy and dark matter, studying the evolution of galaxies and the structure of our own Milky Way, opening up the time domain to discover faint variable objects, and mapping both the inner and outer Solar System) all require wide-field repeated deep imaging of the sky in optical bands.The wide-fast-deep science requirement leads to a single wide-field telescope and camera which can repeatedly survey the sky with deep short exposures. The Large Synoptic Survey Telescope (LSST), a dedicated telecope with an effective aperture of 6.7 meters and a field of view of 9.6 deg 2 , will make major contributions to all these scientific areas and more. It will carry out a survey of 20,000 deg 2 of the sky in six broad photometric bands, imaging each region of sky roughly 2000 times (1000 pairs of back-to-back 15-sec exposures) over a ten-year survey lifetime.The LSST project will deliver fully calibrated survey data to the United States scientific community and the public with no proprietary period. Near real-time alerts for transients will also be provided worldwide. A goal is worldwide participation in all data products. The survey will enable comprehensive exploration of the Solar System beyond the Kuiper Belt, new understanding of the structure of our Galaxy and that of the Local Group, and vast opportunities in cosmology and galaxy evolution using data for billions of distant galaxies. Since many of these science programs will involve the use of the world's largest non-proprietary database, a key goal is maximizing the usability of the data. Experience with previous surveys is that often their most exciting scientific results were unanticipated at the time that the survey was designed; we fully expect this to be the case for the LSST as well.The purpose of this Science Book is to examine and document in detail science goals, opportunities, and capabilities that will be provided by the LSST. The book addresses key questions that will be confronted by the LSST survey, and it poses new questions to be addressed by future study. It contains previously available material (including a number of White Papers submitted to the ASTRO2010 Decadal Survey) as well as new results from a year-long campaign of study and evaluation. This book does not attempt to be complete; there are many ...

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Section: Photometric Separation Of Hydrogen and Helium White Dwarfsmentioning

confidence: 99%

LSST Science Book, Version 2.0

Abell¹,

Burke²,

Hamuy³

et al. 2009

552

653

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“…Photometric measurements, however, are generally more ambiguous, and some sort of Bayesian approach is required to avoid making overly certain classifications (e.g. Mortlock, Peiris & Ivezić 2009a). For this reason only photometric measurements are considered henceforth.…”

Section: Probabilistic Classification Of Astronomical Sourcesmentioning

confidence: 99%

Probabilistic selection of high-redshift quasars

Mortlock¹,

Patel²,

Warren³

et al. 2011

Monthly Notices of the Royal Astronomical Society

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High redshift quasars (HZQs) with redshifts of z >~ 6 are so rare that any photometrically-selected sample of sources with HZQ-like colours is likely to be dominated by Galactic stars and brown dwarfs scattered from the stellar locus. It is impractical to reobserve all such candidates, so an alternative approach was developed in which Bayesian model comparison techniques are used to calculate the probability that a candidate is a HZQ, P_q, by combining models of the quasar and star populations with the photometric measurements of the object. This method was motivated specifically by the large number of HZQ candidates identified by cross-matching the UKIRT Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS) to the Sloan Digital Sky Survey (SDSS): in the ~1900 deg^2 covered by the LAS in the UKIDSS Seventh Data Release (DR7) there are ~10^3 real astronomical point-sources with the measured colours of the target quasars, of which only ~10 are expected to be HZQs. Applying Bayesian model comparison to the sample reveals that most sources with HZQ-like colours have P_q <~ 0.1 and can be confidently rejected without the need for any further observations. In the case of the UKIDSS DR7 LAS, there were just 88 candidates with P_q >= 0.1; these object were prioritized for reobservation by ranking according to P_q (and their likely redshift, which was also inferred from the photometric data). Most candidates were rejected after one or two (moderate depth) photometric measurements by recalculating P_q using the new data. That left seven confirmed HZQs, three of which were previously identified in the SDSS and four of which were new UKIDSS discoveries. The high efficiency of this Bayesian selection method suggests that it could usefully be extended to other HZQ surveys (e.g. searches by Pan-STARRS or VISTA) as well as to other searches for rare objects.Comment: submitted to MNRAS; 20 pages, 13 figure

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“…There exist several different algorithms in the astronomical literature which have been used to estimate stellar parameters from (spectro)photometric data. Without trying to be complete, these include physical line‐based analyses (Beers et al ; Heiter & Luck ), nearest neighbours (often χ 2 ) template‐based methods (Wilhelm, Beers & Gray ; Allernde Prieto et al ; Belikov & Röser ; Straiz˘ys & Lazauskaite ), neural networks or kernel regression (Bailer‐Jones, Irwin & von Hippel ; Winter, Jeffrey & Drilling ; Zhang et al ; Re Fiorentin et al ), methods based on forward modelling schemes (Cayrel et al ; Takeda ; Koleva et al ; Bailer‐Jones ) and Bayesian methods (Hill et al ; Mortlock, Peiris & Ivezić ; Bailer‐Jones ). While these approaches have generally been quite successful, many have been applied either to small data sets or to data sets with a limited and known range of stellar parameters, or they have only attempted to estimate one or two parameters.…”

Section: Introductionmentioning

confidence: 99%

The expected performance of stellar parametrization withGaiaspectrophotometry

Liu

Bailer‐Jones

Sordo

et al. 2012

Monthly Notices of the Royal Astronomical Society

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Gaia will obtain astrometry and spectrophotometry for essentially all sources in the sky down to a broad‐band magnitude limit of G = 20, an expected yield of 109 stars. Its main scientific objective is to reveal the formation and evolution of our Galaxy through chemodynamical analysis. In addition to inferring positions, parallaxes and proper motions from the astrometry, we must also infer the astrophysical parameters of the stars from the spectrophotometry, the blue photometer (BP)/red photometer (RP) spectrum. Here we investigate the performance of three different algorithms [Support Vector Machine (SVM), ilium and Aeneas] for estimating the effective temperature, line‐of‐sight interstellar extinction, metallicity and surface gravity of A–M stars over a wide range of these parameters and over the full magnitude range Gaia will observe (G = 6–20 mag). One of the algorithms, Aeneas, infers the posterior probability density function over all parameters, and can optionally take into account the parallax and the Hertzsprung–Russell diagram to improve the estimates. For all algorithms the accuracy of estimation depends on G and on the value of the parameters themselves, so a broad summary of performance is only approximate. For stars at G = 15 with less than 2 mag extinction, we expect to be able to estimate Teff to within 1 per cent, log g to 0.1–0.2 dex and [Fe/H] (for FGKM stars) to 0.1–0.2 dex, just using the BP/RP spectrum (mean absolute error statistics are quoted). Performance degrades at larger extinctions, but not always by a large amount. Extinction can be estimated to an accuracy of 0.05–0.2 mag for stars across the full parameter range with a priori unknown extinction between 0 and 10 mag. Performance degrades at fainter magnitudes, but even at G = 19 we can estimate log g to better than 0.2 dex for all spectral types and [ Fe /H] to within 0.35 dex for FGKM stars, for extinctions below 1 mag.

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Photometric constraints on white dwarfs and the identification of extreme objects

Cited by 8 publications

References 64 publications

LSST Science Book, Version 2.0

LSST Science Book, Version 2.0

Probabilistic selection of high-redshift quasars

The expected performance of stellar parametrization withGaiaspectrophotometry

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