Exploration of Large Digital Sky Surveys

Djorgovski, S. G.; Brunner, Róbert; Mahabal, A.; Odewahn, S. C.; Carvalho, R. R. de; Gal, R. R.; Stolorz, Paul; Granat, Robert; Curkendall, D. W.; Jacob, Joseph; Castro, S.

doi:10.1007/10849171_37

Cited by 18 publications

(19 citation statements)

References 12 publications

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“…2. Extensive UV absorption plus narrow emission from Fe ii UV1 and Mg ii identifies it as an unusual FeLoBAL quasar similar to FIRST 0840+3633 (Becker et al 1997) and especially PSS 1537+1227 (Djorgovski et al 2001). …”

Section: Spectroscopic Analysismentioning

confidence: 96%

“…FeLoBAL quasars (Becker et al 1997) are LoBAL quasars which also show absorption from excited Fe ii or Fe iii. Populations of unusual BAL quasars with extremely strong or complex absorption have recently been found through followup of FIRST radio sources (Becker et al 1997(Becker et al , 2000Menou et al 2001;Lacy et al 2002), z > 4 quasar candidates from the Digitized Palomar Sky Survey (Djorgovski et al 2001), and color-selected quasar candidates from the Sloan Digital Sky Survey (Hall et al 2002). These unusual BAL quasars suggest that the range of physical conditions present in BAL outflows is larger than previously suspected.…”

Section: Introductionmentioning

confidence: 99%

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An unusual iron Lo-BAL quasar detected by ISOCAM

Duc¹,

Fadda²,

Chanial³

et al. 2002

A&A

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Abstract. We report the discovery of an unusual low-ionization broad absorption line quasar at z = 1.776 which exhibits absorption lines from many excited states of Fe ii. This member of the rare class of "FeLoBAL" quasars was serendipitously found in a mid-infrared (MIR) survey of distant clusters carried out with the ISOCAM camera. ISO J005645.1−273816 has a high MIR to UV luminosity ratio, suggesting a strong dust obscuration plus emission from very hot dust. This characteristic makes MIR surveys particularly efficient at detecting LoBAL quasars.

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Section: Spectroscopic Analysismentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

An unusual iron Lo-BAL quasar detected by ISOCAM

Duc¹,

Fadda²,

Chanial³

et al. 2002

A&A

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“…We note that the same types of classification techniques are also used for more detailed explorations of large digital sky surveys and other astronomical data sets, especially in searches for outliers in some parameter space, which are often some astrophysically interesting type of objects (e.g., distant quasars) [20,21,22,23,24,37,40]. Resolved sources ("galaxies") in principle contain more morphological information, since all unresolved ones ("stars") by definition look alike.…”

Section: Star-galaxy Image Classification: the Next Generationmentioning

confidence: 99%

Some Pattern Recognition Challenges in Data-Intensive Astronomy

Djorgovski

Donalek

Mahabal

et al. 2006

18th International Conference on Pattern Recognition (ICPR'06)

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We review some of the recent developments and challenges posed by the data analysis in modern digital sky surveys, which are representative of the information-rich astronomy in the context of Virtual Observatory. Illustrative examples include the problems of an automated star-galaxy classification in complex and heterogeneous panoramic imaging data sets, and an automated, iterative, dynamical classification of transient events detected in synoptic sky surveys. These problems offer good opportunities for productive collaborations between astronomers and applied computer scientists and statisticians, and are representative of the kind of challenges now present in all data-intensive fields. We discuss briefly some emergent types of scalable scientific data analysis systems with a broad applicability.

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“…This includes an exciting possibility of discovering some previously unknown types of astronomical objects or phenomena (see Djorgovski et al 2001aDjorgovski et al , 2001bDjorgovski et al , 2001c …”

Section: Clustering Analysis Challenges In a Vomentioning

confidence: 99%

Challenges for Cluster Analysis in a Virtual Observatory

Djorgovski

Brunner

Mahabal

et al.

Statistical Challenges in Astronomy

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Abstract. here has been an unprecedented and continuing growth in the volume, quality, and complexity of astronomical data sets over the past few years, mainly through large digital sky surveys. Virtual Observatory (VO) concept represents a scientific and technological framework needed to cope with this data flood. We review some of the applied statistics and computing challenges posed by the analysis of large and complex data sets expected in the VO-based research. The challenges are driven both by the size and the complexity of the data sets (billions of data vectors in parameter spaces of tens or hundreds of dimensions), by the heterogeneity of the data and measurement errors, the selection effects and censored data, and by the intrinsic clustering properties (functional form, topology) of the data distribution in the parameter space of observed attributes. Examples of scientific questions one may wish to address include: objective determination of the numbers of object classes present in the data, and the membership probabilities for each source; searches for unusual, rare, or even new types of objects and phenomena; discovery of physically interesting multivariate correlations which may be present in some of the clusters; etc.

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Exploration of Large Digital Sky Surveys

Cited by 18 publications

References 12 publications

An unusual iron Lo-BAL quasar detected by ISOCAM

An unusual iron Lo-BAL quasar detected by ISOCAM

Some Pattern Recognition Challenges in Data-Intensive Astronomy

Challenges for Cluster Analysis in a Virtual Observatory

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