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Astronomical Data Analysis Software and Systems VI ASP Conference Series, Vol. 125, 1997 Gareth Hunt and H. E. Payne, eds.

Integrating the HST Guide Star Catalog into the NASA/IPAC Extragalactic Database: Initial Results
Oleg Yu. Malkov and Oleg M. Smirnov Institute of Astronomy, Russian Academy of Sciences, 48 Pyatnitskaya St., Moscow 109017, Russia Abstract. We rep ort initial results of cross-identification of extragalactic ob jects from the NASA/IPAC database and Guide Star Catalog (GSC). A distribution of galaxies on the sky is discussed as a tool for estimating the probability for a given GSC ob ject to b e of a particular typ e.

1.

Introduction

The GSC (with 20 million ob jects, making it the biggest and most complete sky survey to date) provides accurate ob ject p ositions. The NASA/IPAC Extragalactic Database (NED)1 contains p ositions, extensive data, and 1,023,000 cross-identifications for over 592,000 extragalactic ob jects (galaxies, quasars, and radio sources). NED currently represents the unique merger of some 40 ma jor catalogs and many shorter listings. Catalogs and lists are b eing integrated into NED on a continuing basis, following a detailed cross-identification process. Benefits of NED-GSC cross-identification are obvious for b oth sides. For many astronomical studies the GSC is unique; but its full p otential is still out of reach. At present, the GSC lacks even rudimentary cross-identifications with other astronomical catalogs, and consequently little is known ab out either the nature of the ob jects themselves or their relationship to other data already cataloged and indep endently available in machine-readable form. NED can make use of the accurate p ositions found in the GSC. 2. General Cross-identification Strategy

The following general strategy is applicable to all kinds of ob ject lists, not only those from NED. By "source list" we will refer to any external list of ob jects of a homogeneous nature (e.g., NED galaxies, NED IR sources, etc.) Stage 1: a small sampling of ob jects from the source list is cross-identified manually, using our GUIDARES (Malkov & Smirnov 1995) and ZGSC software (Smirnov & Malkov 1997) applications. Cross-identification is attempted with b oth GSC ob jects, and in the case of multiple entry GSC ob jects, with individual entries. Results: an initial ruleset for automatic cross-identification; confidence estimates.
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http://www.ipac.caltech.edu/ned/ned.html

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© Copyright 1997 Astronomical Society of the Pacific. All rights reserved.


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Stage 2 (iterative): the full source list is cross-identified automatically, using the current ruleset. Results: Confidently identified ob jects can b e analyzed for hidden dep endencies b etween GSC and external list data. This can yield additional rules and criteria, at which p oint Stage 2 is rep eated. Questionable cases can b e analyzed manually. Final cross-identification results: (i) List of unambiguously cross-identified ob jects, (ii) list of ambiguous (one source ob ject, several GSC ob jects) cross-identifications, (iii) questionable cases--for manual analysis, and (iv ) unidentified ob jects from the source list. These results will b e provided to the maintainers of the source list or database in question. 3. Initial Results

Here we present results of Stage 1 cross-identification process for NED galaxies and NED IR sources. Note that the NED list of IR sources does not contain IR sources with an optical counterpart, e.g., galaxies. The 23% b elow are, therefore, IR sources with an identified GSC optical counterpart not listed in NED.

galaxies IR sources

confidently identified 84% 23%

p oorly identified 4% 4%

not identified 12% 73%

Confident cross-identifications provide an exciting p ossibility. If a sufficient numb er of source ob jects is confidently identified, we can exp ect to derive sp ecific rulesets that describ e the "mean" GSC representation of ob jects of the same typ e. These rulesets, coupled with ob ject probability maps (see b elow), can b e applied to the whole GSC in an automatic scan for unlisted ob jects of the same typ e. For example, the excellent cross-identification results for NED galaxies suggest that the GSC can yield a wealth of previously unknown galaxies. This is also suggested by two of our preliminary findings: 1. GSC photometry for diffuse ob jects is, typically, 3­5 magnitudes brighter than actual values. The GSC's formal limiting magnitude of 15m ­16m is, as far as galaxies are concerned, closer to 18m ­19m . 2. At least 5% of GSC "stars" are in reality galaxies, nebulae, multiples, etc. We also give preliminary results on cross-identification of some other typ es of NED ob jects with the GSC: Quasi-stellar ob jects: too faint to b e included in the GSC. Gamma sources: NED p ositional errors are too high. It is only p ossible to indicate the brightest GSC star in the vicinity of the source.


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Figure 1. Third Reference Catalogue of Galaxies (galactic coordinates, Aitoff pro jection). Clusters of galaxies: Results are very p oor. Planetary nebulae: confidently identified, but no "automatic" discovery is p ossible, as their GSC counterparts are undistinguishable from stars. Radio sources: not identifiable at all. Note again that the NED lists of gamma or radio sources does not contain those sources with a known optical counterpart. 4. Ob ject Probability Maps

Ob ject probability maps (OPMs) are based on the mean density of ob jects of a particular typ e at given coordinates and magnitude. OPMs can b e used to estimate the probability for a given ob ject to b e of a particular typ e. This provides additional information on the nature of GSC ob jects (consider, e.g., galaxies' zone of avoidance, or the lack of asteroids at high elliptic latitudes). To estimate the probability of a given ob ject b eing a galaxy, we have to know b oth the stellar distribution and distribution of galaxies. The density of ob jects is approximated by the function N = N (m, b), where N is the mean numb er of ob jects p er square degree brighter than m at galactic latitude b (dep endence on longitude is assumed to b e negligible). For the stellar distribution, an old but still unsurpassed Seares & Joyner (1928) pap er was selected. In this pap er, m is given in the international photographic scale. The pap er employs the old galactic coordinate system; however, the difference is not significant for our purp oses. To create a distribution of galaxies we had to evaluate available catalogs according to the following criteria: completeness in coordinates, magnitudes, sizes, etc.; large numb er of ob jects. After detailed analysis, the Third Reference Catalogue of Bright Galaxies, RC3 (de Vaucouleurs et al. 1991) was selected. It


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Figure 2.

Stellar distribution and distribution of galaxies.

contains 23,011 ob jects (see Figure 1) and is complete for galaxies having apparent diameters larger than 1 at the D25 isophotal level and total B magnitudes BT brighter than ab out 15.5m , with a redshift not in excess of 15,000 km s-1 . The RC3 employs the new galactic system. The catalog has shortcomings: it is inhomogeneous, and not every ob ject is supplied with a magnitude. The RC3 contains 7 different magnitude bands. We selected mB , b ecause: (i) it yields good correlation with GSC magnitudes, (ii) it is more representative in RC3 than other magnitudes, and (iii) it is close to the system used in the stellar distribution. Only 75.6% of RC3 ob jects have mB magnitudes. We used six other parameters that were well-correlated (b etter than 0.59) with mB , to estimate mB where it was absent. This produced a total of 22,907 (99.5% of RC3) usable ob jects. Distributions of galaxies and stars are shown on Figure 2. This should allow us to create the required galaxy distribution by fitting the density of RC3 ob jects with an analytical formula. Acknowledgments. Drs. Marion Schmitz (Caltech) and Conrad Sturch (STScI) are gratefully acknowledged for valuable advice and constant help in our work. This presentation was made p ossible by financial supp ort from the Logovaz Conference Travel Program. OM is grateful to the Russian Foundation for Fundamental Researches for grant No. 16304. References Malkov, O. Yu., & Smirnov, O. M. 1995, in ASP Conf. Ser., Vol. 77, Astronomical Data Analysis Software and Systems IV, ed. R. A. Shaw, H. E. Payne, & J. J. E. Hayes (San Francisco: ASP), 182 Seares, F. H., & Joyner, M. C. 1928, ApJ, 67, 24 Smirnov, O. M., & Malkov, O. Yu. 1997, this volume, 429 de Vaucouleurs, G., de Vaucouleurs, A., Corwin, H. G., Buta, R. J., Paturel, G., & Fouque, P. 1991, Third reference catalogue of bright galaxies (New York: Springer-Verlag)