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Search for New Open Clusters in Huge Catalogues

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Search for New Open Clusters in Huge Catalogues Astronomical Data Analysis Software and Systems XV P.147 ASP Conference Series, Vol. XXX, 2005 C. Gabriel, C. Arviset, D. Ponz and E. Solano, eds. Search for New Open Clusters in Huge Catalogues Ivan Zolotukhin Moscow State University; Institute of Astronomy of Russian Academy of Sciences; Email: [email protected] Sergey Koposov Moscow State University Elena Glushkova Sternberg Astronomical Institute Abstract. Current catalogues (lists indeed) of open clusters are simply heterogeneous and incomplete selections of them. There has been no attempts of search for open clusters through huge photometric catalogues using homogeneous approach in all-sky. We have developed such a method based on extraction from cata- logue and successive analysis of star densities. Our algorithm finds star density peaks and then builds their color-magnitude diagrams. We ex- ploit the fact that only stars lying on the isochrone show a density peak whereas field stars show flat distribution. Automatic procedure elim- inates occasional density peaks and obtains isochrone and geometrical parameters of survived candidates (coordinates, size, distance, age and color excess). Preliminary study of 150 sq. degrees in Galaxy anticentre region yielded 10 new clusters. The software developed will allow us to build first homogeneous all-sky open cluster catalogue (it will include essen- tially refined known clusters data as well) based on 2MASS data initially. It will be possible to apply automated pipeline on any multicolor cata- logue, where the VO-compliant way of access (e.g. ADQL + SkyNode) is provided (SDSS, etc.). 1. Introduction We present here several new methods which allow to involve the data from existing huge stellar catalogues into the search and analysis of stellar clusters. We also show some preliminary but very promising results of those methods. Currently there are several compiled catalogues of stellar clusters, but they all have several significant disadvantages: • Tens percents of their clusters do not have CMD measured, so they are only unverified groups of stars 1 2 Zolotukhin, Koposov & Glushkova • Many of them do not even have precise equatorial coordinates measure- ments with errors up to 15 arcmin and more • Even well known clusters do not have important parameters measured (radius, distance, color excess) • There is no any catalogue of open clusters, all the clusters are grouped in compiled lists indeed and nobody ever performed really homogeneous search of clusters in full-sky regime 2. Automated Algorithm But now uniform data from huge stellar catalogues allow to apply homogeneous approach to the search of new and investigation of all known open clusters. Our method consists of two main procedures: • search for open clusters based on stellar density analysis • verification if given peak of density is a real cluster but not an occasional group of field stars and measurement of main cluster’s parameters First procedure is not as trivial as simple analysis of surface density of objects from catalogue because of highly variable mean (”background”) stellar density from place to place. So one can not apply a constant threshold filter and get a list of density peaks that would be the open cluster candidates. It is necessary to use a special convolution function to distinct peaks from such a complex background. But even then we can not be sure that density peaks obtained from catalogue are not an occasional groups of stars. We should prove that stars in these groups are evolutionary related with each other, so that they should lie on one isochrone. Our algorithm based on the fact that in real clusters only stars lying on the isochrone show a density peak, but field stars demonstrate flat distribution (Fig. 1). It allows to find the position of the isochrone of the cluster even when the CMD is ”polluted” by field stars. Such a fitting of isochrone yields cluster’s age and color excess. 3. Preliminary Results These two algorithms are developed using C language and tested on several fields from 2MASS catalogue which is the primary catalogue of our interest. From the very preliminary analysis of the 250 sq. degrees in the Galaxy Anticenter region we have found several (> 10) new clusters, and have determined their parameters. In that region also we were able to determine the parameters for several clusters without such measurements. Also, a set of new clusters was found when we just looked in the region of Perseus arm (Fig. 2.). It should be noticed, that the clusters which we have found are not just infrared clusters, most of them are clearly visible in the optical wavelength range. So, finally, we can find clusters, confirm them, and determine their main parameters(radius, distance and color excess) automatically. Our main goal is to process all-sky selection from 2MASS stellar catalogue and make up first homogeneous catalogue of open clusters which will include several percents of Search for New Open Clusters in Huge Catalogues 3 Figure 1. Bold dots – radial density distribution of stars lying on the fitted isochrone; thin dots – radial density distribution of the field stars lying far from isochrone. Contrast in the center is a fit quality criterion: if isochrone is fitted incorrectly, both selections show flat distribution. Here isochrone stars demonstrate explicit peak in the centre. 4 Zolotukhin, Koposov & Glushkova Figure 2. Isochrone automatically fitted into Color-Magnitude Dia- ◦ gram of the new cluster (RA = 05h53m48s, Dec = +26 50′25′′) discov- ered using 2MASS J and H magnitudes data. This yields color excess and cluster’s age. King 11 NGC 7762 Skiff 1 Berkeley 59 Berkeley 61 Berkeley 64 Pfleiderer 1 StockCzernik 18 45 Stock 6 Stock 5 NGCBerkeley 886 63 King 1 NGC 609 Berkeley 4 Berkeley 104 NGC 637 DolidzeKing 13 16 Berkeley 62 NGC 133 Pfleiderer 4 Czernik 6 NGCKing 146 14 NGC 559 King 12 Tombaugh 4 Berkeley 5 Stock 20 Harvard 21 CzernikBerkeley 7 7 Czernik 3 Frolov 1 NGC 7788 IC 166 StockNGC 3 366 Mayer 1 CzernikNGC 1 7790 NGC 654 Stock King24 15 King 13Berkeley 58 Czernik 5 NGC 225NGCNGC 136 103 BerkeleyNGC 6 663TrumplerCzernik 41 NGC 381 Berkeley 60 NGC 189 Berkeley NGC1 7795 Dolidze 12 NGC 659NGC 581 Berkeley 2 NGC 743 NGC 129 Czernik 2 Stock 2 NGC 433 Basel 10 NGC 436 NGC 457 King 2 Stock 21 Stock 4 IC 1590 NGC 744 NGC 657 Figure 3. Perseus arm region (16◦ × 16◦). The left panel is the over- density map obtained by our methods, the right panel is the same map but with overplot of known clusters. It can be seen that most of the known clusters correspond to the peaks on our map, so they can be easily detected by our method. But also, there are several peaks that do not correspond to known clusters. These are new clusters. Search for New Open Clusters in Huge Catalogues 5 new open clusters and references to known ones with main properties determined using uniform approach. Also it would be interesting to involve other surveys catalogues, such as DENIS and SDSS into open clusters search. Acknowledgments. IZ wish to thank Institute of Astronomy of Russian Academy of Sciences and OFN RAS program “Extended Objects in the Uni- verse” for the ADASS conference attendance support. References Koposov S., et al., AN 326, Suppl. Issue 7, p.14, 2005.
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