AAS 207th Meeting, 8-12 January 2006
Session 113 Dwarf Galaxies
Poster, Wednesday, 9:20am-6:30pm, January 11, 2006, Exhibit Hall

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[113.13] A Refined Catalogue of Phoenix Dwarf Galaxy Giant Star Candidates

Joshua Tobolewski (Penn State), M. Siegel (UT Austin), C. Palma, J. Charlton (Penn State)

Continuing our studies of the Phoenix dwarf irregular galaxy and its extended tidal structure, we present the results of a survey using improved photometry with the Washington M-T2-DDO51 photometric method. The three-filter method has the ability to discriminate low surface-gravity giant stars from high surface gravity dwarfs and has proven successful at showing extended distributions of giant stars in other dSph satellites of the Milky Way. Our survey of Phoenix, the most distant (Rgc > 400kpc) of the Milky Way's bound satellites, was taken over a 0.5 square degree region obtained with the CTIO 4-meter telescope and Mosaic II camera. Relying on conservative cuts in photometric error and stellar shape parameter space, our photometry provides a clean list of extratidal giant star candidates. We find 250 giant candidates in our survey that pass both color-magnitude and color-color constraint cuts. Of these, we have roughly 29 candidate giant stars that lie outside the tidal radius of Phoenix. This number of candidate extratidal stars has not been adjusted for background contamination. Further investigations are required to determine if any of these stars were once bound to Phoenix. Using the entire sample of candidate giant stars associated with Phoenix, we also see structural differences in the spatial distribution of high and low metallicity giant stars within the galaxy. Similar differences in the spatial distribution of young and old stars in Phoenix have been noted by other authors. Finally, we compare our photometric selection of Phoenix stars with spectroscopically verified giant stars from Gallart et al (2001) and find that our selection process is successful in identifying these stars as giants, suggesting a high efficiency in selecting giants.

We gratefully acknowledge funding for this work from an NSF REU supplement and grant AST 0306884.

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