Astronomy and Astrophysics – Astronomy
Scientific paper
May 1992
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1992aas...180.2909g&link_type=abstract
American Astronomical Society, 180th AAS Meeting, #29.09; Bulletin of the American Astronomical Society, Vol. 24, p.774
Astronomy and Astrophysics
Astronomy
Scientific paper
We have used a Monte Carlo algorithm to generate synthetic Hubble Space Telescope (HST) Planetary Camera (PC) U-band images for the globular cluster M15 from evolving, Fokker-Planck models with a realistic mass spectrum. We constructed ensembles of 10 images each from a collapsed-core model and a comparison expanded-core model. A realistic reproduction of the actual HST-PC point-spread function was used. From fits of seeing-convolved power-laws to the surface-brightness profiles determined from these images, we find that there is a large range of power-law slope inside of 1'' for each of the two models. We note that either model can produce both cusped and non-cusped central surface-brightness profiles. We have investigated the effect that the removal of resolvable stars has on apparent cusps, both by omitting them while generating the images and by using DAOPHOT to subtract them from complete images. We compare our results with those of Lauer et al. for an actual HST-PC image of M15. We conclude that the occurrence of a central surface-brightness cusp is not tightly correlated with the underlying distribution of the most massive members of the cluster. These massive stars, which dominate the central region, are nonluminous neutron stars and white dwarfs in our models. There appear to be too few luminous stars in the central arcsecond to provide a statistically reliable determination of the cluster structure there. We are investigating the possibility that a population of luminous objects with masses substantially larger than the main-sequence turnoff (e.g. binaries, blue stragglers, or merger products) may be present in sufficient numbers in the central arsecond to act as a reliable tracer of the underlying cluster mass distribution.
Cohn Haldan N.
Grabhorn Robert P.
Irwin Jimmy A.
Lugger Phyllis Minnie
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