3.2. Pegasus

The Pegasus dI galaxy is a gas-rich system in the LG, it is possibly an example of a transition object between a dwarf galaxy dominated by current star-formation and one dominated by past star formation. Analysis of the WFPC2 CMD of the Pegasus dI (see Figure 5) reveals a young main sequence (MS), a well populated RGB, a small number of EAGB stars and near the faint limits of the data a populous RC (Gallagher et al. 1998). The young stellar component is clustered in two centrally-located clumps, while older stars form a more extended disk or halo. The colours of the MS require a relatively large extinction (A_V = 0.47 mag), and the (extinction corrected) mean colour of the well-populated RGB is relatively blue, consistent with a moderate metallicity young, or older and more metal-poor stellar population. The distance of Pegasus was revised to be 760 kpc, taking account of the higher reddening. The RGB has significant width in colour, implying a range of stellar ages and/or metallicities. A SFH which was consistent with the data is one in which the sfr was higher, by a factor of 3-4, about 1 Gyr ago. It was impossible to constrain the SFH beyond 1 Gyr ago, as seen by the large error bars in Figure 5d, without better information on stellar metallicities and deeper photometry. The youngest model consistent with the data contains stars with constant metallicity of Z = 0.001 which mainly formed 2-4 Gyr ago. If stellar metallicity declines with increasing stellar age, then the older ages extend up to 8 Gyr. However, even at its peak of star forming activity, the intermediate-age dominated model for the Pegasus dwarf most likely remained relatively dim with M_V -14.

Figure 5. Here we show the results for the HST / WFPC2 analysis of Pegasus (Gallagher et al. 1998). In a. is the V-I, I CMD, 1 orbit exposure time per filter. In b. is the B-V, V CMD, 2 orbits in B. In c. is the best match Monte-Carlo simulation model, in V-I, I, found for these data (excluding the RC) and convolved with the theoretical measurement error distribution, and in d. is the SFH that created the model CMD which best matches the data. See Gallagher et al. 1998 for more details.