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Imaging dense globular clusters like M3 and M15

Imaging dense globular clusters like M3 and M15. Rodney Howe Deep Space Exploration Society ahowe@frii.com Strikis Iakovos - Marios Hellenic Amateur Astronomy Association Elizabeth Observatory of Athens jdstrikis@hotmail.com

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Imaging dense globular clusters like M3 and M15

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  1. Imaging dense globular clusters like M3 and M15 Rodney Howe Deep Space Exploration Society ahowe@frii.com Strikis Iakovos - MariosHellenic Amateur Astronomy AssociationElizabeth Observatory of Athens jdstrikis@hotmail.com Ido Bareketמצפה הכוכבים ברקת במכביםhttp://www.bareket-astro.comBareket observatory, Israel Stouraitis DimitriosHellenic Amateur Astronomy AssociationGalilaio Astronomical Observatory

  2. Amateur Astronomers have no consistent way of defining the core of a globular cluster, thus differentiating the core from the periphery. This segregation is important for characterizing the gravitational dynamics of the cluster, particularly in the core. The periods of RR Lyrae variable stars introduce segregation errors due to their inherent variation. Current core sizing is a function of the luminosity versus distance from the core center. However, once in the core, the variations in the RR Lyrae stars introduce significant error in the luminosity determination. Hence, by characterizing the RR Lyrae quantities and oscillation periods, we can reduce the core dimension error.

  3. Can Period/Luminosity flux density distributions help determine the core from outer regions?

  4. Outer region cluster RRLyrae phases from stellar pulsation sources • Iakovos writes: “As for the M3 Globular Cluster images I did a random selection of about 100 stars in the outer parts of the cluster images and did the photometry profile in just one window ... Then I started to erase those which did not have an RR-Lyrae type of variation and this is how I finally stopped to those 20 stars “...

  5. Core Period/Luminosity • One approach for better identification of the 'core' area vs. the other outer region areas can be done by finding any potential correlation between the angular size of the target - and its standard deviation of the stars, VS. their distance from the core.There may be another more elegant solutions, but I don't aware of such. I believe that it will be easier to do this manually though. At least with these small lists of targets. • (Ido Bareket)

  6. Core Period/Luminosity Not sure I'm saying this right, but it would be something like this: there is a P/L ratio difference between core and outer region, which would be a Bayesian prior, which would inform the decision to describe the core region. For example:  when the core's P/L ratio is negative at some slope, large enough to be significant when compared to the positive P/L ratio slope for the outer region's RR Lyrae stars, then this difference in slope of the P/L ratio would help inform the algorithm used to describe the core, and we could be confident we've identified the core, in-part because of the difference in the slope of the P/L ratios?That way whether or not we use some B - V color relationship to define the P/L ratio, or a flux density period/luminosity ratio over time (multiple images), we could still determine a significant change of the P/L slopes between core and outer region?  Such that, where there is a 'significant' change in these slopes, which identifies the core.This all depends on the idea that the P/L ratio of the core RR Lyrae stars is less than the P/L ratio of the outer region's RR Lyrae stars.

  7. Core Period/Luminosity Iakovos writes: “As for the decrease of the flux density of the M15 core ... I also think it is not real, and I believe that it is caused from the camera stabilization .... All cameras need about 1+1/2 hours to be thermal stabilized... If I start to image before that time the linearity of the camera (and sensitivity) are going to be changed until the camera gets thermal stabilized “...

  8. All I have are questions.. Photo from home page of Natalia Dziourkevitch: http://www.aip.de/~nsd

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