Identification of Uncharted Star Clusters

1. Identification of Uncharted Star Clusters Dilyana Mihaylova , Joyce Wu, Advisor: Dr. Wen-Ping Chen Abstract Creating the star field and cluster Examples:: The purpose of this project is to search for uncharted clusters by measuring the density and distribution of stars when given their position. Creating the cluster xc=rho*rho*cos(theta/180*!pi)*cdia + ccenx yc=rho*rho*sin(theta/180*!pi)*cdia + cceny Generating a star field xf=RANDOMU(seed, nfield) yf=RANDOMU(seed, nfield) field (N=500) and cluster N=250) Field only (N=750) Background Information Analyzing the field by stellar density Star Clusters : - A group of gravitationally bound stars formed out of the same cloud, at the same time, and at the same distance from us. - They are ideal laboratories to study stellar evolution, and to probe the Galactic formation and evolutionary history Globular Clusters - 12Gyr old and no longer forming in the Milky Way Galaxy - Not possible to study their formation Galactic open clusters - 1Myr to 1Gyr - Born of molecular clouds - Makes them harder to study The output is a contour of the density of the stellar field in which the cluster is clearly visible Examples Field N=2000, cluster N=500 Two Point Correlation Function Analyzing actual data We analyzed data from NGC 752, an open cluster in the constellation Andromeda Procedure The graph on the left shows a cluster of 500 stars centered at (.7,.2) with a background of 2000 stars. The graph on the right is the corresponding density graph in which the cluster is visible Position of each star Contour Plot Two point correlation function 1.Write an IDL code that creates a background field of stars and a star cluster 2.Write a code that searches for this star cluster based on : - Finding an over-density region (where it is, how large it is, etc. - How stars are distributed by analysis of the two-point correlation function Analyzing the field Currently the above two point correlation curve is not an accurate representation of the data. Two point correlation - Measures how the separation of data pairs is distributed. - Monte Carlo Estimator: - Computes the number of pairs for each separation, and compares that with a random field Conclusion We were able to write a code that: Counts the number of stars and outputs a contour of the star density and Calculates the two point correlation function Future work: Use the methods described to search for uncharted star clusters and calculate their size and density