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Discovery and Characterization of Stellar Clusters in the Outer Milky Way

Discovery and Characterization of Stellar Clusters in the Outer Milky Way. Karen Hamm (CLAS) and Gail Zasowski (GSAS). Open Clusters. Groupings of stars Born from the same giant molecular cloud Young, low stellar density objects Contain up to several thousand stars. M67.

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Discovery and Characterization of Stellar Clusters in the Outer Milky Way

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  1. Discovery and Characterization of Stellar Clusters in the Outer Milky Way Karen Hamm (CLAS) and Gail Zasowski (GSAS)

  2. Open Clusters • Groupings of stars • Born from the same giant molecular cloud • Young, low stellar density objects • Contain up to several thousand stars M67 M45: The Pleiades (the “7 Sisters”)

  3. The Importance of Star Clusters • Cluster motions, distances, chemistry, and ages much easier to measure than single stars’ • Very useful tracers of Galactic structure, star formation, and evolution • Probe tangled regions of Milky Way M51, the “Whirlpool Galaxy” Milky Way

  4. Difficulty of Studying Clusters • Clusters in disk of the Milky Way, along with dust • Dust makes stars fainter and changes their color • Dust effects are less severe at longer wavelengths Barnard 68, ESO

  5. Difficulty of Studying Clusters • Clusters in disk of the Milky Way, along with dust • Dust makes stars fainter and changes their color • Dust effects are less severe at longer wavelengths Barnard 68, ESO “Extinction”  fainter “Reddening”  redder

  6. The Infrared Milky Way NASA/ JPL Caltech • NASA Spitzer Space Telescope Surveys • GLIMPSE-360 • Cygnus-X • SMOG • Vela-Carina Sun Spitzer Space Telescope

  7. The Infrared Milky Way NASA/ JPL Caltech • NASA Spitzer Space Telescope Surveys • GLIMPSE-360 • Cygnus-X • SMOG • Vela-Carina Vela-Carina Cygnus-X Sun SMOG GLIMPSE-360 Spitzer Space Telescope

  8. Visual Identification • 575 deg2 of images • Candidate Criteria: • Overdensity of stars • Similar size and brightness Sample screenshot of SAOImage DS9 program

  9. Cluster Examples Each = 1/3600 deg

  10. Cluster Classifications • “Color-magnitude diagrams” (CMDs) • Depends on stars’ temperature, distance, etc. • Sorted candidates based on the clarity of the Spitzer image and the strength and disparity of the CMDs Brightness  Brightness   Temperature  Temperature Brightness  Brightness  Zasowski, Beaton, & Hamm, in prep.  Temperature  Temperature

  11. Cluster Classifications • “Color-magnitude diagrams” (CMDs) • Depends on stars’ temperature, distance, etc. • Sorted candidates based on the clarity of the Spitzer image and the strength and disparity of the CMDs Brightness  Brightness   Temperature  Temperature Brightness  Brightness  Zasowski, Beaton, & Hamm, in prep.  Temperature  Temperature

  12. Characterizing Clusters • Each cluster CMD contains the stellar sequence of that cluster, plus foreground and background stars • Cluster stars should share similar foreground reddening • Fit high-quality models (“isochrones”) to the filtered stellar populations Brightness  Brightness  Number  Temperature  Temperature Reddening compared to cluster Zasowski, Beaton, & Hamm, in prep.

  13. Isochrone-Fitting Examples Cluster Comparison Cluster Comparison Restrict reddening range to [0.2 – 0.45] Restrict reddening range to [0.0 – 0.1] Cluster Cluster Comparison Comparison

  14. Isochrone-Fitting Examples Cluster Comparison Cluster Comparison • Distance = 5.12 light-years • Fraction of heavy elements ~63% that of the Sun • Distance = 4.56 light-years • Fraction of heavy elements equal to that of the Sun Restrict reddening range to [0.2 – 0.45] Restrict reddening range to [0.0 – 0.1] Cluster Cluster Comparison Comparison

  15. Results • Identified ~375 open cluster candidates in the outer Milky Way • Derived basic cluster parameters (reddening, chemical abundance, distance) for objects with well-populated near-IR CMDs • Submitting paper with coordinates & parameters for >30 newly-discovered and unstudied clusters

  16. Future Directions • Vela-Carina survey as focus of senior thesis (Hamm) • Obtain more observations of interesting candidates with large telescopes to determine cluster motions • Write software to detect clusters automatically Primary Team Members Gemini Observatory, HI • R.L. Beaton (GSAS) • S.R. Majewski (Dept of Astronomy) • B.A. Whitney (University of Wisconsin-Madison)

  17. References • Churchwell, E., Babler, B. L., Meade, M. R., et al. 2009, PASP, 121, 213 • Whitney, B., Arendt, R., Babler, B., et al. 2008, in Spitzer Proposal ID #60020, 60020 (GLIMPSE-360) • Carey, S., Ali, B., Berriman, B., et al. 2008, in Spitzer Proposal ID #50398, 50398 (SMOG) • Hora, J., Adams, J., Allen, L., et al. 2007, in Spitzer Proposal ID #40184, 40184 (Cyg-X) • Majewski, S. R., et al. 2008, in Spitzer Proposal ID # 40791,40791  (Vela-Carina) • Whitney, B., Benjamin, R., Meade, M., et al. 2011, in Bulletin of the American Astronomical Society, Vol. 43, American Astronomical Society Meeting Abstracts No. 217, 241.16 • Majewski, S.R., Zasowski, G., & Nidever, D.L. 2011, ApJ, 739, 25 • Girardi, L., Bertelli, G., Bressan, A., et al. 2002, A&A, 391, 195

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