NVO Study of Super Star Clusters in Nearby Galaxies – Proposal and Demo B. Whitmore, C. Hanley, B. Chan, R. Chandar OUTLINE Background and Science Goals A Feasibility Study – M51 Demo Hands-on session (11:00 – 12:00)

Background This proposal was born as a “student project” at the 2005 NVO Summer School in Aspen, which Chris Hanley, Ben Chan, (IPAC) and I all attended. We then put in a proposal as part of the first NVO Research Initiatives program ($25,000 grants). 15/42 proposals successful, 4 with STScI PI’s (Ferguson, Lucas, Wadadekar, Whitmore) and 1 with a JHU PI (Heckman). The following presentation is essentially what we presented at the Aspen Summer School.

Are They Really Globular Clusters ? The young clusters we see in the Antennae (and other galaxies with massive young clusters) have the: Colors (-0.2 < V-I < 0.6) Luminosities (-15 < M v < ?, power law LF with index ~ -2) Sizes(R eff ~ 4 pc) Distributions (similar to the field stars) Spectra(~ 10 objects age dated at Myr) Vel. Dispersions ( km/s) Masses( ) to be globular clusters with ages in the range 1 to ~ 500 Myr.

Mergers, Starbursts, Bars, Rings, and Spirals - (cont.) Roughly 20 gas-rich mergers have now been observed in detail by HST. All show young star clusters. In addition, we find young, massive, compact clusters in: starburst dwarf galaxies (e.g., Meurer et al., 1995), barred galaxies (Barth et al., 1995), spiral galaxies (Larsen & Richtler, 1999) Milky Way and LMC (e.g., Walborn 2000) These clusters have properties similar to those seen in the mergers, but always fewer in number, and generally fainter in luminosity. Science Question # 1 – Is “violent” star cluster formation different than “quiescent” star formation ?

If there are two different modes of star cluster formation we might expect a bimodal distribution in a plot of the magnitude of the brightest cluster in a galaxy vs. the log of the number of clusters. Whitmore, 2000 Violent star formation ? Quiescent star formation ?

However, the data appear to support a universal model rather than a bimodal model, with the correlation being due to statistics, not physics. However, this dataset, and reductions, were very inhomogeneous. Our goal is to redo this diagram: - with a uniform data set (e.g., SDSS, HST) -with uniform analysis (e.g., WESIX) - for larger dataset (e.g., N~ 100) Whitmore, 2000 Best fit Predicted if universal power-law, index = -2 M51 New point from Aspen project

Science Question # 2 – What fraction of clusters are hidden by dust ? Neff & Ulvestad (2000) found that their radio sources were “near but not coincident” with the young clusters in the Antennae”. It appears that this was due to a 1.2” positional offset. Once the offset was made we found that 85 % (11 of 13) of the strong radio sources have optical counterparts

Initial Program Galaxies

Following Holtzman et al. (1992) observations of “proto-globular” clusters in NGC 1275, we observed the two extremes of the Toomre Sequence of merging galaxies using HST in Cycle 2 and Cycle 5. Feasibility Study – M51 (NVO tools used) DataScope – Get SDSS g-band image WESIX - Source extraction and cross matching ALADIN – Visualization Voplot – Analysis

Photometric Calibration Compared SDSS g-mag from sextractor to HST V-mag (Rupali Chandar) Scatter ~ 0.1mag

Analysis with VOplot Source classification with flux concentration index (aperture mag – isophot mag) VOTables exported back to Aladin for various source types

Compact objects (stars) Saturated stars Nucleus Diffuse sources Clusters

Compact objects (stars)

Saturated stars Nucleus

Diffuse sources

Clusters

Whitmore, 2000 Best fit Predicted if universal power-law, index = -2 M51 New point from Aspen project

Fraction of missing clusters: Red crosses = 2 mass Blue squares = clusters Fraction of 2mass sources hidden by dust (outside center) = < 45 % (15/33) NOTE: - Something different near center ! Position offsets = TBD

Conclusions SDSS images can be used for this project (though will probably also try HST preview images) M51 will fit nicely on the Mv(brightest) vs. log N diagram > further support for universal model. NVO tools will be very useful for the project (e.g., datascope, WESIX, Aladin, VOPLOT). Automating the program (e.g., SIAP services and OPENSKYQUERY) is feasible, but will take additional work (e.g., developing a python client for WESIX, correcting for positional offsets)