Mathematics – Logic
Scientific paper
Jan 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21344307l&link_type=abstract
American Astronomical Society, AAS Meeting #213, #443.07; Bulletin of the American Astronomical Society, Vol. 41, p.325
Mathematics
Logic
Scientific paper
As a variety of surveys of the local and distant Universe are approaching a full census of galaxy populations, our attention needs to turn towards understanding and quantifying the physical mechanisms that trigger and regulate the large-scale star formation rates (SFRs) in galaxies. We carried out a NICMOS survey in the Paschen-alpha (1.8756 micron) emission line and adjacent continuum for a sample of 84 nearby galaxies for which high resolution interferometric millimetric CO observations are available. This sample covers the full Hubble sequence and all bar types, providing an opportunity of studying the physical properties of star formation with respect to the morphological types. As an SFR tracer insensitive to extinction, the Paschen-alpha images allow us to probe the highly compact and dusty galaxy centers where H-alpha becomes unqualified. Along with the CO maps tracing circumnuclear molecular gas, we mainly address the following two questions: (1) To study the form of the SFR versus gas density law in a density and dust extinction regime 30 times higher than normally accessible with optical SFR tracers. (2) To investigate the spatial regime for the breakdown of the star formation law, for which the HII regions become spatially unassociated with their molecular cloud progenitors. The ultimate goal is to investigate star formation in the high gas density, short dynamical timescale environments of galaxy centers, that can dominate the star formation in the entire galaxy and, in some cases, become the sites of the most powerful starburst events ever witnessed in the history of the Universe. Here we present our current interesting results of this thorough investigation of spatially-resolved Schmidt-Kennicutt law by utilizing the data representing a quality extreme that is reachable to human at present.
Calzetti Daniela
Egusa Fumi
Kennicutt Rob
Komugi Shinya
Liu Guilin
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