Warm dust and aromatic bands as quantitative probes of star-formation activity

Astronomy and Astrophysics – Astrophysics

Scientific paper

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17 pages, 3 tables, 5 figures -- accepted for publication in A&A

Scientific paper

10.1051/0004-6361:20040963

We combine samples of spiral galaxies and starburst systems observed with ISOCAM to investigate the reliability of mid-infrared (MIR) dust emission as a quantitative tracer of star formation (SF) activity. The total sample covers very diverse galactic environments and probes a much wider dynamic range in SF rate density than previous similar studies. We find that both the monochromatic 15 micron continuum and the 5-8.5 micron emission constitute excellent indicators of the SF rate as quantified by the Lyman continuum luminosity L_Lyc, within specified validity limits which are different for the two tracers. Normalized to projected surface area, the 15 micron luminosity S_15ct is directly proportional to S_Lyc over several orders of magnitude. Two regimes are distinguished from the relative offsets in the observed relation: the proportionality factor increases by a factor of ~ 5 between quiescent disks in spiral galaxies, and moderate to extreme star-forming environments in circumnuclear regions of spirals and in starburst systems. The transition occurs near S_Lyc ~ 10^2 L_sun pc^{-2} and is interpreted as due to very small dust grains starting to dominate the emission at 15 microns over aromatic species above this threshold. The 5-8.5 micron luminosity per unit area is also proportional to S_Lyc, with a single conversion factor from the most quiescent objects in the sample up to S_Lyc ~ 10^4 L_sun pc^{-2}, where the relation then flattens. The turnover is attributed to depletion of aromatic band carriers in the harsher conditions prevailing in extreme starbursts. The observed relations provide empirical calibrations useful for estimating SF rates from mid-IR observations in deeply embedded HII regions and obscured starbursts, and for predictions from evolutionary synthesis models.

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