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Published May 10, 2008 | Published
Journal Article Open

The mid-infrared fundamental plane of early-type galaxies

Abstract

Three observables of early-type galaxies—size (re), surface brightness (Ie), and velocity dispersion (σ0)—form a tight planar correlation known as the fundamental plane (FP), which has provided great insights into the galaxy formation and the evolution processes. However, the FP has been found to be tilted against the simple virial expectation, prompting debates on its origin. In order to investigate the contribution of systematic stellar population variation to the FP tilt, we study here the FP relations of early-type galaxies in the mid-infrared (MIR), which may represent stellar mass well. We examine the wavelength dependence of the FP coefficients a and b in log re = alog σ0 + blog Ie + c, using a sample of 56 early-type galaxies for which visible (V band), near-infrared (K band), and MIR (Spitzer IRAC, 3.6-8.0 μm) data are available. We find that the coefficient a increases as a function of wavelength as da/dλ = 0.11 ± 0.04 μm−1, while the coefficient b reaches the closest to –1 at 3.6-5.8 μm. When applied to the visible FP coefficients derived from a larger sample of nearby early-type galaxies, we get the FP relation with (a, b) (1.6-1.8, –0.9) at 3.6 μm. Our result suggests that the stellar population effect can explain more than half of the FP tilt, closing the gap between the virial expectation and the optical FP. The reduction in the FP tilt is reflected in the dynamical mass-to-light ratio, Mdyn/L, dependence on L which decreases toward 3.6-5.8 μm, suggesting that the MIR light better represents mass than the shorter wavelengths.

Additional Information

© 2008. The American Astronomical Society. Received 2007 December 9; accepted 2008 March 25; published 2008 April 10. This study was supported by a grant (R01-2007-000-20336-0) from the Basic Research Program of the Korea Science and Engineering Foundation, and by the Seoul Science Fellowship (H. J.). We thank the referee for useful comments, and Youngmin Seo and Soonyoung Min for algorithmic and technical advice in data analysis.

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