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An evolutionary disc model of the edge-on galaxy NGC 5907

机译:An evolutionary disc model of the edge-on galaxy NGC 5907

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Context. We present an evolutionary disc model of the edge-on galaxy NGC 5907 based on a continuous star formation history and a continuous dynamical heating of the stellar subpopulations. Aims. This model explains the disparate two observational facts: 1) the exponential vertical disc structure in the optical and NIR of the non-obscured part of the stellar disc and 2) the FIR/submm luminosity enhanced by about a factor of four near the obscured mid-plane, which requires additional dust and also stellar light to heat the dust component. Methods. We use multi-band photometry in U, B, V, R, and I-band combined with radiative transfer through a dust component to simultaneously fit the vertical surface-brightness and colour index profiles in all bands adopting a reasonable star formation history and dynamical heating function. The vertical distribution of the stellar subpopulations are calculated self-consistently in dynamical equilibrium and the intrinsic stellar emissivity is calculated by stellar population synthesis. Results. The final disc model reproduces the surface-brightness profiles in all bands with a moderately declining star formation rate and a slowly starting heating function for young stars. The total dust mass is 5.7 x 10(7) M-circle dot as required from the FIR/submm measurements. Without a recent star burst we find in the midplane an excess of 5.2-, 4.0-, and 3.0-times more stellar light in the U-, B-, and V-band, respectively. The corresponding stellar mass-to-light ratios are 0.91 in V- and 1.0 in R-band. The central face-on optical depth in V-band is tau(f)(V) = 0.81 and the radial scale length of the dust is 40 larger than that of the stellar disc. Conclusions. Evolutionary disc models are a powerful method to understand the vertical structure of edge-on galaxies. Insights into the star formation history and the dynamical evolution of stellar discs can be gained. FIR/submm observations are necessary to restrict the parameter space for the models.

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