In this paper we analyse the results of the two-dimensional (2D) fit of the light distribution of 73 early-type galaxies belonging to the Virgo and Fornax clusters, a sample volume- and magnitude-limited down to MB = -17.3, and highly homogeneous. In our previous paper (Paper I) we have presented the adopted 2D models of the surface-brightness distribution -namely the r1/n and (r1/n + exp) models - we have discussed the main sources of error affecting the structural parameters, and we have tested the ability of the chosen minimization algorithm (MINUIT) in determining the fitting parameters using a sample of artificial galaxies. We show that, with the exception of 11 low-luminosity E galaxies, the best fit of the real galaxy sample is always achieved with the two-component (r1/n + exp) model. The improvement in the χ2 due to the addition of the exponential component is found to be statistically significant. The best fit is obtained with the exponent n of the generalized r1/n Sersic law...

2D modelling of the light distribution of early-type galaxies in a volume-limited sample - II. Results for real galaxies

D'ONOFRIO, MAURO
2001

Abstract

In this paper we analyse the results of the two-dimensional (2D) fit of the light distribution of 73 early-type galaxies belonging to the Virgo and Fornax clusters, a sample volume- and magnitude-limited down to MB = -17.3, and highly homogeneous. In our previous paper (Paper I) we have presented the adopted 2D models of the surface-brightness distribution -namely the r1/n and (r1/n + exp) models - we have discussed the main sources of error affecting the structural parameters, and we have tested the ability of the chosen minimization algorithm (MINUIT) in determining the fitting parameters using a sample of artificial galaxies. We show that, with the exception of 11 low-luminosity E galaxies, the best fit of the real galaxy sample is always achieved with the two-component (r1/n + exp) model. The improvement in the χ2 due to the addition of the exponential component is found to be statistically significant. The best fit is obtained with the exponent n of the generalized r1/n Sersic law...
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2481413
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