Bibcode
Ferreras, Ignacio; Pasquali, Anna; de Carvalho, Reinaldo R.; de la Rosa, I. G.; Lahav, Ofer
Referencia bibliográfica
Monthly Notices of the Royal Astronomical Society, Volume 370, Issue 2, pp. 828-836.
Fecha de publicación:
8
2006
Número de citas
39
Número de citas referidas
32
Descripción
Environmental differences in the stellar populations of early-type
galaxies are explored using principal component analysis (PCA), focusing
on differences between elliptical galaxies in Hickson Compact Groups
(HCGs) and in the field. The method is model-independent and purely
relies on variations between the observed spectra. The projections (PC1,
PC2) of the observed spectra on the first and second principal
components reveal a difference with respect to environment, with a wider
range in PC1 and PC2 in the group sample. We define a spectral parameter
(ζ ≡ 0.36PC1-PC2) which simplifies this result to a single
number: field galaxies have a very similar value of ζ, whereas HCG
galaxies span a wide range in this parameter. The segregation is found
regardless of the way the input spectral energy distributions (SEDs) are
presented to PCA (i.e. changing the spectral range; using uncalibrated
data; subtracting the continuum or masking the SED to include only the
Lick spectral regions). Simple models are applied to give physical
meaning to the PCs. We obtain a strong correlation between the values of
ζ and the mass fraction in younger stars, so that some group
galaxies present a higher fraction of them, implying a more complex star
formation history in groups. Regarding `dynamically related' observables
such as a4 or velocity dispersion, we find a correlation with
PC3, but not with either PC1 or PC2. PCA is more sensitive than other
methods based on a direct analysis of observables such as the structure
of the surface brightness profile or the equivalent width of absorption
lines. The latter do not reveal any significant variation between field
and compact group galaxies. Our results imply that the presence of young
stars only amounts to a fraction of a per cent in its contribution to
the total variance, reflecting the power of PCA as a tool to extract
small variations in the spectra from unresolved stellar populations.