Recent Talks

Two-dimensional stellar kinematics obtained with the integral-field spectrograph SAURON allow the classification of early-type galaxies into 'slow' and 'fast' rotators, different from their morphological classification into ellipticals and lenticulars. Most fast rotators, including lenticular as well as many elliptical galaxies, are consistent with oblate axisymmetric disk-like systems. On the other hand, the slow-rotator ellipticals show clear deviations from axisymmetry, which can be modeled with our extension of Schwarzschild's orbit superposition method to triaxial geometry. Besides galaxies, I show that Schwarzschild's method can also be used to model in detail globular clusters such as ω Cen and M15. The recovered internal orbital structure of ω Cen reveals besides a signature of tidal interaction, also a central stellar disk, supporting its origin as the nucleus of a stripped dwarf galaxy. The formally best-fit Schwarzschild model for M15 includes an intermediate-mass black hole, but we cannot exclude a model in which dark remnants make up the dark mass in the collapsed core.

CALIFA is the largest IFS survey ever performed up to date. Recently started, it will observe ~600 galaxies in the Local Universe with PPAK at the 3.5m of the Calar Alto Observatory, sampling most of the size of these galaxies and covering the optical wavelength range between 3700-7100 Å, using to spectroscopic setups. The main goal of this survey is to characterize the spatially resolved spectroscopic properties (both the stellar and ionized gas components) of all the population of galaxies at the current cosmological time, in order to understand in detail the how is the final product of the evolution of galaxies. To do so, the sample will cover all the possible galaxies within the color-magnitude diagram, down to M_B ~ -18 mag, from big dry early-types to active fainter late-type galaxies. The main science drivers of the survey is to understand how galaxies evolve within the CM-diagram, understanding the details the process of star formation, metal enrichment, migrations and morphological evolution of galaxies.

Using the k-means cluster analysis algorithm, we carry out an unsupervised classification of all galaxy spectra in the seventh and final Sloan Digital Sky Survey data release (SDSS/DR7). Except for the shift to rest-frame wavelengths and the normalization to the g-band flux, no manipulation is applied to the original spectra. The algorithm guarantees that galaxies with similar spectra belong to the same class. We find that 99% of the galaxies can be assigned to only 17 major classes, with 11 additional minor classes including the remaining 1%. The classification is not unique since many galaxies appear in between classes; however, our rendering of the algorithm overcomes this weakness with a tool to identify borderline galaxies. Each class is characterized by a template spectrum, which is the average of all the spectra of the galaxies in the class. These low-noise template spectra vary smoothly and continuously along a sequence labeled from 0 to 27, from the reddest class to the bluest class. Our Automatic Spectroscopic K-means-based (ASK) classification separates galaxies in colors, with classes characteristic of the red sequence, the blue cloud, as well as the green valley. When red sequence galaxies and green valley galaxies present emission lines, they are characteristic of active galactic nucleus activity. Blue galaxy classes have emission lines corresponding to star formation regions. We find the expected correlation between spectroscopic class and Hubble type, but this relationship exhibits a high intrinsic scatter. Several potential uses of the ASK classification are identified and sketched, including fast determination of physical properties by interpolation, classes as templates in redshift determinations, and target selection in follow-up works (we find classes of Seyfert galaxies, green valley galaxies, as well as a significant number of outliers). The ASK classification is publicly accessible through various Web sites.