Feature relevance in morphological galaxy classification

We investigate the utility of a variety of features in performing morphological galaxy classification using back-propagation neural network classifiers based on a sample of 805 galaxies classified by Naim et al. We derive a total of 22 features from each galaxy image and use these as inputs to a neural network trained using back-propagation. The morphological types are subdivided into two to seven groups, and the relevance of each of the features is examined for each grouping. We use the magnitude of the regularization parameter for each input to determine whether a feature can be eliminated. We then prune the input features of the network, typically down to four features. We examine a number of methods of assessing the performance of the network and determine which works best for our task.     

Dynamic evolution of nearby galaxy clusters

A study of the evolution of 377 rich ACO clusters with redshift z < 0.2 is presented. The data concerning galaxies in the investigated clusters were obtained using FOCAS packages applied to Digital Sky Survey I. The 377 galaxy clusters constitute a statistically uniform sample to which visual galaxy/star reclassifications were applied. Cluster shape within 2.0 h^–1 Mpc from the adopted cluster centre (the mean and the median of all galaxy coordinates, the position of the brightest and of the third brightest galaxy in the cluster) was determined through its ellipticity calculated using two methods: the covariance ellipse method (hereafter CEM) and the method based on Minkowski functionals (hereafter MFM). We investigated ellipticity dependence on the radius of circular annuli, in which ellipticity was calculated. This was realized by varying the radius from 0.5 to 2 Mpc in steps of 0.25 Mpc. By performing Monte Carlo simulations, we generated clusters to which the two ellipticity methods were applied. We found that the covariance ellipse method works better than the method based on Minkowski functionals. We also found that ellipticity distributions are different for different methods used. Using the ellipticity‐redshift relation, we investigated the possibility of cluster evolution in the low‐redshift Universe. The correlation of cluster ellipticities with redshifts is undoubtly an indicator of structural evolution. Using the t‐Student statistics, we found a statistically significant correlation between ellipticity and redshift at the significance level of α = 0.95. In one of the two shape determination methods we found that ellipticity grew with redshift, while the other method gave opposite results. Monte Carlo simulations showed that only ellipticities calculated at the distance of 1.5 Mpc from cluster centre in the Minkowski functional method are robust enough to be taken into account, but for that radius we did not find any relation between e and z. Since CEM pointed towards the existence of the e (z) relation, we conclude that such an effect is real though rather weak. A detailed study of the e (z) relation showed that the observed relation is nonlinear, and the number of elongated structures grows rapidly for z > 0.14 (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Recovering physical parameters from galaxy spectra using MOPED

We derive physical parameters of galaxies from their observed spectra using MOPED, the optimized data compression algorithm of Heavens, Jimenez & Lahav. Here we concentrate on parametrizing galaxy properties, and apply the method to the NGC galaxies in Kennicutt's spectral atlas. We focus on deriving the star formation history, metallicity and dust content of galaxies. The method is very fast, taking a few seconds of CPU time to estimate ∼17 parameters, and is therefore specially suited to studying large data sets, such as the Anglo-Australian two-degree-field (2dF) galaxy survey and the Sloan Digital Sky Survey (SDSS). Without the power of MOPED, the recovery of star formation histories in these surveys would be impractical. In Kennicutt's atlas, we find that for the spheroidals a small recent burst of star formation is required to provide the best fit to the spectrum. There is clearly a need for theoretical stellar atmospheric models with spectral resolution better than 1 Å if we are to extract all the rich information that large redshift surveys contain in their galaxy spectra.     

The effect of dwarf galaxy disruption in semi-analytic models

We present results for a galaxy formation model that includes a simple treatment for the disruption of dwarf galaxies by gravitational forces and galaxy encounters within galaxy clusters. This is implemented a posteriori in a semi-analytic model by considering the stability of cluster dark matter subhaloes at   z = 0  . We assume that a galaxy whose dark matter substructure has been disrupted will itself disperse, while its stars become part of the population of intracluster stars responsible for the observed intracluster light. Despite the simplicity of this assumption, our results show a substantial improvement over previous models and indicate that the inclusion of galaxy disruption is indeed a necessary ingredient of galaxy formation models. We find that galaxy disruption suppresses the number density of dwarf galaxies by about a factor of 2. This makes the slope of the faint end of the galaxy luminosity function shallower, in agreement with observations. In particular, the abundance of faint, red galaxies is strongly suppressed. As a result, the luminosity function of red galaxies and the distinction between the red and the blue galaxy populations in colour–magnitude relationships are correctly predicted. Finally, we estimate a fraction of intracluster light comparable to that found in clusters of galaxies.     

The effect of galaxy mass ratio on merger-driven starbursts

We employ numerical simulations of galaxy mergers to explore the effect of galaxy mass ratio on merger-driven starbursts. Our numerical simulations include radiative cooling of gas, star formation, and stellar feedback to follow the interaction and merger of four disc galaxies. The galaxy models span a factor of 23 in total mass and are designed to be representative of typical galaxies in the local universe. We find that the merger-driven star formation is a strong function of merger mass ratio, with very little, if any, induced star formation for large mass ratio mergers. We define a burst efficiency that is useful to characterize the merger-driven star formation and test that it is insensitive to uncertainties in the feedback parametrization. In accord with previous work we find that the burst efficiency depends on the structure of the primary galaxy. In particular, the presence of a massive stellar bulge stabilizes the disc and suppresses merger-driven star formation for large mass ratio mergers. Direct, coplanar merging orbits produce the largest tidal disturbance and yield the most intense burst of star formation. Contrary to naive expectations, a more compact distribution of gas or an increased gas fraction both decrease the burst efficiency. Owing to the efficient feedback model and the newer version of smoothed particle hydrodynamics employed here, the burst efficiencies of the mergers presented here are smaller than in previous studies.     

Objective classification of galaxy spectra using the information bottleneck method

A new method for classification of galaxy spectra is presented, based on a recently introduced information theoretical principle, the information bottleneck . For any desired number of classes, galaxies are classified such that the information content about the spectra is maximally preserved. The result is classes of galaxies with similar spectra, where the similarity is determined via a measure of information. We apply our method to ∼6000 galaxy spectra from the ongoing 2dF redshift survey, and a mock-2dF catalogue produced by a cold dark matter (CDM) based semi-analytic model of galaxy formation. We find a good match between the mean spectra of the classes found in the data and in the models. For the mock catalogue, we find that the classes produced by our algorithm form an intuitively sensible sequence in terms of physical properties such as colour, star formation activity, morphology, and internal velocity dispersion. We also show the correlation of the classes with the projections resulting from a principal component analysis.     

Recovering galaxy star formation and metallicity histories from spectra using VESPA

We introduce versatile spectral analysis (VESPA): a new method which aims to recover robust star formation and metallicity histories from galactic spectra. VESPA uses the full spectral range to construct a galaxy history from synthetic models. We investigate the use of an adaptative parametrization grid to recover reliable star formation histories on a galaxy-by-galaxy basis. Our goal is robustness as opposed to high-resolution histories, and the method is designed to return high time resolution only where the data demand it. In this paper we detail the method and we present our findings when we apply VESPA to synthetic and real Sloan Digital Sky Survey (SDSS) spectroscopic data. We show that the number of parameters that can be recovered from a spectrum depends strongly on the signal-to-noise ratio, wavelength coverage and presence or absence of a young population. For a typical SDSS sample of galaxies, we can normally recover between two and five stellar populations. We find very good agreement between VESPA and our previous analysis of the SDSS sample with MOPED.     

Feedback and the formation of dwarf galaxy stellar haloes

Stellar population studies show that low-mass galaxies in all environments exhibit stellar haloes that are older and more spherically distributed than the main body of the galaxy. In some cases, there is a significant intermediate age component that extends beyond the young disc. We examine a suite of Smoothed Particle Hydrodynamic simulations and find that elevated early star formation activity combined with supernova feedback can produce an extended stellar distribution that resembles these haloes for model galaxies ranging from   v ₂₀₀= 15  to 35 km s⁻¹, without the need for accretion of subhaloes.     

Exploring spiral galaxy potentials with hydrodynamical simulations

We study how well the complex gas velocity fields induced by massive spiral arms are modelled by the hydrodynamical simulations that we used recently to constrain the dark matter fraction in nearby spiral galaxies. More specifically, we explore the dependence of the positions and amplitudes of features in the gas flow on the temperature of the interstellar medium (assumed to behave as a one-component isothermal fluid), the non-axisymmetric disc contribution to the galactic potential, the pattern speed  Ω_p  , and finally the numerical resolution of the simulation. We argue that, after constraining the pattern speed reasonably well by matching the simulations to the observed spiral arm morphology, the amplitude of the non-axisymmetric perturbation (the disc fraction) is left as the primary parameter determining the gas dynamics. However, owing to the sensitivity of the positions of the shocks to modelling parameters, one has to be cautious when quantitatively comparing the simulations to observations. In particular, we show that a global least-squares analysis is not the optimal method for distinguishing different models, as it tends to slightly favour low disc fraction models. Nevertheless, we conclude that, given observational data of reasonably high spatial resolution and an accurate shock-resolving hydro-code, this method tightly constrains the dark matter content within spiral galaxies. We further argue that, even if the perturbations induced by spiral arms are weaker than those of strong bars, they are better suited for this kind of analysis because the spiral arms extend to larger radii where effects like inflows due to numerical viscosity and morphological dependence on gas sound speed are less of a concern than they are in the centres of discs.     

Measuring galaxy potentials using shell kinematics

We show that the kinematics of the shells seen around some elliptical galaxies provide a new, independent means for measuring the gravitational potentials of elliptical galaxies out to large radii. A numerical simulation of a set of shells formed in the merger between an elliptical and a smaller galaxy reveals that the shells have a characteristic observable kinematic structure, with the maximum line-of-sight velocity increasing linearly as one moves inward from a shell edge. A simple analytic calculation shows that this structure provides a direct measure of the gradient of the gravitational potential at the shell radius. In order to extract this information from attainable data, we have also derived a complete distribution of line-of-sight velocities for material within a shell; comparing the observed spectra of a shell to a stellar template convolved with this distribution will enable us to measure the gradient of the potential at this radius. Repeating the analysis for a whole series of nested shells in a galaxy allows the complete form of the gravitational potential as a function of radius to be mapped out. The requisite observations lie within reach of the up-coming generation of large telescopes.