We study the luminosity and color dependence of the galaxy two-point correlation function in the Sloan Digital Sky Survey, starting from a sample of 6200,000 galaxies over 2500 deg super(2). We ...concentrate our analysis on volume-limited subsamples of specified luminosity ranges, for which we measure the projected correlation function w sub(p)(r sub(p)), which is directly related to the real-space correlation function y(r). The amplitude of w sub(p)(r sub(p)) rises continuously with luminosity from M sub(r) - -17.5 to M sub(r) - -22.5, with the most rapid increase occurring above the characteristic luminosity L sub(*) (M sub(r) - -20.5). Over the scales 0.1 h super(-1) Mpc < r sub(p) < 10 h super(-1) Mpc, the measurements for samples with M sub(r) > -22 can be approximated, imperfectly, by power-law three-dimensional correlation functions y(r) = (r/r sub(0)) super(-g) with g - 1.8 and r sub(0)(L sub(*)) - 5.0 h super(-1) Mpc. The brightest subsample, -23 < M sub(r) < -22, has a significantly steeper y(r). When we divide samples by color, redder galaxies exhibit a higher amplitude and steeper correlation function at all luminosities. The correlation amplitude of blue galaxies increases continuously with luminosity, but the luminosity dependence for red galaxies is less regular, with bright red galaxies exhibiting the strongest clustering at large scales and faint red galaxies exhibiting the strongest clustering at small scales. We interpret these results using halo occupation distribution (HOD) models assuming concordance cosmological parameters. For most samples, an HOD model with two adjustable parameters fits the w sub(p)(r sub(p)) data better than a power law, explaining inflections at r sub(p) 6 1-3 h super(-1) Mpc as the transition between the one-halo and two-halo regimes of y(r). The implied minimum mass for a halo hosting a central galaxy more luminous than L grows steadily, with M sub(min) 8 L at low luminosities and a steeper dependence above L sub(*). The mass at which a halo has, on average, one satellite galaxy brighter than L is M sub(1) - 23M sub(min) (L), at all luminosities. These results imply a conditional luminosity function (at fixed halo mass) in which central galaxies lie far above a Schechter function extrapolation of the satellite population. The HOD model fits nicely explain the color dependence of w sub(p)(r sub(p)) and the cross correlation between red and blue galaxies. For galaxies with M sub(r) < -21, halos slightly above M sub(min) have blue central galaxies, while more massive halos have red central galaxies and predominantly red satellite populations. The fraction of blue central galaxies increases steadily with decreasing luminosity and host halo mass. The strong clustering of faint red galaxies follows from the fact that nearly all of them are satellite systems in high-mass halos. The HOD fitting results are in good qualitative agreement with the predictions of numerical and semianalytic models of galaxy formation.
We explore trends in galaxy properties with Mpc-scale structures using catalogues of environment and large-scale structure from the Galaxy And Mass Assembly (GAMA) survey. Existing GAMA catalogues of ...large-scale structure, group, and pair membership allow us to construct galaxy stellar mass functions for different environmental types. To avoid simply extracting the known underlying correlations between galaxy properties and stellar mass, we create a mass matched sample of galaxies with stellar masses within 9.5 ≤ log M
*/h
−2 M⊙ ≤ 11 for each environmental population. Using these samples, we show that mass normalized galaxies in different large-scale environments have similar energy outputs, u − r colours, luminosities, and morphologies. Extending our analysis to group and pair environments, we show that galaxies that are not in groups or pairs exhibit similar characteristics to each other regardless of broader environment. For our mass controlled sample, we fail to see a strong dependence of Sérsic index or galaxy luminosity on halo mass, but do find that it correlates very strongly with colour. Repeating our analysis for galaxies that have not been mass controlled introduces and amplifies trends in the properties of galaxies in pairs, groups, and large-scale structure, indicating that stellar mass is the most important predictor of the galaxy properties we examine, as opposed to environmental classifications.
Abstract
We apply four statistical learning methods to a sample of 7941 galaxies (z < 0.06) from the Galaxy And Mass Assembly survey to test the feasibility of using automated algorithms to classify ...galaxies. Using 10 features measured for each galaxy (sizes, colours, shape parameters, and stellar mass), we apply the techniques of Support Vector Machines, Classification Trees, Classification Trees with Random Forest (CTRF) and Neural Networks, and returning True Prediction Ratios (TPRs) of 75.8 per cent, 69.0 per cent, 76.2 per cent, and 76.0 per cent, respectively. Those occasions whereby all four algorithms agree with each other yet disagree with the visual classification (‘unanimous disagreement’) serves as a potential indicator of human error in classification, occurring in ∼ 9 per cent of ellipticals, ∼ 9 per cent of little blue spheroids, ∼ 14 per cent of early-type spirals, ∼ 21 per cent of intermediate-type spirals, and ∼ 4 per cent of late-type spirals and irregulars. We observe that the choice of parameters rather than that of algorithms is more crucial in determining classification accuracy. Due to its simplicity in formulation and implementation, we recommend the CTRF algorithm for classifying future galaxy data sets. Adopting the CTRF algorithm, the TPRs of the five galaxy types are : E, 70.1 per cent; LBS, 75.6 per cent; S0–Sa, 63.6 per cent; Sab–Scd, 56.4 per cent, and Sd–Irr, 88.9 per cent. Further, we train a binary classifier using this CTRF algorithm that divides galaxies into spheroid-dominated (E, LBS, and S0–Sa) and disc-dominated (Sab–Scd and Sd–Irr), achieving an overall accuracy of 89.8 per cent. This translates into an accuracy of 84.9 per cent for spheroid-dominated systems and 92.5 per cent for disc-dominated systems.
We report on the first result from the clustering analysis of SDSS quasars. We computed the two-point correlation function (2PCF) of SDSS quasars in redshift space at
$8\,h^{-1} \,\mathrm{Mpc} < s < ...500\,h^{-1} \,\mathrm{Mpc}$
, with particular attention to its baryonic signature. Our sample consisted of 19986 quasars extracted from the SDSS Data Release 4. The redshift range of the sample is
$0.72 \le z \le 2.24$
(the mean redshift is
$\overline{z} = 1.46$
) and the reddening-corrected
$i$
-band apparent magnitude range is
$15.0 \le m_{i,\mathrm{rc}} \le 19.1$
. Due to the relatively low number density of the quasar sample, the bump in the power spectrum due to the baryon density,
$\Omega_{\mathrm{b}}$
, is not clearly visible. The effect of the baryon density is, however, to distort the overall shape of the 2PCF. The degree of distortion makes it an interesting alternate measure of the baryonic signature. Assuming a scale-independent linear bias and a spatially flat universe, we combined the observed quasar 2PCF and the predicted matter 2PCF to put constraints on
$\Omega_{\mathrm{b}}$
and
$\Omega_{\Lambda}$
(the cosmological constant). Our result was fitted as
$0.80-2.8\Omega_{\mathrm{b}} < \Omega_{\Lambda} < 0.90-1.4\Omega_{\mathrm{b}}$
at the
$2 \,\sigma$
confidence level. The “mean” bias parameter of our quasar sample is
$1.59 \,{\sigma_8}^{-1}$
(for
$\Omega_{\mathrm{b}} = 0.04$
and
$\Omega_{\Lambda} = 0.7$
), where
$\sigma_8$
is the top-hat mass fluctuation amplitude at
$8\,h^{-1} \,\mathrm{Mpc}$
. We also estimated the corresponding bias parameter of quasars at
$z = 0, b_{\mathrm{QSO,Fry}}(0)$
, assuming Fry’s bias evolution model. For
$\Omega_{\mathrm{b}} = 0.04, \Omega_{\Lambda} = 0.73$
, and
$\Omega_{\mathrm{d}} = 0.23$
, we found
$b_{\mathrm{QSO,Fry}}(0) = 0.54 + 0.83 \,{\sigma_8}^{-1}$
which is valid for
$0.6 < \sigma_8 < 1.0$
.
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