We analyse the observed correlation between galaxy environment and Hα emission‐line strength, using volume‐limited samples and group catalogues of 24 968 galaxies at 0.05 < z < 0.095, drawn from the 2dF Galaxy Redshift Survey (MbJ< −19.5) and the Sloan Digital Sky Survey (Mr < −20.6). We characterize the environment by: (1) Σ5, the surface number density of galaxies determined by the projected distance to the fifth nearest neighbour; and (2) ρ1.1 and ρ5.5, three‐dimensional density estimates obtained by convolving the galaxy distribution with Gaussian kernels of dispersion 1.1 and 5.5 Mpc, respectively. We find that star‐forming and quiescent galaxies form two distinct populations, as characterized by their Hα equivalent width, W0(Hα). The relative numbers of star‐forming and quiescent galaxies vary strongly and continuously with local density. However, the distribution of W0(Hα) amongst the star‐forming population is independent of environment. The fraction of star‐forming galaxies shows strong sensitivity to the density on large scales, ρ5.5, which is likely independent of the trend with local density, ρ1.1. We use two differently selected group catalogues to demonstrate that the correlation with galaxy density is approximately independent of group velocity dispersion, for σ= 200–1000 km s‐1. Even in the lowest‐density environments, no more than ∼70 per cent of galaxies show significant Hα emission. Based on these results, we conclude that the present‐day correlation between star formation rate and environment is a result of short‐time‐scale mechanisms that take place preferentially at high redshift, such as starbursts induced by galaxy–galaxy interactions.

We present an 8 sigma detection of cosmic magnification measured by the variation of quasar density due to gravitational lensing by foreground large scale structure. To make this measurement we used 3800 square degrees of photometric observations from the Sloan Digital Sky Survey (SDSS) containing \~200,000 quasars and 13 million galaxies. Our measurement of the galaxy-quasar cross-correlation function exhibits the amplitude, angular dependence and change in sign as a function of the slope of the observed quasar number counts that is expected from magnification bias due to weak gravitational lensing. We show that observational uncertainties (stellar contamination, Galactic dust extinction, seeing variations and errors in the photometric redshifts) are well controlled and do not significantly affect the lensing signal. By weighting the quasars with the number count slope, we combine the cross-correlation of quasars for our full magnitude range and detect the lensing signal at >4 sigma in all five SDSS filters. Our measurements of cosmic magnification probe scales ranging from 60 kpc/h to 10 Mpc/h and are in good agreement with theoretical predictions based on the WMAP concordance cosmology. As with galaxy-galaxy lensing, future measurements of cosmic magnification will provide useful constraints on the galaxy-mass power spectrum.Comment: 12 pages, 8 figures, 2 tables; accepted for publication in Ap

Abstract-Astronomy and astrophysics are witnessing dramatic increases in data volume as detectors, telescopes and computers become ever more powerful. During the last decade, sky surveys across the electromagnetic spectrum have collected hundreds of terabytes of astronomical data for hundreds of millions of sources. Over the next decade, the data volume will enter the petabyte domain, and provide accurate measurements for billions of sources. Astronomy and physics students are not traditionally trained to handle such voluminous and complex data sets. In this paper we describe astroML; an initiative, based on python and scikit-learn, to develop a compendium of machine learning tools designed to address the statistical needs of the next generation of students and astronomical surveys. We introduce astroML and present a number of example applications that are enabled by this package.

We present measurements of the redshift-space three-point correlation function of 50 967 luminous red galaxies (LRGs) from Data Release 3 (DR3) of the Sloan Digital Sky Survey (SDSS). We have studied the shape dependence of the reduced three-point correlation function (Q z (s, q, θ )) on three different scales, s = 4, 7 and 10 h −1 Mpc, and over the range of 1 < q < 3 and 0 • < θ < 180 • . On small scales (s = 4 h −1 Mpc), Q z is nearly constant, with little change as a function of q and θ. However, there is evidence for a shallow U-shaped behaviour (with θ ) which is expected from theoretical modelling of Q z (s, q, θ). On larger scales (s = 7 and 10 h −1 Mpc), the U-shaped anisotropy in Q z (with θ ) is more clearly detected. We compare this shape dependence in Q z (s, q, θ ) with that seen in mock galaxy catalogues which were generated by populating the dark matter haloes in large N-body simulations with mock galaxies using various halo occupation distributions (HOD). We find that the combination of the observed number density of LRGs, the (redshift-space) two-point correlation function and Q z (s, q, θ ) provides a strong constraint on the allowed HOD parameters (M min , M 1 , α) and breaks key degeneracies between these parameters. For example, our observed Q z (s, q, θ) disfavours mock catalogues that overpopulate massive dark matter haloes with many LRG satellites. We also estimate the linear bias of LRGs to be b = 1.87 ± 0.07 in excellent agreement with other measurements.

We present measurements of the normalized redshift-space three-point correlation function (3PCF) (Q z ) of galaxies from the Sloan Digital Sky Survey (SDSS) main galaxy sample. These measurements were possible because of a fast new N-point correlation function algorithm (called npt) based on multiresolutional k-d trees. We have applied npt to both a volume-limited (36 738 galaxies with 0.05 z 0.095 and −23 M 0.0 r −20.5) and magnitude-limited sample (134 741 galaxies over 0.05 z 0.17 and ∼M * ± 1.5) of SDSS galaxies, and find consistent results between the two samples, thus confirming the weak luminosity dependence of Q z recently seen by other authors. We compare our results to other Q z measurements in the literature and find it to be consistent within the full jackknife error estimates. However, we find these errors are significantly increased by the presence of the 'Sloan Great Wall' (at z ∼0.08) within these two SDSS data sets, which changes the 3PCF by 70 per cent on large scales (s 10 h −1 Mpc). If we exclude this supercluster, our observed Q z is in better agreement with that obtained from the 2-degree Field Galaxy Redshift Survey (2dFGRS) by other authors, thus demonstrating the sensitivity of these higher order correlation functions to large-scale structures in the Universe. This analysis highlights that the SDSS data sets used here are not 'fair samples' of the Universe for the estimation of higher order clustering statistics and larger volumes are required. We study the shape dependence of Q z (s, q, θ) as one expects this measurement to depend on scale if the large-scale structure in the Universe has grown