ANNz: estimating photometric redshifts using artificial neural networks

We introduce ANNz, a freely available software package for photometric redshift estimation using Artificial Neural Networks. ANNz learns the relation between photometry and redshift from an appropriate training set of galaxies for which the redshift is already known. Where a large and representative training set is available ANNz is a highly competitive tool when compared with traditional template-fitting methods. The ANNz package is demonstrated on the Sloan Digital Sky Survey Data Release 1, and for this particular data set the r.m.s. redshift error in the range 0 < z < 0.7 is 0.023. Non-ideal conditions (spectroscopic sets which are small, or which are brighter than the photometric set for which redshifts are required) are simulated and the impact on the photometric redshift accuracy assessed.Comment: 6 pages, 6 figures. Replaced to match version accepted by PASP (minor changes to original submission). The ANNz package may be obtained from http://www.ast.cam.ac.uk/~aa

The distribution of red and blue galaxies in groups: an empirical test of the halo model

The popular halo model predicts that the power spectrum of the galaxy fluctuations is simply the sum of the large scale linear halo-halo power spectrum and the weighted power spectrum of the halo profile. Previous studies have derived halo parameters from the observed galaxy correlation function. Here we test the halo model directly for self-consistency with a minimal set of theoretical assumptions by utilising the 2dF Galaxy Redshift Survey (2dFGRS). We derive empirically the halo occupation and galaxy radial distributions in the haloes of the 2dF Percolation-Inferred Galaxy Group (2PIGG) catalogue. The mean halo occupation number is found to be well-fitted by a power-law, ~ M^b, at high masses, with b = 1.05, 0.88, 0.99 for red, blue and all galaxies respectively (with 1-sigma errors of 15-19%). We find that the truncated NFW profile provides a good fit to the galaxy radial distributions, with concentration parameters c=3.9, 1.3, 2.4 for red, blue and all galaxies respectively (with 1-sigma errors of 8-15%). Adding the observed linear power spectrum to these results, we compare these empirical predictions of the halo model with the observed correlation functions for these same 2dF galaxy populations. We conclude that subject to some fine tuning it is an acceptable model for the two-point correlations. Our analysis also explains why the correlation function slope of the red galaxies is steeper than that of the blue galaxies. It is mainly due to the number of red and blue galaxies per halo, rather than the radial distribution within the haloes of the two galaxy species.Comment: 15 pages, 15 figures. MNRAS accepted version. Adds appx. on profile fitting; now use truncated NF

Faint Blue Galaxies as a Probe of the X-ray Background at High Redshift

We present a formalism describing the physical content of cross-correlation functions between a diffuse background and a population of discrete sources. The formalism is used to interpret cross-correlation signals between the unresolved X-ray background and a galaxy population resolved to high redshift in another spectral band. Specifically, we apply it to the so-called faint blue galaxy population and constrain their X-ray emissivity and clustering properties. A model is presented which satisfies the recently measured constraints on all 3 correlation functions (galaxy/galaxy, background/background and galaxy/background). This model predicts that faint galaxies in the magnitude range B=18-23 (cvering redshifts z \lsim 0.5) make up $\sim 22 \%$ of the X-ray background in the 0.5-2 keV band. At the mean redshift of the galaxy sample, $\bar z=0.26$, the comoving volume emissivity is $\rho_X \sim 6-9 \times 10^{38}h$ ergs s$^{-1}$Mpc$^{-3}$ . When extrapolated to fainter magnitudes, the faint blue galaxy population can account for most of the residual background at soft energy. We show how the measurement of the angular and zero-lag cross-correlation functions between increasingly faint galaxies and the X-ray background can allow us to map the X-ray emissivity as a function of redshift.Comment: uuencoded compressed postscript, without figures. The preprint is available with figures at http://www.ast.cam.ac.uk/preprint/PrePrint.htm

The X-Ray Background as a Probe of Density Fluctuations at High Redshift

The X-Ray Background (XRB) probes structure on scales intermediate between those explored by local galaxy redshift surveys and by the COBE Microwave Background measurements. We predict the large scale angular fluctuations in the XRB, expressed in terms of spherical harmonics for a range of assumed power-spectra and evolution scenarios. The dipole is due to large scale structure as well as to the observer's motion (the Compton-Getting effect). For a typical observer the two effects turn out to be comparable in amplitude. The coupling of the two effects makes it difficult to use the XRB for independent confirmation of the CMB dipole being due to the observer's motion. The large scale structure dipole (rms per component) relative to the monopole is in the range $a_{1m}/a_{00} \sim (0.5-9.0) \times 10^{-3}$. The spread is mainly due to the assumed redshift evolution scenarios of the X-ray volume emissivity $\rho_x(z)$. The dipole's prediction is consistent with a measured dipole in the HEAO1 XRB map. Typically, the harmonic spectrum drops with $l$ like $a_{lm} \sim l^{-0.4}$. This behaviour allows us to discriminate a true clustering signal against the flux shot noise, which is constant with $l$, and may dominate the signal unless bright resolved sources are removed from the XRB map. We also show that Sachs-Wolfe and Doppler (due to the motion of the sources) effects in the XRB are negligible. Although our analysis focuses on the XRB, the formalism is general and can be easily applied to other cosmological backgrounds.Comment: 14 pages, 3 postscript figures, available from ftp://cass41.ast.cam.ac.uk/pub/lahav/xrb accepted for publication in MNRA

The correlation function of radio sources

We investigate the large-scale clustering of radio sources in the Green Bank and Parkes-MIT-NRAO 4.85 GHz surveys by measuring the angular two-point correlation function w(\theta). Excluding contaminated areas, the two surveys together cover 70 per cent of the whole sky. We find both surveys to be reasonably complete above 50 mJy. On the basis of previous studies, the radio sources are galaxies and radio-loud quasars lying at redshifts up to z \sim 4, with a median redshift z \sim 1. This provides the opportunity to probe large-scale structures in a volume far larger than that within the reach of present optical and infrared surveys. We detect a clustering signal w(\theta) \approx 0.01 for \theta = 1\degr. By assuming an evolving power-law spatial correlation function in comoving coordinates \xi(r_c,z) = ( r_c / r_0 )^{-\gamma} (1+z)^{\gamma-(3+\epsilon)}, where \gamma = 1.8, and the redshift distribution N(z) of the radio galaxies, we constrain the r_0--\epsilon parameter space. For `stable clustering' (\epsilon = 0), we find the correlation length r_0 \approx 18 Mpc/h, larger than the value for nearby normal galaxies and comparable to the cluster-cluster correlation length.Comment: 8 pages, 7 ps figures included, LaTeX (mn,sty). Accepted by MNRA

PkANN - II. A non-linear matter power spectrum interpolator developed using artificial neural networks

In this paper we introduce PkANN, a freely available software package for interpolating the non-linear matter power spectrum, constructed using Artificial Neural Networks (ANNs). Previously, using Halofit to calculate matter power spectrum, we demonstrated that ANNs can make extremely quick and accurate predictions of the power spectrum. Now, using a suite of 6380 N-body simulations spanning 580 cosmologies, we train ANNs to predict the power spectrum over the cosmological parameter space spanning $3\sigma$ confidence level (CL) around the concordance cosmology. When presented with a set of cosmological parameters ($\Omega_{\rm m} h^2, \Omega_{\rm b} h^2, n_s, w, \sigma_8, \sum m_\nu$ and redshift $z$), the trained ANN interpolates the power spectrum for $z\leq2$ at sub-per cent accuracy for modes up to $k\leq0.9\,h\textrm{Mpc}^{-1}$. PkANN is faster than computationally expensive N-body simulations, yet provides a worst-case error $<1$ per cent fit to the non-linear matter power spectrum deduced through N-body simulations. The overall precision of PkANN is set by the accuracy of our N-body simulations, at 5 per cent level for cosmological models with $\sum m_\nu<0.5$ eV for all redshifts $z\leq2$. For models with $\sum m_\nu>0.5$ eV, predictions are expected to be at 5 (10) per cent level for redshifts $z>1$ ($z\leq1$). The PkANN interpolator may be freely downloaded from http://zuserver2.star.ucl.ac.uk/~fba/PkANNComment: 21 pages, 14 figures, 2 table

AUTOMATED MORPHOLOGICAL CLASSIFICATION OF APM GALAXIES BY SUPERVISED ARTIFICIAL NEURAL NETWORKS

We train Artificial Neural Networks to classify galaxies based solely on the morphology of the galaxy images as they appear on blue survey plates. The images are reduced and morphological features such as bulge size and the number of arms are extracted, all in a fully automated manner. The galaxy sample was first classified by 6 independent experts. We use several definitions for the mean type of each galaxy, based on those classifications. We then train and test the network on these features. We find that the rms error of the network classifications, as compared with the mean types of the expert classifications, is 1.8 Revised Hubble Types. This is comparable to the overall rms dispersion between the experts. This result is robust and almost completely independent of the network architecture used.Comment: The full paper contains 25 pages, and includes 22 figures. It is available at ftp://ftp.ast.cam.ac.uk/pub/hn/apm2.ps . The table in the appendix is available on request from [email protected]. Mon. Not. R. Astr. Soc., in pres

What is a Peculiar Galaxy ?

Following the recent surge of interest in peculiar galaxies at high redshifts we consider the definition, or lack thereof, of morphological peculiarities on a sample of local universe galaxies. Studying the morphology of local universe galaxies is also of interest in trying to understand galaxy dynamics and quantifying the relations between morphology and environment. We use classifications given by five experts for a sample of 827 APM galaxies and find that there is little agreement between them on what qualifies as a peculiar galaxy. We attempt several objective approaches : matching galaxy images to ``templates''; examinig the 180-degree Asymmetry against Light Concentration (following Abraham et al. 1995); and exploring angle-dependent asymmetry measures. While none of the quantities we use results in a clean distinction between normal and peculiar galaxies, there is a rough correlation between some parameters and image peculiarity. However, the mixing between the two classes is significant. We conclude that the class of peculiar galaxies is not totally distinct from the class of normal galaxies, and that what we are seeing is really a sequence. It is therefore more useful to consider distribution functions of morphological parameters. The current and possibly other, more accurate parametrisations require better data, which is becoming available through CCD imaging.Comment: 6 pages, latex, 12 figures. Postscript also available from ftp://ftp.ast.cam.ac.uk/pub/hn/pecs . Submitted to Mon. Not. R. Astr. Soc

Measuring the Mach number of the Universe via the Sunyaev-Zeldovich effect

We introduce a new statistic to measure more accurately the cosmic sound speed of clusters of galaxies at different redshifts. This statistic is evaluated by cross-correlating cosmic microwave background (CMB) fluctuations caused by the Sunyaev-Zel'dovich effect from observed clusters of galaxies with their redshifts. When clusters are distributed in redshift bins of narrow width, one could measure the mean squared cluster peculiar velocity with an error \sigma_{C_S^2}\lsim (300{\rm km/s})^2. This can be done around z>0.3 with clusters of flux above 200 mJy which will be detected by PLANCK, coupled with high resolution microwave images to eliminate the cosmological part of the CMB fluctuations. The latter can be achieved with observations by the planned ALMA array or the NSF South Pole telescope and other surveys. By measuring the cosmic sound speed and the bulk flow in, e.g., 4 spheres of ~ 100h^{-1}Mpc at z=0.3, we could have a direct measurement of the matter density 0.21<\Omega_m<0.47 at 95 % confidence level.Comment: Ap.J.Letters, submitte