2,483 research outputs found
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 of the X-ray background in the 0.5-2 keV band. At the mean
redshift of the galaxy sample, , the comoving volume emissivity is
ergs sMpc . 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 . The spread is mainly due
to the assumed redshift evolution scenarios of the X-ray volume emissivity
. The dipole's prediction is consistent with a measured dipole in
the HEAO1 XRB map. Typically, the harmonic spectrum drops with like . This behaviour allows us to discriminate a true clustering
signal against the flux shot noise, which is constant with , 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 confidence
level (CL) around the concordance cosmology. When presented with a set of
cosmological parameters ( and redshift ), the trained ANN interpolates the power
spectrum for at sub-per cent accuracy for modes up to
. PkANN is faster than computationally expensive
N-body simulations, yet provides a worst-case error 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 eV for all
redshifts . For models with eV, predictions are
expected to be at 5 (10) per cent level for redshifts (). 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
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