28 research outputs found
A very brief description of LOFAR - the Low Frequency Array
LOFAR (Low Frequency Array) is an innovative radio telescope optimized for
the frequency range 30-240 MHz. The telescope is realized as a phased aperture
array without any moving parts. Digital beam forming allows the telescope to
point to any part of the sky within a second. Transient buffering makes
retrospective imaging of explosive short-term events possible. The scientific
focus of LOFAR will initially be on four key science projects (KSPs): 1)
detection of the formation of the very first stars and galaxies in the universe
during the so-called epoch of reionization by measuring the power spectrum of
the neutral hydrogen 21-cm line (Shaver et al. 1999) on the ~5' scale; 2)
low-frequency surveys of the sky with of order expected new sources; 3)
all-sky monitoring and detection of transient radio sources such as gamma-ray
bursts, x-ray binaries, and exo-planets (Farrell et al. 2004); and 4) radio
detection of ultra-high energy cosmic rays and neutrinos (Falcke & Gorham 2003)
allowing for the first time access to particles beyond 10^21 eV (Scholten et
al. 2006). Apart from the KSPs open access for smaller projects is also
planned. Here we give a brief description of the telescope.Comment: 2 pages, IAU GA 2006, Highlights of Astronomy, Volume 14, K.A. van
der Hucht, e
Constraining the epoch of reionization with the variance statistic: simulations of the LOFAR case
Several experiments are underway to detect the cosmic redshifted 21-cm signal
from neutral hydrogen from the Epoch of Reionization (EoR). Due to their very
low signal-to-noise ratio, these observations aim for a statistical detection
of the signal by measuring its power spectrum. We investigate the extraction of
the variance of the signal as a first step towards detecting and constraining
the global history of the EoR. Signal variance is the integral of the signal's
power spectrum, and it is expected to be measured with a high significance. We
demonstrate this through results from a simulation and parameter estimation
pipeline developed for the Low Frequency Array (LOFAR)-EoR experiment. We show
that LOFAR should be able to detect the EoR in 600 hours of integration using
the variance statistic. Additionally, the redshift () and duration
() of reionization can be constrained assuming a parametrization. We
use an EoR simulation of and to test the
pipeline. We are able to detect the simulated signal with a significance of 4
standard deviations and extract the EoR parameters as and in 600 hours,
assuming that systematic errors can be adequately controlled. We further show
that the significance of detection and constraints on EoR parameters can be
improved by measuring the cross-variance of the signal by cross-correlating
consecutive redshift bins.Comment: 13 pages, 14 figures, Accepted for publication in MNRA
The scale of the problem:Recovering images of reionization with Generalized Morphological Component Analysis
The accurate and precise removal of 21-cm foregrounds from Epoch of
Reionization redshifted 21-cm emission data is essential if we are to gain
insight into an unexplored cosmological era. We apply a non-parametric
technique, Generalized Morphological Component Analysis or GMCA, to simulated
LOFAR-EoR data and show that it has the ability to clean the foregrounds with
high accuracy. We recover the 21-cm 1D, 2D and 3D power spectra with high
accuracy across an impressive range of frequencies and scales. We show that
GMCA preserves the 21-cm phase information, especially when the smallest
spatial scale data is discarded. While it has been shown that LOFAR-EoR image
recovery is theoretically possible using image smoothing, we add that wavelet
decomposition is an efficient way of recovering 21-cm signal maps to the same
or greater order of accuracy with more flexibility. By comparing the GMCA
output residual maps (equal to the noise, 21-cm signal and any foreground
fitting errors) with the 21-cm maps at one frequency and discarding the smaller
wavelet scale information, we find a correlation coefficient of 0.689, compared
to 0.588 for the equivalently smoothed image. Considering only the central 50%
of the maps, these coefficients improve to 0.905 and 0.605 respectively and we
conclude that wavelet decomposition is a significantly more powerful method to
denoise reconstructed 21-cm maps than smoothing.Comment: 13 pages, 12 figures, accepted by MNRA
Fast Large-Scale Reionization Simulations
We present an efficient method to generate large simulations of the Epoch of
Reionization (EoR) without the need for a full 3-dimensional radiative transfer
code. Large dark-matter-only simulations are post-processed to produce maps of
the redshifted 21cm emission from neutral hydrogen. Dark matter haloes are
embedded with sources of radiation whose properties are either based on
semi-analytical prescriptions or derived from hydrodynamical simulations. These
sources could either be stars or power-law sources with varying spectral
indices. Assuming spherical symmetry, ionized bubbles are created around these
sources, whose radial ionized fraction and temperature profiles are derived
from a catalogue of 1-D radiative transfer experiments. In case of overlap of
these spheres, photons are conserved by redistributing them around the
connected ionized regions corresponding to the spheres. The efficiency with
which these maps are created allows us to span the large parameter space
typically encountered in reionization simulations. We compare our results with
other, more accurate, 3-D radiative transfer simulations and find excellent
agreement for the redshifts and the spatial scales of interest to upcoming 21cm
experiments. We generate a contiguous observational cube spanning redshift 6 to
12 and use these simulations to study the differences in the reionization
histories between stars and quasars. Finally, the signal is convolved with the
LOFAR beam response and its effects are analyzed and quantified. Statistics
performed on this mock data set shed light on possible observational strategies
for LOFAR.Comment: 18 pages, 21 figures, submitted to MNRAS For high-resolution images
follow "http://www.astro.rug.nl/~thomas/eormap.pdf
Initial LOFAR observations of epoch of reionization windows: II. diffuse polarized emission in the ELAIS-N1 field
Aims. This study aims to characterise the polarized foreground emission in the ELAIS-N1 field and to address its possible implications for extracting of the cosmological 21 cm signal from the LOw-Frequency ARray-Epoch of Reionization (LOFAR-EoR) data. Methods. We used the high band antennas of LOFAR to image this region and RM-synthesis to unravel structures of polarized emission at high Galactic latitudes. Results. The brightness temperature of the detected Galactic emission is on average ~4 K in polarized intensity and covers the range from-10 to + 13 rad m-2 in Faraday depth. The total polarized intensity and polarization angle show a wide range of morphological features. We have also used the Westerbork Synthesis Radio Telescope (WSRT) at 350 MHz to image the same region. The LOFAR and WSRT images show a similar complex morphology at comparable brightness levels, but their spatial correlation is very low. The fractional polarization at 150 MHz, expressed as a percentage of the total intensity, amounts to 1.5%. There is no indication of diffuse emission in total intensity in the interferometric data, in line with results at higher frequencies Conclusions. The wide frequency range, high angular resolution, and high sensitivity make LOFAR an exquisite instrument for studying Galactic polarized emission at a resolution of ~1-2 rad m-2 in Faraday depth. The different polarized patterns observed at 150 MHz and 350 MHz are consistent with different source distributions along the line of sight wring in a variety of Faraday thin regions of emission. The presence of polarized foregrounds is a serious complication for epoch of reionization experiments. To avoid the leakage of polarized emission into total intensity, which can depend on frequency, we need to calibrate the instrumental polarization across the field of view to a small fraction of 1%
Detection and extraction of signals from the epoch of reionization using higher-order one-point statistics
Detecting redshifted 21-cm emission from neutral hydrogen in the early Universe promises to give direct constraints on the epoch of reionization (EoR). It will, though, be very challenging to extract the cosmological signal (CS) from foregrounds and noise which are orders of magnitude larger. Fortunately, the signal has some characteristics which differentiate it from the foregrounds and noise, and we suggest that using the correct statistics may tease out signatures of reionization. We generate mock data cubes simulating the output of the Low Frequency Array (LOFAR) EoR experiment. These cubes combine realistic models for Galactic and extragalactic foregrounds and the noise with three different simulations of the CS. We fit out the foregrounds, which are smooth in the frequency direction, to produce residual images in each frequency band. We denoise these images and study the skewness of the one-point distribution in the images as a function of frequency. We find that, under sufficiently optimistic assumptions, we can recover the main features of the redshift evolution of the skewness in the 21-cm signal. We argue that some of these features ¿ such as a dip at the onset of reionization, followed by a rise towards its later stages ¿ may be generic, and give us a promising route to a statistical detection of reionization
Non-parametric foreground subtraction for 21cm epoch of reionization experiments
An obstacle to the detection of redshifted 21cm emission from the epoch of
reionization (EoR) is the presence of foregrounds which exceed the cosmological
signal in intensity by orders of magnitude. We argue that in principle it would
be better to fit the foregrounds non-parametrically - allowing the data to
determine their shape - rather than selecting some functional form in advance
and then fitting its parameters. Non-parametric fits often suffer from other
problems, however. We discuss these before suggesting a non-parametric method,
Wp smoothing, which seems to avoid some of them. After outlining the principles
of Wp smoothing we describe an algorithm used to implement it. We then apply Wp
smoothing to a synthetic data cube for the LOFAR EoR experiment. The
performance of Wp smoothing, measured by the extent to which it is able to
recover the variance of the cosmological signal and to which it avoids leakage
of power from the foregrounds, is compared to that of a parametric fit, and to
another non-parametric method (smoothing splines). We find that Wp smoothing is
superior to smoothing splines for our application, and is competitive with
parametric methods even though in the latter case we may choose the functional
form of the fit with advance knowledge of the simulated foregrounds. Finally,
we discuss how the quality of the fit is affected by the frequency resolution
and range, by the characteristics of the cosmological signal and by edge
effects.Comment: 15 pages, 12 figures; lengthened and two figures added, to match
version accepted by MNRA
Power spectrum extraction for redshifted 21-cm Epoch of Reionization experiments: the LOFAR case
One of the aims of the Low Frequency Array (LOFAR) Epoch of Reionization (EoR) project is to measure the power spectrum of variations in the intensity of redshifted 21-cm radiation from the EoR. The sensitivity with which this power spectrum can be estimated depends on the level of thermal noise and sample variance, and also on the systematic errors arising from the extraction process, in particular from the subtraction of foreground contamination. We model the extraction process using realistic simulations of the cosmological signal, the foregrounds and noise, and so estimate the sensitivity of the LOFAR EoR experiment to the redshifted 21-cm power spectrum. Detection of emission from the EoR should be possible within 360 h of observation with a single station beam. Integrating for longer, and synthesizing multiple station beams within the primary (tile) beam, then enables us to extract progressively more accurate estimates of the power at a greater range of scales and redshifts. We discuss different observational strategies which compromise between depth of observation, sky coverage and frequency coverage. A plan in which lower frequencies receive a larger fraction of the time appears to be promising. We also study the nature of the bias which foreground fitting errors induce on the inferred power spectrum and discuss how to reduce and correct for this bias. The angular and line-of-sight power spectra have different merits in this respect, and we suggest considering them separately in the analysis of LOFAR data