Vibor Jelić

Foreground simulations for the LOFAR - Epoch of Reionization Experiment

Future high-redshift 21-cm experiments will suffer from a high degree of contamination, due both to astrophysical foregrounds and to non-astrophysical and instrumental effects. In order to reliably extract the cosmological signal from the observed data, it is essential to understand very well all data components and their influence on the extracted signal. Here we present simulated astrophysical foregrounds data cubes and discuss their possible statistical effects on the data. The foreground maps are produced assuming 5 degrees x 5 degrees windows that match those expected to be observed by the LOFAR epoch of reionization (EoR) key science project. We show that with the expected LOFAR-EoR sky and receiver noise levels, which amount to approximate to 52 mK at 150 MHz after 400 h of total observing time, a simple polynomial fit allows a statistical reconstruction of the signal. We also show that the polynomial fitting will work for maps with realistic yet idealized instrument response, i.e. a response that includes only a uniform uv coverage as a function of frequency and ignores many other uncertainties. Polarized Galactic synchrotron maps that include internal polarization and a number of Faraday screens along the line of sight are also simulated. The importance of these stems from the fact that the LOFAR instrument, in common with all current interferometric EoR experiments, has an instrumentally polarized response.

Reionization and the Cosmic Dawn with the Square Kilometre Array

The Square Kilometre Array (SKA) will have a low frequency component (SKA-low) which has as one of its main science goals the study of the redshifted 21 cm line from the earliest phases of star and galaxy formation in the Universe. This 21 cm signal provides a new and unique window both on the time of the formation of the first stars and accreting black holes and the subsequent period of substantial ionization of the intergalactic medium. The signal will teach us fundamental new things about the earliest phases of structure formation, cosmology and even has the potential to lead to the discovery of new physical phenomena. Here we present a white paper with an overview of the science questions that SKA-low can address, how we plan to tackle these questions and what this implies for the basic design of the telescope.

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.

Fast large‐scale reionization simulations

We present an efficient method to generate large simulations of the epoch of reionization without the need for a full three-dimensional radiative transfer code. Large dark-matter-only simulations are post-processed to produce maps of the redshifted 21-cm 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 one-dimensional 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, three-dimensional radiative transfer simulations and find excellent agreement for the redshifts and the spatial scales of interest to upcoming 21-cm 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 Low Frequency Array (LOFAR) beam response and its effects are analysed and quantified. Statistics performed on this mock data set shed light on possible observational strategies for LOFAR.

Foreground Removal using FastICA: A Showcase of LOFAR-EoR

We introduce a new implementation of the fastica algorithm on simulated Low Frequency Array Epoch of Reionization data with the aim of accurately removing the foregrounds and extracting the 21-cm reionization signal. We find that the method successfully removes the foregrounds with an average fitting error of 0.5 per cent and that the 2D and 3D power spectra are recovered across the frequency range. We find that for scales above several point spread function scales, the 21-cm variance is successfully recovered though there is evidence of noise leakage into the reconstructed foreground components. We find that this blind independent component analysis technique provides encouraging results without the danger of prior foreground assumptions.

Realistic simulations of the Galactic polarized foreground: consequences for 21-cm reionization detection experiments

Experiments designed to measure the redshifted 21-cm line from the epoch of reionization (EoR) are challenged by strong astrophysical foreground contamination, ionospheric distortions, complex instrumental response and other different types of noise (e.g. radio frequency interference). The astrophysical foregrounds are dominated by diffuse synchrotron emission from our Galaxy. Here we present a simulation of the Galactic emission used as a foreground module for the Low Frequency Array (LOFAR)-EoR key science project end-to-end simulations. The simulation produces total and polarized intensity over 10 degrees x 10 degrees maps of the Galactic synchrotron and free-free emission, including all observed characteristics of the emission: spatial fluctuations of amplitude and spectral index of the synchrotron emission, together with Faraday rotation effects. The importance of these simulations arises from the fact that the Galactic polarized emission could behave in a manner similar to the EoR signal along the frequency direction. As a consequence, an improper instrumental calibration will give rise to leakages of the polarized to the total signal and mask the desired EoR signal. In this paper, we address this for the first time through realistic simulations.

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.

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.

Upper Limits on the 21 cm Epoch of Reionization Power Spectrum from One Night with LOFAR

We present the first limits on the Epoch of Reionization 21 cm H I power spectra, in the redshift range z = 7.9–10.6, using the Low-Frequency Array (LOFAR) High-Band Antenna (HBA). In total, 13.0 hr of data were used from observations centered on the North Celestial Pole. After subtraction of the sky model and the noise bias, we detect a non-zero Δ^2_I = (56 ± 13 mK)^2 (1-σ) excess variance and a best 2-σ upper limit of Δ^2_(21) < (79.6 mK)^2 at k = 0.053 h cMpc^(−1) in the range z = 9.6–10.6. The excess variance decreases when optimizing the smoothness of the direction- and frequency-dependent gain calibration, and with increasing the completeness of the sky model. It is likely caused by (i) residual side-lobe noise on calibration baselines, (ii) leverage due to nonlinear effects, (iii) noise and ionosphere-induced gain errors, or a combination thereof. Further analyses of the excess variance will be discussed in forthcoming publications.

The Scale of the Problem : Recovering Images of Reionization with GMCA

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.