On the Non-Gaussianity Observed in the COBE-DMR Sky Maps

In this paper we pursue the origin of the non-Gaussianity determined by a bispectrum analysis of the COBE-DMR 4-year sky maps. The robustness of the statistic is demonstrated by the rebinning of the data into 12 coordinate systems. By computing the bispectrum statistic as a function of various data partitions - by channel, frequency, and time interval, we show that the observed non-Gaussian signal is driven by the 53 GHz data. This frequency dependence strongly rejects the hypothesis that the signal is cosmological in origin. A jack-knife analysis of the coadded 53 and 90 GHz sky maps reveals those sky pixels to which the bispectrum statistic is particularly sensitive. We find that by removing data from the 53 GHz sky maps for periods of time during which a known systematic effect perturbs the 31 GHz channels, the amplitudes of the bispectrum coefficients become completely consistent with that expected for a Gaussian sky. We conclude that the non-Gaussian signal detected by the normalised bispectrum statistic in the publicly available DMR sky maps is due to a systematic artifact. The impact of removing the affected data on estimates of the normalisation of simple models of cosmological anisotropy is negligible.Comment: 14 pages, plus 8 Postscript and 3 GIF figures. LaTeX2e document using AASTeX v5.0 macros. Revised version accepted for publication in the Astrophysical Journal: small changes to the text, minor modifications to figures 1 and

Can We Detect the Anisotropic Shapes of Quasar HII Regions During Reionization Through The Small-Scale Redshifted 21cm Power Spectrum?

Light travel time delays distort the apparent shapes of HII regions surrounding bright quasars during early stages of cosmic reionization. Individual HII regions may remain undetectable in forthcoming redshifted 21 cm experiments. However, the systematic deformation along the line of sight may be detectable statistically, either by stacking tomographic 21cm images of quasars identified, for example, by JWST, or as small-scale anisotropy in the three-dimensional 21cm power spectrum. Here we consider the detectability of this effect. The anisotropy is largest when HII regions are large and expand rapidly, and we find that if bright quasars contributed to the early stages of reionization, then they can produce significant anisotropy, on scales comparable to the typical sizes of HII regions of the bright quasars (approx. 30 Mpc and below). The effect therefore cannot be ignored when analyzing future 21cm power spectra on small scales. If 10 percent of the volume of the IGM at redshift z=10 is ionized by quasars with typical ionizing luminosity of S= 5 x 10^{56} photons/second, the distortions can enhance by more than 10 percent the 21cm power spectrum in the radial (redshift) direction, relative to the transverse directions. The level of this anisotropy exceeds that due to redshift-space distortion, and has the opposite sign. We show that on-going experiments such as MWA should be able to detect this effect. A detection would reveal the presence of bright quasars, and shed light on the ionizing yield and age of the ionizing sources, and the distribution and small-scale clumping of neutral intergalactic gas in their vicinity.Comment: Version accepted by ApJ, with new fiducial model and improved discussio

Radiation from early black holes - I. Effects on the neutral intergalactic medium

In the pre-reionization Universe, the regions of the intergalactic medium (IGM) which are far from luminous sources are the last to undergo reionization. Until then, they should be scarcely affected by stellar radiation; instead, the X-ray emission from an early black hole (BH) population can have much larger influence. We investigate the effects of such emission, looking at a number of BH model populations (differing for the cosmological density evolution of BHs, the BH properties, and the spectral energy distribution of the BH emission). We find that BH radiation can easily heat the IGM to 103-104K, while achieving partial ionization. The most interesting consequence of this heating is that BHs are expected to induce a 21-cm signal (δTb∼ 20-30 mK at z≲ 12) which should be observable with forthcoming experiments (e.g. LOFAR). We also find that at z≲ 10 BH emission strongly increases the critical mass separating star-forming and non-star-forming haloe

Wiener Reconstruction of Large-Scale Structure from Peculiar Velocities

We present an alternative, Bayesian method for large-scale reconstruction from observed peculiar velocity data. The method stresses a rigorous treatment of the random errors and it allows extrapolation into poorly sampled regions in real space or in k-space. A likelihood analysis is used to determine the fluctuation power spectrum, followed by a Wiener Filter (WF) analysis to obtain the minimum-variance mean fields of velocity and mass density. Constrained Realizations (CR) are then used to sample the statistical scatter about the WF mean field. The WF/CR method is applied as a demonstration to the Mark III data with 1200 km/s, 900 km/s, and 500 km/s resolutions. The main reconstructed structures are consistent with those extracted by the POTENT method. A comparison with the structures in the distribution of IRAS 1.2Jy galaxies yields a general agreement. The reconstructed velocity field is decomposed into its divergent and tidal components relative to a cube of +/-8000 km/s centered on the Local Group. The divergent component is very similar to the velocity field predicted from the distribution of IRAS galaxies. The tidal component is dominated by a bulk flow of 194 +/- 32 km/s towards the general direction of the Shapley concentration, and it also indicates a significant quadrupole.Comment: 28 pages and 8 GIF figures, Latex (aasms4.sty), submitted to ApJ. Postscript version of the figures can be obtained by anonymous ftp from: ftp://alf.huji.ac.il/pub/saleem

Post-correlation radio frequency interference classification methods

We describe and compare several post-correlation radio frequency interference classification methods. As data sizes of observations grow with new and improved telescopes, the need for completely automated, robust methods for radio frequency interference mitigation is pressing. We investigated several classification methods and find that, for the data sets we used, the most accurate among them is the SumThreshold method. This is a new method formed from a combination of existing techniques, including a new way of thresholding. This iterative method estimates the astronomical signal by carrying out a surface fit in the time-frequency plane. With a theoretical accuracy of 95% recognition and an approximately 0.1% false probability rate in simple simulated cases, the method is in practice as good as the human eye in finding RFI. In addition it is fast, robust, does not need a data model before it can be executed and works in almost all configurations with its default parameters. The method has been compared using simulated data with several other mitigation techniques, including one based upon the singular value decomposition of the time-frequency matrix, and has shown better results than the rest.Comment: 14 pages, 12 figures (11 in colour). The software that was used in the article can be downloaded from http://www.astro.rug.nl/rfi-software

Post-correlation filtering techniques for off-axis source and RFI removal

Techniques to improve the data quality of interferometric radio observations are considered. Fundaments of fringe frequencies in the uv-plane are discussed and filters are used to attenuate radio-frequency interference (RFI) and off-axis sources. Several new applications of filters are introduced and tested. A low-pass filter in time and frequency direction on single baseline data is successfully used to lower the noise in the area of interest and to remove sidelobes coming from unmodelled off-axis sources and RFI. Related side effects of data integration, averaging and gridding are analysed, and shown to be able to cause ghosts and an increase in noise, especially when using long baselines or interferometric elements that have a large field of view. A novel projected fringe low-pass filter is shown to be potentially useful for first order source separation. Initial tests show that the filters can be several factors faster compared to common source separation techniques such as peeling and a variant of peeling that is currently being tested on LOFAR observations called "demixed peeling". Further testing is required to support the performance of the filters.Comment: 18 pages, 20 figures, accepted for publication in MNRA

Unbiased Reconstruction of the Large Scale Structure

We present a new Unbiased Minimal Variance (UMV) estimator for the purpose of reconstructing the large--scale structure of the universe from noisy, sparse and incomplete data. Similar to the Wiener Filter (WF), the UMV estimator is derived by requiring the linear minimal variance solution given the data and an assumed prior model specifying the underlying field covariance matrix. However, unlike the WF, the minimization is carried out with the added constraint of an unbiased reconstructed mean field. The new estimator does not necessitate a noise model to estimate the underlying field; however, such a model is required for evaluating the errors at each point in space. The general application of the UMV estimator is to predict the values of the reconstructed field in un-sampled regions of space (e.g., interpolation in the unobserved Zone of Avoidance), and to dynamically transform from one measured field to another (e.g., inversion of radial peculiar velocities to over-densities). Here, we provide two very simple applications of the method. The first, is to recover a 1D signal from noisy, convolved data with gaps, e.g., CMB time-ordered data. The second application is a reconstruction of the density and 3D peculiar velocity fields from mock SEcat galaxy peculiar velocity catalogs.Comment: Revised version with new section and figures. To appear in MNRA

Wiener Reconstruction of The Large Scale Structure

The formalism of Wiener filtering is developed here for the purpose of reconstructing the large scale structure of the universe from noisy, sparse and incomplete data. The method is based on a linear minimum variance solution, given data and an assumed \prior model which specifies the covariance matrix of the field to be reconstructed. While earlier applications of the Wiener filter have focused on estimation, namely suppressing the noise in the measured quantities, we extend the method here to perform both prediction and dynamical reconstruction. The Wiener filter is used to predict the values of unmeasured quantities, such as the density field in un-sampled regions of space, or to deconvolve blurred data. The method is developed, within the context of linear gravitational instability theory, to perform dynamical reconstruction of one field which is dynamically related to some other observed field. This is the case, for example, in the reconstruction of the real space galaxy distribution from its redshift distribution When the field to be reconstructed is a Gaussian random field, such as the primordial perturbation field predicted by the canonical model of cosmology, the Wiener filter can be pushed to its fullest potential. In such a case the Wiener estimator coincides with the Bayesian estimator designed to maximize the {\it posterior} probability. The Wiener filter can be also derived by assuming a quadratic regularization function, in analogy with the `Maximum Entropy' method. The mean field obtained by the minimal variance solution can be supplemented with constrained realizations of the Gaussian field toComment: submitted to ApJ, 45 pages, 7 figures, compressed and uuencoded Postscript file. (zhfl