No Arabic abstract
We present two estimators to quantify the angular power spectrum of the sky signal directly from the visibilities measured in radio interferometric observations. This is relevant for both the foregrounds and the cosmological 21-cm signal buried therein. The discussion here is restricted to the Galactic synchrotron radiation, the most dominant foreground component after point source removal. Our theoretical analysis is validated using simulations at 150 MHz, mainly for GMRT and also briefly for LOFAR. The Bare Estimator uses pairwise correlations of the measured visibilities, while the Tapered Gridded Estimator uses the visibilities after gridding in the uv plane. The former is very precise, but computationally expensive for large data. The latter has a lower precision, but takes less computation time which is proportional to the data volume. The latter also allows tapering of the sky response leading to sidelobe suppression, an useful ingredient for foreground removal. Both estimators avoid the positive bias that arises due to the system noise. We consider amplitude and phase errors of the gain, and the w-term as possible sources of errors . We find that the estimated angular power spectrum is exponentially sensitive to the variance of the phase errors but insensitive to amplitude errors. The statistical uncertainties of the estimators are affected by both amplitude and phase errors. The w-term does not have a significant effect at the angular scales of our interest. We propose the Tapered Gridded Estimator as an effective tool to observationally quantify both foregrounds and the cosmological 21-cm signal.
Supernova remnants (SNRs) have a variety of overall morphology as well as rich structures over a wide range of scales. Quantitative study of these structures can potentially reveal fluctuations of density and magnetic field originating from the interaction with ambient medium and turbulence in the expanding ejecta. We have used $1.5$GHz (L band) and $5$GHz (C band) VLA data to estimate the angular power spectrum $C_{ell}$ of the synchrotron emission fluctuations of the Kepler SNR. This is done using the novel, visibility based, Tapered Gridded Estimator of $C_{ell}$. We have found that, for $ell = (1.9 - 6.9) times 10^{4}$, the power spectrum is a broken power law with a break at $ell = 3.3 times 10^{4}$, and power law index of $-2.84pm 0.07$ and $-4.39pm 0.04$ before and after the break respectively. The slope $-2.84$ is consistent with 2D Kolmogorov turbulence and earlier measurements for the Tycho SNR. We interpret the break to be related to the shell thickness of the SNR ($0.35 $ pc) which approximately matches $ell = 3.3 times 10^{4}$ (i.e., $0.48$ pc). However, for $ell > 6.9 times 10^{4}$, the estimated $C_{ell}$ of L band is likely to have dominant contribution from the foregrounds while for C band the power law slope $-3.07pm 0.02$ is roughly consistent with $3$D Kolmogorov turbulence like that observed at large $ell$ for Cas A and Crab SNRs.
The light-cone (LC) effect causes the mean as well as the statistical properties of the redshifted 21-cm signal $T_{rm b}(hat{bf n}, u)$ to change with frequency $ u$ (or cosmic time). Consequently, the statistical homogeneity (ergodicity) of the signal along the line of sight (LoS) direction is broken. This is a severe problem particularly during the Epoch of Reionization (EoR) when the mean neutral hydrogen fraction ($bar{x}_{rm HI}$) changes rapidly as the universe evolves. This will also pose complications for large bandwidth observations. These effects imply that the 3D power spectrum $P(k)$ fails to quantify the entire second-order statistics of the signal as it assumes the signal to be ergodic and periodic along the LoS. As a proper alternative to $P(k)$, we use the multi-frequency angular power spectrum (MAPS) ${mathcal C}_{ell}( u_1, u_2)$ which does not assume the signal to be ergodic and periodic along the LoS. Here, we study the prospects for measuring the EoR 21-cm MAPS using future observations with the upcoming SKA-Low. Ignoring any contribution from the foregrounds, we find that the EoR 21-cm MAPS can be measured at a confidence level $ge 5sigma$ at angular scales $ell sim 1300$ for total observation time $t_{rm obs} ge 128,{rm hrs}$ across $sim 44,{rm MHz}$ observational bandwidth. We also quantitatively address the effects of foregrounds on MAPS detectability forecast by avoiding signal contained within the foreground wedge in $(k_perp, k_parallel)$ plane. These results are very relevant for the upcoming large bandwidth EoR experiments as previous predictions were all restricted to individually analyzing the signal over small frequency (or equivalently redshift) intervals.
Diffuse radio emission from galaxy clusters in the form of radio halos and relics are tracers of the shocks and turbulence in the intra-cluster medium. The imprints of the physical processes that govern their origin and evolution can be found in their radio morphologies and spectra. The role of mildly relativistic population of electrons may be crucial for the acceleration mechanisms to work efficiently. Low frequency observations with telescopes that allow imaging of extended sources over a broad range of low frequencies ($< 2$ GHz) offer the best tools to study these sources. I will review the Giant Metrewave Radio Telescope (GMRT) observations in the past few years that have led to: i) statistical studies of large samples of galaxy clusters, ii) opening of the discovery space in low mass clusters and iii) tracing the spectra of seed relativistic electrons using the Upgraded GMRT.
High-resolution astronomical imaging at sub-GHz radio frequencies has been available for more than 15 years, with the VLA at 74 and 330 MHz, and the GMRT at 150, 240, 330 and 610 MHz. Recent developments include wide-bandwidth upgrades for VLA and GMRT, and commissioning of the aperture-array-based, multi-beam telescope LOFAR. A common feature of these telescopes is the necessity to deconvolve the very many detectable sources within their wide fields-of-view and beyond. This is complicated by gain variations in the radio signal path that depend on viewing direction. One such example is phase errors due to the ionosphere. Here I discuss the inner workings of SPAM, a set of AIPS-based data reduction scripts in Python that includes direction-dependent calibration and imaging. Since its first version in 2008, SPAM has been applied to many GMRT data sets at various frequencies. Many valuable lessons were learned, and translated into various SPAM software modifications. Nowadays, semi-automated SPAM data reduction recipes can be applied to almost any GMRT data set, yielding good quality continuum images comparable with (or often better than) hand-reduced results. SPAM is currently being migrated from AIPS to CASA with an extension to handle wide bandwidths. This is aimed at providing users of the VLA low-band system and the upcoming wide-bandwidth GMRT with the necessary data reduction tools.
We discuss the derivation of the analytic properties of the cross-power spectrum estimator from multi-detector CMB anisotropy maps. The method is computationally convenient and it provides unbiased estimates under very broad assumptions. We also propose a new procedure for testing for the presence of residual bias due to inappropriate noise subtraction in pseudo-$C_{ell}$ estimates. We derive the analytic behavior of this procedure under the null hypothesis, and use Monte Carlo simulations to investigate its efficiency properties, which appear very promising. For instance, for full sky maps with isotropic white noise, the test is able to identify an error of 1% on the noise amplitude estimate.