A study on the Clustering Properties of Radio-Selected sources in the Lockman Hole Region at 325 MHz

Studying the spatial distribution of extragalactic source populations is vital in understanding the matter distribution in the Universe. It also enables understanding the cosmological evolution of dark matter density fields and the relationship between dark matter and luminous matter. Clustering studies are also required for EoR foreground studies since it affects the relevant angular scales. This paper investigates the angular and spatial clustering properties and the bias parameter of radio-selected sources in the Lockman Hole field at 325 MHz. The data probes sources with fluxes $\gtrsim$0.3 mJy within a radius of 1.8$^\circ$ around the phase center of a $6^\circ \times 6^\circ$ mosaic. Based on their radio luminosity, the sources are classified into Active Galactic Nuclei (AGNs) and Star-Forming Galaxies (SFGs). Clustering and bias parameters are determined for the combined populations and the classified sources. The spatial correlation length and the bias of AGNs are greater than SFGs -- indicating that more massive haloes host the former. This study is the first reported estimate of the clustering property of sources at 325 MHz, intermediate between the preexisting studies at high and low-frequency bands. It also probes a well-studied deep field at an unexplored frequency with moderate depth and area. Clustering studies require such observations along different lines of sight, with various fields and data sets across frequencies to avoid cosmic variance and systematics. Thus, an extragalactic deep field has been studied in this work to contribute to this knowledge.Comment: 16 Pages, 10 Figures, submitted after minor revision to MNRA

Detecting the H I power spectrum in the post-reionization Universe with SKA-Low

We present a survey strategy to detect the neutral hydrogen (H i) power spectrum at 5 < z < 6 using the SKA-Low radio telescope in presence of foregrounds and instrumental effects. We simulate observations of the inherently weak HI signal post-reionization with varying levels of noise and contamination with foreground amplitudes equivalent to residuals after sky model subtraction. We find that blind signal separation methods on imaged data are required in order to recover the H i signal at large cosmological scales. Comparing different methods of foreground cleaning, we find that Gaussian Process Regression (GPR) performs better than Principle Component Analysis (PCA), with the key difference being that GPR uses smooth kernels for the total data covariance. The integration time of one field needs to be larger than ∼250 hours to provide large enough signal-to-noise ratio to accurately model the data covariance for foreground cleaning. Images within the primary beam field-of-view give measurements of the H i power spectrum at scales k ∼ 0.02 Mpc−1 − 0.3 Mpc−1 with signal-to-noise ratio ∼2 − 5 in Δ[log(k/Mpc−1)] = 0.25 bins assuming an integration time of 600 hours. Systematic effects, which introduce small-scale fluctuations across frequency channels, need to be ≲ 5 × 10−5 to enable unbiased measurements outside the foreground wedge. Our results provide an important validation towards using the SKA-Low array for measuring the H i power spectrum in the post-reionization Universe

Synthetic Observations with the Square Kilometre Array (SKA) -- development towards an end-to-end pipeline

Detection of the redshifted 21-cm signal of neutral hydrogen from the Cosmic Dawn and the Epoch of Reionization is one of the final frontiers of modern observational cosmology. The inherently faint signal makes it susceptible to contamination by several sources like astrophysical foregrounds and instrumental systematics. Nevertheless, developments achieved in the recent times will combine to make signal detection possible with the upcoming Square Kilometer Array (SKA), both statistically and via tomography. This review describes an indigenously developed end-to-end pipeline that simulates sensitive interferometric observations. It mainly focuses on the requirements for \hi detection in interferometers. In its present form, it can mimic the effects of realistic point source foregrounds and systematics- calibration error and position error on 21-cm observations. The performance of the pipeline is demonstrated for test cases with 0.01\% calibration error and position error. Its performance is consistent across telescope, foreground, and signal models. The focus of the simulation pipeline during the initial stages was for EoR science. But since this is a general interferometric simulation pipeline, it will be helpful to the entire SKA user community, irrespective of the science goals.Comment: 24 Pages, 7 Figures, Review Article to appear in Special Issue of Journal of Astrophysics and Astronomy on "Indian Participation in the SKA'', comments are welcom

Detecting galaxies in a large H{\sc i}~spectral cube

The upcoming Square Kilometer Array (SKA) is expected to produce humongous amount of data for undertaking H{\sc i}~science. We have developed an MPI-based {\sc Python} pipeline to deal with the large data efficiently with the present computational resources. Our pipeline divides such large H{\sc i}~21-cm spectral cubes into several small cubelets, and then processes them in parallel using publicly available H{\sc i}~source finder {\sc SoFiA-$2$}. The pipeline also takes care of sources at the boundaries of the cubelets and also filters out false and redundant detections. By comapring with the true source catalog, we find that the detection efficiency depends on the {\sc SoFiA-$2$} parameters such as the smoothing kernel size, linking length and threshold values. We find the optimal kernel size for all flux bins to be between $3$ to $5$ pixels and $7$ to $15$ pixels, respectively in the spatial and frequency directions. Comparing the recovered source parameters with the original values, we find that the output of {\sc SoFiA-$2$} is highly dependent on kernel sizes and a single choice of kernel is not sufficient for all types of H{\sc i}~galaxies. We also propose use of alternative methods to {\sc SoFiA-$2$} which can be used in our pipeline to find sources more robustly.Comment: 15 pages, 7 figures, Accepted for publication in the Special Issue of Journal of Astrophysics and Astronomy on "Indian Participation in the SKA'', comments are welcom