DELAY SPECTRUM WITH PHASE-TRACKING ARRAYS: EXTRACTING THE H i POWER SPECTRUM FROM THE EPOCH OF REIONIZATION

• Main Authors: de Oliveira Costa, Angelica (Contributor), Ewall-Wice, Aaron Michael (Contributor), Feng, Lu (Contributor), Hewitt, Jacqueline N (Contributor), Neben, Abraham Richard (Contributor), Tegmark, Max Erik (Contributor), Morgan, Eric R. (Contributor), Williams, Christopher Leigh (Contributor)
• Other Authors: Lincoln Laboratory (Contributor), Massachusetts Institute of Technology. Department of Physics (Contributor), MIT Kavli Institute for Astrophysics and Space Research (Contributor)
• Format: Article
• Language: English
• Published: IOP Publishing, 2017-04-26T18:52:34Z.
• Subjects: Article
• Online Access: Get fulltext

 The detection of redshifted 21 cm emission from the epoch of reionization (EoR) is a challenging task owing to strong foregrounds that dominate the signal. In this paper, we propose a general method, based on the delay spectrum approach, to extract H i power spectra that are applicable to tracking observations using an imaging radio interferometer ("Delay Spectrum with Imaging Arrays"). Our method is based on modeling the H i signal taking into account the impact of wide field effects such as the w-term, which are then used as appropriate weights in cross-correlating the measured visibilities. Our method is applicable to any radio interferometer that tracks a phase center and could be utilized for arrays such as the Murchison Widefield Array (MWA), Low Frequency Array (LOFAR), Giant Meterwave Radio Telescope (GMRT), Donald C. Backer Precision Array for Probing the Epoch of Reionization (PAPER), and HERA. In the literature the delay spectrum approach has been implemented for near-redundant baselines using drift scan observations. In this paper we explore the scheme for non-redundant tracking arrays. This is the first application of delay spectrum methodology to such data to extract the H i signal. We analyze 3 hr of MWA tracking data on the EoR1 field. We present both two-dimensional (k[subscript ∥],k[subscript ⊥]) and one-dimensional (k) power spectra from the analysis. Our results are in agreement with the findings of other pipelines developed to analyze the MWA EoR data.