2018
DOI: 10.1093/mnras/sty1786
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Optimal identification of H ii regions during reionization in 21-cm observations

Abstract: The ability of the future low frequency component of the Square Kilometre Array radio telescope (SKA-Low) to produce tomographic images of the redshifted 21-cm signal will enable direct studies of the evolution of the sizes and shapes of ionized regions during the Epoch of Reionization. However, a reliable identification of ionized regions in noisy interferometric data is not trivial. Here, we introduce an image processing method known as superpixels for this purpose. We compare this method with two other prev… Show more

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Cited by 62 publications
(54 citation statements)
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“…In Giri et al (2018b), we presented a method to identify the ionized region in noisy 21-cm observation during the EoR, called superpixels. Below we briefly describe the procedure to create the superpixels and the criteria used to identify superpixels containing ionized regions.…”
Section: Structure Identificationmentioning
confidence: 99%
“…In Giri et al (2018b), we presented a method to identify the ionized region in noisy 21-cm observation during the EoR, called superpixels. Below we briefly describe the procedure to create the superpixels and the criteria used to identify superpixels containing ionized regions.…”
Section: Structure Identificationmentioning
confidence: 99%
“…(12) In order to enhance the convergence of MCMC chains, we set the amplitudes of all the independent peaks in the power spectrum equal to the maximum amplitude and set the amplitudes of combination frequencies and noise to be zero. Since the peaks are generally clustered into groups, we analysed them with a 1-D k-means clustering algorithm (MacQueen 1967;Wu 2010), which is a common and powerful clustering algorithm used in unsupervised machine learning (see two applications in Giri et al 2018;Rahmani et al 2018). We used six frequency groups and in each group we included the pattern around the highest peak if the number of independent frequencies within the group was larger than four, since there are three free parameters in Equ 8 (P0, ∆P0, and Σ).…”
Section: Cross-correlation and Mcmcmentioning
confidence: 99%
“…We follow the method given in Ghara et al (2017) and Giri et al (2018) to simulate the expected noise from the first generation of SKA-Low (hereafter SKA1-Low). Even though the construction of SKA1-Low has not started, the distribution of antennae is being planned.…”
Section: Telescope Noisementioning
confidence: 99%