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Analysis of 21-cm tomographic data

Published online by Cambridge University Press:  08 May 2018

Garrelt Mellema ,
Sambit Giri Open the ORCID record for Sambit Giri [Opens in a new window]  and
Raghunath Ghara
Garrelt Mellema
Affiliation:
Department of astronomy and Oskar Klein Centre, AlbaNova, Stockholm University, SE-10691 Stockholm, Sweden email: [email protected], [email protected], [email protected]
Sambit Giri
Affiliation:
Department of astronomy and Oskar Klein Centre, AlbaNova, Stockholm University, SE-10691 Stockholm, Sweden email: [email protected], [email protected], [email protected]
Raghunath Ghara
Affiliation:
Department of astronomy and Oskar Klein Centre, AlbaNova, Stockholm University, SE-10691 Stockholm, Sweden email: [email protected], [email protected], [email protected]
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Abstract

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The future SKA1-Low radio telescope will be powerful enough to produce tomographic images of the 21-cm signal from the Epoch of Reionization. Here we address how to identify ionized regions in such data sets, taking into account the resolution and noise levels associated with SKA1-Low. We describe three methods of which one, superpixel oversegmentation, consistently performs best.

Keywords

techniques: image processinginterferometric(cosmology:) diffuse radiationintergalactic mediumradio lines: general
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S333: Peering towards Cosmic Dawn , October 2017 , pp. 26 - 29
Copyright
Copyright © International Astronomical Union 2018 

References

Achanta, Radhakrishna, Shaji, Appu, Smith, Kevin, Lucchi, Aurelien, Fua, Pascal, & Süsstrunk, Sabine. Slic superpixels compared to state-of-the-art superpixel methods. IEEE transactions on pattern analysis and machine intelligence, 34 (11): 2274–2282, 2012.Google Scholar
Friedrich, M. M., Mellema, G., Alvarez, M. A., Shapiro, P. R., & Iliev, I. T.. Topology and sizes of H II regions during cosmic reionization. MNRAS, 413: 1353–1372, May 2011.Google Scholar
Sambit, K. Giri, Mellema, Garrelt, Dixon, Keri L., & Iliev, Ilian T.. Bubble size statistics during reionization from 21-cm tomography. MNRAS, 473 (3): 2949–2964, 2018a. URL + http://dx.doi.org/10.1093/mnras/stx2539.Google Scholar
Sambit, K. Giri, Mellema, Garrelt, & Ghara, Raghunath. Optimal identification of hii regions during reionization in 21-cm observations. ArXiv, 1801.06550, 2018b.Google Scholar
Kakiichi, K., Majumdar, S., Mellema, G., Ciardi, B., Dixon, K. L., Iliev, I. T., Jelić, V., Koopmans, L. V. E., Zaroubi, S., & Busch, P.. Recovering the H II region size statistics from 21-cm tomography. MNRAS, 471: 1936–1954, October 2017.Google Scholar
Mellema, G., Iliev, I. T., Pen, U.-L., & Shapiro, P. R.. Simulating cosmic reionization at large scales - II. The 21-cm emission features and statistical signals. MNRAS, 372: 679–692, October 2006.Google Scholar
Mellema, G., Koopmans, L., Shukla, H., Datta, K. K., Mesinger, A., & Majumdar, S.. HI tomographic imaging of the Cosmic Dawn and Epoch of Reionization with SKA. Advancing Astrophysics with the Square Kilometre Array (AASKA14), art. 10, April 2015.CrossRefGoogle Scholar
Wyithe, S., Geil, P., & Kim, H.. Imaging HII Regions from Galaxies and Quasars During Reionisation with SKA. Advancing Astrophysics with the Square Kilometre Array (AASKA14), art. 15, April 2015.CrossRefGoogle Scholar