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Foreground Subtraction and Signal reconstruction in redshifted 21cm Global Signal Experiments using Artificial Neural Networks

Published online by Cambridge University Press:  08 May 2018

Madhurima Choudhury
Affiliation:
Indian Institute of Technology, Indore Simrol, Khandwa Road, Indore, M.P., India email: abhirup.datta@iiti.ac.in
Abhirup Datta
Affiliation:
Indian Institute of Technology, Indore Simrol, Khandwa Road, Indore, M.P., India email: abhirup.datta@iiti.ac.in
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Abstract

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Observations of HI 21cm transition line is a promising probe into the Dark Ages and Epoch-of-Reionization. Detection of this redshifted 21cm signal is one of the key science goal for several upcoming low-frequency radio telescopes like HERA, SKA and DARE. Other global signal experiments include EDGES, LEDA, BIGHORNS, SCI-HI, SARAS. One of the major challenges for the detection of this signal is the accuracy of the foreground source removal. Several novel techniques have been explored already to remove bright foregrounds from both interferometric as well as total power experiments. Here, we present preliminary results from our investigation on application of ANN to detect 21cm global signal amidst bright galactic foreground. Following the formalism of representing the global 21cm signal by ’tanh’ model, this study finds that the global 21cm signal parameters can be accurately determined even in the presence of bright foregrounds represented by 3rd order log-polynomial or higher.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2018 

References

Furlanetto, S. R., Oh, S. P. & Briggs, F. H. Cosmology at low frequencies: The 21 cm transition and the high-redshift Universe. Phys. Rep., 433: 181301, October 2006.Google Scholar
Barkana, R. & Loeb, A. A Method for Separating the Physics from the Astrophysics of High-Redshift 21 Centimeter Fluctuations. ApJL, 624: L65L68, May 2005.Google Scholar
Harker, G. J. A. Selection between foreground models for global 21-cm experiments. MNRAS, 449: L21L25, April 2015.Google Scholar
Pritchard, J., Ichiki, K., Mesinger, A., Metcalf, R. B., Pourtsidou, A., Santos, M., Abdalla, F. B., Chang, T. C., Chen, X., Weller, J. & Zaroubi, S. Cosmology from EoR/Cosmic Dawn with the SKA. Advancing Astrophysics with the Square Kilometre Array (AASKA14), art. 12, April 2015.Google Scholar
Shimabukuro, H. & Semelin, B. Analysing the 21 cm signal from the epoch of reionization with artificial neural networks. MNRAS, 468: 38693877, July 2017.Google Scholar
Mirocha, J., Harker, G. J. A. & Burns, J. O. Interpreting the Global 21-cm Signal from High Redshifts. II. Parameter Estimation for Models of Galaxy Formation. ApJ, 813: 11, November 2015.Google Scholar
Kingma, D. P. & Ba, J. Adam: A Method for Stochastic Optimization. ArXiv e-prints, December 2014.Google Scholar