Abstract Details

Name: Madhurima Choudhury
Affiliation: Indian Institute of Technology Indore
Conference ID: ASI2021_486
Title : Extracting the 21cm signal using artificial neural networks
Authors and Co-Authors : Madhurima Choudhury, IIT Indore
Abstract Type : Poster
Abstract Category : General Relativity and Cosmology
Abstract : The redshifted 21-cm signal of neutral Hydrogen is a promising probe into the period of evolution of our Universe when the first stars were formed (Cosmic Dawn), to the period where the entire Universe changed its state from being completely neutral to completely ionized (Reionization). The most striking feature of this line of neutral Hydrogen is that it can be observed across an entire frequency range as a sky-averaged continuous signature, or its fluctuations can be measured using an interferometer. However, the 21-cm signal is very faint and is dominated by a much brighter Galactic and extra-galactic foregrounds, making it an observational challenge. We have used different physical models to simulate various realizations of the 21-cm Global signals, including an excess radio background to mimic the amplitude of the EDGES 21-cm signal. First, we have used an artificial neural network (ANN) to extract the astrophysical parameters from these simulated datasets. Then, mock observations were generated by adding a physically motivated foreground model and an ANN was used to extract the astrophysical parameters from such data. The R2 score of our predictions from the mock-observations is in the range of 0.65-0.89. We have used this ANN to predict the signal parameters giving the total observed sky temperature of the EDGES detection, as the input. We find that the reconstructed signal closely mimics the amplitude of the reported detection. The recovered parameters can be used to infer the physical state of the gas at high redshifts. We also present some constraints on the astrophysical parameters from simulated 21-cm PS experiments.