Using artificial neural networks to extract the 21-cm global signal from the EDGES data. Issue 2 (22nd January 2021)
- Record Type:
- Journal Article
- Title:
- Using artificial neural networks to extract the 21-cm global signal from the EDGES data. Issue 2 (22nd January 2021)
- Main Title:
- Using artificial neural networks to extract the 21-cm global signal from the EDGES data
- Authors:
- Choudhury, Madhurima
Chatterjee, Atrideb
Datta, Abhirup
Choudhury, Tirthankar Roy - Abstract:
- 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 extragalactic 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 match the amplitude of the Experiment to Detect the Global EoR Signature (EDGES) 21-cm signal. First, we have used an artificial neural network (ANN) to extract the astrophysical parameters from these simulated data sets. 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 R 2 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 EDGES data as the input. We find that the reconstructed signal closely mimics the amplitude of the reported detection. The recovered parametersABSTRACT: 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 extragalactic 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 match the amplitude of the Experiment to Detect the Global EoR Signature (EDGES) 21-cm signal. First, we have used an artificial neural network (ANN) to extract the astrophysical parameters from these simulated data sets. 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 R 2 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 EDGES data 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. … (more)
- Is Part Of:
- Monthly notices of the Royal Astronomical Society. Volume 502:Issue 2(2021)
- Journal:
- Monthly notices of the Royal Astronomical Society
- Issue:
- Volume 502:Issue 2(2021)
- Issue Display:
- Volume 502, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 502
- Issue:
- 2
- Issue Sort Value:
- 2021-0502-0002-0000
- Page Start:
- 2815
- Page End:
- 2825
- Publication Date:
- 2021-01-22
- Subjects:
- methods: numerical -- methods: statistical -- dark ages, reionization, first stars -- cosmology: observations -- cosmology: theory
Astronomy -- Periodicals
Periodicals
520.5 - Journal URLs:
- http://mnras.oxfordjournals.org/ ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2966 ↗
http://www.blackwell-synergy.com/issuelist.asp?journal=mnr ↗
http://www.blackwell-synergy.com/loi/mnr ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/mnras/stab180 ↗
- Languages:
- English
- ISSNs:
- 0035-8711
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5943.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24966.xml