5 citations · 13 across the 11 of their papers we have counts for
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Exploring Machine Learning Regression Models for Advancing Foreground Mitigation and Global 21cm Signal Parameter Extraction
Anshuman Tripathi, Abhirup Datta, Gursharanjit Kaur
Extracting parameters from the global 21cm signal is crucial for understanding the early Universe. However, detecting the 21cm signal is challenging due to the brighter foreground…
Mitigating gain calibration errors from EoR observations with SKA1-Low AA*
Eeshan Beohar, Abhirup Datta, Anshuman Tripathi +2
The observations of the redshifted 21-cm signal from neutral hydrogen are a promising probe for understanding the Cosmic Dawn and the Epoch of Reionisation (EoR). One of the primar…
Interpreting the HI 21-cm cosmology maps through Largest Cluster Statistics. Part II. Impact of the realistic foreground and instrumental noise on synthetic SKA1-Low observations
Samit Kumar Pal, Saswata Dasgupta, Abhirup Datta +3
The Largest Cluster Statistics\,(LCS) analysis of the redshifted 21\,cm maps has been demonstrated to be an efficient and robust method for following the time evolution of the larg…
Impact of Calibration and Position Errors on Astrophysical Parameters of the HI 21cm Signal
Anshuman Tripathi, Abhirup Datta, Aishrila Mazumder +1
The Epoch of Reionization (EoR) and Cosmic Dawn (CD) are pivotal stages during the first billion years of the universe, exerting a significant influence on the development of cosmi…