7 citations · 15 across the 5 of their papers we have counts for
5 papers
Accurate and Unbiased Reconstruction of CMB B Mode using Deep Learning
Srikanta Pal, Sarvesh Kumar Yadav, Rajib Saha +1
An ingeniously designed autoencoder (PrimeNet) using simulated observations of future generation ECHO satellite mission recovers CMB B mode map, angular spectrum for multipoles $\e…
ParamANN: A Neural Network to Estimate Cosmological Parameters for CDM Universe Using Hubble Measurements
Srikanta Pal, Rajib Saha
In this article, we employ a machine learning (ML) approach for the estimations of four fundamental parameters, namely, the Hubble constant (), matter (), curvature ($…
Reconstruction of full sky CMB and modes spectra removing -to- leakage from partial sky using deep learning
Srikanta Pal, Rajib Saha
Incomplete sky analysis of cosmic microwave background (CMB) polarization spectra poses a major problem of leakage between - and -modes. We present a machine learning approac…
On Direct Estimation of Density Parameters and Hubble Constant for CDM Universe using Hubble Measurements
Srikanta Pal, Rajib Saha
The set of cosmological density parameters (, , ) and Hubble constant () are useful for fundamental understanding of…
Estimation of Full Sky Power Spectrum between Intermediate to Large Angular Scales from Partial Sky CMB Anisotropies using Artificial Neural Network
Srikanta Pal, Pallav Chanda, Rajib Saha
Reliable extraction of cosmological information from observed cosmic microwave background (CMB) maps may require removal of strongly foreground contaminated regions from the analys…