Primordial power spectrum: a complete analysis with the WMAP nine-year data
Dhiraj Kumar Hazra, Arman Shafieloo, Tarun Souradeep

TL;DR
This paper introduces an improved deconvolution algorithm to reconstruct the primordial power spectrum from WMAP 9-year data, achieving higher accuracy and efficiency, and revealing potential features beyond the standard power-law model.
Contribution
The authors develop a more straightforward, error-sensitive Richardson-Lucy deconvolution method applicable directly to unbinned CMB data, enabling more precise primordial spectrum reconstruction.
Findings
Achieved over 300 improvement in fit compared to power-law
Reconstructed spectrum consistent with power-law within error margins
Method capable of detecting features beyond standard models
Abstract
We have improved further the error sensitive Richardson-Lucy deconvolution algorithm making it applicable directly on the un-binned measured angular power spectrum of Cosmic Microwave Background observations to reconstruct the form of the primordial power spectrum. This improvement makes the application of the method significantly more straight forward by removing some intermediate stages of analysis allowing a reconstruction of the primordial spectrum with higher efficiency and precision and with lower computational expenses. Applying the modified algorithm we fit the WMAP 9 year data using the optimized reconstructed form of the primordial spectrum with more than 300 improvement in \chi^2 with respect to the best fit power-law. This is clearly beyond the reach of other alternative approaches and reflects the efficiency of the proposed method in the reconstruction process and allow us…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
