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Investigating blind and artificial neural network-based methods to reconstruct the faint CMB B-modes

Implementing Organization

Raman Research Institute, Karnataka
Principal Investigator
Dr. Sarvesh Kumar Yadav
Raman Research Institute, Karnataka

About

Accurate CMB polarization measurements are crucial in observational cosmology, as they constrain neutrino physics, reionization, primordial fluctuations, and dark matter annihilation. The CMB polarization curl component (B-modes) measurement offers a unique window to probe the early universe. Several new space-based CMB mission proposals are under consideration, including ECHO (CMB Bharat), PICO, PIXIE, and LiteBIRD satellite concepts, which aim to measure CMB B-modes at r less than 10^−3 small level. To improve the method for future CMB missions, researchers propose investigating bias or more significant uncertainty due to complex foreground models. They also propose performing analysis on the partial sky with intricate foreground models for optimal performance. To minimize reconstruction errors due to inefficient performance using more realistic foregrounds, a supervised deep-learning regression technique can be employed to learn the reconstruction errors in various scenarios. To generate Monte Carlo simulations with diverse frameworks, foreground models, tensor to scalar ratios, and noise levels in each input frequency channel can be varied. This investigation is necessary to develop methods to reconstruct the weak CMB B-mode signal and determine the parameter r accurately for upcoming satellite and ground-based CMB experiments. The proposed investigation can significantly contribute to current and future CMB data analysis techniques.
Funding Organization
Funding Organization
Science and Engineering Research Board (SERB), New Delhi
Anusandhan National Research Foundation (ANRF)
Quick Information
Area of Research
Physical Sciences
Start Year
2022
End Year
2024
Status
Completed
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
N/A
Startup (If Any)
00
No. of Patents
Filed :01
Grant :00
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