Application of Neural Networks and Machine Learning in CMB data analysis

Farida Farsian

Alma Mater Studiorum – Università di Bologna

 

Abstract:  In the next decade, Primordial Gravitation Waves detection as a CMB B-mode polarization source will play an important role in leading the CMB experiments and constraining inflationary models. To reach this detection, CMB foregrounds seem to be the most challenging problem.

On the other hand, the application of Neural Networks and Machine Learning (ML) in general, as computational tools, expands exponentially in the scientific fields. With their unique computational power, these methods can become a very helpful implement in solving the computational challenges in Cosmology and specifically in the CMB field.

In this talk, at first, I will quickly review the ML methods and then introduce new applications of NNs in the CMB data analysis that we recently developed. We will see that the implemented methods gain advantages in terms of accuracy and efficiency compared to traditional methods.

یکشنبه 12 بهمن 1399، ساعت 19:00

Sunday 31 January 2021 – 19:00 Tehran Time

اتاق سمینار مجازی –Virtual Seminar Room

https://vc.sharif.edu/ch/cosmology

گزینه ورود به صورت مهمان – Enter as a Guest