تقرير
Delensing of Cosmic Microwave Background Polarization with machine learning
| العنوان: | Delensing of Cosmic Microwave Background Polarization with machine learning |
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| المؤلفون: | Yan, Ye-Peng, Wang, Guo-Jian, Li, Si-Yu, Xia, Jun-Qing |
| سنة النشر: | 2023 |
| المجموعة: | Astrophysics |
| مصطلحات موضوعية: | Astrophysics - Cosmology and Nongalactic Astrophysics |
| الوصف: | Primordial B-mode detection is one of the main goals of next-generation cosmic microwave background (CMB) experiments. Primordial B-modes are a unique signature of primordial gravitational waves (PGWs). However, the gravitational interaction of CMB photons with large-scale structures will distort the primordial E modes, adding a lensing B-mode component to the primordial B-mode signal. Removing the lensing effect (`delensing') from observed CMB polarization maps will be necessary to improve the constraint of PGWs and obtain a primordial E-mode signal. Here, we introduce a deep convolutional neural network model named multi-input multi-output U-net (MIMO-UNet) to perform CMB delensing. The networks are trained on simulated CMB maps with size $20^{\circ} \times 20^{\circ}$. We first use MIMO-UNet to reconstruct the unlensing CMB polarization ($Q$ and $U$) maps from observed CMB maps. The recovered E-mode power spectrum exhibits excellent agreement with the primordial EE power spectrum. The recovery of the primordial B-mode power spectrum for noise levels of 0, 1, and 2 $\mu$K-arcmin is greater than 98\% at the angular scale of $\ell<150$. We additionally reconstruct the lensing B map from observed CMB maps. The recovery of the lensing B-mode power spectrum is greater than roughly 99\% at the scales of $\ell>200$. We delens observed B-mode power spectrum by subtracting reconstructed lensing B-mode spectrum. The recovery of tensor B-mode power spectrum for noise levels of 0, 1, 2 $\mu$K-arcmin is greater than 98 \% at the angular scales of $\ell<120$. Even at $\ell=160$, the recovery of tensor B-mode power spectrum is still around 71 \%. Comment: 18 pages, 14 figures, 1 table, accepted by ApJS |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.3847/1538-4365/acd2ce |
| URL الوصول: | http://arxiv.org/abs/2305.02490 |
| رقم الأكسشن: | edsarx.2305.02490 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.3847/1538-4365/acd2ce |
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