Difference between revisions of "Lensing map reconstruction from 02.00 sims w/ and w/o foreground+inhomogeneous noise"

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- The true input phi map
 
- The true input phi map
 
   /project/projectdirs/cmb/data/generic/cmb/ffp10/mc/scalar/ffp10_unlensed_scl_cmb_000_tebplm_mc_0000.fits (4th binary table)
 
   /project/projectdirs/cmb/data/generic/cmb/ffp10/mc/scalar/ffp10_unlensed_scl_cmb_000_tebplm_mc_0000.fits (4th binary table)
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 +
- The input lensed-LCDM angular power spectra (TT,TE,EE,BB)
 +
  /project/projectdirs/cmb/data/generic/cmb/ffp10/cls/ffp10_lensedCls.dat
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 +
(Note that what I actually use is the mirror of the above data at Odyssey.)
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----
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'''Method'''
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The method of the lensing reconstruction is very similar to that of BICEP2/Keck Array Results Paper VIII [[https://arxiv.org/abs/1606.01968]] (hereafter BKVIII), except the curved sky analysis.
 +
 +
I first compute the diagonal filtering to be applied to the CMB harmonic coefficients (see text around Eq.(17) of BKVIII). The T, E and B at 500<L<3000 are used for the reconstruction. The unnormalized kappa estimator is then computed (e.g., for EB, fullsky counterpart of Eq.(19) of BKVIII). The analytic fullsky normalization is computed and multiplied to the unnormalized estimator. The reconstructed kappa map is finally cross-correlated with the input kappa map.
  
  

Revision as of 07:05, 26 September 2018

Septemper 26, 2018 (Toshiya Namikawa posted)



Summary

In this posting, I show some results of the reconstruction of the CMB lensing kappa map from the signal only or signal+noise+foreground simulations. I used two quadratic estimators, TT and EB, and show that the reconstructed kappa map looks agree with the input kappa map even after including the noise and foreground. However, the reconstruction noise becomes larger at smaller scales of the reconstructed kappa. This could affect the delensing efficiency.



Data

Following [1], I use the following simulation data set:

- The high res masked lensed-LCDM single frequency map

 /project/projectdirs/cmbs4/data_xx.yy/02.00/cmbs4_02_llcdm_f145_b04_ellmin30_map_2048_mc_0000.fits

- The high res masked lensed-LCDM + noise + foreground single frequency map

 /project/projectdirs/cmbs4/data_xx.yy/02.00/cmbs4_02.00_comb_f145_b04_ellmin30_map_2048_mc_0000.fits

- Relative hits mask

 /project/projectdirs/cmbs4/expt_xx/02/rhits/n2048.fits.

- The true input phi map

 /project/projectdirs/cmb/data/generic/cmb/ffp10/mc/scalar/ffp10_unlensed_scl_cmb_000_tebplm_mc_0000.fits (4th binary table)

- The input lensed-LCDM angular power spectra (TT,TE,EE,BB)

 /project/projectdirs/cmb/data/generic/cmb/ffp10/cls/ffp10_lensedCls.dat

(Note that what I actually use is the mirror of the above data at Odyssey.)


Method

The method of the lensing reconstruction is very similar to that of BICEP2/Keck Array Results Paper VIII [[2]] (hereafter BKVIII), except the curved sky analysis.

I first compute the diagonal filtering to be applied to the CMB harmonic coefficients (see text around Eq.(17) of BKVIII). The T, E and B at 500<L<3000 are used for the reconstruction. The unnormalized kappa estimator is then computed (e.g., for EB, fullsky counterpart of Eq.(19) of BKVIII). The analytic fullsky normalization is computed and multiplied to the unnormalized estimator. The reconstructed kappa map is finally cross-correlated with the input kappa map.



Results

Fig kmap input.jpg

Fig.1: Example of the input kappa map after applying the mask. The kappa multipole at 50<L<200 is included in the fluctuations.

Fig kmap recon.jpg

Fig.2: Same as Fig.1 but for the reconstructed kappa map using EB estimator from signal+noise+foreground simulation.



Output/Usage

The input/reconstructed kappa map is currently located at

 /n/holylfs02/LABS/kovac_lab/cmbs4/nersc_mirror/cmbs4dat/reanalysis/phi_recons/02.00_namikawa_180920/kmap_inp/
 /n/holylfs02/LABS/kovac_lab/cmbs4/nersc_mirror/cmbs4dat/reanalysis/phi_recons/02.00_namikawa_180920/kmap_rec/

The file format is the fortran binary file. An example of reading the files (and showing the kappa map) is written in showkmap.py.