Difference between revisions of "Lensing reconstructions 02.00"
| Line 5: | Line 5: | ||
There are 6 type of maps, labeled with | There are 6 type of maps, labeled with | ||
| − | sim_ptt_????_lmax3000.fits | + | *sim_ptt_????_lmax3000.fits |
| − | + | lensing map from temperature only, simulation index ???? 0000 to 0099 | |
| − | sim_p_p_????_lmax3000.fits | + | *sim_p_p_????_lmax3000.fits |
| − | + | lensing map from polarization only | |
| − | sim_p_????_lmax3000.fits | + | *sim_p_????_lmax3000.fits |
| − | + | lensing map from temperature and polarization (MV) | |
| − | sim_xtt_????_lmax3000.fits | + | *sim_xtt_????_lmax3000.fits |
| − | + | lensing curl map from temperature, useful for null tests | |
| − | sim_x_p_????_lmax3000.fits | + | *sim_x_p_????_lmax3000.fits |
| − | + | lensing curl map from polarization | |
| − | sim_x_????_lmax3000.fits | + | *sim_x_????_lmax3000.fits |
| + | lensing curl from temperature and polarization (MV) | ||
The maps were built using the quadratic estimator implementation described [https://arxiv.org/abs/1807.06210 in the 2018 CMB lensing paper], | The maps were built using the quadratic estimator implementation described [https://arxiv.org/abs/1807.06210 in the 2018 CMB lensing paper], | ||
| − | with the exception of the filtering, which is isotropic after application of a slightly apodized mask. | + | with the exception of the filtering, which is isotropic after application of a slightly apodized mask. |
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
For illustration, the temperature (TT), polarization (PP) and Minimum Variance (MV) Wiener-filtered displacement reconstructions, together with the input, for realization 99: | For illustration, the temperature (TT), polarization (PP) and Minimum Variance (MV) Wiener-filtered displacement reconstructions, together with the input, for realization 99: | ||
| Line 29: | Line 25: | ||
[[File:recmaps_cmbs4_apo.png]] | [[File:recmaps_cmbs4_apo.png]] | ||
== Reconstruction parameters == | == Reconstruction parameters == | ||
| + | |||
| + | * CMB multipoles from 200 to 3000 | ||
| + | * Analysis mask: fmask.fits in same folder | ||
| + | * Gaussian beam of 4 arcmin FWHM | ||
| + | * Flat noise of 1.5 and 2.12 muK-arcmin | ||
| + | * FFP10 fiducial lensing spectra | ||
| + | * Separate temperature and polarization filtering | ||
== Fidelity to the input == | == Fidelity to the input == | ||
| − | The cross-correlation correlation to the input maps, as calculated across the entire patch is | + | |
| + | The cross-correlation correlation to the input maps, as calculated across the entire patch is like this: | ||
[[File:cmbs4rho.png]] | [[File:cmbs4rho.png]] | ||
Revision as of 08:40, 27 September 2018
This page documents the 600 lensing maps (healpy alm fits file, lmax=3000) available at
/project/projectdirs/cmbs4/reanalysis/phi_recons/02.00_carron_180920/plms_sepTP_apo_lmin200lmax3000_fsky5pc_cut10_180925
There are 6 type of maps, labeled with
- sim_ptt_????_lmax3000.fits
lensing map from temperature only, simulation index ???? 0000 to 0099
- sim_p_p_????_lmax3000.fits
lensing map from polarization only
- sim_p_????_lmax3000.fits
lensing map from temperature and polarization (MV)
- sim_xtt_????_lmax3000.fits
lensing curl map from temperature, useful for null tests
- sim_x_p_????_lmax3000.fits
lensing curl map from polarization
- sim_x_????_lmax3000.fits
lensing curl from temperature and polarization (MV)
The maps were built using the quadratic estimator implementation described in the 2018 CMB lensing paper, with the exception of the filtering, which is isotropic after application of a slightly apodized mask.
For illustration, the temperature (TT), polarization (PP) and Minimum Variance (MV) Wiener-filtered displacement reconstructions, together with the input, for realization 99:
Reconstruction parameters
- CMB multipoles from 200 to 3000
- Analysis mask: fmask.fits in same folder
- Gaussian beam of 4 arcmin FWHM
- Flat noise of 1.5 and 2.12 muK-arcmin
- FFP10 fiducial lensing spectra
- Separate temperature and polarization filtering
Fidelity to the input
The cross-correlation correlation to the input maps, as calculated across the entire patch is like this:
Mean-fields
The mean-field (here, contribution from the mask and noise anisotropies) has not been subtracted out from the maps on disk. The mean-field spectra look like this:
The mean-field subtraction can be performed subtracting the lensing reconstructed maps averaged over a subset of the simulations.
