CMB and astrophysical component maps

Overview

This section describes the maps of astrophysical components produced from the Planck data. These products are derived from some or all of the nine frequency channel maps described above using different techniques and, in some cases, using other constraints from external data sets. Here we give a brief description of the product and how it is obtained, followed by a description of the FITS file containing the data and associated information. All the details can be found in Planck-2013-XII.

CMB maps

CMB maps have been produced by the SMICA SEVEM, NILC and COMMANDER pipelines, which are described in the CMB and foreground separation section and also in Section 3 and Appendices A-D of Planck-2013-XII and references therein.. For each pipeline we provide:

• Full-mission CMB intensity map, confidence mask and beam transfer function.
• Full-mission high-pass filtered CMB polarisation map,
• A confidence mask.
• A beam transfer function.

In addition, and for characterisation purposes, there are six other sets of maps from three data splits: first/second half-ring, odd/even years and first/second half-mission. And for each of these data splits we provide half-sum and half-difference maps. The half-difference maps can be used to provide an approximate noise estimate for the full mission, but they should be used with caution. Each split has caveats in this regard: there are noise correlations between the half-ring maps, and missing pixels in the other splits. The Intensity maps are provided at Nside = 2048, at 5 arcmin resolution, while the Polarisation ones are provided at Nside = 1024 at 10 arcmin resolution. All maps are in units of K_cmb.

These maps can be found in the files COM_CMB_IQU-{pipeline}-field-{Int/Pol}_Nside_R2.00.fits. The Int files have two extensions, for the Intensity maps and the beam transfer function, the Pol files have three extensions, for Q and U maps, and for the beam transfer function. For a complete description of the data structure, see the below; the content of the first extensions is illustrated and commented in the table below.

The gallery below shows the Intensity, noise from half-mission, half-difference, and confidence mask for the four pipelines, in the order SMICA, SEVEM, NILC and COMMANDER, from top to bottom. The Intensity maps scale is [–500.+500] μK, and the noise are between [–25,+25] μK. We do not show the Q and U maps since they have no significant visible structure to contemplate.

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Product description

SMICA

Principle

SMICA produces a CMB map by linearly combining all Planck input channels (from 30 to 857 GHz) with weights which vary with the multipole. It includes multipoles up to [math]\ell = 4000[/math].

Resolution (effective beam)

The SMICA map has an effective beam window function of 5 arc-minutes truncated at [math]\ell=4000[/math] and deconvolved from the pixel window. It means that, ideally, one would have [math]C_\ell(map) = C_\ell(sky) * B_\ell(5')^2[/math], where [math]C_\ell(map)[/math] is the angular spectrum of the map, where [math]C_\ell(sky)[/math] is the angular spectrum of the CMB and [math]B_\ell(5')[/math] is a 5-arcminute Gaussian beam function. Note however that, by convention, the effective beam window function [math]B_\ell(fits)[/math] provided in the FITS file does include a pixel window function. Therefore, it is equal to [math]B_\ell(fits) = B_\ell(5') / p_\ell(2048)[/math] where [math]p_\ell(2048)[/math] denotes the pixel window function for an Nside=2048 pixelization.

Confidence mask

A confidence mask is provided which excludes some parts of the Galactic plane, some very bright areas and the masked point sources. This mask provides a qualitative (and subjective) indication of the cleanliness of a pixel.

Masks and inpainting

The raw SMICA CMB map has valid pixels except at the location of masked areas: point sources, Galactic plane, some other bright regions. Those invalid pixels are indicated with the mask named 'I_MASK'. The raw SMICA map has been inpainted, producing the map named "INP_CMB". Inpainting consists in replacing some pixels (as indicated by the mask named INP_MASK) by the values of a constrained Gaussian realization which is computed to ensure good statistical properties of the whole map (technically, the inpainted pixels are a sample realisation drawn under the posterior distribution given the un-masked pixels.

NILC (done by CB, checks with producers in progress)

Principle

The Needlet-ILC (hereafter NILC) CMB map is constructed both in total intensity as well as polarization, Q and U Stokes parameters. For total intensity, all Planck frequency channels are included. For polarization, all polarization sensitive frequency channels are included, from 30 to 353 GHz. The solution, for T, Q and U is obtained by applying the Internal Linear Combination (ILC) technique in needlet space, that is, with combination weights which are allowed to vary over the sky and over the whole multipole range.

Resolution (effective beam)

The spectral analysis, and estimation of the NILC coefficients, is performed up to a maximum [math]\ell=4000[/math]. The effective beam is equivalent of a Gaussian circular beam with FWHM=5 arcminutes.

Confidence mask

The same procedure is followed by SMICA and NILC for producing confidence masks, though with different parametrizations. A low resolution smoothed version of the NILC map, noise subtracted, is thresholded to 73.5 squared micro-K for T, and 6,75 squared micro-K for Q and U.

SEVEM

The aim of SEVEM is to produce clean CMB maps at one or several frequencies by using a procedure based on template fitting. The templates are internal, i.e., they are constructed from Planck data, avoiding the need for external data sets, which usually complicates the analyses and may introduce inconsistencies. The method has been successfully applied to Planck simulations and to WMAP polarisation data. In the cleaning process, no assumptions about the foregrounds or noise levels are needed, rendering the technique very robust. Note that unlike the other products, SEVEM does not provide the mask of regions not used in the productions of the CMB. On the other hand, it provides channel maps and 100, 143, and 217 GHz for Intensity and 70, 100 and 143 GHz for Polarization which are used as the building blocks of the final map.

COMMANDER-Ruler

COMMANDER-Ruler is the Planck software implementing a pixel based parametric component separation. Amplitude of CMB and the main diffuse foregrounds along with the relevant spectral parameters for those (see below in the Astrophysical Foreground Section for the latter) are parametrized and fitted in single MCMC chains conducted at N_side=256 using COMMANDER, implementing a Gibbs Sampling. The CMB amplitude which is obtained in these runs corresponds to the delivered low resolution CMB component from COMMANDER-Ruler which has a FWHM of 40 arcminutes. The sampling of the foreground parameters is applied to the data at full resolution for obtaining the high resolution CMB component from Ruler which is available on the PLA. In the Planck Component Separation paper Planck-2013-XIIadditional material is discussed, specifically concerning the sky region where the solutions are reliable, in terms of chi2 maps. The products mainly consist of:

• Maps of the Amplitudes of the CMB at low resolution, N_side=256, along with the standard deviations of the outputs, beam profiles derived from the production process.
• Maps of the CMB amplitude, along with the standard deviations, at high resolution, N_{side=2048, beam profiles derived from the production process.}
• Mask obtained on the basis of the precision in the fitting procedure; the thresholding is evaluated through the COMMANDER-Ruler likelihood analysis and excludes 13% of the sky, see Planck-2013-XII.

Production process

SMICA

1) Pre-processing

All input maps undergo a pre-processing step to deal with point sources. The point sources with SNR > 5 in the PCCS catalogue are fitted in each input map. If the fit is successful, the fitted point source is removed from the map; otherwise it is masked and the hole is filled in by a simple diffusive process to ensure a smooth transition and mitigate spectral leakage. This is done at all frequencies but 545 and 857 GHz, here all point sources with SNR > 7.5 are masked and filled-in similarly.

2) Linear combination

The nine pre-processed Planck frequency channels from 30 to 857 GHzare harmonically transformed up to [math]\ell = 4000[/math] and co-added with multipole-dependent weights as shown in the figure.

3) Post-processing

The areas masked in the pre-processing step are replaced by a constrained Gaussian realization.

Note: The visible power deficit in the raw CMB map around the galactic plane is due to the smooth fill-in of the masked areas in the input maps (the result of the pre-processing). It is not to be confused with the post-processing step of inpainting of the CMB map with a constrained Gaussian realization.

Weights given by SMICA to the input maps (after they are re-beamed to 5 arcmin and expressed in K[math]_\rm{RJ}[/math]), as a function of multipole.

NILC (done by CB, check by producers in progress)

Pre-processing

All sky frequency maps are deconvolved using the DPC beam transfer function provided, and re-convolved with a 5 arcminutes FWHM circular Gaussian beam. In polarization, prior to the smoothing process, all sky E and B maps are derived from Q and U using standard HEALPix tools from each individual frequency channels

Linear combination

Pre-processed input frequency maps are decomposed in needlet coefficients, specified in the Appendix B of the Planck A11 paper, with shape given by Table B.1. Minimum variance coefficients are then obtained, using all channels for T, from 30 to 353 for E and B.

Post-processing

E and B maps are re-combined into Q and U products using standard HEALPix tools.

SEVEM

The templates are internal, i.e., they are constructed from Planck data, avoiding the need for external data sets, which usually complicates the analyses and may introduce inconsistencies. In the cleaning process, no assumptions about the foregrounds or noise levels are needed, rendering the technique very robust. The fitting can be done in real or wavelet space (using a fast wavelet adapted to the HEALPix pixelization) to properly deal with incomplete sky coverage. By expediency, however, we fill in the small number of unobserved pixels at each channel with the mean value of its neighbouring pixels before applying SEVEM.

We construct our templates by subtracting two close Planck frequency channel maps, after first smoothing them to a common resolution to ensure that the CMB signal is properly removed. A linear combination of the templates [math]t_j[/math] is then subtracted from (hitherto unused) map d to produce a clean CMB map at that frequency. This is done either in real or in wavelet space (i.e., scale by scale) at each position on the sky: [math] T_c(\mathbf{x}, ν) = d(\mathbf{x}, ν) − \sum_{j=1}^{n_t} α_j t(\mathbf{x}) [/math] where [math]n_t[/math] is the number of templates. If the cleaning is performed in real space, the [math]α_j[/math] coefficients are obtained by minimising the variance of the clean map [math]T_c[/math] outside a given mask. When working in wavelet space, the cleaning is done in the same way at each wavelet scale independently (i.e., the linear coefficients depend on the scale). Although we exclude very contaminated regions during the minimization, the subtraction is performed for all pixels and, therefore, the cleaned maps cover the full-sky (although we expect that foreground residuals are present in the excluded areas).

It should be stressed that the method is very fast and permits the generation of thousands of simulations to characterize the statistical properties of the outputs, a critical need for many cosmological applications. The final CMB map retains the angular resolution of the original frequency map.

There are several possible configurations of SEVEM with regard to the number of frequency maps which are cleaned or the number of templates that are used in the fitting. Note that the production of clean maps at different frequencies is of great interest in order to test the robustness of the results. Therefore, to define the best strategy, one needs to find a compromise between the number of maps that can be cleaned independently and the number of templates that can be constructed.

Intensity

For the CMB intensity map, we have cleaned the 100 GHz, 143 GHz and 217 GHz maps using three templates constructed as the difference of the following Planck channels (smoothed to a common resolution): (30-44), (44-70), (545-353) and 857 as the fourth template. For simplicity, the three maps have been cleaned in real space, since there was not a significant improvement when using wavelets (especially at high latitude). First of all, the six frequency channels which are going to be used to construct templates are inpainted at the point source positions detected using the Mexican Hat Wavelet algorithm (Planck Collaboration A35 2014). The size of the holes to be inpainted is determined taking into account the beam size of the channel as well as the flux of each source. The inpainting algorithm is based on simple diffuse inpainting, which fills one pixel with the mean value of the neighbouring pixels in an iterative way. To avoid inconsistencies when subtracting two channels, each frequency map is inpainted on the sources detected in that map and on the second map (if any) used to construct the template. Then the maps are smoothed to a common resolution (the first channel in the subtraction is smoothed with the beam of the second map and viceversa). For the 857 GHz template, we simply filter this map with the beam from 545 GHz (this is for comparison with the previous pipeline, where the 857 GHz was smoothed at this resolution when using it to construct the 857–545 template).

The coefficients are obtained outside the analysis mask, that covers the 1 per cent brightest emission of the sky as well as point sources detected at all frequency channels. Once the maps are cleaned, each of them is inpainted on the point sources positions detected at that (raw) channel. Then, the MHW algorithm is run again, now on the clean maps. A relatively small number of new sources are found and are also inpainted at each channel. The resolution of the clean map is the same as that of the raw map. Our final CMB map has then been constructed by combining the 143 and 217 GHz maps by weighting the maps in harmonic space taking into account the noise level, the resolution and a rough estimation of the foreground residuals of each map (obtained from realistic simulations). This final map has a resolution corresponding to a Gaussian beam of fwhm=5 arcminutes.

COMMANDER-Ruler

The production process consist in low and high resolution runs according to the description above.

Low Resolution Runs

Same as the Astrophysics Foregrounds Section below; The CMB amplitude is fitted along with the other foreground parameters and constitutes the CMB Low Resolution Rendering which is in the PLA.

Ruler Runs

the sampling at high resolution is used to infer the probability distribution of spectral parameters which is exploited at full resolution in order to obtain the High Resolution CMB Rendering which is in the PLA.

Inputs

The input maps are the sky temperature maps described in the Sky temperature maps section. SMICA and SEVEM use all the maps between 30 and 857 GHz; NILC uses the ones between 44 and 857 GHz. Commander-Ruler uses frequency channel maps from 30 to 353 GHz.

File names and structure

The FITS files corresponding to the three CMB products are the following:

COM_CMB_IQU-{method}-field-{Int,Pol}_Nside_R2.nn.fits

where method is mica, nilc, sevem, or commander, and Int and Pol indicate whether the file contains the temperature (Int) or the polarisation (Pol) maps. For this release the temperature maps are provided at Nside = 2048, and the polarisation maps at Nside = 1024.

The files contain

• a minimal primary extension with no data;
• one or two BINTABLE data extensions with a table of Npix lines by 14 columns in which the first 13 columns is a CMB map produced from the full or a subset of the data, as described in the table below, and the last column in a confidence mask. There is a single extension for Int files, and two, for Q and U, for Pol files.
• a BINTABLE extension containing the beam window function.

CMB map file data structure

Ext. 1. or 2. EXTNAME = COMP-MAP (BINTABLE)
Column Name	Data Type	Units	Description
I or Q or U	Real*4	uK_cmb	I or U or Q map
U	Real*4	uK_cmb	U-polarization
HM1	Real*4	uK_cmb	Half-miss 1
HM2	Real*4	uK_cmb	Half-miss 2
YR1	Real*4	uK_cmb	Year 1
YR2	Real*4	uK_cmb	Year 2
HR1	Real*4	uK_cmb	Half-ring 1
HR2	Real*4	uK_cmb	Half-ring 2
HMHS	Real*4	uK_cmb	Half-miss, half sum
HMHD	Real*4	uK_cmb	Half-miss, half diff
YRHS	Real*4	uK_cmb	Year, half sum
YRHD	Real*4	uK_cmb	Year, half diff
HRHS	Real*4	uK_cmb	Half-ring half sum
HRHD	Real*4	uK_cmb	Half-ring half diff
MASK	BYTE		Confidence mask
Keyword	Data Type	Value	Description
AST-COMP	String	CMB	Astrophysical compoment name
PIXTYPE	String	HEALPIX
COORDSYS	String	GALACTIC	Coordinate system
POLCCONV	String	COSMO	Polarization convention
ORDERING	String	NESTED	Healpix ordering
NSIDE	Int	2048	Healpix Nside
METHOD	String	name	Cleaning method (smica/nilc/sevem/commander)
Keyword	Data Type	Value	Description
PIXTYPE	String	HEALPIX
COORDSYS	String	GALACTIC	Coordinate system
ORDERING	String	NESTED	Healpix ordering
NSIDE	Int	1024	Healpix Nside
METHOD	String	name	Cleaning method (SMICA/NILC/SEVEM)
Ext. 2. or 3. EXTNAME = BEAM_WF (BINTABLE)
Column Name	Data Type	Units	Description
BEAM_WF	Real*4	none	The effective beam window function, including the pixel window function. See Note 1.
Keyword	Data Type	Value	Description
LMIN	Int	value	First multipole of beam WF
LMAX	Int	value	Lsst multipole of beam WF
METHOD	String	name	Cleaning method (SMICA/NILC/SEVEM/COMMANDER-Ruler)

Notes:

1. The beam window function [math]B_\ell[/math] given here includes the pixel window function [math]p_\ell[/math] for the Nside=2048 pixelization. It means that, ideally, [math]C_\ell(map) = C_\ell(sky) \, B_\ell^2 \, p_\ell^2[/math].

Astrophysical foregrounds from parametric component separation

We describe diffuse foreground products for the Planck 2013 release. See Planck Component Separation paper Planck-2013-XII for a detailed description and astrophysical discussion of those.

Product description

Low frequency foreground component

The products below contain the result of the fitting for one foreground component at low frequencies in Planck bands,along with its spectral behavior parametrized by a power law spectral index. Amplitude and spectral indeces are evaluated at N$_\rm{side}$ 256 (see below in the production process), along with standard deviation from sampling and instrumental noise on both. An amplitude solution at N$_\rm{side}$=2048 is also given, along with standard deviation from sampling and instrumental noise as well as solutions on halfrings. The beam profile associated to this component is also provided as a secondary Extension in the N$_\rm{side}$ 2048 product.

Thermal dust

The products below contain the result of the fitting for one foreground component at high frequencies in Planck bands, along with its spectral behavior parametrized by temperature and emissivity. Amplitude, temperature and emissivity are evaluated at N$_\rm{side}$ 256 (see below in the production process), along with standard deviation from sampling and instrumental noise on all of them. An amplitude solution at N$_\rm{side}$=2048 is also given, along with standard deviation from sampling and instrumental noise as well as solutions on halfrings. The beam profile associated to this component is provided.

Sky mask

The delivered mask is defined as the sky region where the fitting procedure was conducted and the solutions presented here were obtained. It is made by masking a region where the Galactic emission is too intense to perform the fitting, plus the masking of brightest point sources.

Production process

CODE: COMMANDER-RULER. The code exploits a parametrization of CMB and main diffuse foreground observables. The naive resolution of input frequency channels is reduced to N$_\rm{side}$=256 first. Parameters related to the foreground scaling with frequency are estimated at that resolution by using Markov Chain Monte Carlo analysis using Gibbs sampling. The foreground parameters make the foreground mixing matrix which is applied to the data at full resolution in order to obtain the provided products at N$_\rm{side}$=2048. In the Planck Component Separation paper Planck-2013-XII additional material is discussed, specifically concerning the sky region where the solutions are reliable, in terms of chi2 maps.

Inputs

Nominal frequency maps at 30, 44, 70, 100, 143, 217, 353 GHz (LFI 30 GHz frequency maps, LFI 44 GHz frequency maps and LFI 70 GHz frequency maps, HFI 100 GHz frequency maps, HFI 143 GHz frequency maps,HFI 217 GHz frequency maps and HFI 353 GHz frequency maps) and their II column corresponding to the noise covariance matrix. Halfrings at the same frequencies. Beam window functions as reported in the LFI and HFI RIMO.

Related products

None.

File names

• Low frequency component at N$_\rm{side}$ 256: COM_CompMap_Lfreqfor-commrul_0256_R1.00.fits
• Low frequency component at N$_\rm{side}$ 2048: COM_CompMap_Lfreqfor-commrul_2048_R1.00.fits
• Thermal dust at N$_\rm{side}$ 256: COM_CompMap_dust-commrul_0256_R1.00.fits
• Thermal dust at N$_\rm{side}$ 2048: COM_CompMap_dust-commrul_2048_R1.00.fits
• Mask: COM_CompMap_Mask-rulerminimal_2048_R1.00.fits

Meta Data

Low frequency foreground component

Low frequency component at N_side = 256

File name: COM_CompMap_Lfreqfor-commrul_0256_R1.00.fits

Name HDU -- COMP-MAP

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
I	Real*4	uKCMB	Intensity
I_stdev	Real*4	uKCMB	standard deviation of intensity
Beta	Real*4		effective spectral index
B_stdev	Real*4		standard deviation on the effective spectral index

Notes

Comment: The Intensity is normalized at 30 GHz

Comment: The intensity was estimated during mixing matrix estimation

Low frequency component at N_side = 2048

File name: COM_CompMap_Lfreqfor-commrul_2048_R1.00.fits

Name HDU -- COMP-MAP

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
I	Real*8	uKCMB	Intensity
I_stdev	Real*8	uKCMB	standard deviation of intensity
I_hr1	Real*8	uKCMB	Intensity on half ring 1
I_hr2	Real*8	uKCMB	Intensity on half ring 2

Notes

Comment: The intensity was computed after mixing matrix application

Name HDU -- BeamWF

The Fits second extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
BeamWF	Real*4		beam profile

Notes

Comment: Beam window function used in the Component separation process

Thermal dust

Thermal dust component at N_side=256

File name: COM_CompMap_dust-commrul_0256_R1.00.fits

Name HDU -- COMP-MAP

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
I	Real*4	MJy/sr	Intensity
I_stdev	Real*4	MJy/sr	standard deviation of intensity
Em	Real*4		emissivity
Em_stdev	Real*4		standard deviation on emissivity
T	Real*4	uKCMB	temperature
T_stdev	Real*4	uKCMB	standard deviation on temerature

Notes

Comment: The intensity is normalized at 353 GHz

Thermal dust component at N_side=2048

File name: COM_CompMap_dust-commrul_2048_R1.00.fits

Name HDU -- COMP-MAP

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
I	Real*8	MJy/sr	Intensity
I_stdev	Real*8	MJy/sr	standard deviation of intensity
I_hr1	Real*8	MJy/sr	Intensity on half ring 1
I_hr2	Real*8	MJy/sr	Intensity on half ring 2

Name HDU -- BeamWF

The Fits second extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
BeamWF	Real*4		beam profile

Notes

Comment: Beam window function used in the Component separation process

Sky mask

File name: COM_CompMap_Mask-rulerminimal_2048.fits

Name HDU -- COMP-MASK

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
Mask	Real*4		Mask