# Astrophysical Components

## 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 each 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-2015-A10[1] and {PlanckPapers|planck20}}.

## Astrophysical foregrounds from parametric component separation

We describe diffuse foreground products for the Planck 2015 release. See the Planck Foregrounds Component Separation paper Planck-2015-A10[1] for a detailed description of these products. Further scientific discussion and interpretation may be found in Planck-2015-A25[2].

### Low-resolution temperature products

The Planck 2015 astrophysical component separation analysis combines Planck observations with the 9-year WMAP temperature sky maps (Bennett et al. 2013) and the 408 MHz survey by Haslam et al. (1982). This allows a direct decomposition of the low-frequency foregrounds into separate synchrotron, free-free and spinning dust components without strong spatial priors.

#### Inputs

The following data products are used for the low-resolution analysis:

• Full-mission 30 GHz frequency map, LFI 30 GHz frequency maps
• Full-mission 44 GHz frequency map, LFI 44 GHz frequency maps
• Full-mission 70 GHz ds1 (18+23), ds2 (19+22), and ds3 (20+21) detector-set maps
• Full-mission 100 GHz ds1 and ds2 detector set maps
• Full-mission 143 GHz ds1 and ds2 detector set maps and detectors 5, 6, and 7 maps
• Full-mission 217 GHz detector 1, 2, 3 and 4 maps
• Full-mission 353 GHz detector set ds2 and detector 1 maps
• Full-mission 545 GHz detector 2 and 4 maps
• Full-mission 857 GHz detector 2 map
• Beam-symmetrized 9-year WMAP K-band map (Lambda)
• Beam-symmetrized 9-year WMAP Ka-band map (Lambda)
• Default 9-year WMAP Q1 and Q2 differencing assembly maps (Lambda)
• Default 9-year WMAP V1 and V2 differencing assembly maps (Lambda)
• Default 9-year WMAP W1, W2, W3, and W4 differencing assembly maps (Lambda)
• Re-processed 408 MHz survey map, Remazeilles et al. (2014) (Lambda)

All maps are smoothed to a common resolution of 1 degree FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=256.

#### Outputs

##### Synchrotron emission
File name: COM_CompMap_Synchrotron-commander_0256_R2.00.fits
Reference frequency: 408 MHz
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-Synchrotron
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Amplitude posterior maximum
I_MEAN Real*4 uK_RJ Amplitude posterior mean
I_RMS Real*4 uK_RJ Amplitude posterior rms

Extension 1 -- SYNC-TEMP
Column Name Data Type Units Description
nu Real*4 Hz Frequency
intensity Real*4 W/Hz/m2/sr GALPROP z10LMPD_SUNfE spectrum
##### Free-free emission
File name: COM_CompMap_freefree-commander_0256_R2.00.fits
Reference frequency: NA
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-freefree
Column Name Data Type Units Description
EM_ML Real*4 cm^-6 pc Emission measure posterior maximum
EM_MEAN Real*4 cm^-6 pc Emission measure posterior mean
EM_RMS Real*4 cm^-6 pc Emission measure posterior rms
TEMP_ML Real*4 K Electron temperature posterior maximum
TEMP_MEAN Real*4 K Electron temperature posterior mean
TEMP_RMS Real*4 K Electron temperature posterior rms

##### Spinning dust emission
File name: COM_CompMap_AME-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin

Note: The spinning dust component has two independent constituents, each corresponding to one spdust2 component, but with different peak frequencies. The two components are stored in the two first FITS extensions, and the template frequency spectrum is stored in the third extension.

Reference frequency: 22.8 GHz
HDU -- COMP-MAP-AME1
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Primary amplitude posterior maximum
I_MEAN Real*4 uK_RJ Primary amplitude posterior mean
I_RMS Real*4 uK_RJ Primary amplitude posterior rms
FREQ_ML Real*4 GHz Primary peak frequency posterior maximum
FREQ_MEAN Real*4 GHz Primary peak frequency posterior mean
FREQ_RMS Real*4 GHz Primary peak frequency posterior rms
Reference frequency: 41.0 GHz
Peak frequency: 33.35 GHz
Extension 1 -- COMP-MAP-AME2
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Secondary amplitude posterior maximum
I_MEAN Real*4 uK_RJ Secondary amplitude posterior mean
I_RMS Real*4 uK_RJ Secondary amplitude posterior rms

Extension 2 -- SPINNING-DUST-TEMP
Column Name Data Type Units Description
nu Real*4 GHz Frequency
j_nu/nH Real*4 Jy sr-1 cm2/H spdust2 spectrum
##### CO line emission
File name: COM_CompMap_CO-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin

Note: The CO line emission component has three independent objects, corresponding to the J1->0, 2->1 and 3->2 lines, stored in separate extensions.

HDU -- COMP-MAP-co10
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(1-0) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(1-0) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(1-0) amplitude posterior rms
Extension 1 -- COMP-MAP-co21
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(2-1) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(2-1) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(2-1) amplitude posterior rms
Extension 2 -- COMP-MAP-co32
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(3-2) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(3-2) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(3-2) amplitude posterior rms
##### 94/100 GHz line emission
File name: COM_CompMap_xline-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-xline
Column Name Data Type Units Description
I_ML Real*4 uK_cmb Amplitude posterior maximum
I_MEAN Real*4 uK_cmb Amplitude posterior mean
I_RMS Real*4 uK_cmb Amplitude posterior rms

Note: The amplitude of this component is normalized according to the 100-ds1 detector set map, ie., it is the amplitude as measured by this detector combination.

##### Thermal dust emission
File name: COM_CompMap_dust-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
Reference frequency: 545 GHz
HDU -- COMP-MAP-dust
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Amplitude posterior maximum
I_MEAN Real*4 uK_RJ Amplitude posterior mean
I_RMS Real*4 uK_RJ Amplitude posterior rms
TEMP_ML Real*4 K Dust temperature posterior maximum
TEMP_MEAN Real*4 K Dust temperature posterior mean
TEMP_RMS Real*4 K Dust temperature posterior rms
BETA_ML Real*4 NA Emissivity index posterior maximum
BETA_MEAN Real*4 NA Emissivity index posterior mean
BETA_RMS Real*4 NA Emissivity index posterior rms
##### Thermal Sunyaev-Zeldovich emission around the Coma and Virgo clusters
File name: COM_CompMap_SZ-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-SZ
Column Name Data Type Units Description
Y_ML Real*4 y_SZ Y parameter posterior maximum
Y_MEAN Real*4 y_SZ Y parameter posterior mean
Y_RMS Real*4 y_SZ Y parameter posterior rms

### High-resolution temperature products

High-resolution foreground products at 7.5 arcmin FWHM are derived with the same algorithm as for the low-resolution analyses, but including frequency channels above (and including) 143 GHz.

#### Inputs

The following data products are used for the low-resolution analysis:

• Full-mission 143 GHz ds1 and ds2 detector set maps and detectors 5, 6, and 7 maps
• Full-mission 217 GHz detector 1, 2, 3 and 4 maps
• Full-mission 353 GHz detector set ds2 and detector 1 maps
• Full-mission 545 GHz detector 2 and 4 maps
• Full-mission 857 GHz detector 2 map

All maps are smoothed to a common resolution of 7.5 arcmin FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=2048.

#### Outputs

##### CO J2->1 emission
File name: COM_CompMap_CO21-commander_2048_R2.00.fits
Nside = 2048
Angular resolution = 7.5 arcmin
HDU -- COMP-MAP-CO21
Column Name Data Type Units Description
I_ML_FULL Real*4 K_RJ km/s Full-mission amplitude posterior maximum
I_ML_HM1 Real*4 K_RJ km/s First half-mission amplitude posterior maximum
I_ML_HM2 Real*4 K_RJ km/s Second half-mission amplitude posterior maximum
I_ML_HR1 Real*4 K_RJ km/s First half-ring amplitude posterior maximum
I_ML_HR2 Real*4 K_RJ km/s Second half-ring amplitude posterior maximum
I_ML_YR1 Real*4 K_RJ km/s "First year" amplitude posterior maximum
I_ML_YR2 Real*4 K_RJ km/s "Second year" amplitude posterior maximum

##### Thermal dust emission
File name: COM_CompMap_ThermalDust-commander_2048_R2.00.fits
Nside = 2048
Angular resolution = 7.5 arcmin
Reference frequency: 545 GHz
HDU -- COMP-MAP-dust
Column Name Data Type Units Description
I_ML_FULL Real*4 uK_RJ Full-mission amplitude posterior maximum
I_ML_HM1 Real*4 uK_RJ First half-mission amplitude posterior maximum
I_ML_HM2 Real*4 uK_RJ Second half-mission amplitude posterior maximum
I_ML_HR1 Real*4 uK_RJ First half-ring amplitude posterior maximum
I_ML_HR2 Real*4 uK_RJ Second half-ring amplitude posterior maximum
I_ML_YR1 Real*4 uK_RJ "First year" amplitude posterior maximum
I_ML_YR2 Real*4 uK_RJ "Second year" amplitude posterior maximum
BETA_ML_FULL Real*4 NA Full-mission emissivity index posterior maximum
BETA_ML_HM1 Real*4 NA First half-mission emissivity index posterior maximum
BETA_ML_HM2 Real*4 NA Second half-mission emissivity index posterior maximum
BETA_ML_HR1 Real*4 NA First half-ring emissivity index posterior maximum
BETA_ML_HR2 Real*4 NA Second half-ring emissivity index posterior maximum
BETA_ML_YR1 Real*4 NA "First year" emissivity index posterior maximum
BETA_ML_YR2 Real*4 NA "Second year" emissivity index posterior maximum

### Polarization products

Two polarization foreground products are provided, namely synchrotron and thermal dust emission. The spectral models are assumed identical to the corresponding temperature spectral models.

#### Inputs

The following data products are used for the polarization analysis:

In the low-resolution analysis, all maps are smoothed to a common resolution of 40 arcmin FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=256. In the high-resolution analysis (including only CMB and thermal dust emission), the corresponding resolution is 10 arcmin FWHM and Nside=1024.

#### Outputs

##### Synchrotron emission
File name: COM_CompMap_SynchrotronPol-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 40 arcmin
Reference frequency: 30 GHz
HDU -- COMP-MAP-SynchrotronPol
Column Name Data Type Units Description
Q_ML_FULL Real*4 μK_RJ Full-mission Stokes Q posterior maximum
U_ML_FULL Real*4 μK_RJ Full-mission Stokes U posterior maximum
Q_ML_HM1 Real*4 μK_RJ First half-mission Stokes Q posterior maximum
U_ML_HM1 Real*4 μK_RJ First half-mission Stokes U posterior maximum
Q_ML_HM2 Real*4 μK_RJ Second half-mission Stokes Q posterior maximum
U_ML_HM2 Real*4 μK_RJ Second half-mission Stokes U posterior maximum
Q_ML_HR1 Real*4 μK_RJ First half-ring Stokes Q posterior maximum
U_ML_HR1 Real*4 μK_RJ First half-ring Stokes U posterior maximum
Q_ML_HR2 Real*4 μK_RJ Second half-ring Stokes Q posterior maximum
U_ML_HR2 Real*4 μK_RJ Second half-ring Stokes U posterior maximum
Q_ML_YR1 Real*4 μK_RJ "First year" Stokes Q posterior maximum
U_ML_YR1 Real*4 μK_RJ "First year" Stokes U posterior maximum
Q_ML_YR2 Real*4 μK_RJ "Second year" Stokes Q posterior maximum
U_ML_YR2 Real*4 μK_RJ "Second year" Stokes U posterior maximum
##### Thermal dust emission
File name: COM_CompMap_DustPol-commander_1024_R2.00.fits
Nside = 1024
Angular resolution = 10 arcmin
Reference frequency: 353 GHz
HDU -- COMP-MAP-DustPol
Column Name Data Type Units Description
Q_ML_FULL Real*4 uK_RJ Full-mission Stokes Q posterior maximum
U_ML_FULL Real*4 uK_RJ Full-mission Stokes U posterior maximum
Q_ML_HM1 Real*4 uK_RJ First half-mission Stokes Q posterior maximum
U_ML_HM1 Real*4 uK_RJ First half-mission Stokes U posterior maximum
Q_ML_HM2 Real*4 uK_RJ Second half-mission Stokes Q posterior maximum
U_ML_HM2 Real*4 uK_RJ Second half-mission Stokes U posterior maximum
Q_ML_HR1 Real*4 uK_RJ First half-ring Stokes Q posterior maximum
U_ML_HR1 Real*4 uK_RJ First half-ring Stokes U posterior maximum
Q_ML_HR2 Real*4 uK_RJ Second half-ring Stokes Q posterior maximum
U_ML_HR2 Real*4 uK_RJ Second half-ring Stokes U posterior maximum
Q_ML_YR1 Real*4 uK_RJ "First year" Stokes Q posterior maximum
U_ML_YR1 Real*4 uK_RJ "First year" Stokes U posterior maximum
Q_ML_YR2 Real*4 uK_RJ "Second year" Stokes Q posterior maximum
U_ML_YR2 Real*4 uK_RJ "Second year" Stokes U posterior maximum

## CO emission maps

CO rotational transition line emission is present in all HFI bands except for the 143 GHz channel. It is especially significant in the 100, 217 and 353 GHz channels (due to the 115 (1-0), 230 (2-1) and 345 GHz (3-2) CO transitions). This emission comes essentially from the Galactic interstellar medium and is mainly located at low and intermediate Galactic latitudes. Three approaches (summarised below) have been used to extract CO velocity-integrated emission maps from HFI maps and to make three types of CO products. A full description of how these products were generated is given in Planck-2013-XIII[3] and Planck-2015-A10[1].

• Type 1 product: it is based on a single channel approach using the fact that each CO line has a slightly different transmission in each bolometer at a given frequency channel. These transmissions can be evaluated from bandpass measurements that were performed on the ground or empirically determined from the sky using existing ground-based CO surveys. From these, the J=1-0, J=2-1 and J=3-2 CO lines can be extracted independently. As this approach is based on individual bolometer maps of a single channel, the resulting Signal-to-Noise ratio (SNR) is relatively low. The benefit, however, is that these maps do not suffer from contamination from other HFI channels (as is the case for the other approaches) and are more reliable, especially in the Galactic Plane. The improvement relative to the 2013 release comes from the combined effect of the ADC correction, the VLTC correction, and the improved calibration scheme. As a result, the noise level is ~30% lower in the new products, and the maps are much better behaved at high latitudes.
• Type 2 product: this product is obtained using a multi frequency approach. Three frequency channel maps are combined to extract the J=1-0 (using the 100, 143 and 353 GHz channels) and J=2-1 (using the 143, 217 and 353 GHz channels) CO maps. Because frequency channels are combined, the spectral behaviour of other foregrounds influences the result. The two type 2 CO maps produced in this way have a higher SNR than the type 1 maps at the cost of a larger possible residual contamination from other diffuse foregrounds.
• Type 3 product: to generate this product, fixed CO line ratios are assumed and a high-resolution parametric foreground model is fit. In 2013 this product was generated using the Commander-Ruler technique. In 2015, this technique is superseded by the high-resolution Commander-only, used to produce the J=2-1 map presented in [1] and described in Section 5.4 of Planck-2015-A10[1].

Type 1 and 2 maps have been produced using the MILCA algorithm. Commander has been used to produce low resolution CO J=1-0,2-1,3-2 maps (here) and high resolution CO J=2-1 maps (here).

A summary of all the 2015 CO maps can be found in Table 9 from Planck-2015-A10[1], also shown here:

Characteristics of the released maps are the following. We provide Healpix maps with Nside=2048. For one transition, the CO velocity-integrated line signal map is given in K_RJ.km/s units. A conversion factor from this unit to the native unit of HFI maps (K_CMB) is provided in the header of the data files and in the RIMO. Four maps are given per transition and per type:

• The signal map
• The standard deviation map (same unit as the signal),
• A null test noise map (same unit as the signal) with similar statistical properties. It is made out of half the difference of half-ring maps.
• A mask map (0 or 1) giving the regions (1) where the CO measurement is not reliable because of some severe identified foreground contamination.

File name: HFI_CompMap_CO-Type1_2048_R2.00.fits
Nside = 2048

Type-1 CO map file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
INTEN10 Real*4 K_RJ km/sec The CO(1-0) intensity map
ERR10 Real*4 K_RJ km/sec Uncertainty in the CO(1-0) intensity
NULL10 Real*4 K_RJ km/sec Map built from the half-ring difference maps
MASK10 Byte none Region over which the CO(1-0) intensity is considered reliable
INTEN21 Real*4 K_RJ km/sec The CO(2-1) intensity map
ERR21 Real*4 K_RJ km/sec Uncertainty in the CO(2-1) intensity
NULL21 Real*4 K_RJ km/sec Map built from the half-ring difference maps
MASK21 Byte none Region over which the CO(2-1) intensity is considered reliable
INTEN32 Real*4 K_RJ km/sec The CO(3-2) intensity map
ERR32 Real*4 K_RJ km/sec Uncertainty in the CO(3-2) intensity
NULL32 Real*4 K_RJ km/sec Map built from the half-ring difference maps
MASK32 Byte none Region over which the CO(3-2) intensity is considered reliable
Keyword Data Type Value Description
AST-COMP string CO-TYPE1 Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively
CNV 1-0 Real*4 value Factor to convert CO(1-0) intensity to Kcmb (units Kcmb/(Krj*km/s))
CNV 2-1 Real*4 value Factor to convert CO(2-1) intensityto Kcmb (units Kcmb/(Krj*km/s))
CNV 3-2 Real*4 value Factor to convert CO(3-2) intensityto Kcmb (units Kcmb/(Krj*km/s))

File name: HFI_CompMap_CO-Type2_2048_R2.00.fits
Nside = 2048

Type-2 CO map file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
I10 Real*4 K_RJ km/sec The CO(1-0) intensity map
E10 Real*4 K_RJ km/sec Uncertainty in the CO(1-0) intensity
N10 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M10 Byte none Region over which the CO(1-0) intensity is considered reliable
I21 Real*4 K_RJ km/sec The CO(2-1) intensity map
E21 Real*4 K_RJ km/sec Uncertainty in the CO(2-1) intensity
N21 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M21 Byte none Region over which the CO(2-1) intensity is considered reliable
Keyword Data Type Value Description
AST-COMP String CO-TYPE2 Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively
CNV 1-0 Real*4 value Factor to convert CO(1-0) intensity to Kcmb (units Kcmb/(Krj*km/s))
CNV 2-1 Real*4 value Factor to convert CO(2-1) intensityto Kcmb (units Kcmb/(Krj*km/s))

## Modelling of the thermal dust emission with the Draine and Li dust model

The Planck, IRAS, and WISE infrared observations were fit with the dust model presented by Draine & Li in 2007 (DL07). The input maps, the DL07 model, and the fitting procedure and results are presented in Planck-2014-XXIX[4]. Here, we describe the input maps and the output maps, which are made available on the Planck Legacy Archive.

### Inputs

The following data have been fit:

• WISE 12 micron map
• IRAS 60 micron map
• IRAS 100 micron map
• Full-mission 353 GHz PR2 map
• Full-mission 545 GHz PR2 map
• Full-mission 857 GHz PR2 map

The CIB monopole, the CMB anisotropries and the zodiacal light were subtracted to obtain dust emission maps from the sky emission maps. All maps were smoothed to a common angular resolution of 5'.

### Model Parameters

For each pixel of the inputs maps, we have fitted four parameters of the DL07 model:

• the dust mass surface density, Sigma_Mdust,
• the dust mass fraction in small PAH grains, q_PAH,
• the fraction of the total luminosity from dust heated by intense radiation fields, f_PDR,
• the starlight intensity heating the bulk of the dust, U_min.

The parameter maps and their uncertainties are gathered in one file. This file also includes the chi2 of the fit per degree of freedom.

File name: COM_CompMap_Dust-DL07-Parameters_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-Parameters
Column Name Data Type Units Description
Sigma_Mdust Real*4 Solar masses/kpc^2 Dust mass surface density
Sigma_Mdust_unc Real*4 Solar masses/kpc^2 Uncertainty (1 sigma) on Sigma_Mdust
q_PAH Real*4 dimensionless Dust mass fraction in small PAH grains
q_PAH_unc Real*4 dimensionless Uncertainty (1 sigma) on q_PAH
f_PDR Real*4 dimensionless Fraction of the total luminosity from dust heated by intense radiation fields
f_PDR_unc Real*4 dimensionless Uncertainty (1 sigma) on f_PDR
U_min Real*4 dimensionless Starlight intensity heating the bulk of the dust
U_min_unc Real*4 dimensionless Uncertainty (1 sigma) on U_min
Chi2_DOF Real*4 dimensionless Chi2 of the fit per degree of freedom

### Visible extinction maps

We provide two exinctions maps at the visible V band: the value from the model (Av_DL) and the renormalized one (Av_RQ) that matches extinction estimates for quasars (QSOs) derived from the Sloan digital sky survey (SDSS) data.

File name: COM_CompMap_Dust-DL07-AvMaps_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-AvMaps
Column Name Data Type Units Description
Av_DL Real*4 magnitude Extinction in the V band from the DL model
Av_DL_unc Real*4 magnitude Uncertainty (1 sigma) on Av_DL
Av_RQ Real*4 magnitude Extinction in the V band renormalized to match estimates from QSO SDSS observations
Av_RQ_unc Real*4 magnitude Uncertainty (1 sigma) on Av_RQ

### Model Fluxes

We provide the model predicted fluxes in the following file.

File name: COM_CompMap_Dust-DL07-ModelFluxes_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-ModelFluxes
Column Name Data Type Units Description
Planck_857 Real*4 MJy/sr Model flux in the Planck 857 GHz band
Planck_545 Real*4 MJy/sr Model flux in the Planck 545 GHz band
Planck_353 Real*4 MJy/sr Model flux in the Planck 353 GHz band
WISE_12 Real*4 MJy/sr Model flux in the WISE 12 micron band
IRAS_60 Real*4 MJy/sr Model flux in the IRAS 60 micron band
IRAS_100 Real*4 MJy/sr Model flux in the IRAS 100 micron band

## Thermal dust and CIB all-sky maps from GNILC component separation

We describe diffuse foreground products for the Planck 2015 release produced with the GNILC component separation method. See the Planck paper Planck-2016-XLVIII[5] for a detailed discussion on these products.

### Method

The basic idea behind the Generalized Needlet Internal Linear Combination (GNILC) component-separation method (Remazeilles et al, MNRAS 2011) is to disentangle specific components of emission not on the sole basis of the spectral (frequency) information but also on the basis of their distinct spatial information (angular power spectrum). The GNILC method has been applied to Planck data in order to disentangle Galactic dust emission and Cosmic Infrared Background (CIB) anisotropies. Both components have a similar spectral signature but a distinct angular power spectrum (spatial signature). The spatial information used by GNILC is under the form of priors for the angular power spectra of the CIB, the CMB, and the instrumental noise. No assumption is made on the Galactic signal, neither spectral or spatial. In that sense, GNILC is a blind component-separation method. GNILC operates on a needlet (spherical wavelet) frame, therefore adapting the component separation to the local conditions of contamination both over the sky and over the angular scales.

### Data

The data used by GNILC for the analysis are the Planck data release 2 (PR2) frequency maps from 30 to 857 GHz, and a 100 micron hybrid map combined from the SFD map (Schlegel et al, ApJ 1998) at large angular scales (> 30') and the IRIS map (Miville-Deschênes et al, ApJS 2005) at small angular scales (< 30'). This special 100 micron map can be obtained in the External Maps section of the PLA.

### Pre-processing

The point-sources with a signal-to-noise ratio, S/N > 5, in each individual frequency map (30 to 857 GHz, and 100 micron) have been pre-processed by a minimum curvature surface inpainting technique (Remazeilles et al, MNRAS 2015) prior to performing component separation with GNILC.

### GNILC thermal dust and CIB products

The result of GNILC component separation are thermal dust and CIB maps at 353, 545, and 857 GHz. In addition, by fitting a modified blackbody model to the GNILC thermal dust products at 353, 545, 857, and 100 micron, we have created all-sky maps of the dust optical depth, dust temperature, and dust emmissivity index. Note that the thermal dust maps have a variable angular resolution over the sky with an effective beam FWHM varying from 21.8' to 5'. The dust beam FWHM map is also released as a product.

#### Thermal dust maps

HDU -- COMP-MAP-DUST
File Name Nside Units Reference frequency Angular resolution Description
COM_CompMap_Dust-GNILC-F353_2048_R2.00.fits 2048 MJy/sr 353 GHz COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust amplitude at 353 GHz
COM_CompMap_Dust-GNILC-F545_2048_R2.00.fits 2048 MJy/sr 545 GHz COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust amplitude at 545 GHz
COM_CompMap_Dust-GNILC-F857_2048_R2.00.fits 2048 MJy/sr 857 GHz COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust amplitude at 857 GHz
COM_CompMap_Dust-GNILC-Model-Opacity_2048_R2.01.fits (version 2.01 includes the error map)
COM_CompMap_Dust-GNILC-Model-Opacity_2048_R2.00.fits
2048 NA 353 GHz COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust optical depth at 353 GHz
COM_CompMap_Dust-GNILC-Model-Spectral-Index_2048_R2.01.fits (version 2.01 includes the error map)
COM_CompMap_Dust-GNILC-Model-Spectral-Index_2048_R2.00.fits
2048 NA NA COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust emissivity index
COM_CompMap_Dust-GNILC-Model-Temperature_2048_R2.01.fits (version 2.01 includes the error map)
COM_CompMap_Dust-GNILC-Model-Temperature_2048_R2.00.fits
2048 K NA COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits Thermal dust temperature
COM_DocMap_Dust-GNILC-Beam-FWHM_R2.00.fits 128 Arcminute NA NA Effective dust beam FWHM

#### CIB maps

HDU -- COMP-MAP-CIB
File Name Nside Units Reference frequency Angular resolution Description
COM_CompMap_CIB-GNILC-F353_2048_R2.00.fits 2048 MJy/sr 353 GHz 5 arcmin CIB amplitude at 353 GHz
COM_CompMap_CIB-GNILC-F545_2048_R2.00.fits 2048 MJy/sr 545 GHz 5 arcmin CIB amplitude at 545 GHz
COM_CompMap_CIB-GNILC-F857_2048_R2.00.fits 2048 MJy/sr 857 GHz 5 arcmin CIB amplitude at 857 GHz

# Other maps that require special processing

## 2015 Lensing map

We distribute the minimum-variance (MV) lensing potential estimate presented in Planck-2015-A15[6] as part of the 2014 data release. This map represents an estimate of the CMB lensing potential on approximately 70% of the sky, and also forms the basis for the Planck 2014 lensing likelihood. It is produced using filtered temperature and polarization data from the SMICA DX11 CMB map; its construction is discussed in detail in Planck-2015-A09[7].

The estimate is contained in a single gzipped tarball named COM_CompMap_Lensing_2048_R2.00.tgz. Its contents are described below. The convergence map "dat_klm.fits" that can be found in the tarball, has been categorized as COM_Lensing-Convergence-dat-klm_2048_R2.00.fits in the Lensing Products section of the archive.

Contents of Lensing package
Filename Format Description
dat_klm.fits HEALPix FITS format alm, with Contains the estimated lensing convergence .
mask.fits.gz HEALPix FITS format map, with Contains the lens reconstruction analysis mask.
nlkk.dat ASCII text file, with columns = (, , ) The approximate noise (and signal+noise, ) power spectrum of , for the fiducial cosmology used in Planck-2015-A13[8].

### Previous Releases: (2013) Lensing Maps

2013 Release of the lensing map

Description

Here we present the minimum-variance (MV) lens reconstruction which forms the basis for the main results of Planck-2013-XVII[9]. This map is produced using a combination of the 143 and 217 GHz Planck maps on approximately 70% of the sky, and is the same map on which the Planck lensing likelihood is based.

We distribute:

PHIBAR
A (transfer-function convolved) map of the lensing potential, in NSIDE 2048 HEALPix RING format. It is obtained by convolving the lensing potential estimate with the lensing response function . This map has been band-limited between multipoles .
This is a NSIDE = 2048 HEALPix map, containing the analysis mask used in the lens reconstruction. Note: the lensing map PHIBAR may take small but non-zero values inside the masked regions because it has been bandlimited.
RLPP
This column contains the response function .
NLPP
This column contains a sky-averaged estimate of the noise power spectrum of PHIBAR, . The noise is highly coloured. There is a dependence of the noise power spectrum on the local noise level of the map, discussed in Appendix A of Planck-2013-XVII[9]. Note that the noise power spectrum estimate here is not sufficiently accurate for a power spectrum analysis.

Also, the table below gives the lensing curl-mode power spectrum data used to produce Figure A2 of Planck-2013-XVII[9]:

'MV' curl reconstruction bandpowers from Fig A2 of Planck-2013-XVII[9]
min max
2 7 -13.6379 15.3409
8 20 6.0184 4.8881
21 39 -1.0675 3.0940
40 65 0.6135 1.8474
66 100 1.5030 1.2696
101 144 1.3760 0.9950
145 198 -1.2289 0.8286
199 263 1.1910 0.7001
264 338 -0.6567 0.6197
339 425 -0.8201 0.5235
426 525 -0.7581 0.4850
526 637 -0.3201 0.5134
638 762 -0.1589 0.4073
763 901 -0.6451 0.4044
902 1054 0.4910 0.3718
1055 1221 -0.2186 0.3702
1222 1404 -0.3295 0.4146
1405 1602 -0.3647 0.4703
1603 1816 -0.1060 0.5904
1817 2020 -0.7887 0.8507

Production process

The construction PHIBAR, RLPP and NLPP are described in detail in Sec. 2.1 of Planck-2013-XVII[9]. The response function here is analogous to the the beam transfer function in a CMB temperature or polarization map. We have chosen to distribute this transfer-function convolved map rather than the normalized lens reconstruction as it is a significantly more localized function of the CMB temperature map from which it is derived, and therefore more useful for cross-correlation studies.

Inputs

This product is built from the 143 and 217 GHz Planck frequency maps, with 857GHz projected out as a dust template. The analysis mask is constructed from a combination of thresholding in the 857GHz map (to remove the regions which are most contaminated by Galactic dust) and the Type2 CO map (to reduce contamination from CO lines at 217GHz). This is joined with a compact object mask synthesized from several Planck source catalogues, including the ERCSC, SZ and PCCS . The reconstruction was performed using the fiducial beam window functions B(l) from the HFI RIMO . Details of the procedure used to produce a lensing estimate from these inputs are given in Planck-2013-XVII[9].

File names and format

A single file named

with two BINTABLE extensions containing the items described below.

For illustration, we show in the figures below the maps of the Wiener-filtered CMB lensing potential in Galactic coordinates using orthographic projection. The reconstruction was bandpass filtered to . Note that the lensing reconstruction, while highly statistically significant, is still noise dominated for every individual mode, and is at best around .

FITS file structure
1. EXTNAME = LENS-MAP
Column Name Data Type Units Description
PHIBAR Real*4 none Map of the lensing potential estimate, convolved with RLPP
MASK Int none Region over which the lensing potential is reconstructed
Keyword Data Type Value Description
PIXTYPE string HEALPIX
COORDSYS string GALACTIC Coordinate system
ORDERING string NESTED Healpix ordering
NSIDE Int*4 2048 Healpix Nside
FIRSTPIX Int*4 0
LASTPIX Int*4 50331647
2. EXTNAME = TransFun
Column Name Data Type Units Description
RLPP Real*4 none Response function
NLPP Real*4 none Sky-averaged noise power spectrum estimate
Keyword Data Type Value Description
L_MIN Int*4 0 First multipole
L_MAX Int*4 2048 Last multipole

## 2015 Compton y parameter map

We distribute here the Planck full mission Compton parameter maps (y-maps hereafter) obtained using the NILC and MILCA component-separation algorithms as described in Planck-2015-A22[10]. We also provide the ILC weights per scale and per frequency that were used to produce these y-maps. IDL routines are also provided to allow the user to apply those weights. Compton parameters produced by keeping either the first or the second half of stable pointing periods are also provided; we call these the FIRST and LAST y-maps. Additionally we construct noise estimates of full mission Planck y-maps from the half difference of the FIRST and LAST y-maps. These estimates are used to construct standard deviation maps of the noise in the full mission Planck y-maps, which are also provided. To complement this we also provide the power spectra of the noise estimate maps after correcting for inhomogeneities using the standard deviation maps. We also deliver foreground masks including point-source and Galactic masks. The file containing the masks named COM_CompMap_Compton-SZMap-masks_2048_R2.00.fits has been updated with the file COM_CompMap_Compton-SZMap-masks_2048_R2.01.fits. The difference between the two is that in the R2.00 version a region around the Galactic pole had been masked, while only the Galactic plane should be masked. This has been fixed in version R2.01.

The full data set is contained in a single gzipped tarball named COM_CompMap_YSZ_R2.00.fits.tgz. Its contents are described below. Temporarily the tarball file can be found in the Supplement Data area of the PLA (go to pla.esac.esa.int/pla, go to Subsection Supplementary Data and type "YSZ" in the search form)

Contents of COM_CompMap_YSZ_R2.00.fits.tgz}
Filename Format Description
nilc_ymaps.fits HEALPix FITS format map in Galactic coordinates with Contains the NILC full mission, FIRST and LAST y-maps.
milca_ymaps.fits HEALPix FITS format map in Galactic coordinates with Contains the MILCA full mission, FIRST and LAST y-maps.
nilc_weights_BAND.fits HEALPix FITS format map in Galactic coordinates with Contains the NILC ILC weights for the full mission y-map for band BAND 0 to 9. For each band we provide a weight map per frequency.
milca_FREQ_Csz.fits HEALPix FITS format map in Galactic coordinates with Contains the MILCA ILC weights for the full mission y-map for frequency FREQ (100, 143, 217, 353, 545, 857). For each frequency we provide a weight map per filter band.
nilc_stddev.fits HEALPix FITS format map in Galactic coordinates with Contains the stddev map for the NILC full mission y-map.
milca_stddev.fits HEALPix FITS format map in Galactic coordinates with Contains the stddev maps for the MILCA full mission y-map.
nilc_homnoise_spect.fits ASCII table FITS format Contains the angular power spectrum of the homogeneous noise in the NILC full mission y-map.
milca_homnoise_spect.fits ASCII table FITS format Contains the angular power spectrum of the homogeneous noise in the MILCA full mission y-map.
nilc_bands.fits ASCII table FITS format Contains NILC wavelet bands in multipole space

## 2015 Lensing-induced B-mode map

We distribute the Planck map of the lensing-induced B-modes presented in Planck-2015-XLI[11]. The Stokes parameter maps of the lensing B-modes are produced by combining the lensing potential map extracted from the SMICA CMB temperature map with E-mode data from the SMICA CMB polarization maps. The SMICA temperature and polarization products are described in Planck-2015-A09[7]. The lensing-induced B-mode polarization maps are used in cross-correlation with the SMICA CMB polarization maps to obtain a lensing B-mode power spectrum measurement from approximately 70% of the sky.

We provide both raw products, which can be utilized to generate products adapted to one's specific needs in term of mask, filtering, etc., and "ready-to-use" products for cross-correlation study purposes.

### Raw products

We deliver the non-normalized lensing-induced Stokes parameter maps, labelled and , which form the basis of the final lensing B-mode estimator defined in equation (6) of the paper. They are defined as

where and are the filtered pure E-mode polarization maps given in equation (5), and is the filtered lensing potential estimate.

We also provide the normalization transfer function defined in equation (12), as well as the "B70" mask that retains 69% of the sky before apodization, and its apodized version , which has an effective sky fraction .

As an example of the utilization of these products, the lensing B-mode maps that are shown in figure 4 are generated from

,

where is a Gaussian filter of 60 arcmin FWHM (introduced for highlighting large angular scales, although it can be removed or replaced by any other filter). This can be practically done by ingesting and in the HEALPix "smoothing" routine, and using the product as an input filtering function.

The lensing-induced Stokes parameter maps are provided without being masked for the user's convenience (in particular, it allows for various filtering to be tested). However, whenever they are utilized in view of obtaining scientific outcomes, they should be masked using the B70 mask, which is also provided.

### Specific products

We provide the lensing B-mode spherical harmonic coefficient estimate over approximately 70% of the sky.

It can also be constructed using the raw products described above from

,

where is a band-pass filter that retain the multipole range , and is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients , and forming . This can be done using, e.g., the HEALPix "anafast" tool.

The lensing B-mode power spectrum estimate is obtained by forming the cross-correlation power spectrum of and the B-mode data from the SMICA polarization maps :

,

where is the 5 arcmin Gaussian beam that convolves the SMICA CMB maps.

The products are contained in a single gzipped tarball named COM_Lensing-Bmode_R2.01.tgz. Its contents are described below.

Contents of Lensing B-mode package
Filename Format Description
bar_q_lens_map.fits HEALPix FITS format map in Galactic coordinates with Contains the non-normalized lensing-induced Q Stokes parameter map .
bar_u_lens_map.fits HEALPix FITS format map in Galactic coordinates with Contains the non-normalized lensing-induced U Stokes parameter map .
mask.fits HEALPix FITS format map in Galactic coordinates with The B70 mask (apodized version).
mask_noapo.fits HEALPix FITS format map in Galactic coordinates with The B70 mask without apodization.
transfer_function_b_l.dat ASCII text file, with columns = (, ) The transfer function of the lensing B-mode estimator.
lensing_bmode_b_lm.fits HEALPix FITS format alm, with Contains the lensing B-mode harmonic coefficients .
lensing_bmode_bandpowers.dat ASCII text file, with columns = (, , , , ) The lensing B-mode bandpower estimate on approximativily 70% of the sky and over the multipole range from 10 to 2000 shown in figure 10 of Planck-2015-XLI[11] (for plotting purposes only).

## 2015 Integrated Sachs-Wolfe effect map

We distribute estimates of the integrated Sachs-Wolfe (ISW) maps presented in Planck-2015-A21[12] as part of the 2015 data release. These map represents an estimate of the ISW anisotropies using different data sets:

• SEVEM DX11 CMB map, together with all the large-scale structure tracers considered in the ISW paper, namely: NVSS, SDSS, WISE, and the Planck lensing map
• Using only the large-scale structure tracers mentioned above
• SEVEM DX11 CMB map, together with NVSS and the Planck lensing maps (since these two tracers capture most of the information, as compared to SDSS and WISE)

For all the three cases, the reconstruction is provided on approximately 85% of the sky, and they are produced using the LCB filter described in the Planck ISW paper (Section 5), described in detail in Barreiro et al. 2008 and Bonavera et al. 2016.

These ISW maps, together with their corresponding uncertainties maps and masks, are given in a file named COM_CompMap_ISW_0064_R2.00.fits. Its contents are described below.

Contents of the ISW maps file: COM_CompMap_ISW_0064_R2.00.fits
Extension Format Description Used data sets
0 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map SEVEM DX11 CMB + NVSS + SDSS + WISE + Planck lensing.
1 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map NVSS + SDSS + WISE + Planck lensing.
2 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map SEVEM DX11 CMB + NVSS + Planck lensing.

## 2013 IRAM Maps of the Crab nebula

Maps of the Crab nebula at 89.189 GHz (HCO+(1-0) transition) in both temperature and polarization, prodouced from observations performed at the IRAM 30m telescope from January 9th to January 12th 2009, are delivered as a tarball of 416 KB in the file

File:Crab IRAM 2010.zip

See README in the tarball for full details. These data were used in[13]

# Previous Releases: (2015) and (2013) CMB Maps

Astrophysical components based on the 2015 data release

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 each 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-2015-A10[1] and {PlanckPapers|planck20}}.

Astrophysical foregrounds from parametric component separation We describe diffuse foreground products for the Planck 2015 release. See the Planck Foregrounds Component Separation paper Planck-2015-A10[1] for a detailed description of these products. Further scientific discussion and interpretation may be found in Planck-2015-A25[2].

Low-resolution temperature products

The Planck 2015 astrophysical component separation analysis combines Planck observations with the 9-year WMAP temperature sky maps (Bennett et al. 2013) and the 408 MHz survey by Haslam et al. (1982). This allows a direct decomposition of the low-frequency foregrounds into separate synchrotron, free-free and spinning dust components without strong spatial priors.

Inputs

The following data products are used for the low-resolution analysis:

• Full-mission 30 GHz frequency map, LFI 30 GHz frequency maps
• Full-mission 44 GHz frequency map, LFI 44 GHz frequency maps
• Full-mission 70 GHz ds1 (18+23), ds2 (19+22), and ds3 (20+21) detector-set maps
• Full-mission 100 GHz ds1 and ds2 detector set maps
• Full-mission 143 GHz ds1 and ds2 detector set maps and detectors 5, 6, and 7 maps
• Full-mission 217 GHz detector 1, 2, 3 and 4 maps
• Full-mission 353 GHz detector set ds2 and detector 1 maps
• Full-mission 545 GHz detector 2 and 4 maps
• Full-mission 857 GHz detector 2 map
• Beam-symmetrized 9-year WMAP K-band map (Lambda)
• Beam-symmetrized 9-year WMAP Ka-band map (Lambda)
• Default 9-year WMAP Q1 and Q2 differencing assembly maps (Lambda)
• Default 9-year WMAP V1 and V2 differencing assembly maps (Lambda)
• Default 9-year WMAP W1, W2, W3, and W4 differencing assembly maps (Lambda)
• Re-processed 408 MHz survey map, Remazeilles et al. (2014) (Lambda)

All maps are smoothed to a common resolution of 1 degree FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=256.

Outputs

Synchrotron emission

File name: COM_CompMap_Synchrotron-commander_0256_R2.00.fits
Reference frequency: 408 MHz
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-Synchrotron
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Amplitude posterior maximum
I_MEAN Real*4 uK_RJ Amplitude posterior mean
I_RMS Real*4 uK_RJ Amplitude posterior rms

Extension 1 -- SYNC-TEMP
Column Name Data Type Units Description
nu Real*4 Hz Frequency
intensity Real*4 W/Hz/m2/sr GALPROP z10LMPD_SUNfE spectrum

Free-free emission

File name: COM_CompMap_freefree-commander_0256_R2.00.fits
Reference frequency: NA
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-freefree
Column Name Data Type Units Description
EM_ML Real*4 cm^-6 pc Emission measure posterior maximum
EM_MEAN Real*4 cm^-6 pc Emission measure posterior mean
EM_RMS Real*4 cm^-6 pc Emission measure posterior rms
TEMP_ML Real*4 K Electron temperature posterior maximum
TEMP_MEAN Real*4 K Electron temperature posterior mean
TEMP_RMS Real*4 K Electron temperature posterior rms

Spinning dust emission

File name: COM_CompMap_AME-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin

Note: The spinning dust component has two independent constituents, each corresponding to one spdust2 component, but with different peak frequencies. The two components are stored in the two first FITS extensions, and the template frequency spectrum is stored in the third extension.

Reference frequency: 22.8 GHz
HDU -- COMP-MAP-AME1
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Primary amplitude posterior maximum
I_MEAN Real*4 uK_RJ Primary amplitude posterior mean
I_RMS Real*4 uK_RJ Primary amplitude posterior rms
FREQ_ML Real*4 GHz Primary peak frequency posterior maximum
FREQ_MEAN Real*4 GHz Primary peak frequency posterior mean
FREQ_RMS Real*4 GHz Primary peak frequency posterior rms
Reference frequency: 41.0 GHz
Peak frequency: 33.35 GHz
Extension 1 -- COMP-MAP-AME2
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Secondary amplitude posterior maximum
I_MEAN Real*4 uK_RJ Secondary amplitude posterior mean
I_RMS Real*4 uK_RJ Secondary amplitude posterior rms

Extension 2 -- SPINNING-DUST-TEMP
Column Name Data Type Units Description
nu Real*4 GHz Frequency
j_nu/nH Real*4 Jy sr-1 cm2/H spdust2 spectrum

CO line emission

File name: COM_CompMap_CO-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin

Note: The CO line emission component has three independent objects, corresponding to the J1->0, 2->1 and 3->2 lines, stored in separate extensions.

HDU -- COMP-MAP-co10
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(1-0) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(1-0) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(1-0) amplitude posterior rms
Extension 1 -- COMP-MAP-co21
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(2-1) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(2-1) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(2-1) amplitude posterior rms
Extension 2 -- COMP-MAP-co32
Column Name Data Type Units Description
I_ML Real*4 K_RJ km/s CO(3-2) amplitude posterior maximum
I_MEAN Real*4 K_RJ km/s CO(3-2) amplitude posterior mean
I_RMS Real*4 K_RJ km/s CO(3-2) amplitude posterior rms

94/100 GHz line emission

File name: COM_CompMap_xline-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-xline
Column Name Data Type Units Description
I_ML Real*4 uK_cmb Amplitude posterior maximum
I_MEAN Real*4 uK_cmb Amplitude posterior mean
I_RMS Real*4 uK_cmb Amplitude posterior rms

Note: The amplitude of this component is normalized according to the 100-ds1 detector set map, ie., it is the amplitude as measured by this detector combination.

Thermal dust emission

File name: COM_CompMap_dust-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
Reference frequency: 545 GHz
HDU -- COMP-MAP-dust
Column Name Data Type Units Description
I_ML Real*4 uK_RJ Amplitude posterior maximum
I_MEAN Real*4 uK_RJ Amplitude posterior mean
I_RMS Real*4 uK_RJ Amplitude posterior rms
TEMP_ML Real*4 K Dust temperature posterior maximum
TEMP_MEAN Real*4 K Dust temperature posterior mean
TEMP_RMS Real*4 K Dust temperature posterior rms
BETA_ML Real*4 NA Emissivity index posterior maximum
BETA_MEAN Real*4 NA Emissivity index posterior mean
BETA_RMS Real*4 NA Emissivity index posterior rms

Thermal Sunyaev-Zeldovich emission around the Coma and Virgo clusters

File name: COM_CompMap_SZ-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 60 arcmin
HDU -- COMP-MAP-SZ
Column Name Data Type Units Description
Y_ML Real*4 y_SZ Y parameter posterior maximum
Y_MEAN Real*4 y_SZ Y parameter posterior mean
Y_RMS Real*4 y_SZ Y parameter posterior rms

High-resolution temperature products

High-resolution foreground products at 7.5 arcmin FWHM are derived with the same algorithm as for the low-resolution analyses, but including frequency channels above (and including) 143 GHz.

Inputs

The following data products are used for the low-resolution analysis:

• Full-mission 143 GHz ds1 and ds2 detector set maps and detectors 5, 6, and 7 maps
• Full-mission 217 GHz detector 1, 2, 3 and 4 maps
• Full-mission 353 GHz detector set ds2 and detector 1 maps
• Full-mission 545 GHz detector 2 and 4 maps
• Full-mission 857 GHz detector 2 map

All maps are smoothed to a common resolution of 7.5 arcmin FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=2048.

Outputs

CO J2->1 emission

File name: COM_CompMap_CO21-commander_2048_R2.00.fits
Nside = 2048
Angular resolution = 7.5 arcmin
HDU -- COMP-MAP-CO21
Column Name Data Type Units Description
I_ML_FULL Real*4 K_RJ km/s Full-mission amplitude posterior maximum
I_ML_HM1 Real*4 K_RJ km/s First half-mission amplitude posterior maximum
I_ML_HM2 Real*4 K_RJ km/s Second half-mission amplitude posterior maximum
I_ML_HR1 Real*4 K_RJ km/s First half-ring amplitude posterior maximum
I_ML_HR2 Real*4 K_RJ km/s Second half-ring amplitude posterior maximum
I_ML_YR1 Real*4 K_RJ km/s "First year" amplitude posterior maximum
I_ML_YR2 Real*4 K_RJ km/s "Second year" amplitude posterior maximum

Thermal dust emission

File name: COM_CompMap_ThermalDust-commander_2048_R2.00.fits
Nside = 2048
Angular resolution = 7.5 arcmin
Reference frequency: 545 GHz
HDU -- COMP-MAP-dust
Column Name Data Type Units Description
I_ML_FULL Real*4 uK_RJ Full-mission amplitude posterior maximum
I_ML_HM1 Real*4 uK_RJ First half-mission amplitude posterior maximum
I_ML_HM2 Real*4 uK_RJ Second half-mission amplitude posterior maximum
I_ML_HR1 Real*4 uK_RJ First half-ring amplitude posterior maximum
I_ML_HR2 Real*4 uK_RJ Second half-ring amplitude posterior maximum
I_ML_YR1 Real*4 uK_RJ "First year" amplitude posterior maximum
I_ML_YR2 Real*4 uK_RJ "Second year" amplitude posterior maximum
BETA_ML_FULL Real*4 NA Full-mission emissivity index posterior maximum
BETA_ML_HM1 Real*4 NA First half-mission emissivity index posterior maximum
BETA_ML_HM2 Real*4 NA Second half-mission emissivity index posterior maximum
BETA_ML_HR1 Real*4 NA First half-ring emissivity index posterior maximum
BETA_ML_HR2 Real*4 NA Second half-ring emissivity index posterior maximum
BETA_ML_YR1 Real*4 NA "First year" emissivity index posterior maximum
BETA_ML_YR2 Real*4 NA "Second year" emissivity index posterior maximum

Polarization products

Two polarization foreground products are provided, namely synchrotron and thermal dust emission. The spectral models are assumed identical to the corresponding temperature spectral models.

Inputs

The following data products are used for the polarization analysis:

In the low-resolution analysis, all maps are smoothed to a common resolution of 40 arcmin FWHM by deconvolving their original instrumental beam and pixel window, and convolving with the new common Gaussian beam, and repixelizing at Nside=256. In the high-resolution analysis (including only CMB and thermal dust emission), the corresponding resolution is 10 arcmin FWHM and Nside=1024.

Outputs Synchrotron emission

File name: COM_CompMap_SynchrotronPol-commander_0256_R2.00.fits
Nside = 256
Angular resolution = 40 arcmin
Reference frequency: 30 GHz
HDU -- COMP-MAP-SynchrotronPol
Column Name Data Type Units Description
Q_ML_FULL Real*4 K_RJ km/s Full-mission Stokes Q posterior maximum
U_ML_FULL Real*4 K_RJ km/s Full-mission Stokes U posterior maximum
Q_ML_HM1 Real*4 K_RJ km/s First half-mission Stokes Q posterior maximum
U_ML_HM1 Real*4 K_RJ km/s First half-mission Stokes U posterior maximum
Q_ML_HM2 Real*4 K_RJ km/s Second half-mission Stokes Q posterior maximum
U_ML_HM2 Real*4 K_RJ km/s Second half-mission Stokes U posterior maximum
Q_ML_HR1 Real*4 K_RJ km/s First half-ring Stokes Q posterior maximum
U_ML_HR1 Real*4 K_RJ km/s First half-ring Stokes U posterior maximum
Q_ML_HR2 Real*4 K_RJ km/s Second half-ring Stokes Q posterior maximum
U_ML_HR2 Real*4 K_RJ km/s Second half-ring Stokes U posterior maximum
Q_ML_YR1 Real*4 K_RJ km/s "First year" Stokes Q posterior maximum
U_ML_YR1 Real*4 K_RJ km/s "First year" Stokes U posterior maximum
Q_ML_YR2 Real*4 K_RJ km/s "Second year" Stokes Q posterior maximum
U_ML_YR2 Real*4 K_RJ km/s "Second year" Stokes U posterior maximum

Thermal dust emission

File name: COM_CompMap_DustPol-commander_1024_R2.00.fits
Nside = 1024
Angular resolution = 10 arcmin
Reference frequency: 353 GHz
HDU -- COMP-MAP-DustPol
Column Name Data Type Units Description
Q_ML_FULL Real*4 uK_RJ Full-mission Stokes Q posterior maximum
U_ML_FULL Real*4 uK_RJ Full-mission Stokes U posterior maximum
Q_ML_HM1 Real*4 uK_RJ First half-mission Stokes Q posterior maximum
U_ML_HM1 Real*4 uK_RJ First half-mission Stokes U posterior maximum
Q_ML_HM2 Real*4 uK_RJ Second half-mission Stokes Q posterior maximum
U_ML_HM2 Real*4 uK_RJ Second half-mission Stokes U posterior maximum
Q_ML_HR1 Real*4 uK_RJ First half-ring Stokes Q posterior maximum
U_ML_HR1 Real*4 uK_RJ First half-ring Stokes U posterior maximum
Q_ML_HR2 Real*4 uK_RJ Second half-ring Stokes Q posterior maximum
U_ML_HR2 Real*4 uK_RJ Second half-ring Stokes U posterior maximum
Q_ML_YR1 Real*4 uK_RJ "First year" Stokes Q posterior maximum
U_ML_YR1 Real*4 uK_RJ "First year" Stokes U posterior maximum
Q_ML_YR2 Real*4 uK_RJ "Second year" Stokes Q posterior maximum
U_ML_YR2 Real*4 uK_RJ "Second year" Stokes U posterior maximum

Modelling of the thermal dust emission with the Draine and Li dust model

The Planck, IRAS, and WISE infrared observations were fit with the dust model presented by Draine & Li in 2007 (DL07). The input maps, the DL07 model, and the fitting procedure and results are presented in Planck-2014-XXIX[4]. Here, we describe the input maps and the output maps, which are made available on the Planck Legacy Archive.

Inputs

The following data have been fit:

• WISE 12 micron map
• IRAS 60 micron map
• IRAS 100 micron map
• Full-mission 353 GHz PR2 map
• Full-mission 545 GHz PR2 map
• Full-mission 857 GHz PR2 map

The CIB monopole, the CMB anisotropries and the zodiacal light were subtracted to obtain dust emission maps from the sky emission maps. All maps were smoothed to a common angular resolution of 5'.

Model Parameters

For each pixel of the inputs maps, we have fitted four parameters of the DL07 model:

• the dust mass surface density, Sigma_Mdust,
• the dust mass fraction in small PAH grains, q_PAH,
• the fraction of the total luminosity from dust heated by intense radiation fields, f_PDR,
• the starlight intensity heating the bulk of the dust, U_min.

The parameter maps and their uncertainties are gathered in one file. This file also includes the chi2 of the fit per degree of freedom.

File name: COM_CompMap_Dust-DL07-Parameters_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-Parameters
Column Name Data Type Units Description
Sigma_Mdust Real*4 Solar masses/kpc^2 Dust mass surface density
Sigma_Mdust_unc Real*4 Solar masses/kpc^2 Uncertainty (1 sigma) on Sigma_Mdust
q_PAH Real*4 dimensionless Dust mass fraction in small PAH grains
q_PAH_unc Real*4 dimensionless Uncertainty (1 sigma) on q_PAH
f_PDR Real*4 dimensionless Fraction of the total luminosity from dust heated by intense radiation fields
f_PDR_unc Real*4 dimensionless Uncertainty (1 sigma) on f_PDR
U_min Real*4 dimensionless Starlight intensity heating the bulk of the dust
U_min_unc Real*4 dimensionless Uncertainty (1 sigma) on U_min
Chi2_DOF Real*4 dimensionless Chi2 of the fit per degree of freedom

Visible extinction maps

We provide two exinctions maps at the visible V band: the value from the model (Av_DL) and the renormalized one (Av_RQ) that matches extinction estimates for quasars (QSOs) derived from the Sloan digital sky survey (SDSS) data.

File name: COM_CompMap_Dust-DL07-AvMaps_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-AvMaps
Column Name Data Type Units Description
Av_DL Real*4 magnitude Extinction in the V band from the DL model
Av_DL_unc Real*4 magnitude Uncertainty (1 sigma) on Av_DL
Av_RQ Real*4 magnitude Extinction in the V band renormalized to match estimates from QSO SDSS observations
Av_RQ_unc Real*4 magnitude Uncertainty (1 sigma) on Av_RQ

Model Fluxes

We provide the model predicted fluxes in the following file.

File name: COM_CompMap_Dust-DL07-ModelFluxes_2048_R2.00.fits
Nside = 2048
Angular resolution = 5 arcmin
HDU -- COMP-MAP-Dust-DL07-ModelFluxes
Column Name Data Type Units Description
Planck_857 Real*4 MJy/sr Model flux in the Planck 857 GHz band
Planck_545 Real*4 MJy/sr Model flux in the Planck 545 GHz band
Planck_353 Real*4 MJy/sr Model flux in the Planck 353 GHz band
WISE_12 Real*4 MJy/sr Model flux in the WISE 12 micron band
IRAS_60 Real*4 MJy/sr Model flux in the IRAS 60 micron band
IRAS_100 Real*4 MJy/sr Model flux in the IRAS 100 micron band

Other Special maps

Introduction

This section describes the map-based products that required special processing.

2015 lensing map

We distribute the minimum-variance (MV) lensing potential estimate presented in Planck-2015-A15[6] as part of the 2014 data release. This map represents an estimate of the CMB lensing potential on approximately 70% of the sky, and also forms the basis for the Planck 2014 lensing likelihood. It is produced using filtered temperature and polarization data from the SMICA DX11 CMB map; its construction is discussed in detail in Planck-2015-A09[7].

The estimate is contained in a single gzipped tarball named COM_CompMap_Lensing_2048_R2.00.tgz. Its contents are described below. The convergence map "dat_klm.fits" that can be found in the tarball, has been categorized as COM_Lensing-Convergence-dat-klm_2048_R2.00.fits in the Lensing Products section of the archive.

Contents of Lensing package
Filename Format Description
dat_klm.fits HEALPix FITS format alm, with Contains the estimated lensing convergence .
mask.fits.gz HEALPix FITS format map, with Contains the lens reconstruction analysis mask.
nlkk.dat ASCII text file, with columns = (, , ) The approximate noise (and signal+noise, ) power spectrum of , for the fiducial cosmology used in Planck-2015-A13[8].

2015 Compton y parameter map

We distribute here the Planck full mission Compton parameter maps (y-maps hereafter) obtained using the NILC and MILCA component-separation algorithms as described in Planck-2015-A22[10]. We also provide the ILC weights per scale and per frequency that were used to produce these y-maps. IDL routines are also provided to allow the user to apply those weights. Compton parameters produced by keeping either the first or the second half of stable pointing periods are also provided; we call these the FIRST and LAST y-maps. Additionally we construct noise estimates of full mission Planck y-maps from the half difference of the FIRST and LAST y-maps. These estimates are used to construct standard deviation maps of the noise in the full mission Planck y-maps, which are also provided. To complement this we also provide the power spectra of the noise estimate maps after correcting for inhomogeneities using the standard deviation maps. We also deliver foreground masks including point-source and Galactic masks.

The full data set is contained in a single gzipped tarball named COM_CompMap_YSZ_R2.00.fits.tgz. Its contents are described below. Temporarily the tarball file can be found in the Supplement Data area of the PLA (go to pla.esac.esa.int/pla, go to Subsection Supplementary Data and type "YSZ" in the search form)

Contents of COM_CompMap_YSZ_R2.00.fits.tgz}
Filename Format Description
nilc_ymaps.fits HEALPix FITS format map in Galactic coordinates with Contains the NILC full mission, FIRST and LAST y-maps.
milca_ymaps.fits HEALPix FITS format map in Galactic coordinates with Contains the MILCA full mission, FIRST and LAST y-maps.
nilc_weights_BAND.fits HEALPix FITS format map in Galactic coordinates with Contains the NILC ILC weights for the full mission y-map for band BAND 0 to 9. For each band we provide a weight map per frequency.
milca_FREQ_Csz.fits HEALPix FITS format map in Galactic coordinates with Contains the MILCA ILC weights for the full mission y-map for frequency FREQ (100, 143, 217, 353, 545, 857). For each frequency we provide a weight map per filter band.
nilc_stddev.fits HEALPix FITS format map in Galactic coordinates with Contains the stddev map for the NILC full mission y-map.
milca_stddev.fits HEALPix FITS format map in Galactic coordinates with Contains the stddev maps for the MILCA full mission y-map.
nilc_homnoise_spect.fits ASCII table FITS format Contains the angular power spectrum of the homogeneous noise in the NILC full mission y-map.
milca_homnoise_spect.fits ASCII table FITS format Contains the angular power spectrum of the homogeneous noise in the MILCA full mission y-map.
nilc_bands.fits ASCII table FITS format Contains NILC wavelet bands in multipole space

2015 lensing-induced B-mode map

We distribute the lensing-induced B-mode map presented in Planck-2015-XLI[11]. The lensing B-mode Stokes parameter maps are produced by combining the lensing potential reconstruction from the SMICA CMB temperature map with E-mode data from the SMICA CMB polarization maps. The SMICA temperature and polarization products are described in Planck-2015-A09[7]. The lensing-induced B-mode polarization maps are used in cross-correlation with the SMICA CMB polarization maps to obtain a lensing B-mode power spectrum measurement from approximately 70% of the sky, as described in Planck-2015-XLI[11].

We provide both raw products, which can be utilized to generate products adapted to one's specific needs in term of mask, filtering, etc., and "ready-to-use" products for cross-correlation study purposes.

Raw products

We deliver the non-normalized lensing-induced Stokes parameter maps, labelled and , which form the basis of the final lensing B-mode estimator defined in equation (6) of Planck-2015-XLI[11]. They are defined as

where and are the filtered pure E-mode polarization maps given in equation (5) of Planck-2015-XLI[11], and is the filtered lensing potential estimate.

We also provide the normalization transfer function defined in equation (11) of Planck-2015-XLI[11], as well as the "L70" mask that retains 69% of the sky before apodization, and its apodized version , which has an effective sky fraction .

As an example of the utilization of these products, the lensing B-mode maps that are shown in figure 4 of Planck-2015-XLI[11] are generated from

,

where is a Gaussian of 60 arcmin FWHM (introduced for highlighting large angular scales, although it can be removed or replaced by any other filter). This can be practically done by ingesting and in the HEALPix "smoothing" routine, and using the product as an input filtering function.

Specific products

We provide the lensing B-mode spherical harmonic coefficient estimate over approximately 70% of the sky.

It can also be constructed using the raw products described above from

,

where is a function for producing band-powers over the range , and is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients , and forming . This can be done using, e.g., the HEALPix "anafast" tool.

The lensing B-mode power spectrum estimate discussed in Planck-2015-XLI[11] is obtained by forming the cross-correlation power spectrum of and the B-mode data from the SMICA polarization maps :

,

where is the 5 arcmin Gaussian beam that convolves the SMICA CMB maps.

The products are contained in a single gzipped tarball named COM_Lensing-Bmode_R2.00.tgz. Its contents are described below.

Contents of Lensing B-mode package
Filename Format Description
bar_q_lens_map.fits HEALPix FITS format map in Galactic coordinates with Contains the non-normalized lensing-induced Q Stokes parameter map .
bar_u_lens_map.fits HEALPix FITS format map in Galactic coordinates with Contains the non-normalized lensing-induced U Stokes parameter map .
mask.fits HEALPix FITS format map in Galactic coordinates with The L70 mask.
mask_noapo.fits HEALPix FITS format map in Galactic coordinates with The L70 mask without apodization.
transfer_function_b_l.dat ASCII text file, with columns = (, ) The transfer function.
lensing_bmode_b_lm.fits HEALPix FITS format alm, with Contains the lensing B-mode harmonic coefficients .
lensing_bmode_bandpowers.dat ASCII text file, with columns = (, , , , ) The lensing B-mode bandpower estimate on approximativily 70% of the sky and over the multipole range from 10 to 2000 shown in figure 9 of Planck-2015-XLI[11] (for plotting purposes only).

2015 Integrated Sachs-Wolfe effect map

We distribute estimates of the integrated Sachs-Wolfe (ISW) maps presented in Planck-2015-A21[12] as part of the 2015 data release. These map represents an estimate of the ISW anisotropies using different data sets:

• SEVEM DX11 CMB map, together with all the large-scale structure tracers considered in the ISW paper, namely: NVSS, SDSS, WISE, and the Planck lensing map
• Using only the large-scale structure tracers mentioned above
• SEVEM DX11 CMB map, together with NVSS and the Planck lensing maps (since these two tracers capture most of the information, as compared to SDSS and WISE)

For all the three cases, the reconstruction is provided on approximately 85% of the sky, and they are produced using the LCB filter described in the Planck ISW paper (Section 5), described in detail in Barreiro et al. 2008 and Bonavera et al. 2016.

These ISW maps, together with their corresponding uncertainties maps and masks, are given in a file named COM_CompMap_ISW_0064_R2.00.fits. Its contents are described below.

Contents of the ISW maps file: COM_CompMap_ISW_0064_R2.00.fits
Extension Format Description Used data sets
0 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map SEVEM DX11 CMB + NVSS + SDSS + WISE + Planck lensing.
1 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map NVSS + SDSS + WISE + Planck lensing.
2 HEALPix FITS format map with three components, , Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map SEVEM DX11 CMB + NVSS + Planck lensing.

Astrophysical components based on the 2013 data release

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[14].

CMB maps

CMB maps have been produced by the SMICA, NILC, SEVEM and COMMANDER-Ruler pipelines. Of these, the SMICA product is considered the preferred one overall and is labelled Main product in the Planck Legacy Archive, while the other two are labeled as Additional product.

SMICA and NILC also produce inpainted maps, in which the Galactic Plane, some bright regions and masked point sources are replaced with a constrained CMB realization such that the whole map has the same statistical distribution as the observed CMB.

The results of SMICA, NILC and SEVEM pipeline are distributed as a FITS file containing 4 extensions:

1. CMB maps and ancillary products (3 or 6 maps)
2. CMB-cleaned foreground maps from LFI (3 maps)
3. CMB-cleaned foreground maps from HFI (6 maps)
4. Effective beam of the CMB maps (1 vector)

The results of COMMANDER-Ruler are distributed as two FITS files (the high and low resolution) containing the following extensions: High resolution N$_\rm{side}$=2048 (note that we don't provide the CMB-cleaned foregrounds maps for LFI and HFI because the Ruler resolution (~7.4') is lower than the HFI highest channel and and downgrading it will introduce noise correlation).

1. CMB maps and ancillary products (4 maps)
2. Effective beam of the CMB maps (1 vector)

Low resolution N$_\rm{side}$=256

1. CMB maps and ancillary products (3 maps)
2. 10 example CMB maps used in the montecarlo realization (10 maps)
3. Effective beam of the CMB maps (1 vector)

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 maps (CMB, noise, masks) contained in the first extension
Col name SMICA NILC SEVEM COMMANDER-Ruler H COMMANDER-Ruler L Description / notes
1: I Raw CMB anisotropy map. These are the maps used in the component separation paper Planck-2013-XII[14].
2: NOISE not applicable Noise map. Obtained by propagating the half-ring noise through the CMB cleaning pipelines.
3: VALMASK Confidence map. Pixels with an expected low level of foreground contamination. These maps are only indicative and obtained by different ad hoc methods. They cannot be used to rank the CMB maps.
4: I_MASK not applicable not applicable not applicable Some areas are masked for the production of the raw CMB maps (for NILC: point sources from 44 GHz to 857 GHz; for SMICA: point sources from 30 GHz to 857 GHz, Galatic region and additional bright regions).
5: INP_CMB not applicable not applicable not applicable Inpainted CMB map. The raw CMB maps with some regions (as indicated by INP_MASK) replaced by a constrained Gaussian realization. The inpainted SMICA map was used for PR.
6: INP_MASK not applicable not applicable not applicable Mask of the inpainted regions. For SMICA, this is identical to I_MASK. For NILC, it is not.

The component separation pipelines are described in the CMB and foreground separation section and also in Section 3 and Appendices A-D of Planck-2013-XII[14] and references therein.

The union (or common) mask is defined as the union of the confidence masks from the four component separation pipelines, the three listed above and Commander-Ruler. It leaves 73% of the sky available, and so it is denoted as U73.

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 .
Resolution (effective beam)
The SMICA map has an effective beam window function of 5 arc-minutes truncated at and deconvolved from the pixel window. It means that, ideally, one would have , where is the angular spectrum of the map, where is the angular spectrum of the CMB and is a 5-arcminute Gaussian beam function. Note however that, by convention, the effective beam window function provided in the FITS file does include a pixel window function. Therefore, it is equal to where denotes the pixel window function for an Nside=2048 pixelization.
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.
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

Principle
The Needlet-ILC (hereafter NILC) CMB map is constructed from all Planck channels from 44 to 857 GHz and includes multipoles up to . It 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)
As in the SMICA product except that there is no abrupt truncation at but a smooth transition to over the range .
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 indication of the cleanliness of a pixel. The threshold is somewhat arbitrary.
The raw NILC map has valid pixels except at the location of masked point sources. This is indicated with the mask named 'I_MASK'. The raw NILC map has been inpainted, producing the map named "INP_CMB". The 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.

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[15] and to WMAP polarisation data[16]. 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 ma (I_MASK) nor an inpainted version of the map and its associated mask. On the other hand, it provides channel maps and 100, 143, and 217 GHz 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 $N_\rm{side}$=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[14] additional 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, $N_\rm{side}$=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, $N_\rm{side}$=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[14].

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 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), as a function of multipole.

NILC

1) Pre-processing
Same pre-processing as SMICA (except the 30 GHz channel is not used).
2) Linear combination
The pre-processed Planck frequency channels from 44 to 857 GHz are linearly combined with weights which depend on location on the sky and on the multipole range up to . This is achieved using a needlet (redundant spherical wavelet) decomposition. For more details, see Planck-2013-XII[14].
3) Post-processing
The areas masked in the pre-processing plus other bright regions step are replaced by a constrained Gaussian realization as in the SMICA post-processing step.

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[17]) 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 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: where is the number of templates. If the cleaning is performed in real space, the coefficients are obtained by minimising the variance of the clean map 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).

An additional level of flexibility can also be considered: the linear coefficients can be the same for all the sky, or several regions with different sets of coefficients can be considered. The regions are then combined in a smooth way, by weighting the pixels at the boundaries, to avoid discontinuities in the clean maps. Since the method is linear, we may easily propagate the noise properties to the final CMB map. Moreover, it is very fast and permits the generation of thousands of simulations to character- ize 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.

In particular, we have cleaned the 143 GHz and 217 GHz maps using four templates constructed as the difference of the following Planck channels (smoothed to a common resolution): (30-44), (44-70), (545-353) and (857-545). 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). In order to take into account the different spectral behaviour of the foregrounds at low and high galactic latitudes, we have considered two independent regions of the sky, for which we have used a different set of coefficients. The first region corresponds to the 3 per cent brightest Galactic emission, whereas the second region is defined by the remaining 97 per cent of the sky. For the first region, the coefficients are actually estimated over the whole sky (we find that this is more optimal than perform the minimisation only on the 3 per cent brightest region, where the CMB emission is very sub-dominant) while for the second region, we exclude the 3 per cent brightest region of the sky, point sources detected at any frequency and those pixels which have not been observed at all channels. 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.

Moreover, additional CMB clean maps (at frequencies between 44 and 353 GHz) have also been produced using different combinations of templates for some of the analyses carried out in Planck-2013-XXIII[18] and Planck-2013-XIX[19]. In particular, clean maps from 44 to 353 GHz have been used for the stacking analysis presented in Planck-2013-XIX[19], while frequencies from 70 to 217 GHz were used for consistency tests in Planck-2013-XXIII[18].

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.

Summary table with the different masks that have been used by the component separation methods to pre-process and to process the frequency maps and the CMB maps.

Commander 2013 (PR1) Used for diffuse inpainting of input frequency maps Used for constrained Gaussian realization inpaiting of CMB map Description
VALMASK NO NO VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside

COM_CompMap_CMB-commrul_2048_R1.00.fits and COM_CompMap_CMB-commrul_0256_R1.00.fits for low resolution analyses.

SEVEM 2013 (PR1) Used diffuse inpainting of input frequency maps Used for Constrained Gaussian realization inpaiting of CMB map Description
VALMASK NO NO VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside
NILC 2013 (PR1) Used for diffuse inpainting of input frequency maps Used for constrained Gaussian realization inpaiting of CMB map Description
VALMASK NO NO VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits.
I_MASK NO NO I_MASK defines the regions over which CMB is not built. It is a combination of point source masks, Galactic plane mask and other bright regions like LMC, SMC, etc. It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits.
INP_MASK NO YES It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits.
SMICA 2013 (PR1) Used for diffuse inpainting of input frequency maps Used for constrained Gaussian realization inpaiting of CMB map Description
VALMASK NO NO VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside
I_MASK YES YES I_MASK defines the regions over which CMB is not built. It is a combination of point source masks, Galactic plane mask and other bright regions like LMC, SMC, etc. It can be found inside COM_CompMap_CMB-smica_2048_R1.20.fits.

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:

The files contain a minimal primary extension with no data and four BINTABLE data extensions. Each column of the BINTABLE is a (Healpix) map; the column names and the most important keywords of each extension are described in the table below; for the remaining keywords, please see the FITS files directly.

CMB map file data structure
Ext. 1. EXTNAME = COMP-MAP (BINTABLE)
Column Name Data Type Units Description
I Real*4 uK_cmb CMB temperature map
NOISE Real*4 uK_cmb Estimated noise map (note 1)
I_STDEV Real*4 uK_cmb Standard deviation, ONLY on COMMANDER-Ruler products
I_MASK Byte none Mask of regions over which CMB map is not built (Optional - see note 3)
INP_CMB Real*4 uK_cmb Inpainted CMB temperature map (Optional - see note 3)
INP_MASK Byte none mask of inpainted pixels (Optional - see note 3)
Keyword Data Type Value Description
AST-COMP String CMB Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside
METHOD String name Cleaning method (SMICA/NILC/SEVEM/COMMANDER-Ruler)
Ext. 2. EXTNAME = FGDS-LFI (BINTABLE) - Note 4
Column Name Data Type Units Description
LFI_030 Real*4 K_cmb 30 GHz foregrounds
LFI_044 Real*4 K_cmb 44 GHz foregrounds
LFI_070 Real*4 K_cmb 70 GHz foregrounds
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. 3. EXTNAME = FGDS-HFI (BINTABLE) - Note 4
Column Name Data Type Units Description
HFI_100 Real*4 K_cmb 100 GHz foregrounds
HFI_143 Real*4 K_cmb 143 GHz foregrounds
HFI_217 Real*4 K_cmb 217 GHz foregrounds
HFI_353 Real*4 K_cmb 353 GHz foregrounds
HFI_545 Real*4 MJy/sr 545 GHz foregrounds
HFI_857 Real*4 MJy/sr 857 GHz foregrounds
Keyword Data Type Value Description
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside
METHOD String name Cleaning method (SMICA/NILC/SEVEM/COMMANDER-Ruler)
Ext. 4. 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 5.
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 half-ring half-difference (HRHD) map is made by passing the half-ring frequency maps independently through the component separation pipeline, then computing half their difference. It approximates a noise realisation, and gives an indication of the uncertainties due to instrumental noise in the corresponding CMB map.
2. The confidence mask indicates where the CMB map is considered valid.
3. This column is not present in the SEVEM and COMMANDER-Ruler product file. For SEVEM these three columns give the CMB channel maps at 100, 143, and 217 GHz (columns C100, C143, and C217, in units of K_cmb.
4. The subtraction of the CMB from the sky maps in order to produce the foregrounds map is done after convolving the CMB map to the resolution of the given frequency. Those columns are not present in the COMMANDER-Ruler product file.
5. The beam window function given here includes the pixel window function for the Nside=2048 pixelization. It means that, ideally, .

The low resolution COMMANDER-Ruler CMB product is organized in the following way:

CMB low resolution COMMANDER-Ruler map file data structure
Ext. 1. EXTNAME = COMP-MAP (BINTABLE)
Column Name Data Type Units Description
I Real*4 uK_cmb CMB temperature map obtained as average over 1000 samples
I_stdev Real*4 uK_cmb Corresponding Standard deviation amongst the 1000 samples
Keyword Data Type Value Description
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside
METHOD String name Cleaning method (SMICA/NILC/SEVEM/COMMANDER-Ruler)
Ext. 2. EXTNAME = CMB-Sample (BINTABLE)
Column Name Data Type Units Description
I_SIM01 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM02 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM03 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM04 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM05 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM06 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM07 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM08 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM09 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
I_SIM10 Real*4 K_cmb CMB Sample, smoothed to 40 arcmin
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/COMMANDER-Ruler)
Ext. 4. 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.
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)

The FITS files containing the union (or common) maks is:

which contains a single BINTABLE extension with a single column (named U73) for the mask, which is boolean (FITS TFORM = B), in GALACTIC coordinates, NESTED ordering, and Nside=2048.

For the benefit of users who are only looking for a small file containing the SMICA cmb map with no additional information (noise or masks) we provide such a file here

This file contains a single extension with a single column containing the SMICA cmb temperature map.

Cautionary notes

1. The half-ring CMB maps are produced by the pipelines with parameters/weights fixed to the values obtained from the full maps. Therefore the CMB HRHD maps do not capture all of the uncertainties due to foreground modelling on large angular scales.
2. The HRHD maps for the HFI frequency channels underestimate the noise power spectrum at high l by typically a few percent. This is caused by correlations induced in the pre-processing to remove cosmic ray hits. The CMB is mostly constrained by the HFI channels at high l, and so the CMB HRHD maps will inherit this deficiency in power.
3. The beam transfer functions do not account for uncertainties in the beams of the frequency channel maps.

Astrophysical foregrounds from parametric component separation

We describe diffuse foreground products for the Planck 2013 release. See Planck Component Separation paper Planck-2013-XII[14] 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.
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[14] 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

Meta Data

Low frequency foreground component

Low frequency component at N$_\rm{side}$ = 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:

Column Name Data Type Units Description
I Real*4 uK Intensity
I_stdev Real*4 uK 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$_\rm{side}$ = 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:

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

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$_\rm{side}$=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:

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 uK temperature
T_stdev Real*4 uK standard deviation on temerature
Notes
Comment: The intensity is normalized at 353 GHz

Thermal dust component at N$_\rm{side}$=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:

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:

Column Name Data Type Units Description
BeamWF Real*4 beam profile
Notes
Comment: Beam window function used in the Component separation process

The Fits extension is composed by the columns described below:

Column Name Data Type Units Description

Thermal dust emission

Thermal emission from interstellar dust is captured by Planck-HFI over the whole sky, at all frequencies from 100 to 857 GHz. This emission is well modelled by a modified black body in the far-infrared to millimeter range. It is produced by the biggest interstellar dust grain that are in thermal equilibrium with the radiation field from stars. The grains emission properties in the sub-millimeter are therefore directly linked to their absorption properties in the UV-visible range. By modelling the thermal dust emission in the sub-millimeter, a map of dust reddening in the visible can then be constructed. The details of the model can be found here Planck-2013-XI[20].

Model of all-sky thermal dust emission

The model of the thermal dust emission is based on a modified black body (MBB) fit to the data

where is the Planck function for dust equilibirum temperature , is the amplitude of the MBB and the dust spectral index. The dust optical depth at frequency is

The dust parameters provided are , and . They were obtained by fitting the Planck data at 353, 545 and 857 GHz (from which the Planck zodiacal light model was removed) together with the IRAS 100 micron data. The latter is a combination of the 100 micron maps from IRIS (Miville-Deschenes & Lagache, 2005) and from Schlegel et al. (1998), SFD1998. The IRIS (SFD1998) map is used at scales smaller (larger) than 30 arcmin; this combination allows to take advantage of the higher angular resolution and better control of gain variations of the IRIS map and of the better removal of the zodiacal light emission of the SFD1998 map.

All maps (in Healpix Nside=2048 were smoothed to a common resolution of 5 arcmin. The CMB anisotropies, clearly visible at 353 GHz, were removed from all the HFI maps using the SMICA map. An offset was removed from each map to set a Galactic zero level, using a correlation with the LAB 21 cm data in diffuse areas of the sky (). Because the dust emission is so well correlated between frequencies in the Rayleigh-Jeans part of the dust spectrum, the zero level of the 545 and 353 GHz were improved by correlating with the 857 GHz over a larger mask (). Faint residual dipole structures, identified in the 353 and 545 GHz maps, were removed prior to the fit.

The MBB fit was performed using a minimization method, assuming errors for each data point that include instrumental noise, calibration uncertainties (on both the dust emission and the CMB anisotropies) and uncertainties on the zero levels. Because of the known degeneracy between and in the presence of noise, we performed tge fit in two steps. First we produced a model of dust emission using data smoothed to 30 arcmin; at such resolution no systematic bias of the parameters is observed. In a second step the map of the spectral index at 30 arcmin was used to fit the data for and at 5 arcmin.

The map for extra-galactic studies For the production of the map, we used a MBB fit to Planck and IRAS data from which point sources were removed to avoid contamination by galaxies. In the hypothesis of constant dust emission cross-section, the optical depth map is proportional to dust column density and therefore often used to estimate E(B-V). The analysis of Planck data revealed that the ratio and are not constant, even in the diffuse ISM, but that they depend on revealing possible spatial variations of the dust emission cross-section. It appears that the dust radiance, , i.e. the dust emission integrated in frequency, is a better tracer of column density in the diffuse ISM, implying small spatial variations of the radiation field strength at high Galactic latitude. Given those results, we also deliver the map of as a dust product and we propose to use it as an estimator of Galactic dust reddening for extra-galactic studies: .

To estimate the calibration factor q, we followed a method similar to[21] based on SDSS reddening measurements of quasars in the u, g, r, i and z bands[22]. We used a sample of 53 399 quasars, selecting objects at redshifts for which Ly does not enter the SDSS filters. The interstellar HI column densities covered on the lines of sight of this sample ranges from to . Therefore this sample allows us to estimate q in the diffuse ISM where this map of E(B-V) is intended to be used.

Dust optical depth products The dust model maps are found in the file HFI_CompMap_ThermalDustModel_2048_R1.20.fits (see the note below for an important clarification regarding the thermal dust model); its characteristics are:

• Dust optical depth at 353 GHz: Nside=2048, fwhm=5', no units
• Dust temperature: Nside 2048, fwhm=5', units=Kelvin
• Dust spectral index: Nside=2048, fwhm=30', no units
• Dust radiance: Nside=2048, fwhm=5', units=Wm-2sr-1
• E(B-V) for extragalactic studies: Nside=2048, fwhm=5', units=magnitude, obtained with data from which point sources were removed.

Dust opacity file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
TAU353 Real*4 none The optical depth at 353GHz
ERR_TAU Real*4 none Error on the optical depth
EBV Real*4 mag E(B-V) for extra-galactic studies
TEMP Real*4 K Dust temperature
ERR_TEMP Real*4 K Error on the temperature
BETA Real*4 none Dust spectral index
ERR_BETA Real*4 none Error on Beta
Keyword Data Type Value Description
AST-COMP String DUST Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively

IMPORTANT NOTE: The dust model has recently (4 December 2013) been updated and the new model is the one being distributed by default. A detailed description of the model can be found here Planck-2013-XI[20]. Users interested in the old dust model map should contact the PLA help desk.

CO emission maps

CO rotational transition line emission is present in all HFI bands but for the 143 GHz channel. It is especially significant in the 100, 217 and 353 GHz channels (due to the 115 (1-0), 230 (2-1) and 345 GHz (3-2) CO transitions). This emission comes essentially from the Galactic interstellar medium and is mainly located at low and intermediate Galactic latitudes. Three approaches (summarised below) have been used to extract CO velocity-integrated emission maps from HFI maps and to make three types of CO products. A full description of how these products were produced is given in Planck-2013-XIII[3].

• Type 1 product: it is based on a single channel approach using the fact that each CO line has a slightly different transmission in each bolometer at a given frequency channel. These transmissions can be evaluated from bandpass measurements that were performed on the ground or empirically determined from the sky using existing ground-based CO surveys. From these, the J=1-0, J=2-1 and J=3-2 CO lines can be extracted independently. As this approach is based on individual bolometer maps of a single channel, the resulting Signal-to-Noise ratio (SNR) is relatively low. The benefit, however, is that these maps do not suffer from contamination from other HFI channels (as is the case for the other approaches) and are more reliable, especially in the Galactic Plane.
• Type 2 product: this product is obtained using a multi frequency approach. Three frequency channel maps are combined to extract the J=1-0 (using the 100, 143 and 353 GHz channels) and J=2-1 (using the 143, 217 and 353 GHz channels) CO maps. Because frequency channels are combined, the spectral behaviour of other foregrounds influences the result. The two type 2 CO maps produced in this way have a higher SNR than the type 1 maps at the cost of a larger possible residual contamination from other diffuse foregrounds.
• Type 3 product: using prior information on CO line ratios and a multi-frequency component separation method, we construct a combined CO emission map with the largest possible SNR. This type 3 product can be used as a sensitive finder chart for low-intensity diffuse CO emission over the whole sky.

The released Type 1 CO maps have been produced using the MILCA-b algorithm, Type 2 maps using a specific implementation of the Commander algorithm, and the Type 3 map using the full Commander-Ruler component separation pipeline (see above).

Characteristics of the released maps are the following. We provide Healpix maps with Nside=2048. For one transition, the CO velocity-integrated line signal map is given in K_RJ.km/s units. A conversion factor from this unit to the native unit of HFI maps (K_CMB) is provided in the header of the data files and in the RIMO. Four maps are given per transition and per type:

• The signal map
• The standard deviation map (same unit as the signal),
• A null test noise map (same unit as the signal) with similar statistical properties. It is made out of half the difference of half-ring maps.
• A mask map (0B or 1B) giving the regions (1B) where the CO measurement is not reliable because of some severe identified foreground contamination.

All products of a given type belong to a single file. Type 1 products have the native HFI resolution i.e. approximately 10, 5 and 5 arcminutes for the CO 1-0, 2-1, 3-2 transitions respectively. Type 2 products have a 15 arcminute resolution The Type 3 product has a 5.5 arcminute resolution.

Type-1 CO map file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
I10 Real*4 K_RJ km/sec The CO(1-0) intensity map
E10 Real*4 K_RJ km/sec Uncertainty in the CO(1-0) intensity
N10 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M10 Byte none Region over which the CO(1-0) intensity is considered reliable
I21 Real*4 K_RJ km/sec The CO(2-1) intensity map
E21 Real*4 K_RJ km/sec Uncertainty in the CO(2-1) intensity
N21 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M21 Byte none Region over which the CO(2-1) intensity is considered reliable
I32 Real*4 K_RJ km/sec The CO(3-2) intensity map
E32 Real*4 K_RJ km/sec Uncertainty in the CO(3-2) intensity
N32 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M32 Byte none Region over which the CO(3-2) intensity is considered reliable
Keyword Data Type Value Description
AST-COMP string CO-TYPE2 Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively
CNV 1-0 Real*4 value Factor to convert CO(1-0) intensity to Kcmb (units Kcmb/(Krj*km/s))
CNV 2-1 Real*4 value Factor to convert CO(2-1) intensityto Kcmb (units Kcmb/(Krj*km/s))
CNV 3-2 Real*4 value Factor to convert CO(3-2) intensityto Kcmb (units Kcmb/(Krj*km/s))

Type-2 CO map file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
I10 Real*4 K_RJ km/sec The CO(1-0) intensity map
E10 Real*4 K_RJ km/sec Uncertainty in the CO(1-0) intensity
N10 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M10 Byte none Region over which the CO(1-0) intensity is considered reliable
I21 Real*4 K_RJ km/sec The CO(2-1) intensity map
E21 Real*4 K_RJ km/sec Uncertainty in the CO(2-1) intensity
N21 Real*4 K_RJ km/sec Map built from the half-ring difference maps
M21 Byte none Region over which the CO(2-1) intensity is considered reliable
Keyword Data Type Value Description
AST-COMP String CO-TYPE2 Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively
CNV 1-0 Real*4 value Factor to convert CO(1-0) intensity to Kcmb (units Kcmb/(Krj*km/s))
CNV 2-1 Real*4 value Factor to convert CO(2-1) intensityto Kcmb (units Kcmb/(Krj*km/s))

Type-3 CO map file data structure
1. EXTNAME = 'COMP-MAP'
Column Name Data Type Units Description
INTEN Real*4 K_RJ km/sec The CO intensity map
ERR Real*4 K_RJ km/sec Uncertainty in the intensity
NUL Real*4 K_RJ km/sec Map built from the half-ring difference maps
MASK Byte none Region over which the intensity is considered reliable
Keyword Data Type Value Description
AST-COMP String CO-TYPE1 Astrophysical compoment name
PIXTYPE String HEALPIX
COORDSYS String GALACTIC Coordinate system
ORDERING String NESTED Healpix ordering
NSIDE Int 2048 Healpix Nside for LFI and HFI, respectively
FIRSTPIX Int*4 0 First pixel number
LASTPIX Int*4 50331647 Last pixel number, for LFI and HFI, respectively
CNV Real*4 value Factor to convert to Kcmb (units Kcmb/(Krj*km/s))

# References

1. Planck 2015 results. X. Diffuse component separation: Foreground maps, Planck Collaboration, 2016, A&A, 594, A10.
2. Planck 2015 results. XXV. Diffuse low frequency Galactic foregrounds, Planck Collaboration, 2016, A&A, 594, A25.
3. Planck 2013 results. XIII. Galactic CO emission, Planck Collaboration, 2014, A&A, 571, A13.
4. Planck intermediate results. XXIX. All-sky dust modelling with Planck, IRAS, and WISE observations', Planck Collaboration Int. XXIX, A&A, 586, A132, (2016).
5. Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies, Planck Collaboration Int. XLVIII A&A, 596, A109, (2016).
6. Planck 2015 results. XV. Gravitational Lensing, Planck Collaboration, 2016, A&A, 594, A15.
7. Planck 2015 results. XI. Diffuse component separation: CMB maps, Planck Collaboration, 2016, A&A, 594, A9.
8. Planck 2015 results. XIII. Cosmological parameters, Planck Collaboration, 2016, A&A, 594, A13.
9. Planck 2013 results. XVII. Gravitational lensing by large-scale structure, Planck Collaboration, 2014, A&A, 571, A17.
10. Planck 2015 results. XXII. A map of the thermal Sunyaev-Zeldovich effect, Planck Collaboration, 2016, A&A, 594, A22.
11. Planck intermediate results. XLI. A map of lensing-induced B-modes, Planck Collaboration Int. XLI A&A, 596, A102, (2016).
12. Planck 2015 results. XXI. The integrated Sachs-Wolfe effect, Planck Collaboration, 2016, A&A, 594, A21.
13. Measurement of the Crab nebula polarization at 90 GHz as a calibrator for CMB experiments, J. Aumont, L. Conversi, C. Thum, H. Wiesemeyer, E. Falgarone, J. F. Macías-Pérez, F. Piacentini, E. Pointecouteau, N. Ponthieu, J. L. Puget, C. Rosset, J. A. Tauber, M. Tristram, A&A, 514, A70+, (2010).
14. Planck 2013 results. XI. Component separation, Planck Collaboration, 2014, A&A, 571, A11.
15. Component separation methods for the PLANCK mission, S. M. Leach, J.-F. Cardoso, C. Baccigalupi, R. B. Barreiro, M. Betoule, J. Bobin, A. Bonaldi, J. Delabrouille, G. de Zotti, C. Dickinson, H. K. Eriksen, J. González-Nuevo, F. K. Hansen, D. Herranz, M. Le Jeune, M. López-Caniego, E. Martínez-González, M. Massardi, J.-B. Melin, M.-A. Miville-Deschênes, G. Patanchon, S. Prunet, S. Ricciardi, E. Salerno, J. L. Sanz, J.-L. Starck, F. Stivoli, V. Stolyarov, R. Stompor, P. Vielva, A&A, 491, 597-615, (2008).
16. Multiresolution internal template cleaning: an application to the Wilkinson Microwave Anisotropy Probe 7-yr polarization data, R. Fernández-Cobos, P. Vielva, R. B. Barreiro, E. Martínez-González, MNRAS, 420, 2162-2169, (2012).
17. Wilkinson Microwave Anisotropy Probe 7-yr constraints on fNL with a fast wavelet estimator, B. Casaponsa, R. B. Barreiro, A. Curto, E. Martínez-González, P. Vielva, MNRAS, 411, 2019-2025, (2011).
18. Planck 2013 results. XXIII. Isotropy and statistics of the CMB, Planck Collaboration, 2014, A&A, 571, A23.
19. Planck 2013 results. XIX. The integrated Sachs-Wolfe effect, Planck Collaboration, 2014, A&A, 571, A19.
20. Planck 2013 results. XII. All-sky model of thermal dust emission, Planck Collaboration, 2014, A&A, 571, A12.
21. Calibrating Milky Way dust extinction using cosmological sources, E. Mörtsell, A&A, 550, A80, (2013).
22. The Sloan Digital Sky Survey Quasar Catalog. IV. Fifth Data Release, D. P. Schneider, P. B. Hall, G. T. Richards, M. A. Strauss, D. E. Vanden Berk, S. F. Anderson, W. N. Brandt, X. Fan, S. Jester, J. Gray, J. E. Gunn, M. U. SubbaRao, A. R. Thakar, C. Stoughton, A. S. Szalay, B. Yanny, D. G. York, N. A. Bahcall, J. Barentine, M. R. Blanton, H. Brewington, J. Brinkmann, R. J. Brunner, F. J. Castander, I. Csabai, J. A. Frieman, M. Fukugita, M. Harvanek, D. W. Hogg, Z. Ivezic, S. M. Kent, S. J. Kleinman, G. R. Knapp, R. G. Kron, J. Krzesinski, D. C. Long, R. H. Lupton, A. Nitta, J. R. Pier, D. H. Saxe, Y. Shen, S. A. Snedden, D. H. Weinberg, J. Wu, ApJ, 134, 102-117, (2007).

Flexible Image Transfer Specification

Full-Width-at-Half-Maximum

Sunyaev-Zel'dovich

Cosmic Microwave background

(Planck) High Frequency Instrument

analog to digital converter

reduced IMO

(Planck) Low Frequency Instrument

Planck Legacy Archive

(Hierarchical Equal Area isoLatitude Pixelation of a sphere, <ref name="Template:Gorski2005">HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere, K. M. Górski, E. Hivon, A. J. Banday, B. D. Wandelt, F. K. Hansen, M. Reinecke, M. Bartelmann, ApJ, 622, 759-771, (2005).