Foreground maps

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-2020-A4 and .

Astrophysical foregrounds from Commander

As discussed in detail in Planck-2020-A4, the main Planck 2018 frequency sky maps have significantly lower systematic errors than earlier versions. At the same time, these maps are also associated with a significant limitation, in that no robust single detector or detector set maps are available. As described in Planck-2020-A3, such maps do not contain the full signal content of the true sky. As a result, only full frequency maps are distributed and used in the 2018 analysis.

For polarization analysis, this is not a significant issue, and the 2018 polarization foreground products therefore supersede the 2015 release in all respects. However, for temperature analysis the lack of single-detector maps strongly limits the ability to extract CO line emission from the data set, and it is also not possible to exclude known detector outliers; see Planck-2015-A10 for details. For these reasons, we consider the parametric foreground products from 2015 to represent a more accurate description of the true sky than the corresponding 2018 version. As a result, we do not release parametric temperature foreground products from the 2018 data set, but rather recommend continued usage of the 2015 temperature model. For polarization, we recommend usage of the 2018 model.

Two Commander-based polarization foreground products are provided for the Planck 2018 releaes, namely synchrotron and thermal dust emission. For synchrotron emission, a spatially constant spectral index of β=-3.1 is adopted. For thermal dust emission, the dust temperature is fixed to that derived from the corresponding 2018 intensity analysis, while the spectral index is fitted directly from the polarization measurements, smoothed to 3 degrees FWHM. For both synchrotron and thermal dust emission, we provide results derived from both the full-mission data set, and from the half-mission and odd-even splits.

In addition to the real observations, we also provide 300 end-to-end noise simulations processed through the algorithm with the same spectral parameters as derived from the data for each of the data splits. The filenames of these simulations have the following format:

• dx12_v3_commander_{synch,dust}_noise_{full,hm1,hm2,oe1,oe2}_00???_raw.fits

Inputs

The following data products are used for the full-mission polarization analysis (corresponding data are used for the data split products):

• 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 frequency map, LFI 70 GHz frequency maps
• Full-mission 100 GHz frequency map, HFI 100 GHz frequency maps
• Full-mission 143 GHz frequency map, HFI 143 GHz frequency maps
• Full-mission 217 GHz frequency map, HFI 217 GHz frequency maps
• Full-mission 353 GHz frequency map, HFI 353 GHz frequency maps

Outputs

Synchrotron emission

Full-mission file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_full.fits

First half-mission split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_hm1.fits

Second half-mission split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_hm2.fits

Odd ring split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_oe1.fits

Even ring split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_oe2.fits

Nside = 2048

Angular resolution = 40 arcmin

Reference frequency: 30 GHz

HDU -- COMP-MAP

Column Name	Data Type	Units	Description
Q_STOKES	Real*4	μK_RJ	Stokes Q posterior maximum
U_STOKES	Real*4	μK_RJ	Stokes U posterior maximum

Thermal dust emission

Full-mission file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_full.fits

First half-mission split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_hm1.fits

Second half-mission split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_hm2.fits

Odd ring split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_oe1.fits

Even ring split file name: COM_CompMap_QU_synchrotron-commander_2048_R3.00_oe2.fits

Nside = 2048

Angular resolution = 5 arcmin

Reference frequency: 353 GHz

HDU -- COMP-MAP

Column Name	Data Type	Units	Description
Q_STOKES	Real*4	uK_RJ	Full-mission Stokes Q posterior maximum
U_STOKES	Real*4	uK_RJ	Full-mission Stokes U posterior maximum

Astrophysical foregrounds from SMICA

Two SMICA-based polarization foreground products are provided, namely synchrotron and thermal dust emission. These are derived using the usual SMICA spectral matching algorithm, but tuned specifically for foreground reconstruction. Specifically, three assumptions are imposed on the solution: 1) CMB is neglected from the analysis; 2) synchrotron emission is assumed negligible at 353 GHz; and 3) thermal dust emission is assumed negligible at 30 GHz. Otherwise, no additional constraints are imposed on either the angular power spectrum or the spectral energy density of the two components. For both synchrotron and thermal dust emission, we provide results derived from both the full-mission data set, and from the half-mission and odd-even splits.

In addition to the real observations, we also provide 300 end-to-end noise simulations processed through the algorithm with the same spectral parameters as derived from the data for each of the data splits. The filenames of these simulations have the following format:

• dx12_v3_smica_{synch,dust}_noise_{full,hm1,hm2,oe1,oe2}_00???_raw.fits

Inputs

The following data products are used for the full-mission polarization analysis (corresponding data are used for the data split products):

• 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 frequency map, LFI 70 GHz frequency maps
• Full-mission 100 GHz frequency map, HFI 100 GHz frequency maps
• Full-mission 143 GHz frequency map, HFI 143 GHz frequency maps
• Full-mission 217 GHz frequency map, HFI 217 GHz frequency maps
• Full-mission 353 GHz frequency map, HFI 353 GHz frequency maps

Outputs

Synchrotron emission

Full-mission file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_full.fits

First half-mission split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_hm1.fits

Second half-mission split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_hm2.fits

Odd ring split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_oe1.fits

Even ring split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_oe2.fits

Nside = 2048

Angular resolution = 40 arcmin

Reference frequency: Integrated 30 GHz band; no colour corrections have been applied

HDU -- COMP-MAP

Column Name	Data Type	Units	Description
Q_STOKES	Real*4	mK_RJ	Stokes Q posterior maximum
U_STOKES	Real*4	mK_RJ	Stokes U posterior maximum

Thermal dust emission

Full-mission file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_full.fits

First half-mission split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_hm1.fits

Second half-mission split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_hm2.fits

Odd ring split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_oe1.fits

Even ring split file name: COM_CompMap_QU_synchrotron-smica_2048_R3.00_oe2.fits

Nside = 2048

Angular resolution = 12 arcmin

Reference frequency: Integrated 353 GHz band; no colour corrections have been applied

HDU -- COMP-MAP

Column Name	Data Type	Units	Description
Q_STOKES	Real*4	mK_RJ	Full-mission Stokes Q posterior maximum
U_STOKES	Real*4	mK_RJ	Full-mission 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 and Planck-2015-A10.

• 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.

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, 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. 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 and 2018 releases produced with the GNILC component separation method. See the Planck paper Planck-2016-XLVIII and Planck-2020-A4 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.

Intensity products are provided both from the 2015 and 2018 data releases, while polarization products are only provided from the 2018 data set. For analyses that only involve intensity alone, we recommend usage of the 2015 GNILC products, as these are considered more robust than the corresponding 2018 products. However, for analyses that require intensity products in order to characterize polarization measurements (such as estimation of polarization fraction), we recommend usage of the 2018 GNILC intensity products, in order to ensure that effective bandpasses are identical within a given analysis.

Data

The data used by GNILC for the analysis are the Planck data release 2 (PR2) and release 3 (PR3) 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.

2015 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_CompMap_Dust-GNILC-Radiance_2048_R2.00.fits	2048	W/m2/sr	NA	COM_CompMap_Dust-GNILC-Beam-FWHM_0128_R2.00.fits	Thermal dust radiance
COM_DocMap_Dust-GNILC-Beam-FWHM_R2.00.fits	128	Arcminute	NA	NA	Effective dust beam FWHM

2018 thermal dust maps

The 2018 GNILC thermal dust products are provided as single files that include both intensity and polarization, 3x3 IQU noise covariance matrices per pixel, and as well as local smoothing scale for the variable resolution map. The structure of the data files is the following:

Uniform resolution file name: COM_CompMap_IQU_thermaldust-gnilc-unires_2048_R3.00.fits

Variable resolution file name: COM_CompMap_IQU_thermaldust-gnilc-varres_2048_R3.00.fits

Nside = 2048

Angular resolution = 80 arcmin FWHM, or variable

Reference frequency: Integrated 353 GHz band; no colour corrections have been applied

HDU -- COMP-MAP

Column Name	Data Type	Units	Description
I_STOKES	Real*4	K_cmb	Stokes I estimate
Q_STOKES	Real*4	K_cmb	Stokes Q estimate
U_STOKES	Real*4	K_cmb	Stokes U estimate
II_COV	Real*4	K_cmb^2	Covariance matrix II element
IQ_COV	Real*4	K_cmb^2	Covariance matrix IQ element
IU_COV	Real*4	K_cmb^2	Covariance matrix IU element
QQ_COV	Real*4	K_cmb^2	Covariance matrix QQ element
QU_COV	Real*4	K_cmb^2	Covariance matrix QU element
UU_COV	Real*4	K_cmb^2	Covariance matrix UU element
FWHM	Real*4	arcmin	Local FWHM smoothing scale

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 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.

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 $L_{\rm max}=2048$	Contains the estimated lensing convergence $\hat{\kappa}_{LM} = \frac{1}{2} L(L+1)\hat{\phi}_{LM}$.
mask.fits.gz	HEALPix FITS format map, with $N_{\rm side}=2048$	Contains the lens reconstruction analysis mask.
nlkk.dat	ASCII text file, with columns = ($L$, $N_L$, $C_L+N_L$)	The approximate noise $N_L$ (and signal+noise, $C_L+N_L$) power spectrum of $\hat{\kappa}_{LM}$, for the fiducial cosmology used in Planck-2015-A13.

Previous Releases: (2013) Lensing Maps

Expand

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. 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 $\hat{\phi}$ with the lensing response function $R_L^{\phi\phi}$. This map has been band-limited between multipoles $10 \le L \le 2048$.

MASK 

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 $R_L^{\phi\phi}$.

NLPP 

This column contains a sky-averaged estimate of the noise power spectrum of PHIBAR, $N_L^{\phi\phi}$. 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. 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:

'MV' curl reconstruction bandpowers from Fig A2 of Planck-2013-XVII

$L$min	$L$max	${\hat{C}_L}^{\psi\psi} (L(L+1))^2/(2\pi)$	$std({\hat{C}_L}^{\psi\psi}) (L(L+1))^2 /(2\pi)$
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. The response function $R_L^{\phi\phi}$ 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.

File names and format

A single file named

• COM_CompMap_Lensing_2048_R1.10.fits

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 $L \in [10, 2048]$. Note that the lensing reconstruction, while highly statistically significant, is still noise dominated for every individual mode, and is at best $S/N \simeq 0.7$ around $L = 30$.

• 

  Galactic north

• 

  Galactic south

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 Lensing-induced B-mode map

We distribute the Planck map of the lensing-induced B-modes presented in Planck-2015-XLI. 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. 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 $\bar{Q}^{\rm{lens}}$ and $\bar{U}^{\rm{lens}}$, which form the basis of the final lensing B-mode estimator defined in equation (6) of the paper. They are defined as

$\begin{eqnarray} \bar Q^{\rm{lens}}({\bf n}) &=& \widetilde Q^{E}({\bf n}) \cdot \nabla \widetilde \phi({\bf n}), \\ \bar U^{\rm{lens}}({\bf n}) &=& \widetilde U^{E}({\bf n}) \cdot \nabla \widetilde \phi({\bf n}), \end{eqnarray}$

where $\widetilde Q^{E}$ and $\widetilde U^{E}$ are the filtered pure E-mode polarization maps given in equation (5), and $\widetilde \phi$ is the filtered lensing potential estimate.

We also provide the normalization transfer function $\mathcal{B}_\ell$ defined in equation (12), as well as the "B70" mask $M({\bf n})$ that retains 69% of the sky before apodization, and its apodized version $\tilde{M}({\bf n})$, which has an effective sky fraction $f_{\rm{sky}}^{\rm{eff}} = 65\%$.

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

$Q^{\rm{lens}} \pm i U^{\rm{lens}} = \sum_{\ell m} \left( G_\ell \mathcal{B}_\ell^{-1} \int d{\bf n} {\, }_{\pm 2}Y_{\ell m}^*({\bf n}) \left(\bar{Q}^{\rm{lens}} \pm i \bar{U}^{\rm{lens}} \right) \right) {\, }_{\pm 2}Y_{\ell m}({\bf n})$,

where $G_\ell$ 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 $\bar{Q}^{\rm{lens}}$ and $\bar{U}^{\rm{lens}}$ in the HEALPix "smoothing" routine, and using the product $G_\ell\mathcal{B}_\ell^{-1}$ 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 $B_{\ell m}^{\rm{lens}}$ over approximately 70% of the sky.

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

$B_{\ell m}^{\rm{lens}} = f_{10 \rightarrow 2000} \, \mathcal{B}_\ell^{-1} \, \, {\, }_{\pm 2}\mathcal{Y} \left[ \tilde{M}({\bf n}) \left( \bar{Q}^{\rm{lens}}({\bf n}) \pm i \bar{U}^{\rm{lens}}({\bf n}) \right) \right]$,

where $f_{10 \rightarrow 2000}$ is a band-pass filter that retain the multipole range $10 \le \ell \le 2000$, and ${\, }_{\pm2}\mathcal{Y}$ is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients ${\, }_{+2}a_{\ell m}$, ${\, }_{-2}a_{\ell m}$ and forming $1/(2i)\left({\, }_{+2}a_{\ell m} - {\, }_{-2}a_{\ell m}\right)$. This can be done using, e.g., the HEALPix "anafast" tool.

The lensing B-mode power spectrum estimate $\hat{C}_\ell^{BB^{\rm{lens}}}$ is obtained by forming the cross-correlation power spectrum of $B_{\ell m}^{\rm{lens}}$ and the B-mode data from the SMICA polarization maps $B_{\ell m}$:

$\hat{C}_\ell^{BB^{\rm{lens}}} = \frac{\left(f_{\rm{sky}}^{\rm{eff}}\right)^{-1}}{2 \ell +1} G_\ell^{-2} \sum_m B_{\ell m}^* B_{\ell m}^{\rm{lens}}$,

where $G_\ell$ 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 $N_{\rm side} = 2048$	Contains the non-normalized lensing-induced Q Stokes parameter map $\bar Q^{\rm{lens}}({\bf n})$.
bar_u_lens_map.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	Contains the non-normalized lensing-induced U Stokes parameter map $\bar U^{\rm{lens}}({\bf n})$.
mask.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	The B70 mask (apodized version).
mask_noapo.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	The B70 mask without apodization.
transfer_function_b_l.dat	ASCII text file, with columns = ($\ell$, $\mathcal{B}_\ell$)	The transfer function of the lensing B-mode estimator.
lensing_bmode_b_lm.fits	HEALPix FITS format alm, with $\ell_{\rm max} = 2000$	Contains the lensing B-mode harmonic coefficients $B_{\ell m}^{\rm{lens}}$.
lensing_bmode_bandpowers.dat	ASCII text file, with columns = ($\ell_{\rm min}$, $\ell_{\rm b}$, $\ell_{\rm max}$, $\hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}}$, $\Delta \hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}}$ )	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 (for plotting purposes only).

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. 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.

Update 04 Aug 2017: 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 updated data set is contained in a single gzipped tarball named COM_CompMap_YSZ_R2.01.fits.tgz. The R2.00 version of the mask is not available in the PLA anymore, but can be requested via the PLA Helpdesk.

The contents of the full data set are described below.

Contents of COM_CompMap_YSZ_R2.01.fits.tgz

Filename	Format	Description
nilc_ymaps.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side}=2048$	Contains the NILC full mission, FIRST and LAST y-maps.
milca_ymaps.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	Contains the MILCA full mission, FIRST and LAST y-maps.
nilc_weights_BAND.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 128$	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 $N_{\rm side} = 2048$	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 $N_{\rm side} = 2048$	Contains the stddev map for the NILC full mission y-map.
milca_stddev.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	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.
masks.fits	HEALPix FITS format map, with $N_{\rm side} = 2048$	Contains foreground masks.
nilc_bands.fits	ASCII table FITS format	Contains NILC wavelet bands in multipole space

2015 Integrated Sachs-Wolfe effect map

We distribute estimates of the integrated Sachs-Wolfe (ISW) maps presented in Planck-2015-A21 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, $N_{\rm side}=64$, 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, $N_{\rm side}=64$, 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, $N_{\rm side}=64$, Ordering='Nest'	Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map	SEVEM DX11 CMB + NVSS + Planck lensing.

2015 Low-frequency foregrounds maps (Planck only & Planck+WMAP)

1) CMB/free-free/Dust Nulled ILC at 28.4 GHz (Planck only)

Linear combination of Planck 28.4, 44.1, 143 and 353 GHz maps (all at 1 degree resolution), with weights listed in column w_2 of Table 1 in Planck-2015-A25. These weights exactly null the CMB, almost exactly null free-free emission, and null thermal dust emission to high accuracy except along the inner Galactic plane,where the brightness is uncertain by around 20% due to variation in the dust spectrum. The normalisation leaves a beta = -3 power law at the same amplitude as in the Planck 28.4 GHz map. (As presented in Fig. 3a of Planck 2015 Results XXV.)

2) CMB/free-free/Dust Nulled ILC at 28.4 GHz (Planck + WMAP) Linear combination of WMAP K, Ka, and Q band, and Planck 28.4, 44.1, 143 and 353 GHz maps (all at 1 degree resolution), with weights listed in column w_3 of Table 1 in Planck-2015-A25. These weights exactly null the CMB, almost exactly null free-free emission, and null thermal dust emission to high accuracy except along the inner Galactic plane, where the brightness is uncertain by around 20% due to variation in the dust spectrum. The normalisation leaves a beta = -3 power law at the same amplitude as in the Planck 28.4 GHz map. (As presented in Fig. 3b of Planck-2015-A25.)

Previous Releases: (2015) and (2013) Foreground Maps

Expand

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 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 for a detailed description of these products. Further scientific discussion and interpretation may be found in Planck-2015-A25.

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:

• (Only low-resolution analysis) Full-mission 30 GHz frequency map, LFI 30 GHz frequency maps
• (Only low-resolution analysis) Full-mission 44 GHz frequency map, LFI 44 GHz frequency maps
• (Only low-resolution analysis) Full-mission 70 GHz frequency map, LFI 70 GHz frequency maps
• Full-mission 100 GHz frequency map, HFI 100 GHz frequency maps
• Full-mission 143 GHz frequency map, HFI 143 GHz frequency maps
• Full-mission 217 GHz frequency map, HFI 217 GHz frequency maps
• Full-mission 353 GHz frequency map, HFI 353 GHz frequency maps

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. 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 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.

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 $L_{\rm max}=2048$	Contains the estimated lensing convergence $\hat{\kappa}_{LM} = \frac{1}{2} L(L+1)\hat{\phi}_{LM}$.
mask.fits.gz	HEALPix FITS format map, with $N_{\rm side}=2048$	Contains the lens reconstruction analysis mask.
nlkk.dat	ASCII text file, with columns = ($L$, $N_L$, $C_L+N_L$)	The approximate noise $N_L$ (and signal+noise, $C_L+N_L$) power spectrum of $\hat{\kappa}_{LM}$, for the fiducial cosmology used in Planck-2015-A13.

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. 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 $N_{\rm side}=2048$	Contains the NILC full mission, FIRST and LAST y-maps.
milca_ymaps.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	Contains the MILCA full mission, FIRST and LAST y-maps.
nilc_weights_BAND.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 128$	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 $N_{\rm side} = 2048$	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 $N_{\rm side} = 2048$	Contains the stddev map for the NILC full mission y-map.
milca_stddev.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	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.
masks.fits	HEALPix FITS format map, with $N_{\rm side} = 2048$	Contains foreground masks.
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. 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. 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.

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 $\bar{Q}^{\rm{lens}}$ and $\bar{U}^{\rm{lens}}$, which form the basis of the final lensing B-mode estimator defined in equation (6) of Planck-2015-XLI. They are defined as

$\begin{eqnarray} \bar Q^{\rm{lens}}({\bf n}) &=& \widetilde Q^{E}({\bf n}) \cdot \nabla \widetilde \phi({\bf n}), \\ \bar U^{\rm{lens}}({\bf n}) &=& \widetilde U^{E}({\bf n}) \cdot \nabla \widetilde \phi({\bf n}), \end{eqnarray}$

where $\widetilde Q^{E}$ and $\widetilde U^{E}$ are the filtered pure E-mode polarization maps given in equation (5) of Planck-2015-XLI, and $\widetilde \phi$ is the filtered lensing potential estimate.

We also provide the normalization transfer function $\mathcal{B}_\ell$ defined in equation (11) of Planck-2015-XLI, as well as the "L70" mask $M({\bf n})$ that retains 69% of the sky before apodization, and its apodized version $\tilde{M}({\bf n})$, which has an effective sky fraction $f_{\rm{sky}}^{\rm{eff}} = 65\%$.

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

$Q^{\rm{lens}} \pm i U^{\rm{lens}} = \sum_{\ell m} \left( G_\ell \mathcal{B}_\ell^{-1} \int d{\bf n} {\, }_{\pm 2}Y_{\ell m}^*({\bf n}) \left(\bar{Q}^{\rm{lens}} \pm i \bar{U}^{\rm{lens}} \right) \right) {\, }_{\pm 2}Y_{\ell m}({\bf n})$,

where $G_\ell$ 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 $\bar{Q}^{\rm{lens}}$ and $\bar{U}^{\rm{lens}}$ in the HEALPix "smoothing" routine, and using the product $G_\ell\mathcal{B}_\ell^{-1}$ as an input filtering function.

Specific products

We provide the lensing B-mode spherical harmonic coefficient estimate $B_{\ell m}^{\rm{lens}}$ over approximately 70% of the sky.

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

$B_{\ell m}^{\rm{lens}} = f_{10 \rightarrow 2000} \, \mathcal{B}_\ell^{-1} \, \, {\, }_{\pm 2}\mathcal{Y} \left[ \tilde{M}({\bf n}) \left( \bar{Q}^{\rm{lens}}({\bf n}) \pm i \bar{U}^{\rm{lens}}({\bf n}) \right) \right]$,

where $f_{10 \rightarrow 2000}$ is a function for producing band-powers over the range $10 \le \ell \le 2000$, and ${\, }_{\pm2}\mathcal{Y}$ is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients ${\, }_{+2}a_{\ell m}$, ${\, }_{-2}a_{\ell m}$ and forming $1/(2i)\left({\, }_{+2}a_{\ell m} - {\, }_{-2}a_{\ell m}\right)$. This can be done using, e.g., the HEALPix "anafast" tool.

The lensing B-mode power spectrum estimate $\hat{C}_\ell^{BB^{\rm{lens}}}$ discussed in Planck-2015-XLI is obtained by forming the cross-correlation power spectrum of $B_{\ell m}^{\rm{lens}}$ and the B-mode data from the SMICA polarization maps $B_{\ell m}$:

$\hat{C}_\ell^{BB^{\rm{lens}}} = \frac{\left(f_{\rm{sky}}^{\rm{eff}}\right)^{-1}}{2 \ell +1} G_\ell^{-2} \sum_m B_{\ell m}^* B_{\ell m}^{\rm{lens}}$,

where $G_\ell$ 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 $N_{\rm side} = 2048$	Contains the non-normalized lensing-induced Q Stokes parameter map $\bar Q^{\rm{lens}}({\bf n})$.
bar_u_lens_map.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	Contains the non-normalized lensing-induced U Stokes parameter map $\bar U^{\rm{lens}}({\bf n})$.
mask.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	The L70 mask.
mask_noapo.fits	HEALPix FITS format map in Galactic coordinates with $N_{\rm side} = 2048$	The L70 mask without apodization.
transfer_function_b_l.dat	ASCII text file, with columns = ($\ell$, $\mathcal{B}_\ell$)	The transfer function.
lensing_bmode_b_lm.fits	HEALPix FITS format alm, with $\ell_{\rm max} = 2000$	Contains the lensing B-mode harmonic coefficients $B_{\ell m}^{\rm{lens}}$.
lensing_bmode_bandpowers.dat	ASCII text file, with columns = ($\ell_{\rm min}$, $\ell_{\rm b}$, $\ell_{\rm max}$, $\hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}}$, $\Delta \hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}}$ )	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 (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 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, $N_{\rm side}=64$, 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, $N_{\rm side}=64$, 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, $N_{\rm side}=64$, Ordering='Nest'	Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map	SEVEM DX11 CMB + NVSS + Planck lensing.

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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.

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.
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 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 $\ell = 4000$.

Resolution (effective beam)

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

Confidence mask

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

Masks and inpainting

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

NILC

Principle

The Needlet-ILC (hereafter NILC) CMB map is constructed from all Planck channels from 44 to 857 GHz and includes multipoles up to $\ell = 3200$. 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 $\ell_{max}= 3200$ but a smooth transition to $0$ over the range $2700\leq\ell\leq 3200$.

Confidence mask

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

Masks and inpainting

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 and to WMAP polarisation data. In the cleaning process, no assumptions about the foregrounds or noise levels are needed, rendering the technique very robust. Note that unlike the other products, SEVEM does not provide the mask of regions not used in the productions of the CMB 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 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.

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 $\ell = 4000$ 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$_\rm{RJ}$), 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 $\ell = 3200$. This is achieved using a needlet (redundant spherical wavelet) decomposition. For more details, see Planck-2013-XII.

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) 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 $t_j$ 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: $T_c(\mathbf{x}, ν) = d(\mathbf{x}, ν) − \sum_{j=1}^{n_t} α_j t(\mathbf{x})$ where $n_t$ is the number of templates. If the cleaning is performed in real space, the $α_j$ coefficients are obtained by minimising the variance of the clean map $T_c$ 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 and Planck-2013-XIX. In particular, clean maps from 44 to 353 GHz have been used for the stacking analysis presented in Planck-2013-XIX, while frequencies from 70 to 217 GHz were used for consistency tests in Planck-2013-XXIII.

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.

Masks

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 COM_CompMap_CMB-sevem_2048_R1.12.fits.
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 COM_CompMap_CMB-smica_2048_R1.20.fits.
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.
INP_MASK	YES	YES	INP_MASK for SMICA 2013 release is identical to I_MASK above.

Inputs

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

File names and structure

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

• COM_CompMap_CMB-nilc_2048_R1.20.fits
• COM_CompMap_CMB-sevem_2048_R1.12.fits
• COM_CompMap_CMB-smica_2048_R1.20.fits
• COM_CompMap_CMB-commrul_2048_R1.00.fits
• COM_CompMap_CMB-commrul_0256_R1.00.fits

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
VALMASK	Byte	none	Confidence mask (note 2)
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 $B_\ell$ given here includes the pixel window function $p_\ell$ for the Nside=2048 pixelization. It means that, ideally, $C_\ell(map) = C_\ell(sky) \, B_\ell^2 \, p_\ell^2$.

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
VALMASK	Byte	none	Confidence mask
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:

• COM_Mask_CMB-common

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

• COM_CompMap_CMB-smica-field-I_2048_R1.20.fits

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 for a detailed description and astrophysical discussion of those.

Product description

Low frequency foreground component

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

Thermal dust

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

Sky mask

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

Production process

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

Inputs

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

Related products

None.

File names

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

Meta Data

Low frequency foreground component

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

FITS header

Column Name	Data Type	Units	Description
I	Real*4	uK[math]_{CMB}[/math]	Intensity
I_stdev	Real*4	uK[math]_{CMB}[/math]	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:

FITS header

Column Name	Data Type	Units	Description
I	Real*8	uK[math]_{CMB}[/math]	Intensity
I_stdev	Real*8	uK[math]_{CMB}[/math]	standard deviation of intensity
I_hr1	Real*8	uK[math]_{CMB}[/math]	Intensity on half ring 1
I_hr2	Real*8	uK[math]_{CMB}[/math]	Intensity on half ring 2

Notes

Comment: The intensity was computed after mixing matrix application

Name HDU -- BeamWF

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

FITS header

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

Notes

Comment: Beam window function used in the Component separation process

Thermal dust

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

FITS header

Column Name	Data Type	Units	Description
I	Real*4	MJy/sr	Intensity
I_stdev	Real*4	MJy/sr	standard deviation of intensity
Em	Real*4		emissivity
Em_stdev	Real*4		standard deviation on emissivity
T	Real*4	uK[math]_{CMB}[/math]	temperature
T_stdev	Real*4	uK[math]_{CMB}[/math]	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:

FITS header

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

Name HDU -- BeamWF

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

FITS header

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

Notes

Comment: Beam window function used in the Component separation process

Sky mask

File name: COM_CompMap_Mask-rulerminimal_2048.fits

Name HDU -- COMP-MASK

The Fits extension is composed by the columns described below:

FITS header

Column Name	Data Type	Units	Description
Mask	Real*4		Mask

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.

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 $I_\nu$

$I_\nu = A\, B_\nu(T)\, \nu^\beta$

where $B_\nu(T)$ is the Planck function for dust equilibirum temperature $T$, $A$ is the amplitude of the MBB and $\beta$ the dust spectral index. The dust optical depth at frequency $\nu$ is

$\tau_\nu = I_\nu / B_\nu(T) = A\, \nu^\beta$

The dust parameters provided are $T$, $\beta$ and $\tau_{353}$. 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 ($N_{HI} \lt 2\times10^{20} cm^{-2}$). 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 ($N_{HI} \lt 3\times10^{20} cm^{-2}$). 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 $\chi^2$ 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 $T$ and $\beta$ 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 $\beta$ at 30 arcmin was used to fit the data for $T$ and $\tau_{353}$ at 5 arcmin.

The $E(B-V)$ map for extra-galactic studies For the production of the $E(B-V)$ 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 $\tau_{353}$ is proportional to dust column density and therefore often used to estimate E(B-V). The analysis of Planck data revealed that the ratio $\tau_{353}/N_{HI}$ and $\tau_{353}/E(B-V)$ are not constant, even in the diffuse ISM, but that they depend on $T$ revealing possible spatial variations of the dust emission cross-section. It appears that the dust radiance, $R$, 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 $R$ as a dust product and we propose to use it as an estimator of Galactic dust reddening for extra-galactic studies: $E(B-V) = q\, R$.

To estimate the calibration factor q, we followed a method similar to based on SDSS reddening measurements of quasars in the u, g, r, i and z bands. We used a sample of 53 399 quasars, selecting objects at redshifts for which Ly$\alpha$ does not enter the SDSS filters. The interstellar HI column densities covered on the lines of sight of this sample ranges from $0.5$ to $10\times10^{20}\,cm^{-2}$. 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
RADIANCE	Real*4	Wm-2sr-1	Integrated emission
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. 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.

• 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))