Foreground maps

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Astrophysical Components[edit]

Overview[edit]

This section describes the maps of astrophysical components produced from the Planck data. These products are derived from some or all of the nine frequency channel maps described above using different techniques and, in some cases, using other constraints from external data sets. Here we give a brief description of each product and how it is obtained, followed by a description of the FITS file containing the data and associated information. All the details can be found in Planck-2015-A10[1], Planck-2020-A4[2] and {PlanckPapers|planck20}}.

Astrophysical foregrounds from Commander[edit]

As discussed in detail in Planck-2020-A4[2], 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[3], 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[1] 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.

Low-resolution temperature products[edit]

The Planck 2015 astrophysical component separation analysis in temperature 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[edit]

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[edit]

Synchrotron emission[edit]
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[edit]
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[edit]
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[edit]
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[edit]
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[edit]
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[edit]
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[edit]

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[edit]

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[edit]

CO J2->1 emission[edit]
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[edit]
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

2018 polarization products[edit]

Two Commander-based polarization foreground products are provided, namely synchrotron and thermal dust emission. For synchrotron emission, a spatially constant spectral index of %beta=-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[edit]

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

Outputs[edit]

Synchrotron emission[edit]
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[edit]
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 the Planck 2018 observations with SMICA[edit]

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[edit]

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

Outputs[edit]

Synchrotron emission[edit]
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[edit]
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

Thermal dust emission from the Planck 2018 observations with GNILC[edit]

Using the Generalized Needlet Internal Linear Combination (GNILC) method, we produce two different estimates of thermal dust emission from the Planck 2018 data set. The first set has variable angular resolution on the sky, depending on the local signal-to-noise ratio of a given region, while the second set has a uniform angular resolution of 80 arcmin FWHM. Both products include both temperature and polarization estimates, and are associated with a 3x3 I,Q,U noise covariance matrix per pixel.

Inputs[edit]

The following data products are used for the full-mission polarization analysis:

Outputs[edit]

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
Q_STOKES Real*4 uK_RJ Full-mission Stokes Q posterior maximum
U_STOKES Real*4 uK_RJ Full-mission Stokes U posterior maximum

CO emission maps[edit]

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[4] and Planck-2015-A10[1].

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

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

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

Planck 2015 A10 Fig9 CO maps.png


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[edit]

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[5]. Here, we describe the input maps and the output maps, which are made available on the Planck Legacy Archive.

Inputs[edit]

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[edit]

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[edit]

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[edit]

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[edit]

We describe diffuse foreground products for the Planck 2015 release produced with the GNILC component separation method. See the Planck paper Planck-2016-XLVIII[6] for a detailed discussion on these products.

Method[edit]

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

Data[edit]

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

Pre-processing[edit]

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[edit]

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

Thermal dust maps[edit]

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


CIB maps[edit]

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[edit]

2015 Lensing map[edit]

We distribute the minimum-variance (MV) lensing potential estimate presented in Planck-2015-A15[7] 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[8].


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 [math]L_{\rm max}=2048[/math] Contains the estimated lensing convergence [math] \hat{\kappa}_{LM} = \frac{1}{2} L(L+1)\hat{\phi}_{LM} [/math].
mask.fits.gz HEALPix FITS format map, with [math]N_{\rm side}=2048[/math] Contains the lens reconstruction analysis mask.
nlkk.dat ASCII text file, with columns = ([math]L[/math], [math]N_L [/math], [math]C_L+N_L[/math]) The approximate noise [math]N_L[/math] (and signal+noise, [math]C_L+N_L[/math]) power spectrum of [math] \hat{\kappa}_{LM} [/math], for the fiducial cosmology used in Planck-2015-A13[9].

Previous Releases: (2013) Lensing Maps[edit]

Expand

2013 Release of the lensing map

2015 Compton y parameter map[edit]

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

2015 Lensing-induced B-mode map[edit]

We distribute the Planck map of the lensing-induced B-modes presented in Planck-2015-XLI[12]. 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[8]. 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[edit]

We deliver the non-normalized lensing-induced Stokes parameter maps, labelled [math] \bar{Q}^{\rm{lens}} [/math] and [math] \bar{U}^{\rm{lens}} [/math], which form the basis of the final lensing B-mode estimator defined in equation (6) of the paper. They are defined as

[math] \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} [/math]

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

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

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

[math] 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}) [/math],

where [math]G_\ell[/math] 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 [math]\bar{Q}^{\rm{lens}} [/math] and [math] \bar{U}^{\rm{lens}} [/math] in the HEALPix "smoothing" routine, and using the product [math] G_\ell\mathcal{B}_\ell^{-1} [/math] 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[edit]

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

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

[math] 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] [/math],

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

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

[math] \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}}[/math],

where [math] G_\ell [/math] 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 [math] N_{\rm side} = 2048 [/math] Contains the non-normalized lensing-induced Q Stokes parameter map [math] \bar Q^{\rm{lens}}({\bf n}) [/math].
bar_u_lens_map.fits HEALPix FITS format map in Galactic coordinates with [math] N_{\rm side} = 2048 [/math] Contains the non-normalized lensing-induced U Stokes parameter map [math] \bar U^{\rm{lens}}({\bf n}) [/math].
mask.fits HEALPix FITS format map in Galactic coordinates with [math] N_{\rm side} = 2048 [/math] The B70 mask (apodized version).
mask_noapo.fits HEALPix FITS format map in Galactic coordinates with [math] N_{\rm side} = 2048 [/math] The B70 mask without apodization.
transfer_function_b_l.dat ASCII text file, with columns = ([math]\ell[/math], [math] \mathcal{B}_\ell [/math]) The transfer function of the lensing B-mode estimator.
lensing_bmode_b_lm.fits HEALPix FITS format alm, with [math] \ell_{\rm max} = 2000 [/math] Contains the lensing B-mode harmonic coefficients [math] B_{\ell m}^{\rm{lens}} [/math].
lensing_bmode_bandpowers.dat ASCII text file, with columns = ([math]\ell_{\rm min}[/math], [math]\ell_{\rm b} [/math], [math]\ell_{\rm max} [/math], [math] \hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}} [/math], [math] \Delta \hat{C}_{\ell_{\rm b}}^{BB^{\rm{lens}}} [/math] ) 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[12] (for plotting purposes only).

2015 Integrated Sachs-Wolfe effect map[edit]

We distribute estimates of the integrated Sachs-Wolfe (ISW) maps presented in Planck-2015-A21[13] 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, [math]N_{\rm side}=64[/math], 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, [math]N_{\rm side}=64[/math], 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, [math]N_{\rm side}=64[/math], Ordering='Nest' Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map SEVEM DX11 CMB + NVSS + Planck lensing.


2013 IRAM Maps of the Crab nebula[edit]

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

File:Crab IRAM 2010.zip

See README in the tarball for full details. These data were used in[14]

Previous Releases: (2015) and (2013) CMB Maps[edit]

Expand

Astrophysical components based on the 2015 data release

Expand

Astrophysical components based on the 2013 data release



References[edit]

  1. ↑ Jump up to: 1.01.11.21.31.41.51.6 Planck 2015 results. X. Diffuse component separation: Foreground maps, Planck Collaboration, 2016, A&A, 594, A10.
  2. ↑ Jump up to: 2.02.1 Planck 2018 results. IV. Diffuse component separation, Planck Collaboration, 2020, A&A, 641, A4.
  3. Jump up ↑ Planck 2018 results. III. High Frequency Instrument data processing and frequency maps, Planck Collaboration, 2020, A&A, 641, A3.
  4. ↑ Jump up to: 4.04.1 Planck 2013 results. XIII. Galactic CO emission, Planck Collaboration, 2014, A&A, 571, A13.
  5. ↑ Jump up to: 5.05.1 Planck intermediate results. XXIX. All-sky dust modelling with Planck, IRAS, and WISE observations', Planck Collaboration Int. XXIX, A&A, 586, A132, (2016).
  6. Jump up ↑ Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies, Planck Collaboration Int. XLVIII A&A, 596, A109, (2016).
  7. ↑ Jump up to: 7.07.1 Planck 2015 results. XV. Gravitational Lensing, Planck Collaboration, 2016, A&A, 594, A15.
  8. ↑ Jump up to: 8.08.18.28.3 Planck 2015 results. XI. Diffuse component separation: CMB maps, Planck Collaboration, 2016, A&A, 594, A9.
  9. ↑ Jump up to: 9.09.1 Planck 2015 results. XIII. Cosmological parameters, Planck Collaboration, 2016, A&A, 594, A13.
  10. ↑ Jump up to: 10.010.110.210.310.410.5 Planck 2013 results. XVII. Gravitational lensing by large-scale structure, Planck Collaboration, 2014, A&A, 571, A17.
  11. ↑ Jump up to: 11.011.1 Planck 2015 results. XXII. A map of the thermal Sunyaev-Zeldovich effect, Planck Collaboration, 2016, A&A, 594, A22.
  12. ↑ Jump up to: 12.012.112.212.312.412.512.612.712.812.9 Planck intermediate results. XLI. A map of lensing-induced B-modes, Planck Collaboration Int. XLI A&A, 596, A102, (2016).
  13. ↑ Jump up to: 13.013.1 Planck 2015 results. XXI. The integrated Sachs-Wolfe effect, Planck Collaboration, 2016, A&A, 594, A21.
  14. Jump up ↑ Measurement of the Crab nebula polarization at 90 GHz as a calibrator for CMB experiments, J. Aumont, L. Conversi, C. Thum, H. Wiesemeyer, E. Falgarone, J. F. Macías-Pérez, F. Piacentini, E. Pointecouteau, N. Ponthieu, J. L. Puget, C. Rosset, J. A. Tauber, M. Tristram, A&A, 514, A70+, (2010).
  15. Jump up ↑ Planck 2015 results. XXV. Diffuse low frequency Galactic foregrounds, Planck Collaboration, 2016, A&A, 594, A25.
  16. ↑ Jump up to: 16.016.116.216.316.416.516.616.7 Planck 2013 results. XI. Component separation, Planck Collaboration, 2014, A&A, 571, A11.
  17. Jump up ↑ Component separation methods for the PLANCK mission, S. M. Leach, J.-F. Cardoso, C. Baccigalupi, R. B. Barreiro, M. Betoule, J. Bobin, A. Bonaldi, J. Delabrouille, G. de Zotti, C. Dickinson, H. K. Eriksen, J. González-Nuevo, F. K. Hansen, D. Herranz, M. Le Jeune, M. López-Caniego, E. Martínez-González, M. Massardi, J.-B. Melin, M.-A. Miville-Deschênes, G. Patanchon, S. Prunet, S. Ricciardi, E. Salerno, J. L. Sanz, J.-L. Starck, F. Stivoli, V. Stolyarov, R. Stompor, P. Vielva, A&A, 491, 597-615, (2008).
  18. Jump up ↑ Multiresolution internal template cleaning: an application to the Wilkinson Microwave Anisotropy Probe 7-yr polarization data, R. Fernández-Cobos, P. Vielva, R. B. Barreiro, E. Martínez-González, MNRAS, 420, 2162-2169, (2012).
  19. Jump up ↑ Wilkinson Microwave Anisotropy Probe 7-yr constraints on fNL with a fast wavelet estimator, B. Casaponsa, R. B. Barreiro, A. Curto, E. Martínez-González, P. Vielva, MNRAS, 411, 2019-2025, (2011).
  20. ↑ Jump up to: 20.020.1 Planck 2013 results. XXIII. Isotropy and statistics of the CMB, Planck Collaboration, 2014, A&A, 571, A23.
  21. ↑ Jump up to: 21.021.1 Planck 2013 results. XIX. The integrated Sachs-Wolfe effect, Planck Collaboration, 2014, A&A, 571, A19.
  22. ↑ Jump up to: 22.022.1 Planck 2013 results. XII. All-sky model of thermal dust emission, Planck Collaboration, 2014, A&A, 571, A12.
  23. Jump up ↑ Calibrating Milky Way dust extinction using cosmological sources, E. Mörtsell, A&A, 550, A80, (2013).
  24. Jump up ↑ The Sloan Digital Sky Survey Quasar Catalog. IV. Fifth Data Release, D. P. Schneider, P. B. Hall, G. T. Richards, M. A. Strauss, D. E. Vanden Berk, S. F. Anderson, W. N. Brandt, X. Fan, S. Jester, J. Gray, J. E. Gunn, M. U. SubbaRao, A. R. Thakar, C. Stoughton, A. S. Szalay, B. Yanny, D. G. York, N. A. Bahcall, J. Barentine, M. R. Blanton, H. Brewington, J. Brinkmann, R. J. Brunner, F. J. Castander, I. Csabai, J. A. Frieman, M. Fukugita, M. Harvanek, D. W. Hogg, Z. Ivezic, S. M. Kent, S. J. Kleinman, G. R. Knapp, R. G. Kron, J. Krzesinski, D. C. Long, R. H. Lupton, A. Nitta, J. R. Pier, D. H. Saxe, Y. Shen, S. A. Snedden, D. H. Weinberg, J. Wu, ApJ, 134, 102-117, (2007).

Flexible Image Transfer Specification

Full-Width-at-Half-Maximum

Sunyaev-Zel'dovich

Cosmic Microwave background

(Planck) High Frequency Instrument

analog to digital converter

reduced IMO

(Planck) Low Frequency Instrument

Planck Legacy Archive

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

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