Difference between revisions of "Foreground maps"
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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 {{PlanckPapers|planck2014-a12}} 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.''' | 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 {{PlanckPapers|planck2014-a12}} 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. | 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. |
Revision as of 08:05, 6 July 2018
Contents
- 1 Astrophysical Components
- 2 Other maps that require special processing
- 3 Previous Releases: (2015) and (2013) Foreground Maps
- 4 References
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-2020-A4[1] and [2].
Astrophysical foregrounds from Commander[edit]
As discussed in detail in Planck-2020-A4[1], 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[4] 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[edit]
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[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
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
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[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):
- 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[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
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
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[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[5] and Planck-2015-A10[4].
- 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[4].
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[4], 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
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
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[6]. 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
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
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
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 and 2018 releases produced with the GNILC component separation method. See the Planck paper Planck-2016-XLVIII[7] and Planck-2020-A4[1] 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.
- 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[edit]
- 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[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.
2015 thermal dust maps[edit]
2018 thermal dust maps[edit]
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
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[edit]
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[8] 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[9].
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.
Filename | Format | Description |
---|---|---|
dat_klm.fits | HEALPix FITS format alm, with | Contains the estimated lensing convergence | .
mask.fits.gz | HEALPix FITS format map, with | Contains the lens reconstruction analysis mask. |
nlkk.dat | ASCII text file, with columns = ( | , , )The approximate noise Planck-2015-A13[10]. | (and signal+noise, ) power spectrum of , for the fiducial cosmology used in
Previous Releases: (2013) Lensing Maps[edit]
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[11]. This map is produced using a combination of the 143 and 217 GHz Planck maps on approximately 70% of the sky, and is the same map on which the Planck lensing likelihood is based.
We distribute:
- PHIBAR
- A (transfer-function convolved) map of the lensing potential, in NSIDE 2048 HEALPix RING format. It is obtained by convolving the lensing potential estimate with the lensing response function . This map has been band-limited between multipoles .
- 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 .
- NLPP
- This column contains a sky-averaged estimate of the noise power spectrum of PHIBAR, Planck-2013-XVII[11]. Note that the noise power spectrum estimate here is not sufficiently accurate for a power spectrum analysis. . 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
Also, the table below gives the lensing curl-mode power spectrum data used to produce Figure A2 of Planck-2013-XVII[11]:
min | max | ||
---|---|---|---|
2 | 7 | -13.6379 | 15.3409 |
8 | 20 | 6.0184 | 4.8881 |
21 | 39 | -1.0675 | 3.0940 |
40 | 65 | 0.6135 | 1.8474 |
66 | 100 | 1.5030 | 1.2696 |
101 | 144 | 1.3760 | 0.9950 |
145 | 198 | -1.2289 | 0.8286 |
199 | 263 | 1.1910 | 0.7001 |
264 | 338 | -0.6567 | 0.6197 |
339 | 425 | -0.8201 | 0.5235 |
426 | 525 | -0.7581 | 0.4850 |
526 | 637 | -0.3201 | 0.5134 |
638 | 762 | -0.1589 | 0.4073 |
763 | 901 | -0.6451 | 0.4044 |
902 | 1054 | 0.4910 | 0.3718 |
1055 | 1221 | -0.2186 | 0.3702 |
1222 | 1404 | -0.3295 | 0.4146 |
1405 | 1602 | -0.3647 | 0.4703 |
1603 | 1816 | -0.1060 | 0.5904 |
1817 | 2020 | -0.7887 | 0.8507 |
Production process
The construction PHIBAR, RLPP and NLPP are described in detail in Sec. 2.1 of Planck-2013-XVII[11]. The response function here is analogous to the the beam transfer function in a CMB temperature or polarization map. We have chosen to distribute this transfer-function convolved map rather than the normalized lens reconstruction as it is a significantly more localized function of the CMB temperature map from which it is derived, and therefore more useful for cross-correlation studies.
Inputs
This product is built from the 143 and 217 GHz Planck frequency maps, with 857GHz projected out as a dust template. The analysis mask is constructed from a combination of thresholding in the 857GHz map (to remove the regions which are most contaminated by Galactic dust) and the Type2 CO map (to reduce contamination from CO lines at 217GHz). This is joined with a compact object mask synthesized from several Planck source catalogues, including the ERCSC, SZ and PCCS . The reconstruction was performed using the fiducial beam window functions B(l) from the HFI RIMO . Details of the procedure used to produce a lensing estimate from these inputs are given in Planck-2013-XVII[11].
File names and format
A single file named
with two BINTABLE extensions containing the items described below.
For illustration, we show in the figures below the maps of the Wiener-filtered CMB lensing potential in Galactic coordinates using orthographic projection. The reconstruction was bandpass filtered to . Note that the lensing reconstruction, while highly statistically significant, is still noise dominated for every individual mode, and is at best around .
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[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[9]. 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
and , which form the basis of the final lensing B-mode estimator defined in equation (6) of the paper. They are defined as
where
and are the filtered pure E-mode polarization maps given in equation (5), and is the filtered lensing potential estimate.We also provide the normalization transfer function
defined in equation (12), as well as the "B70" mask that retains 69% of the sky before apodization, and its apodized version , which has an effective sky fraction .As an example of the utilization of these products, the lensing B-mode maps that are shown in figure 4 are generated from
,
where FWHM (introduced for highlighting large angular scales, although it can be removed or replaced by any other filter). This can be practically done by ingesting and in the HEALPix "smoothing" routine, and using the product as an input filtering function.
is a Gaussian filter of 60 arcminThe 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
over approximately 70% of the sky.It can also be constructed using the raw products described above from
,
where HEALPix "anafast" tool.
is a band-pass filter that retain the multipole range , and is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients , and forming . This can be done using, e.g., theThe lensing B-mode power spectrum estimate
is obtained by forming the cross-correlation power spectrum of and the B-mode data from the SMICA polarization maps :,
where CMB maps.
is the 5 arcmin Gaussian beam that convolves the SMICA
The products are contained in a single gzipped tarball named COM_Lensing-Bmode_R2.01.tgz. Its contents are described below.
Filename | Format | Description |
---|---|---|
bar_q_lens_map.fits | HEALPix FITS format map in Galactic coordinates with | Contains the non-normalized lensing-induced Q Stokes parameter map | .
bar_u_lens_map.fits | HEALPix FITS format map in Galactic coordinates with | Contains the non-normalized lensing-induced U Stokes parameter map | .
mask.fits | HEALPix FITS format map in Galactic coordinates with | The B70 mask (apodized version). |
mask_noapo.fits | HEALPix FITS format map in Galactic coordinates with | The B70 mask without apodization. |
transfer_function_b_l.dat | ASCII text file, with columns = ( | , )The transfer function of the lensing B-mode estimator. |
lensing_bmode_b_lm.fits | HEALPix FITS format alm, with | Contains the lensing B-mode harmonic coefficients | .
lensing_bmode_bandpowers.dat | ASCII text file, with columns = ( | , , , , )The lensing B-mode bandpower estimate on approximativily 70% of the sky and over the multipole range from 10 to 2000 shown in figure 10 of Planck-2015-XLI[12] (for plotting purposes only). |
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[13]. 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.
Filename | Format | Description |
---|---|---|
nilc_ymaps.fits | HEALPix FITS format map in Galactic coordinates with | Contains the NILC full mission, FIRST and LAST y-maps. |
milca_ymaps.fits | HEALPix FITS format map in Galactic coordinates with | Contains the MILCA full mission, FIRST and LAST y-maps. |
nilc_weights_BAND.fits | HEALPix FITS format map in Galactic coordinates with | Contains the NILC ILC weights for the full mission y-map for band BAND 0 to 9. For each band we provide a weight map per frequency. |
milca_FREQ_Csz.fits | HEALPix FITS format map in Galactic coordinates with | Contains the MILCA ILC weights for the full mission y-map for frequency FREQ (100, 143, 217, 353, 545, 857). For each frequency we provide a weight map per filter band. |
nilc_stddev.fits | HEALPix FITS format map in Galactic coordinates with | Contains the stddev map for the NILC full mission y-map. |
milca_stddev.fits | HEALPix FITS format map in Galactic coordinates with | Contains the stddev maps for the MILCA full mission y-map. |
nilc_homnoise_spect.fits | ASCII table FITS format | Contains the angular power spectrum of the homogeneous noise in the NILC full mission y-map. |
milca_homnoise_spect.fits | ASCII table FITS format | Contains the angular power spectrum of the homogeneous noise in the MILCA full mission y-map. |
masks.fits | HEALPix FITS format map, with | Contains foreground masks. |
nilc_bands.fits | ASCII table FITS format | Contains NILC wavelet bands in multipole space |
2015 Integrated Sachs-Wolfe effect map[edit]
We distribute estimates of the integrated Sachs-Wolfe (ISW) maps presented in Planck-2015-A21[14] 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.
Extension | Format | Description | Used data sets |
---|---|---|---|
0 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | SEVEM DX11 CMB + NVSS + SDSS + WISE + Planck lensing. |
1 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | NVSS + SDSS + WISE + Planck lensing. |
2 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | SEVEM DX11 CMB + NVSS + Planck lensing. |
2015 Low-frequency foregrounds maps (Planck only & Planck+WMAP)[edit]
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[15]. 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[15]. 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[15].)
Previous Releases: (2015) and (2013) Foreground Maps[edit]
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[4] 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[4] for a detailed description of these products. Further scientific discussion and interpretation may be found in Planck-2015-A25[15].
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
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 |
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
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
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
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 |
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.
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 |
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 |
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
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
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
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
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
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
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
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[6]. 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
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
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
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[8] 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[9].
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.
Filename | Format | Description |
---|---|---|
dat_klm.fits | HEALPix FITS format alm, with | Contains the estimated lensing convergence | .
mask.fits.gz | HEALPix FITS format map, with | Contains the lens reconstruction analysis mask. |
nlkk.dat | ASCII text file, with columns = ( | , , )The approximate noise Planck-2015-A13[10]. | (and signal+noise, ) power spectrum of , for the fiducial cosmology used in
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[13]. 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)
Filename | Format | Description |
---|---|---|
nilc_ymaps.fits | HEALPix FITS format map in Galactic coordinates with | Contains the NILC full mission, FIRST and LAST y-maps. |
milca_ymaps.fits | HEALPix FITS format map in Galactic coordinates with | Contains the MILCA full mission, FIRST and LAST y-maps. |
nilc_weights_BAND.fits | HEALPix FITS format map in Galactic coordinates with | Contains the NILC ILC weights for the full mission y-map for band BAND 0 to 9. For each band we provide a weight map per frequency. |
milca_FREQ_Csz.fits | HEALPix FITS format map in Galactic coordinates with | Contains the MILCA ILC weights for the full mission y-map for frequency FREQ (100, 143, 217, 353, 545, 857). For each frequency we provide a weight map per filter band. |
nilc_stddev.fits | HEALPix FITS format map in Galactic coordinates with | Contains the stddev map for the NILC full mission y-map. |
milca_stddev.fits | HEALPix FITS format map in Galactic coordinates with | Contains the stddev maps for the MILCA full mission y-map. |
nilc_homnoise_spect.fits | ASCII table FITS format | Contains the angular power spectrum of the homogeneous noise in the NILC full mission y-map. |
milca_homnoise_spect.fits | ASCII table FITS format | Contains the angular power spectrum of the homogeneous noise in the MILCA full mission y-map. |
masks.fits | HEALPix FITS format map, with | 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[12]. 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[9]. 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[12].
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 Planck-2015-XLI[12]. They are defined as
and , which form the basis of the final lensing B-mode estimator defined in equation (6) of
where Planck-2015-XLI[12], and is the filtered lensing potential estimate.
and are the filtered pure E-mode polarization maps given in equation (5) ofWe also provide the normalization transfer function Planck-2015-XLI[12], as well as the "L70" mask that retains 69% of the sky before apodization, and its apodized version , which has an effective sky fraction .
defined in equation (11) ofAs an example of the utilization of these products, the lensing B-mode maps that are shown in figure 4 of Planck-2015-XLI[12] are generated from
,
where FWHM (introduced for highlighting large angular scales, although it can be removed or replaced by any other filter). This can be practically done by ingesting and in the HEALPix "smoothing" routine, and using the product as an input filtering function.
is a Gaussian of 60 arcminSpecific products
We provide the lensing B-mode spherical harmonic coefficient estimate
over approximately 70% of the sky.It can also be constructed using the raw products described above from
,
where HEALPix "anafast" tool.
is a function for producing band-powers over the range , and is a short-hand notation for transforming a map into spin-weighted spherical harmonic coefficients , and forming . This can be done using, e.g., theThe lensing B-mode power spectrum estimate Planck-2015-XLI[12] is obtained by forming the cross-correlation power spectrum of and the B-mode data from the SMICA polarization maps :
discussed in,
where CMB maps.
is the 5 arcmin Gaussian beam that convolves the SMICA
The products are contained in a single gzipped tarball named COM_Lensing-Bmode_R2.00.tgz. Its contents are described below.
Filename | Format | Description |
---|---|---|
bar_q_lens_map.fits | HEALPix FITS format map in Galactic coordinates with | Contains the non-normalized lensing-induced Q Stokes parameter map | .
bar_u_lens_map.fits | HEALPix FITS format map in Galactic coordinates with | Contains the non-normalized lensing-induced U Stokes parameter map | .
mask.fits | HEALPix FITS format map in Galactic coordinates with | The L70 mask. |
mask_noapo.fits | HEALPix FITS format map in Galactic coordinates with | The L70 mask without apodization. |
transfer_function_b_l.dat | ASCII text file, with columns = ( | , )The transfer function. |
lensing_bmode_b_lm.fits | HEALPix FITS format alm, with | Contains the lensing B-mode harmonic coefficients | .
lensing_bmode_bandpowers.dat | ASCII text file, with columns = ( | , , , , )The lensing B-mode bandpower estimate on approximativily 70% of the sky and over the multipole range from 10 to 2000 shown in figure 9 of Planck-2015-XLI[12] (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[14] 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.
Extension | Format | Description | Used data sets |
---|---|---|---|
0 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | SEVEM DX11 CMB + NVSS + SDSS + WISE + Planck lensing. |
1 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | NVSS + SDSS + WISE + Planck lensing. |
2 | HEALPix FITS format map with three components, , Ordering='Nest' | Contains three components: i) ISW map [Kelvin], ii) Error map [Kelvin], iii) Mask map | SEVEM DX11 CMB + NVSS + Planck lensing. |
Astrophysical components based on the 2013 data release
Overview
This section describes the maps of astrophysical components produced from the Planck data. These products are derived from some or all of the nine frequency channel maps described above using different techniques and, in some cases, using other constraints from external data sets. Here we give a brief description of the product and how it is obtained, followed by a description of the FITS file containing the data and associated information. All the details can be found in Planck-2013-XII[16].
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:
- CMB maps and ancillary products (3 or 6 maps)
- CMB-cleaned foreground maps from LFI (3 maps)
- CMB-cleaned foreground maps from HFI (6 maps)
- 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).
- CMB maps and ancillary products (4 maps)
- Effective beam of the CMB maps (1 vector)
Low resolution N$_\rm{side}$=256
- CMB maps and ancillary products (3 maps)
- 10 example CMB maps used in the montecarlo realization (10 maps)
- 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.
Col name | SMICA | NILC | SEVEM | COMMANDER-Ruler H | COMMANDER-Ruler L | Description / notes |
---|---|---|---|---|---|---|
1: I | ![]() |
![]() |
![]() |
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Raw CMB anisotropy map. These are the maps used in the component separation paper Planck-2013-XII[16]. |
2: NOISE | ![]() |
![]() |
![]() |
![]() |
not applicable | Noise map. Obtained by propagating the half-ring noise through the CMB cleaning pipelines. |
3: VALMASK | ![]() |
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![]() |
![]() |
![]() |
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[16] and references therein.
The union (or common) mask is defined as the union of the confidence masks from the four component separation pipelines, the three listed above and Commander-Ruler. It leaves 73% of the sky available, and so it is denoted as U73.
Product description
SMICA
- Principle
- SMICA produces a CMB map by linearly combining all Planck input channels (from 30 to 857 GHz) with weights which vary with the multipole. It includes multipoles up to .
- Resolution (effective beam)
- The SMICA map has an effective beam window function of 5 arc-minutes truncated at CMB and is a 5-arcminute Gaussian beam function. Note however that, by convention, the effective beam window function provided in the FITS file does include a pixel window function. Therefore, it is equal to where denotes the pixel window function for an Nside=2048 pixelization. and deconvolved from the pixel window. It means that, ideally, one would have , where is the angular spectrum of the map, where is the angular spectrum of the
- 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 . It is obtained by applying the Internal Linear Combination (ILC) technique in needlet space, that is, with combination weights which are allowed to vary over the sky and over the whole multipole range.
- Resolution (effective beam)
- As in the SMICA product except that there is no abrupt truncation at but a smooth transition to over the range .
- 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[17] and to WMAP polarisation data[18]. 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[16] 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[16].
Production process
SMICA
- 1) Pre-processing
- All input maps undergo a pre-processing step to deal with point sources. The point sources with SNR > 5 in the PCCS catalogue are fitted in each input map. If the fit is successful, the fitted point source is removed from the map; otherwise it is masked and the hole is filled in by a simple diffusive process to ensure a smooth transition and mitigate spectral leakage. This is done at all frequencies but 545 and 857 GHz, here all point sources with SNR > 7.5 are masked and filled-in similarly.
- 2) Linear combination
- The nine pre-processed Planck frequency channels from 30 to 857 GHzare harmonically transformed up to and co-added with multipole-dependent weights as shown in the figure.
- 3) Post-processing
- The areas masked in the pre-processing step are replaced by a constrained Gaussian realization.
Note: The visible power deficit in the raw CMB map around the galactic plane is due to the smooth fill-in of the masked areas in the input maps (the result of the pre-processing). It is not to be confused with the post-processing step of inpainting of the CMB map with a constrained Gaussian realization.
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 Planck-2013-XII[16]. . This is achieved using a needlet (redundant spherical wavelet) decomposition. For more details, see
- 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[19]) to properly deal with incomplete sky coverage. By expediency, however, we fill in the small number of unobserved pixels at each channel with the mean value of its neighbouring pixels before applying SEVEM.
We construct our templates by subtracting two close Planck frequency channel maps, after first smoothing them to a common resolution to ensure that the CMB signal is properly removed. A linear combination of the templates is then subtracted from (hitherto unused) map d to produce a clean CMB map at that frequency. This is done either in real or in wavelet space (i.e., scale by scale) at each position on the sky: where is the number of templates. If the cleaning is performed in real space, the coefficients are obtained by minimising the variance of the clean map outside a given mask. When working in wavelet space, the cleaning is done in the same way at each wavelet scale independently (i.e., the linear coefficients depend on the scale). Although we exclude very contaminated regions during the minimization, the subtraction is performed for all pixels and, therefore, the cleaned maps cover the full-sky (although we expect that foreground residuals are present in the excluded areas).
An additional level of flexibility can also be considered: the linear coefficients can be the same for all the sky, or several regions with different sets of coefficients can be considered. The regions are then combined in a smooth way, by weighting the pixels at the boundaries, to avoid discontinuities in the clean maps. Since the method is linear, we may easily propagate the noise properties to the final CMB map. Moreover, it is very fast and permits the generation of thousands of simulations to character- ize the statistical properties of the outputs, a critical need for many cosmological applications. The final CMB map retains the angular resolution of the original frequency map.
There are several possible configurations of SEVEM with regard to the number of frequency maps which are cleaned or the number of templates that are used in the fitting. Note that the production of clean maps at different frequencies is of great interest in order to test the robustness of the results. Therefore, to define the best strategy, one needs to find a compromise between the number of maps that can be cleaned independently and the number of templates that can be constructed.
In particular, we have cleaned the 143 GHz and 217 GHz maps using four templates constructed as the difference of the following Planck channels (smoothed to a common resolution): (30-44), (44-70), (545-353) and (857-545). For simplicity, the three maps have been cleaned in real space, since there was not a significant improvement when using wavelets (especially at high latitude). In order to take into account the different spectral behaviour of the foregrounds at low and high galactic latitudes, we have considered two independent regions of the sky, for which we have used a different set of coefficients. The first region corresponds to the 3 per cent brightest Galactic emission, whereas the second region is defined by the remaining 97 per cent of the sky. For the first region, the coefficients are actually estimated over the whole sky (we find that this is more optimal than perform the minimisation only on the 3 per cent brightest region, where the CMB emission is very sub-dominant) while for the second region, we exclude the 3 per cent brightest region of the sky, point sources detected at any frequency and those pixels which have not been observed at all channels. Our final CMB map has then been constructed by combining the 143 and 217 GHz maps by weighting the maps in harmonic space taking into account the noise level, the resolution and a rough estimation of the foreground residuals of each map (obtained from realistic simulations). This final map has a resolution corresponding to a Gaussian beam of fwhm=5 arcminutes.
Moreover, additional CMB clean maps (at frequencies between 44 and 353 GHz) have also been produced using different combinations of templates for some of the analyses carried out in Planck-2013-XXIII[20] and Planck-2013-XIX[21]. In particular, clean maps from 44 to 353 GHz have been used for the stacking analysis presented in Planck-2013-XIX[21], while frequencies from 70 to 217 GHz were used for consistency tests in Planck-2013-XXIII[20].
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 |
NILC 2013 (PR1) | Used for diffuse inpainting of input frequency maps | Used for constrained Gaussian realization inpaiting of CMB map | Description |
VALMASK | NO | NO | VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits. |
I_MASK | NO | NO | I_MASK defines the regions over which CMB is not built. It is a combination of point source masks, Galactic plane mask and other bright regions like LMC, SMC, etc. It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits. |
INP_MASK | NO | YES | It can be found inside COM_CompMap_CMB-nilc_2048_R1.20.fits. |
SMICA 2013 (PR1) | Used for diffuse inpainting of input frequency maps | Used for constrained Gaussian realization inpaiting of CMB map | Description |
VALMASK | NO | NO | VALMASK is the confidence mask that defines the region where the reconstructed CMB is trusted. It can be found inside |
I_MASK | YES | YES | I_MASK defines the regions over which CMB is not built. It is a combination of point source masks, Galactic plane mask and other bright regions like LMC, SMC, etc. It can be found inside COM_CompMap_CMB-smica_2048_R1.20.fits. |
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.
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:
- 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.
- The confidence mask indicates where the CMB map is considered valid.
- 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.
- 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.
- The beam window function given here includes the pixel window function for the Nside=2048 pixelization. It means that, ideally, .
The low resolution COMMANDER-Ruler CMB product is organized in the following way:
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:
which contains a single BINTABLE extension with a single column (named U73) for the mask, which is boolean (FITS TFORM = B), in GALACTIC coordinates, NESTED ordering, and Nside=2048.
For the benefit of users who are only looking for a small file containing the SMICA cmb map with no additional information (noise or masks) we provide such a file here
This file contains a single extension with a single column containing the SMICA cmb temperature map.
Cautionary notes
- 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.
- 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.
- 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[16] 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[16] 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:
Column Name | Data Type | Units | Description |
---|---|---|---|
I | Real*4 | uK | Intensity |
I_stdev | Real*4 | uK | standard deviation of intensity |
Beta | Real*4 | effective spectral index | |
B_stdev | Real*4 | standard deviation on the effective spectral index |
- Notes
- Comment: The Intensity is normalized at 30 GHz
- Comment: The intensity was estimated during mixing matrix estimation
Low frequency component at N$_\rm{side}$ = 2048
- File name: COM_CompMap_Lfreqfor-commrul_2048_R1.00.fits
- Name HDU -- COMP-MAP
The Fits extension is composed by the columns described below:
Column Name | Data Type | Units | Description |
---|---|---|---|
I | Real*8 | uK | Intensity |
I_stdev | Real*8 | uK | standard deviation of intensity |
I_hr1 | Real*8 | uK | Intensity on half ring 1 |
I_hr2 | Real*8 | uK | Intensity on half ring 2 |
- Notes
- Comment: The intensity was computed after mixing matrix application
- Name HDU -- BeamWF
The Fits second extension is composed by the columns described below:
Column Name | Data Type | Units | Description |
---|---|---|---|
BeamWF | Real*4 | beam profile |
- Notes
- Comment: Beam window function used in the Component separation process
Thermal dust
Thermal dust component at N$_\rm{side}$=256
- File name: COM_CompMap_dust-commrul_0256_R1.00.fits
- Name HDU -- COMP-MAP
The Fits extension is composed by the columns described below:
Column Name | Data Type | Units | Description |
---|---|---|---|
I | Real*4 | MJy/sr | Intensity |
I_stdev | Real*4 | MJy/sr | standard deviation of intensity |
Em | Real*4 | emissivity | |
Em_stdev | Real*4 | standard deviation on emissivity | |
T | Real*4 | uK | temperature |
T_stdev | Real*4 | uK | standard deviation on temerature |
- Notes
- Comment: The intensity is normalized at 353 GHz
Thermal dust component at N$_\rm{side}$=2048
File name: COM_CompMap_dust-commrul_2048_R1.00.fits
- Name HDU -- COMP-MAP
The Fits extension is composed by the columns described below:
Column Name | Data Type | Units | Description |
---|---|---|---|
I | Real*8 | MJy/sr | Intensity |
I_stdev | Real*8 | MJy/sr | standard deviation of intensity |
I_hr1 | Real*8 | MJy/sr | Intensity on half ring 1 |
I_hr2 | Real*8 | MJy/sr | Intensity on half ring 2 |
- Name HDU -- BeamWF
The Fits second extension is composed by the columns described below:
Column Name | Data Type | Units | Description |
---|---|---|---|
BeamWF | Real*4 | beam profile |
- Notes
- Comment: Beam window function used in the Component separation process
Sky mask
File name: COM_CompMap_Mask-rulerminimal_2048.fits
- Name HDU -- COMP-MASK
The Fits extension is composed by the columns described below:
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[22].
Model of all-sky thermal dust emission
The model of the thermal dust emission is based on a modified black body (MBB) fit to the data
where
is the Planck function for dust equilibirum temperature , is the amplitude of the MBB and the dust spectral index. The dust optical depth at frequency isThe dust parameters provided are
, and . They were obtained by fitting the Planck data at 353, 545 and 857 GHz (from which the Planck zodiacal light model was removed) together with the IRAS 100 micron data. The latter is a combination of the 100 micron maps from IRIS (Miville-Deschenes & Lagache, 2005) and from Schlegel et al. (1998), SFD1998. The IRIS (SFD1998) map is used at scales smaller (larger) than 30 arcmin; this combination allows to take advantage of the higher angular resolution and better control of gain variations of the IRIS map and of the better removal of the zodiacal light emission of the SFD1998 map.All maps (in Healpix Nside=2048 were smoothed to a common resolution of 5 arcmin. The CMB anisotropies, clearly visible at 353 GHz, were removed from all the HFI maps using the SMICA map. An offset was removed from each map to set a Galactic zero level, using a correlation with the LAB 21 cm data in diffuse areas of the sky ( ). Because the dust emission is so well correlated between frequencies in the Rayleigh-Jeans part of the dust spectrum, the zero level of the 545 and 353 GHz were improved by correlating with the 857 GHz over a larger mask ( ). Faint residual dipole structures, identified in the 353 and 545 GHz maps, were removed prior to the fit.
The MBB fit was performed using a CMB anisotropies) and uncertainties on the zero levels. Because of the known degeneracy between and in the presence of noise, we performed tge fit in two steps. First we produced a model of dust emission using data smoothed to 30 arcmin; at such resolution no systematic bias of the parameters is observed. In a second step the map of the spectral index at 30 arcmin was used to fit the data for and at 5 arcmin.
minimization method, assuming errors for each data point that include instrumental noise, calibration uncertainties (on both the dust emission and theThe
map for extra-galactic studies For the production of the map, we used a MBB fit to Planck and IRAS data from which point sources were removed to avoid contamination by galaxies. In the hypothesis of constant dust emission cross-section, the optical depth map is proportional to dust column density and therefore often used to estimate E(B-V). The analysis of Planck data revealed that the ratio and are not constant, even in the diffuse ISM, but that they depend on revealing possible spatial variations of the dust emission cross-section. It appears that the dust radiance, , i.e. the dust emission integrated in frequency, is a better tracer of column density in the diffuse ISM, implying small spatial variations of the radiation field strength at high Galactic latitude. Given those results, we also deliver the map of as a dust product and we propose to use it as an estimator of Galactic dust reddening for extra-galactic studies: .To estimate the calibration factor q, we followed a method similar to[23] based on SDSS reddening measurements of quasars in the u, g, r, i and z bands[24]. We used a sample of 53 399 quasars, selecting objects at redshifts for which Ly does not enter the SDSS filters. The interstellar HI column densities covered on the lines of sight of this sample ranges from to . Therefore this sample allows us to estimate q in the diffuse ISM where this map of E(B-V) is intended to be used.
Dust optical depth products The dust model maps are found in the file HFI_CompMap_ThermalDustModel_2048_R1.20.fits (see the note below for an important clarification regarding the thermal dust model); its characteristics are:
- Dust optical depth at 353 GHz: Nside=2048, fwhm=5', no units
- Dust temperature: Nside 2048, fwhm=5', units=Kelvin
- Dust spectral index: Nside=2048, fwhm=30', no units
- Dust radiance: Nside=2048, fwhm=5', units=Wm-2sr-1
- E(B-V) for extragalactic studies: Nside=2048, fwhm=5', units=magnitude, obtained with data from which point sources were removed.
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 |
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[5].
- 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.
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)) |
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)) |
1. EXTNAME = 'COMP-MAP' | |||
---|---|---|---|
Column Name | Data Type | Units | Description |
INTEN | Real*4 | K_RJ km/sec | The CO intensity map |
ERR | Real*4 | K_RJ km/sec | Uncertainty in the intensity |
NUL | Real*4 | K_RJ km/sec | Map built from the half-ring difference maps |
MASK | Byte | none | Region over which the intensity is considered reliable |
Keyword | Data Type | Value | Description |
AST-COMP | String | CO-TYPE1 | Astrophysical compoment name |
PIXTYPE | String | HEALPIX | |
COORDSYS | String | GALACTIC | Coordinate system |
ORDERING | String | NESTED | Healpix ordering |
NSIDE | Int | 2048 | Healpix Nside for LFI and HFI, respectively |
FIRSTPIX | Int*4 | 0 | First pixel number |
LASTPIX | Int*4 | 50331647 | Last pixel number, for LFI and HFI, respectively |
CNV | Real*4 | value | Factor to convert to Kcmb (units Kcmb/(Krj*km/s)) |
References[edit]
- ↑ 1.01.11.2 Planck 2018 results. IV. Diffuse component separation, Planck Collaboration, 2020, A&A, 641, A4.
- ↑
- ↑ Planck 2018 results. III. High Frequency Instrument data processing and frequency maps, Planck Collaboration, 2020, A&A, 641, A3.
- ↑ 4.04.14.24.34.44.5 Planck 2015 results. X. Diffuse component separation: Foreground maps, Planck Collaboration, 2016, A&A, 594, A10.
- ↑ 5.05.1 Planck 2013 results. XIII. Galactic CO emission, Planck Collaboration, 2014, A&A, 571, A13.
- ↑ 6.06.1 Planck intermediate results. XXIX. All-sky dust modelling with Planck, IRAS, and WISE observations', Planck Collaboration Int. XXIX, A&A, 586, A132, (2016).
- ↑ Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies, Planck Collaboration Int. XLVIII A&A, 596, A109, (2016).
- ↑ 8.08.1 Planck 2015 results. XV. Gravitational Lensing, Planck Collaboration, 2016, A&A, 594, A15.
- ↑ 9.09.19.29.3 Planck 2015 results. XI. Diffuse component separation: CMB maps, Planck Collaboration, 2016, A&A, 594, A9.
- ↑ 10.010.1 Planck 2015 results. XIII. Cosmological parameters, Planck Collaboration, 2016, A&A, 594, A13.
- ↑ 11.011.111.211.311.411.5 Planck 2013 results. XVII. Gravitational lensing by large-scale structure, Planck Collaboration, 2014, A&A, 571, A17.
- ↑ 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).
- ↑ 13.013.1 Planck 2015 results. XXII. A map of the thermal Sunyaev-Zeldovich effect, Planck Collaboration, 2016, A&A, 594, A22.
- ↑ 14.014.1 Planck 2015 results. XXI. The integrated Sachs-Wolfe effect, Planck Collaboration, 2016, A&A, 594, A21.
- ↑ 15.015.115.215.3 Planck 2015 results. XXV. Diffuse low frequency Galactic foregrounds, Planck Collaboration, 2016, A&A, 594, A25.
- ↑ 16.016.116.216.316.416.516.616.7 Planck 2013 results. XI. Component separation, Planck Collaboration, 2014, A&A, 571, A11.
- ↑ 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).
- ↑ 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).
- ↑ 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).
- ↑ 20.020.1 Planck 2013 results. XXIII. Isotropy and statistics of the CMB, Planck Collaboration, 2014, A&A, 571, A23.
- ↑ 21.021.1 Planck 2013 results. XIX. The integrated Sachs-Wolfe effect, Planck Collaboration, 2014, A&A, 571, A19.
- ↑ 22.022.1 Planck 2013 results. XII. All-sky model of thermal dust emission, Planck Collaboration, 2014, A&A, 571, A12.
- ↑ Calibrating Milky Way dust extinction using cosmological sources, E. Mörtsell, A&A, 550, A80, (2013).
- ↑ 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
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).
Sunyaev-Zel'dovich