Difference between revisions of "CMB spectrum & Likelihood Code"

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The <math>\ell</math> < 50 part of the Planck power spectrum is derived from the Commander approach, which implements Bayesian component separation in pixel space, fitting a parametric model to the data by sampling the posterior distribution for the model parameters {{PlanckPapers|planck2013-p06}}. The power spectrum at any multipole <math>\ell</math> is given as the maximum probability point for the posterior <math>C_\ell</math> distribution, marginalized over the other multipoles, and the error bars are 68% confidence level {{PlanckPapers|planck2013-p08}}.  
 
The <math>\ell</math> < 50 part of the Planck power spectrum is derived from the Commander approach, which implements Bayesian component separation in pixel space, fitting a parametric model to the data by sampling the posterior distribution for the model parameters {{PlanckPapers|planck2013-p06}}. The power spectrum at any multipole <math>\ell</math> is given as the maximum probability point for the posterior <math>C_\ell</math> distribution, marginalized over the other multipoles, and the error bars are 68% confidence level {{PlanckPapers|planck2013-p08}}.  
 
</span>
 
</span>
The <math>\ell</math> > 30 part of the CMB temperature power spectrum has been derived by the Plik likelihood, a code that implements a pseudo-Cl based technique, extensively described in Sec. 2 and the Appendix of {{PlanckPapers|planck2013-p08}}. Frequency spectra are computed as cross-spectra between half-mission maps. Mask and multipole range choices for each frequency spectrum are summarized in Section 3.3 of {{PlanckPapers|planck2014-p15}} and in {{PlanckPapers|planck2014-p13}}. The final power spectrum is an optimal combination of the 100, 143, 143x217 and 217 GHz spectra, corrected for the best-fit unresolved foregrounds and inter-frequency calibration factors, as derived from the full likelihood analysis (cf Planck+TT+lowP in Table 3 of {{PlanckPapers|planck2014-p15}}). A thorough description of the models of unresolved foregrounds is given in {{PlanckPapers|planck2014-p13}}. The spectrum covariance matrix accounts for cosmic variance and noise contributions, together with beam uncertainties. Both spectrum and associated covariance matrix are available in two formats:
+
The <math>\ell</math> > 30 part of the CMB temperature power spectrum has been derived by the Plik likelihood, a code that implements a pseudo-Cl based technique, extensively described in Sec. 2 and the Appendix of {{PlanckPapers|planck2013-p08}}. Frequency spectra are computed as cross-spectra between half-mission maps. Mask and multipole range choices for each frequency spectrum are summarized in Section 3.3 of {{PlanckPapers|planck2014-p15}} and in {{PlanckPapers|planck2014-p13}}. The final power spectrum is an optimal combination of the 100, 143, 143x217 and 217 GHz spectra, corrected for the best-fit unresolved foregrounds and inter-frequency calibration factors, as derived from the full likelihood analysis (cf Planck+TT+lowP in Table 3 of {{PlanckPapers|planck2014-p15}}). A thorough description of the models of unresolved foregrounds is given in {{PlanckPapers|planck2014-p13}}. The spectrum covariance matrix accounts for cosmic variance and noise contributions, together with beam uncertainties. The <math>\ell</math> > 30 CMB TT spectrum and associated covariance matrix are available in two formats:
#Unbinned, in 2479 bandpowers.
+
#Unbinned, with 2479 bandpowers (\ell=30-2508).
#Binned, in 83 bandpowers. We bin the Cl power spectra with a weight proportional to <math> \ell (\ell+1) </math>, so that the binned bandpower centered in \ell_b is:
+
#Binned, in bins of <math>\Delta\ell=30 </math>, with 83 bandpowers in total. We bin the Cl power spectra with a weight proportional to <math> \ell (\ell+1) </math>, so that the binned bandpower centered in \ell_b is:
 
<math>
 
<math>
 
C_{\ell_b}=\Sigma_{\ell \in b}  w^b_\ell C_\ell \quad \text{with} \quad w^b_\ell=\frac{\ell (\ell+1)}{\Sigma_{\ell \in b} \ell (\ell+1)} </math>
 
C_{\ell_b}=\Sigma_{\ell \in b}  w^b_\ell C_\ell \quad \text{with} \quad w^b_\ell=\frac{\ell (\ell+1)}{\Sigma_{\ell \in b} \ell (\ell+1)} </math>
  
Equivalently, using the matrix formalism, we can construct the binning matrix B, with:
+
Equivalently, using the matrix formalism, we can construct the binning matrix B as:
<math>
+
<math> B_{\ell \ell_b}=w^{\ell_b}_\ell </math>
B_{\ell \ell_b}=w^{\ell_b}_\ell </math>
+
where B is a <math> n_bxn_\ell=83x2479</math> matrix, with n_b the number of bins and n_\ell the number of unbinned multipoles.
 
+
Thus:
so that
 
 
<math>
 
<math>
 
\vec{C}^{binned}_{\ell_b}=B \vec{C}_\ell \\
 
\vec{C}^{binned}_{\ell_b}=B \vec{C}_\ell \\
Line 30: Line 29:
 
\ell_b=B \ell
 
\ell_b=B \ell
 
</math>
 
</math>
Here, \vec{C}^{binned}_{\ell_b} just indicates the vector containing all the binned bandpowers. The binned D_{\ell_B} power spectra are then :
+
Here, \vec{C}^{binned}_{\ell_b} (\vec{C}_{\ell}) just indicates the vector containing all the binned (unbinned) bandpowers. Note that we use the binning matrix also to calculate the average value of the bin \ell_b.
 +
The binned D_{\ell_B} power spectra are then calculated as:
 
<math>
 
<math>
 
D_\ell_b=\ell_b (\ell_b+1)/2/\pi C_{\ell_b}
 
D_\ell_b=\ell_b (\ell_b+1)/2/\pi C_{\ell_b}

Revision as of 23:50, 3 February 2015


CMB spectra[edit]

General description[edit]

The Planck best-fit CMB temperature power spectrum, shown in figure below, covers the wide range of multipoles [math] \ell [/math] = 2-2508. Over the multipole range [math] \ell [/math] = 2–29, the power spectrum is derived from a component-separation algorithm, Commander, UPDATE COMMANDER: applied to maps in the frequency range 30–353 GHz over 91% of the sky Planck-2013-XII[1] . The asymmetric error bars associated to this spectrum are the 68% confidence limits and include the uncertainties due to foreground subtraction . For multipoles equal or greater than [math]\ell=30[/math], instead, the spectrum is derived from the Plik likelihood Planck-2015-A11[2] by optimally combining the spectra in the frequency range 100-217 GHz, and correcting them for unresolved foregrounds. Associated 1-sigma errors include beam uncertainties. Both Commander and Plik are described in more details in the sections below.

CMB spectrum. Logarithmic x-scale up to [math]\ell=30[/math], linear at higher [math]\ell[/math]; all points with error bars. The red line is the Planck best-fit primordial power spectrum (cf Planck TT+lowP in Table 3 of Planck-2015-A13[3]).

Production process[edit]

UPDATE COMMANDER The [math]\ell[/math] < 50 part of the Planck power spectrum is derived from the Commander approach, which implements Bayesian component separation in pixel space, fitting a parametric model to the data by sampling the posterior distribution for the model parameters Planck-2013-XII[1]. The power spectrum at any multipole [math]\ell[/math] is given as the maximum probability point for the posterior [math]C_\ell[/math] distribution, marginalized over the other multipoles, and the error bars are 68% confidence level Planck-2013-XV[4]. The [math]\ell[/math] > 30 part of the CMB temperature power spectrum has been derived by the Plik likelihood, a code that implements a pseudo-Cl based technique, extensively described in Sec. 2 and the Appendix of Planck-2013-XV[4]. Frequency spectra are computed as cross-spectra between half-mission maps. Mask and multipole range choices for each frequency spectrum are summarized in Section 3.3 of [5] and in [6]. The final power spectrum is an optimal combination of the 100, 143, 143x217 and 217 GHz spectra, corrected for the best-fit unresolved foregrounds and inter-frequency calibration factors, as derived from the full likelihood analysis (cf Planck+TT+lowP in Table 3 of [5]). A thorough description of the models of unresolved foregrounds is given in [6]. The spectrum covariance matrix accounts for cosmic variance and noise contributions, together with beam uncertainties. The [math]\ell[/math] > 30 CMB TT spectrum and associated covariance matrix are available in two formats:

  1. Unbinned, with 2479 bandpowers (\ell=30-2508).
  2. Binned, in bins of [math]\Delta\ell=30 [/math], with 83 bandpowers in total. We bin the Cl power spectra with a weight proportional to [math] \ell (\ell+1) [/math], so that the binned bandpower centered in \ell_b is:

[math] C_{\ell_b}=\Sigma_{\ell \in b} w^b_\ell C_\ell \quad \text{with} \quad w^b_\ell=\frac{\ell (\ell+1)}{\Sigma_{\ell \in b} \ell (\ell+1)} [/math]

Equivalently, using the matrix formalism, we can construct the binning matrix B as: [math] B_{\ell \ell_b}=w^{\ell_b}_\ell [/math] where B is a [math] n_bxn_\ell=83x2479[/math] matrix, with n_b the number of bins and n_\ell the number of unbinned multipoles. Thus: [math] \vec{C}^{binned}_{\ell_b}=B \vec{C}_\ell \\ cov^{binned}= B cov B^T \\ \ell_b=B \ell [/math] Here, \vec{C}^{binned}_{\ell_b} (\vec{C}_{\ell}) just indicates the vector containing all the binned (unbinned) bandpowers. Note that we use the binning matrix also to calculate the average value of the bin \ell_b. The binned D_{\ell_B} power spectra are then calculated as: [math] D_\ell_b=\ell_b (\ell_b+1)/2/\pi C_{\ell_b} [/math]

Inputs[edit]

Low-l spectrum ([math]\ell \lt 50[/math])
High-l spectrum ([math]50 \lt \ell \lt 2500[/math])

File names and Meta data[edit]

The CMB spectrum and its covariance matrix are distributed in a single FITS file named

which contains 3 extensions

LOW-ELL (BINTABLE)
with the low ell part of the spectrum, not binned, and for l=2-49. The table columns are
  1. ELL (integer): multipole number
  2. D_ELL (float): $D_l$ as described below
  3. ERRUP (float): the upward uncertainty
  4. ERRDOWN (float): the downward uncertainty
HIGH-ELL (BINTABLE)
with the high-ell part of the spectrum, binned into 74 bins covering [math]\langle l \rangle = 47-2419\ [/math] in bins of width [math]l=31[/math] (with the exception of the last 4 bins that are wider). The table columns are as follows:
  1. ELL (integer): mean multipole number of bin
  2. L_MIN (integer): lowest multipole of bin
  3. L_MAX (integer): highest multipole of bin
  4. D_ELL (float): $D_l$ as described below
  5. ERR (float): the uncertainty
COV-MAT (IMAGE)
with the covariance matrix of the high-ell part of the spectrum in a 74x74 pixel image, i.e., covering the same bins as the HIGH-ELL table.

The spectra give $D_\ell = \ell(\ell+1)C_\ell / 2\pi$ in units of $\mu\, K^2$, and the covariance matrix is in units of $\mu\, K^4$. The spectra are shown in the figure below, in blue and red for the low- and high-[math]\ell[/math] parts, respectively, and with the error bars for the high-ell part only in order to avoid confusion.

CMB spectrum. Linear x-scale; error bars only at high [math]\ell[/math].

The CMB spectrum is also given in a simple text comma-separated file:

Likelihood[edit]

TO BE WRITTEN.

References[edit]

  1. 1.01.11.2 Planck 2013 results. XI. Component separation, Planck Collaboration, 2014, A&A, 571, A11
  2. Planck 2015 results. XI. CMB power spectra, likelihoods, and robustness of cosmological parameters, Planck Collaboration, 2016, A&A, 594, A11.
  3. Planck 2015 results. XIII. Cosmological parameters, Planck Collaboration, 2016, A&A, 594, A13.
  4. 4.04.14.2 Planck 2013 results. XV. CMB power spectra and likelihood, Planck Collaboration, 2014, A&A, 571, A15
  5. 5.05.1
  6. 6.06.1
  7. Planck 2013 results. XVI. Cosmological parameters, Planck Collaboration, 2014, A&A, 571, A16
  8. Planck 2013 results. VII. HFI time response and beams, Planck Collaboration, 2014, A&A, 571, A7

Cosmic Microwave background

Flexible Image Transfer Specification