Residual noise covariance for<i>Planck</i>low-resolution data analysis

Keskitalo, R.; Ashdown, M.; Cabella, P.; Kisner, T. S.; Poutanen, T.; Stompor, R.; Bartlett, J. G.; Borrill, J.; Cantalupo, C. M.; Gasperis, G. de; Rosa, A. de; Troia, G. De; Eriksen, H. K.; Finelli⋆, F.; Górski, K. M.; Gruppuso, A.; Hivon, E.; Jaffe, A. H.; Keihänen, E.; Kurki-Suonio, H.; Lawrence, C. R.; Natoli, P.; Paci, F.; Polenta, G.; Rocha, G.

doi:10.1051/0004-6361/200912606

Cited by 10 publications

(11 citation statements)

References 43 publications

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“…As already stated in Planck Collaboration Int. XLVI (2016) and Planck Collaboration V (2019), FFP8 covariance matrices (Keskitalo et al 2010;Planck Collaboration XII 2016) represent a sub-optimal, but unavoidable, choice. Those matrices do not capture properly the variance of the systematic effects but only the white and 1/ f noise components.…”

Section: Power Spectrummentioning

confidence: 99%

Reionization optical depth determination from Planck HFI data with ten percent accuracy

Pagano

Delouis

Mottet

et al. 2020

A&A

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We present an estimation of the reionization optical depth τ from an improved analysis of the High Frequency Instrument (HFI) data of Planck satellite. By using an improved version of the HFI map-making code, we greatly reduce the residual large scale contamination affecting the data, characterized, but not fully removed, in the Planck 2018 legacy release. This brings the dipole distortion systematic effect, contaminating the very low multipoles, below the noise level. On large scale polarization only data, we measure τ = 0.0566 +0.0053 −0.0062 at 68% C.L., reducing the Planck 2018 legacy release uncertainty by ∼ 40%. Within the ΛCDM model, in combination with the Planck large scale temperature likelihood, and the high-temperature and polarization likelihood, we measure τ = 0.059±0.006 at 68% C.L. which corresponds to a mid-point reionization redshift of z re = 8.14±0.61 at 68% C.L.. This estimation of the reionization optical depth with 10% accuracy is the strongest constraint to date.

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Section: Power Spectrummentioning

confidence: 99%

Reionization optical depth determination from Planck HFI data with ten percent accuracy

Pagano

Delouis

Mottet

et al. 2020

A&A

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“…Each map is smoothed to an effective resolution of 329.81 FWHM, to suppress aliasing from high multipoles (Keskitalo et al 2010), and repixelised on an N side = 32 HEALPix grid. Gaussian white noise with a variance of 4 µK 2 is added to each map to regularise the noise covariance matrix.…”

Section: Low-power Spectrum -Consistency and Robustnessmentioning

confidence: 99%

Planck2013 results. XV. CMB power spectra and likelihood

Ade¹,

Aghanim²,

Armitage-Caplan³

et al. 2014

A&A

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This paper presents the Planck 2013 likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations that accounts for all known relevant uncertainties, both instrumental and astrophysical in nature. We use this likelihood to derive our best estimate of the CMB angular power spectrum from Planck over three decades in multipole moment, , covering 2 ≤ ≤ 2500. The main source of uncertainty at < ∼ 1500 is cosmic variance. Uncertainties in small-scale foreground modelling and instrumental noise dominate the error budget at higher s. For < 50, our likelihood exploits all Planck frequency channels from 30 to 353 GHz, separating the cosmological CMB signal from diffuse Galactic foregrounds through a physically motivated Bayesian component separation technique. At ≥ 50, we employ a correlated Gaussian likelihood approximation based on a fine-grained set of angular cross-spectra derived from multiple detector combinations between the 100, 143, and 217 GHz frequency channels, marginalising over power spectrum foreground templates. We validate our likelihood through an extensive suite of consistency tests, and assess the impact of residual foreground and instrumental uncertainties on the final cosmological parameters. We find good internal agreement among the high-cross-spectra with residuals below a few µK 2 at < ∼ 1000, in agreement with estimated calibration uncertainties. We compare our results with foreground-cleaned CMB maps derived from all Planck frequencies, as well as with cross-spectra derived from the 70 GHz Planck map, and find broad agreement in terms of spectrum residuals and cosmological parameters. We further show that the best-fit ΛCDM cosmology is in excellent agreement with preliminary Planck EE and T E polarisation spectra. We find that the standard ΛCDM cosmology is well constrained by Planck from the measurements at < ∼ 1500. One specific example is the spectral index of scalar perturbations, for which we report a 5.4σ deviation from scale invariance, n s = 1. Increasing the multipole range beyond 1500 does not increase our accuracy for the ΛCDM parameters, but instead allows us to study extensions beyond the standard model. We find no indication of significant departures from the ΛCDM framework. Finally, we report a tension between the Planck best-fit ΛCDM model and the low-spectrum in the form of a power deficit of 5-10% at < ∼ 40, with a statistical significance of 2.5-3σ. Without a theoretically motivated model for this power deficit, we do not elaborate further on its cosmological implications, but note that this is our most puzzling finding in an otherwise remarkably consistent data set.

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“…Previous work on production of lowresolution maps have been published in Keskitalo et al (2010). An ideal method would simultaneously minimize the pixelization effects and the residual noise.…”

Section: Low-resolution Mapsmentioning

confidence: 99%

“…For generalized destriping the formalism was developed in Keihänen et al (2005) and Keskitalo et al (2010). Using the formalism introduced in Sect.…”

Section: Noise Covariance Matricesmentioning

confidence: 99%

Planck2015 results

Ade

Aghanim

Ashdown

et al. 2016

A&A

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This paper describes the mapmaking procedure applied to Planck Low Frequency Instrument (LFI) data. The mapmaking step takes as input the calibrated timelines and pointing information. The main products are sky maps of I, Q, and U Stokes components. For the first time, we present polarization maps at LFI frequencies. The mapmaking algorithm is based on a destriping technique, which is enhanced with a noise prior. The Galactic region is masked to reduce errors arising from bandpass mismatch and high signal gradients. We apply horn-uniform radiometer weights to reduce the effects of beam-shape mismatch. The algorithm is the same as used for the 2013 release, apart from small changes in parameter settings. We validate the procedure through simulations. Special emphasis is put on the control of systematics, which is particularly important for accurate polarization analysis. We also produce low-resolution versions of the maps and corresponding noise covariance matrices. These serve as input in later analysis steps and parameter estimation. The noise covariance matrices are validated through noise Monte Carlo simulations. The residual noise in the map products is characterized through analysis of half-ring maps, noise covariance matrices, and simulations.

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Residual noise covariance forPlancklow-resolution data analysis

Cited by 10 publications

References 43 publications

Reionization optical depth determination from Planck HFI data with ten percent accuracy

Reionization optical depth determination from Planck HFI data with ten percent accuracy

Planck2013 results. XV. CMB power spectra and likelihood

Planck2015 results

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