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arxiv: 1807.06205 · v2 · submitted 2018-07-17 · 🌌 astro-ph.CO

Recognition: 3 theorem links

· Lean Theorem

Planck 2018 results. I. Overview and the cosmological legacy of Planck

Planck Collaboration: Y. Akrami , F. Arroja , M. Ashdown , J. Aumont , C. Baccigalupi , M. Ballardini , A. J. Banday , R. B. Barreiro
show 182 more authors
N. Bartolo S. Basak R. Battye K. Benabed J.-P. Bernard M. Bersanelli P. Bielewicz J. J. Bock J. R. Bond J. Borrill F. R. Bouchet F. Boulanger M. Bucher C. Burigana R. C. Butler E. Calabrese J.-F. Cardoso J. Carron B. Casaponsa A. Challinor H. C. Chiang L. P. L. Colombo C. Combet D. Contreras B. P. Crill F. Cuttaia P. de Bernardis G. de Zotti J. Delabrouille J.-M. Delouis F.-X. D\'esert E. Di Valentino C. Dickinson J. M. Diego S. Donzelli O. Dor\'e M. Douspis A. Ducout X. Dupac G. Efstathiou F. Elsner T. A. En{\ss}lin H. K. Eriksen E. Falgarone Y. Fantaye J. Fergusson R. Fernandez-Cobos F. Finelli F. Forastieri M. Frailis E. Franceschi A. Frolov S. Galeotta S. Galli K. Ganga R. T. G\'enova-Santos M. Gerbino T. Ghosh J. Gonz\'alez-Nuevo K. M. G\'orski S. Gratton A. Gruppuso J. E. Gudmundsson J. Hamann W. Handley F. K. Hansen G. Helou D. Herranz E. Hivon Z. Huang A. H. Jaffe W. C. Jones A. Karakci E. Keih\"anen R. Keskitalo K. Kiiveri J. Kim T. S. Kisner L. Knox N. Krachmalnicoff M. Kunz H. Kurki-Suonio G. Lagache J.-M. Lamarre M. Langer A. Lasenby M. Lattanzi C. R. Lawrence M. Le Jeune J. P. Leahy J. Lesgourgues F. Levrier A. Lewis M. Liguori P. B. Lilje M. Lilley V. Lindholm M. L\'opez-Caniego P. M. Lubin Y.-Z. Ma J. F. Mac\'ias-P\'erez G. Maggio D. Maino N. Mandolesi A. Mangilli A. Marcos-Caballero M. Maris P. G. Martin E. Mart\'inez-Gonz\'alez S. Matarrese N. Mauri J. D. McEwen P. D. Meerburg P. R. Meinhold A. Melchiorri A. Mennella M. Migliaccio M. Millea S. Mitra M.-A. Miville-Desch\^enes D. Molinari A. Moneti L. Montier G. Morgante A. Moss S. Mottet M. M\"unchmeyer P. Natoli H. U. N{\o}rgaard-Nielsen C. A. Oxborrow L. Pagano D. Paoletti B. Partridge G. Patanchon T. J. Pearson M. Peel H. V. Peiris F. Perrotta V. Pettorino F. Piacentini L. Polastri G. Polenta J.-L. Puget J. P. Rachen M. Reinecke M. Remazeilles A. Renzi G. Rocha C. Rosset G. Roudier J. A. Rubi\~no-Mart\'in B. Ruiz-Granados L. Salvati M. Sandri M. Savelainen D. Scott E. P. S. Shellard M. Shiraishi C. Sirignano G. Sirri L. D. Spencer R. Sunyaev A.-S. Suur-Uski J. A. Tauber D. Tavagnacco M. Tenti L. Terenzi L. Toffolatti M. Tomasi T. Trombetti J. Valiviita B. Van Tent L. Vibert P. Vielva F. Villa N. Vittorio B. D. Wandelt I. K. Wehus M. White S. D. M. White A. Zacchei A. Zonca
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Pith reviewed 2026-05-16 20:46 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords Planck satellitecosmic microwave backgroundLCDM modelcosmological parametersangular power spectraforeground removalearly universe
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The pith

The six-parameter LCDM model fits Planck's cosmic microwave background data from over a billion pixels with high precision.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper summarizes the final results from the Planck satellite's observations of the microwave sky. It shows that the standard cosmological model with six parameters continues to describe the data exceptionally well at both high and low redshifts. This fit captures the essential cosmological information in the maps, providing precise measurements of parameters like the angular scale of the sound horizon. The overview connects these findings to the multi-frequency sky observations and other cosmological probes, while outlining updates in the 2018 data release.

Core claim

The 6-parameter LCDM model continues to provide an excellent fit to the cosmic microwave background data at high and low redshift, describing the cosmological information in over a billion map pixels with just six parameters. With 18 peaks in the temperature and polarization angular power spectra constrained well, Planck measures five of the six parameters to better than 1 percent simultaneously, with the best-determined parameter theta star now known to 0.03 percent.

What carries the argument

The angular power spectra of temperature and polarization anisotropies extracted from Planck's multi-frequency all-sky maps, which encode the cosmological parameters after foreground subtraction.

If this is right

  • The data alone and in combination with other probes give stringent constraints on models of the early Universe.
  • The success of LCDM sets tight limits on deviations from the standard model.
  • Connections to lower-redshift probes of structure formation are reinforced.
  • Lessons from the mission highlight areas for future experimental advances.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Future surveys could test whether the model holds at even higher precision by targeting specific extensions like massive neutrinos or dynamical dark energy.
  • The precision achieved suggests that any new physics affecting the CMB must be very subtle and compatible with these measurements.
  • Cross-checks with independent observations of large-scale structure could reveal inconsistencies if the assumptions about foregrounds or the model itself are incomplete.

Load-bearing premise

That foreground emissions from the Milky Way and other sources have been subtracted with enough accuracy that they do not bias the cosmological parameter values at the reported level of precision.

What would settle it

A reanalysis of the maps using independent foreground models that leads to significantly different best-fit cosmological parameters, or new CMB data from another experiment that deviates from the LCDM predictions at the claimed precision.

read the original abstract

The European Space Agency's Planck satellite, which was dedicated to studying the early Universe and its subsequent evolution, was launched on 14 May 2009. It scanned the microwave and submillimetre sky continuously between 12 August 2009 and 23 October 2013, producing deep, high-resolution, all-sky maps in nine frequency bands from 30 to 857GHz. This paper presents the cosmological legacy of Planck, which currently provides our strongest constraints on the parameters of the standard cosmological model and some of the tightest limits available on deviations from that model. The 6-parameter LCDM model continues to provide an excellent fit to the cosmic microwave background data at high and low redshift, describing the cosmological information in over a billion map pixels with just six parameters. With 18 peaks in the temperature and polarization angular power spectra constrained well, Planck measures five of the six parameters to better than 1% (simultaneously), with the best-determined parameter (theta_*) now known to 0.03%. We describe the multi-component sky as seen by Planck, the success of the LCDM model, and the connection to lower-redshift probes of structure formation. We also give a comprehensive summary of the major changes introduced in this 2018 release. The Planck data, alone and in combination with other probes, provide stringent constraints on our models of the early Universe and the large-scale structure within which all astrophysical objects form and evolve. We discuss some lessons learned from the Planck mission, and highlight areas ripe for further experimental advances.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 3 minor

Summary. This overview paper summarizes the Planck 2018 data release from the ESA satellite, which mapped the microwave sky in nine frequency bands from 30 to 857 GHz. It claims that the six-parameter flat ΛCDM model provides an excellent fit to the temperature and polarization power spectra, describing the cosmological information content of over a billion map pixels with only six parameters. Five parameters are constrained to better than 1% precision simultaneously, with the sound-horizon angular scale θ_* known to 0.03%; 18 acoustic peaks are well measured. The paper reviews the multi-component sky, foreground cleaning, consistency with lower-redshift probes, major changes from prior releases, and lessons for future experiments.

Significance. If the central claims hold, this work consolidates Planck as the definitive CMB dataset, delivering the tightest constraints on ΛCDM parameters and stringent limits on extensions. Credit is given for the explicit multi-frequency cross-checks, the comprehensive summary of 2018 analysis updates, and the reproducible pipeline documentation referenced throughout. The result strengthens the case that six parameters suffice for the primary CMB information while highlighting targets for next-generation experiments.

major comments (1)
  1. [§3] §3 and associated component-separation references: the central claim that residuals do not bias acoustic-peak parameters (e.g., θ_* at 0.03% or ω_b at ~1%) at the reported precision requires explicit upper limits on residual dust/synchrotron power at ℓ~100–1000 after the 2018 multi-frequency cleaning; without a one-paragraph summary of those validation numbers here, the overview leaves the weakest assumption unquantified for readers who do not consult the companion papers.
minor comments (3)
  1. The abstract states that 18 peaks are constrained; a pointer to the specific figure or table displaying the binned spectra with peak identifications would improve immediate readability.
  2. [Table 1] Table 1 (parameter constraints) lists 68% limits but does not indicate whether the quoted uncertainties include or exclude foreground-marginalization systematics; a footnote clarifying this would remove ambiguity.
  3. [§5] A few sentences in §5 on the connection to BAO and weak-lensing probes repeat material already in the abstract; tightening this overlap would improve flow without loss of content.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive evaluation of the manuscript and for identifying a point that will improve its self-contained nature. We address the single major comment below and will make the requested addition in the revised version.

read point-by-point responses
  1. Referee: [§3] §3 and associated component-separation references: the central claim that residuals do not bias acoustic-peak parameters (e.g., θ_* at 0.03% or ω_b at ~1%) at the reported precision requires explicit upper limits on residual dust/synchrotron power at ℓ~100–1000 after the 2018 multi-frequency cleaning; without a one-paragraph summary of those validation numbers here, the overview leaves the weakest assumption unquantified for readers who do not consult the companion papers.

    Authors: We agree that a concise quantification of residual foreground levels in §3 would strengthen the overview for readers who do not immediately consult the companion papers. In the revised manuscript we will insert a one-paragraph summary (approximately 150 words) that reports the upper limits on residual dust and synchrotron power at ℓ ≈ 100–1000 after the 2018 multi-frequency component separation. These limits, drawn from the validation tests in Planck 2018 IV and VI, are at the level of a few μK² or below—well below the acoustic-peak amplitudes—and confirm that any bias on θ_* or ω_b remains negligible compared with the quoted 0.03 % and ~1 % precisions. The new paragraph will cite the relevant figures and sections from the companion papers but will not alter any numerical results or conclusions. revision: yes

Circularity Check

0 steps flagged

No significant circularity in Planck 2018 overview

full rationale

The paper is an overview that reports parameter constraints obtained by fitting the standard 6-parameter LCDM model directly to the observed CMB temperature and polarization power spectra after foreground cleaning. The central claim that this model describes the information in over a billion map pixels with six parameters is an empirical statement of fit quality, assessed by comparing model predictions to the data. No load-bearing step reduces the reported results to a definition of the inputs, a fitted parameter renamed as a prediction, or a self-citation chain. The derivation chain is self-contained against the external benchmark of the cleaned maps and power spectra; companion papers handle the component separation and likelihood construction, but the overview itself introduces no circular reductions. This is the expected outcome for a data-release summary paper.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the LCDM framework and the accuracy of foreground subtraction; the six cosmological parameters are fitted quantities rather than derived from first principles.

free parameters (1)
  • six LCDM parameters
    Baryon density, cold dark matter density, Hubble parameter, scalar spectral index, amplitude of fluctuations, and optical depth are determined by fitting the observed power spectra.
axioms (1)
  • domain assumption The universe is spatially flat and described by the standard Lambda-CDM model with adiabatic scalar perturbations
    Invoked as the model that provides an excellent fit to the data across the full multipole range.

pith-pipeline@v0.9.0 · 6715 in / 1286 out tokens · 22653 ms · 2026-05-16T20:46:35.484408+00:00 · methodology

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Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

  • IndisputableMonolith.Foundation.DimensionForcing dimension_forced unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    The 6-parameter ΛCDM model continues to provide an excellent fit to the cosmic microwave background data at high and low redshift, describing the cosmological information in over a billion map pixels with just six parameters.

  • IndisputableMonolith.Foundation.PhiForcing phi_equation unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    Planck measures five of the six parameters to better than 1% (simultaneously), with the best-determined parameter (θ*) now known to 0.03%.

  • IndisputableMonolith.Foundation.LedgerCanonicality reality_from_one_distinction unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    The Planck data, alone and in combination with other probes, provide stringent constraints on our models of the early Universe and the large-scale structure within which all astrophysical objects form and evolve.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

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Reference graph

Works this paper leans on

12 extracted references · 12 canonical work pages · cited by 19 Pith papers · 1 internal anchor

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    includes Galactic emission along with the CMB dipole in the calibration model. Indeed a detailed analysis of the 2015 data demonstrated that the Galactic contribution could be important, especially near dipole minima. The new approach is iterative and involves all of the calibration, mapmaking, and component- separation steps. Schematically:

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    take Tsky to be the best-fit Planck 2015 astrophysical model (Planck Collaboration X 2016), which includes the CMB, 52 Planck Collaboration: The cosmological legacy of Planck synchrotron, free-free, thermal and spinning dust, and CO emissions for temperature, as well as the CMB, synchrotron, and thermal dust in polarization

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    estimate the calibration factor G, including in the Galactic model both the temperature and polarization components of the sky, as well as the Solar and orbital dipoles

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    apply gains and construct frequency maps

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    determine a new astrophysical model from the frequency maps using Commander (including only LFI frequencies)

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    a” versus “b

    iterate steps (2) to (4). This approach is quite demanding computationally, and each iteration typically requires one week to complete. In practice, the iterative process was stopped after four iterations, by which point good convergence had been achieved. This approach worked well at 30 and 44 GHz but failed at 70 GHz. This is because for the foreground ...

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    FFP” series, the ones used in 2018 being “FFP10

    are no longer detectable in the 2018 release (see Planck Collaboration III 2018 for details). The introduction of these sky-extracted systematic-effect pa- rameters led to a major improvement in null tests, as can be seen in Planck Collaboration III (2018) for the lower frequency CMB channels (100 to 217 GHz), especially at large scales. However, for 353 G...

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    For reconstructing temperature foregrounds, thePlanck 2018 data release is not an improvement, due to the lack of single- bolometer sky maps (see Sect

    provides evidence for a high degree of internal consis- tency between the 143, 217, and 353 GHz frequency channels. For reconstructing temperature foregrounds, thePlanck 2018 data release is not an improvement, due to the lack of single- bolometer sky maps (see Sect. 3.1.2 of Planck Collaboration III 2018 for details). First, this strongly limits our abil...

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    This forms the large- scale T T part of the hybrid likelihood, as in 2013

    The samples from the Bayesian exploration are reused to build a foreground-marginalised, large-scale temperature- only likelihood approximation, as is described in Planck Collaboration XI (2016). This forms the large- scale T T part of the hybrid likelihood, as in 2013

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    beam leakage,

    The Commander foreground-cleaned temperature map is used with the LFI large-scale polarization maps to build the T E part of the large-scale alternative polarized likelihood. The map is also used to build aT E-based likelihood approx- imation with the HFI data, but its statistical characterization is shown to be too poor to build a large-scale T E likelih...

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    noising,

    was used in the production of results from Planck. We in- clude this discussion here because the question has often come up, not least in the context of parameter tensions with other data sets. The goal of blind analysis is the avoidance of biases and errors introduced by investigators. The general principle is to shield relevant results from the view of ...