The ESA's Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. This paper gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the CMB and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the SZ effect. The likelihood code used to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter LCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25 sigma. Planck finds no evidence for non-Gaussianity in the CMB. Planck's results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations derived from CMB data and that derived from SZ data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak.
Using the ${\it Planck}$ full-mission data, we present a detection of the temperature (and therefore velocity) dispersion due to the kinetic Sunyaev-Zeldovich (kSZ) effect from clusters of galaxies. To suppress the primary CMB and instrumental noise we derive a matched filter and then convolve it with the ${\it Planck}$ foreground-cleaned `${\tt 2D-ILC\,}$' maps. By using the Meta Catalogue of X-ray detected Clusters of galaxies (MCXC), we determine the normalized ${\it rms}$ dispersion of the temperature fluctuations at the positions of clusters, finding that this shows excess variance compared with the noise expectation. We then build an unbiased statistical estimator of the signal, determining that the normalized mean temperature dispersion of $1526$ clusters is $\langle \left(\Delta T/T \right)^{2} \rangle = (1.64 \pm 0.48) \times 10^{-11}$. However, comparison with analytic calculations and simulations suggest that around $0.7\,\sigma$ of this result is due to cluster lensing rather than the kSZ effect. By correcting this, the temperature dispersion is measured to be $\langle \left(\Delta T/T \right)^{2} \rangle = (1.35 \pm 0.48) \times 10^{-11}$, which gives a detection at the $2.8\,\sigma$ level. We further convert uniform-weight temperature dispersion into a measurement of the line-of-sight velocity dispersion, by using estimates of the optical depth of each cluster (which introduces additional uncertainty into the estimate). We find that the velocity dispersion is $\langle v^{2} \rangle =(123\,000 \pm 71\,000)\,({\rm km}\,{\rm s}^{-1})^{2}$, which is consistent with findings from other large-scale structure studies, and provides direct evidence of statistical homogeneity on scales of $600\,h^{-1}{\rm Mpc}$. Our study shows the promise of using cross-correlations of the kSZ effect with large-scale structure in order to constrain the growth of structure.
Taking advantage of the all-sky coverage and broad frequency range of the Planck satellite, we study the Sunyaev-Zeldovich (SZ) and pressure profiles of 62 nearby massive clusters detected at high significance in the 14-month nominal survey. Careful reconstruction of the SZ signal indicates that most clusters are individually detected at least out to R500. By stacking the radial profiles, we have statistically detected the radial SZ signal out to 3 x R500, i.e., at a density contrast of about 50-100, though the dispersion about the mean profile dominates the statistical errors across the whole radial range. Our measurement is fully consistent with previous Planck results on integrated SZ fluxes, further strengthening the agreement between SZ and X-ray measurements inside R500. Correcting for the effects of the Planck beam, we have calculated the corresponding pressure profiles. This new constraint from SZ measurements is consistent with the X-ray constraints from XMM-Newton in the region in which the profiles overlap (i.e., [0.1-1]R500), and is in fairly good agreement with theoretical predictions within the expected dispersion. At larger radii the average pressure profile is slightly flatter than most predictions from numerical simulations. Combining the SZ and X-ray observed profiles into a joint fit to a generalised pressure profile gives best-fit parameters [P0, c500, gamma, alpha, beta] = [6.41, 1.81, 0.31, 1.33, 4.13]. Using a reasonable hypothesis for the gas temperature in the cluster outskirts we reconstruct from our stacked pressure profile the gas mass fraction profile out to 3 x R500. Within the temperature driven uncertainties, our Planck constraints are compatible with the cosmic baryon fraction and expected gas fraction in halos.
We describe the BeyondPlanck project in terms of motivation, methodology and main products, and provide a guide to a set of companion papers that describe each result in fuller detail. We implement a complete end-to-end Bayesian analysis framework for the Planck LFI observations. The primary product is a full joint posterior distribution $P(\omega|d)$, where $\omega$ represents the set of all free instrumental, astrophysical, and cosmological parameters. Notable advantages of this approach are seamless end-to-end propagation of uncertainties; accurate modeling of both astrophysical and instrumental effects in the most natural basis for each uncertain quantity; optimized computational costs with little or no need for intermediate human interaction between various analysis steps; and a complete overview of the entire analysis process within one single framework. We focus in particular on low-$\ell$ CMB polarization reconstruction with Planck LFI. We identify several important new effects that have not been accounted for in previous pipelines, including gain over-smoothing and time-variable and non-$1/f$ correlated noise in the 30 and 44 GHz channels. We find that all results are consistent with the $\Lambda$CDM model, and we constrain the reionization optical depth to $\tau=0.066\pm0.013$, with a low-resolution $\chi^2$ probability-to-exceed of 32%. This uncertainty is about 30% larger than the official pipelines, arising from taking into account a more complete instrumental model. The marginal CMB Solar dipole amplitude is $3362.7\pm1.4\mu\mathrm{K}$, where the error bar is derived directly from the posterior distribution without the need of any ad-hoc instrumental corrections. We are currently not aware of any significant unmodelled systematic effects remaining in the Planck LFI data, and, for the first time, the 44 GHz channel is fully exploited. (Abridged.)
We present an analysis of the main systematic effects that could impact the measurement of CMB polarization with the proposed CORE space mission. We employ timeline-to-map simulations to verify that the CORE instrumental set-up and scanning strategy allow us to measure sky polarization to a level of accuracy adequate to the mission science goals. We also show how the CORE observations can be processed to mitigate the level of contamination by potentially worrying systematics, including intensity-to-polarization leakage due to bandpass mismatch, asymmetric main beams, pointing errors and correlated noise. We use analysis techniques that are well validated on data from current missions such as Planck to demonstrate how the residual contamination of the measurements by these effects can be brought to a level low enough not to hamper the scientific capability of the mission, nor significantly increase the overall error budget. We also present a prototype of the CORE photometric calibration pipeline, based on that used for Planck, and discuss its robustness to systematics, showing how CORE can achieve its calibration requirements. While a fine-grained assessment of the impact of systematics requires a level of knowledge of the system that can only be achieved in a future study phase, the analysis presented here strongly suggests that the main areas of concern for the CORE mission can be addressed using existing knowledge, techniques and algorithms.
The all-sky coverage of the Planck Early Release Compact Source Catalogue (ERCSC) provides an unsurpassed survey of galaxies at submillimetre (submm) wavelengths, representing a major improvement in the numbers of galaxies detected, as well as the range of far-IR/submm wavelengths over which they have been observed. We here present the first results on the properties of nearby galaxies using these data. We match the ERCSC catalogue to IRAS-detected galaxies in the Imperial IRAS Faint Source Redshift Catalogue (IIFSCz), so that we can measure the spectral energy distributions (SEDs) of these objects from 60 to 850 microns. This produces a list of 1717 galaxies with reliable associations between Planck and IRAS, from which we select a subset of 468 for SED studies, namely those with strong detections in the three highest frequency Planck bands and no evidence of cirrus contamination. The SEDs are fitted using parametric dust models to determine the range of dust temperatures and emissivities. We find evidence for colder dust than has previously been found in external galaxies, with T<20K. Such cold temperatures are found using both the standard single temperature dust model with variable emissivity beta, or a two dust temperature model with beta fixed at 2. We also compare our results to studies of distant submm galaxies (SMGs) which have been claimed to contain cooler dust than their local counterparts. We find that including our sample of 468 galaxies significantly reduces the distinction between the two populations. Fits to SEDs of selected objects using more sophisticated templates derived from radiative transfer models confirm the presence of the colder dust found through parameteric fitting. We thus conclude that cold (T<20K) dust is a significant and largely unexplored component of many nearby galaxies.
Using the ${\it Planck}$ full-mission data, we present a detection of the temperature (and therefore velocity) dispersion due to the kinetic Sunyaev-Zeldovich (kSZ) effect from clusters of galaxies. To suppress the primary CMB and instrumental noise we derive a matched filter and then convolve it with the ${\it Planck}$ foreground-cleaned `${\tt 2D-ILC\,}$' maps. By using the Meta Catalogue of X-ray detected Clusters of galaxies (MCXC), we determine the normalized ${\it rms}$ dispersion of the temperature fluctuations at the positions of clusters, finding that this shows excess variance compared with the noise expectation. We then build an unbiased statistical estimator of the signal, determining that the normalized mean temperature dispersion of $1526$ clusters is $\langle \left(\Delta T/T \right)^{2} \rangle = (1.64 \pm 0.48) \times 10^{-11}$. However, comparison with analytic calculations and simulations suggest that around $0.7\,\sigma$ of this result is due to cluster lensing rather than the kSZ effect. By correcting this, the temperature dispersion is measured to be $\langle \left(\Delta T/T \right)^{2} \rangle = (1.35 \pm 0.48) \times 10^{-11}$, which gives a detection at the $2.8\,\sigma$ level. We further convert uniform-weight temperature dispersion into a measurement of the line-of-sight velocity dispersion, by using estimates of the optical depth of each cluster (which introduces additional uncertainty into the estimate). We find that the velocity dispersion is $\langle v^{2} \rangle =(123\,000 \pm 71\,000)\,({\rm km}\,{\rm s}^{-1})^{2}$, which is consistent with findings from other large-scale structure studies, and provides direct evidence of statistical homogeneity on scales of $600\,h^{-1}{\rm Mpc}$. Our study shows the promise of using cross-correlations of the kSZ effect with large-scale structure in order to constrain the growth of structure.
We present Planck LFI frequency sky maps derived within the BeyondPlanck framework. This framework draws samples from a global posterior distribution that includes instrumental, astrophysical and cosmological parameters, and the main product is an entire ensemble of frequency sky map samples. This ensemble allows for computationally convenient end-to-end propagation of low-level instrumental uncertainties into higher-level science products. We show that the two dominant sources of LFI instrumental systematic uncertainties are correlated noise and gain fluctuations, and the products presented here support - for the first time - full Bayesian error propagation for these effects at full angular resolution. We compare our posterior mean maps with traditional frequency maps delivered by the Planck collaboration, and find generally good agreement. The most important quality improvement is due to significantly lower calibration uncertainties in the new processing, as we find a fractional absolute calibration uncertainty at 70 GHz of $\delta g_{0}/g_{0} =5 \cdot 10^{-5}$, which is nominally 40 times smaller than that reported by Planck 2018. However, the original Planck 2018 estimate has a non-trivial statistical interpretation, and this further illustrates the advantage of the new framework in terms of producing self-consistent and well-defined error estimates of all involved quantities without the need of ad hoc uncertainty contributions. We describe how low-resolution data products, including dense pixel-pixel covariance matrices, may be produced directly from the posterior samples without the need for computationally expensive analytic calculations or simulations. We conclude that posterior-based frequency map sampling provides unique capabilities in terms of low-level systematics modelling and error propagation, and may play an important role for future CMB B-mode experiments. (Abridged.)
We describe the processing of the 336 billion raw data samples from the High Frequency Instrument (HFI) which we performed to produce six temperature maps from the first 295 days of Planck-HFI survey data. These maps provide an accurate rendition of the sky emission at 100, 143, 217, 353, 545 and 857 GHz with an angular resolution ranging from 9.9 to 4.4^2. The white noise level is around 1.5 μK degree or less in the 3 main CMB channels (100--217GHz). The photometric accuracy is better than 2% at frequencies between 100 and 353 GHz and around 7% at the two highest frequencies. The maps created by the HFI Data Processing Centre reach our goals in terms of sensitivity, resolution, and photometric accuracy. They are already sufficiently accurate and well-characterised to allow scientific analyses which are presented in an accompanying series of early papers. At this stage, HFI data appears to be of high quality and we expect that with further refinements of the data processing we should be able to achieve, or exceed, the science goals of the Planck project.
We present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. We refer to other related papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.
