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We present an improved zodiacal light model for COBE-DIRBE derived through global Bayesian analysis within the Cosmoglobe Data Release 2 framework. The parametric form of the ZL model is identical to that introduced by Kelsall et al. (1998), but the specific best-fit parameter values are re-derived using the combination of DIRBE Calibrated Individual Observations, Planck HFI sky maps, and WISE and Gaia compact object catalogs. Furthermore, the ZL parameters are fitted jointly with astrophysical parameters, such as thermal dust and starlight emission, and the new model takes into account excess radiation that appears stationary in solar-centric coordinates as reported in a companion paper. The relative differences between the predicted signals from K98 and our new model are $\lesssim 5\%$ in the 12 and 25 $\mu$m channels over the full sky. The zero-levels of the cleaned DR2 maps are lower than those of the K98 Zodiacal light Subtracted Mission Average maps by $\sim 10$ kJy/sr at 1.25-3.5 $\mu$m, which is larger than the entire predicted contribution from high-redshift galaxies to the Cosmic Infrared Background at the same wavelengths. The total RMS of each DR2 map at wavelengths up to and including 25 $\mu$m are $\sim 30$ $\%$ lower at high Galactic latitudes than the corresponding DIRBE ZSMA maps. Still, obvious ZL residuals can be seen in several of the DR2 maps, and further work is required to mitigate these. Joint analysis with existing and future high-resolution full-sky surveys such as AKARI, IRAS, Planck HFI, and SPHEREx will be essential both to break key degeneracies in the current model and to determine whether the reported solar-centric excess radiation has a ZL or instrumental origin. Thus, while the results presented in this paper do redefine the state-of-the-art for DIRBE modelling, it also only represents the first among many steps toward a future optimal Bayesian ZL model., Comment: 27 pages, 21 figures, submitted to A&A

We present the first global Bayesian analysis of the time-ordered DIRBE data within the Cosmoglobe framework, building on the same methodology that has previously been successfully applied to Planck LFI and WMAP. These data are analyzed jointly with COBE-FIRAS, Gaia, Planck HFI, and WISE, allowing for more accurate instrumental and astrophysical characterization than possible through single-experiment analysis. This paper provides an overview of the analysis pipeline and main results, and we present and characterize a new set of zodiacal light subtracted mission average (ZSMA) DIRBE maps spanning 1.25 to 240 $\mu$m. A novel aspect of this processing is the characterization and removal of excess radiation between 4.9 and 60$\,\mu$m that appears static in solar-centric coordinates. The DR2 ZSMA maps have several advantages with respect to the previously available maps, including 1) lower zodiacal light (and possibly straylight) residuals; 2) better determined zero-levels; 3) natively HEALPix tessellated maps with a $7'$ pixel size; 4) nearly white noise at pixel scales; and 5) a more complete and accurate noise characterization established through the combination of MCMC samples and half-mission maps. In addition, because the model has been simultaneously fitted with both DIRBE and HFI data, this is the first consistent unification of the infrared and CMB wavelength ranges into one global sky model covering 100 GHz to 1 $\mu$m. However, even though the new maps are improved with respect to the official maps, and should be preferred for most future analyses that require DIRBE sky maps, they still exhibit non-negligible zodiacal light residuals between 12 and 60$\,\mu$m. Further improvements should be made through joint analysis with complementary infrared experiments such IRAS, AKARI, WISE and SPHEREx, and releasing the full combined potential of all these powerful infrared observatories., Comment: 30 pages, 23 figures, submitted to A&A. Comments welcome! Data can be found at https://www.cosmoglobe.uio.no/products/cosmoglobe-dr2.html

We derive new constraints on the CIB monopole spectrum from a set of reprocessed COBE-DIRBE sky maps that have lower instrumental and astrophysical contamination than the legacy DIRBE maps. These maps have been generated through a global Bayesian analysis framework that simultaneously fits cosmological, astrophysical, and instrumental parameters, as described in a series of papers collectively referred to as Cosmoglobe DR2. We have applied this method to the DIRBE TODs, complemented by selected HFI and FIRAS sky maps to break key astrophysical degeneracies, as well as WISE and Gaia compact object catalogs. In this paper, we focus on the CIB monopole constraints that result from this work. We report positive detections of an isotropic signal in six out of the ten DIRBE bands (1.25, 2.2, 3.5, 100, 140, and 240 $\mathrm{\mu m}$). For the 2.2 $\mu$m channel, we find an amplitude of $10.2\pm1.2\,\mathrm{nW\,m^{-2}\,sr^{-1}}$, 74 % lower than that reported from the official DIRBE maps. For the 240 $\mu\mathrm{m}$ channel, we find $6\pm3\mathrm{nW\,m^{-2}\,sr^{-1}}$, 56 % lower than the official DIRBE release. We interpret these lower values as resulting from improved zodiacal light and Galactic foreground modeling. For the bands between 4.9 and 60 $\mu\mathrm{m}$, the presence of excess radiation in solar-centric coordinates precludes the definition of lower limits. However, the analysis still provides well-defined upper limits. For the 12 $\mu\mathrm{m}$ channel, we find an upper 95 % confidence limit of 55 $\mathrm{nW\,m^{-2}\,sr^{-1}}$, more than a factor of eight lower than the corresponding legacy result of 468 $\mathrm{nW\,m^{-2}\,sr^{-1}}$. The results presented in this paper redefine the state-of-the-art CIB monopole constraints from COBE-DIRBE, and provide a real-world illustration of the power of global end-to-end analysis of multiple complementary datasets., Comment: 17 pages, 9 figures, submitted to A&A. Comments welcome! Data products can be found at https://www.cosmoglobe.uio.no/products/cosmoglobe-dr2.html

We revisit the impact of finite time responses of bolometric detectors used for deep observations of the cosmic microwave background (CMB). Until now, bolometer transfer functions have been accounted for through a two-step procedure by first deconvolving an estimate of their Fourier-space representation from the raw time-ordered data (TOD), and then averaging the deconvolved TOD into pixelized maps. However, for many experiments, including the Planck High Frequency Instrument (HFI), it is necessary to apply an additional low-pass filter to avoid an excessive noise boost, which leads to an asymmetric effective beam. In this paper we demonstrate that this effect can be avoided if the transfer function deconvolution and pixelization operations are performed simultaneously through integrated maximum likelihood mapmaking. The resulting algorithm is structurally identical to the artDeco algorithm introduced by Keih\"anen & Reinecke (2012) for beam deconvolution. We illustrate the relevance of this method with simulated Planck HFI 143 GHz data, and find that the resulting effective beam is both more symmetric than with the two-step procedure, resulting in a sky-averaged ellipticity that is 64 % lower, and an effective beam full-width-at-half-maximum (FWHM) that is 2.3 % smaller. Similar improvements are expected for any other bolometer-based CMB experiments with long time constants., Comment: 7 pages, 11 figures

We present the first model of full-sky polarized synchrotron emission that is derived from all WMAP and Planck LFI frequency maps. The basis of this analysis is the set of end-to-end reprocessed Cosmoglobe Data Release 1 sky maps presented in a companion paper, which have significantly lower instrumental systematics than the legacy products from each experiment. We find that the resulting polarized synchrotron amplitude map has an average noise rms of $3.2\,\mathrm{\mu K}$ at 30 GHz and $2^{\circ}$ FWHM, which is 30% lower than the recently released BeyondPlanck model that included only LFI+WMAP Ka-V data, and 29% lower than the WMAP K-band map alone. The mean $B$-to-$E$ power spectrum ratio is $0.40\pm0.02$, with amplitudes consistent with those measured previously by Planck and QUIJOTE. Assuming a power law model for the synchrotron spectral energy distribution, and using the $T$--$T$ plot method, we find a full-sky inverse noise-variance weighted mean of $\beta_{\mathrm{s}}=-3.07\pm0.07$ between Cosmoglobe DR1 K-band and 30 GHz, in good agreement with previous estimates. In summary, the novel Cosmoglobe DR1 synchrotron model is both more sensitive and systematically cleaner than similar previous models, and it has a more complete error description that is defined by a set of Monte Carlo posterior samples. We believe that these products are preferable over previous Planck and WMAP products for all synchrotron-related scientific applications, including simulation, forecasting and component separation., Comment: 15 pages, 15 figures, submitted to A&A

We implement support for a cosmological parameter estimation algorithm as proposed by Racine et al. (2016) in Commander, and quantify its computational efficiency and cost. For a semi-realistic simulation similar to Planck LFI 70 GHz, we find that the computational cost of producing one single sample is about 20 CPU-hours and that the typical Markov chain correlation length is $\sim$100 samples. The net effective cost per independent sample is $\sim$2 000 CPU-hours, in comparison with all low-level processing costs of 812 CPU-hours for Planck LFI and WMAP in Cosmoglobe Data Release 1. Thus, although technically possible to run already in its current state, future work should aim to reduce the effective cost per independent sample by one order of magnitude to avoid excessive runtimes, for instance through multi-grid preconditioners and/or derivative-based Markov chain sampling schemes. This work demonstrates the computational feasibility of true Bayesian cosmological parameter estimation with end-to-end error propagation for high-precision CMB experiments without likelihood approximations, but it also highlights the need for additional optimizations before it is ready for full production-level analysis., Comment: 10 pages, 8 figures. Accepted in A&A

Cosmic birefringence is a parity-violating effect that might have rotated the plane of linearly polarized light of the cosmic microwave background (CMB) by an angle $\beta$ since its emission. This has recently been measured to be non-zero at a statistical significance of $3.6\sigma$ in the official Planck PR4 and 9-year WMAP data. In this work, we constrain $\beta$ using the reprocessed BeyondPlanck LFI and Cosmoglobe DR1 WMAP polarization maps. These novel maps have both lower systematic residuals and a more complete error description than the corresponding official products. Foreground $EB$ correlations could bias measurements of $\beta$, and while thermal dust $EB$ emission has been argued to be statistically non-zero, no evidence for synchrotron $EB$ power has been reported. Unlike the dust-dominated Planck HFI maps, the majority of the LFI and WMAP polarization maps are instead dominated by synchrotron emission. Simultaneously constraining $\beta$ and the polarization miscalibration angle, $\alpha$, of each channel, we find a best-fit value of $\beta=0.35^{\circ}\pm0.70^{\circ}$ with LFI and WMAP data only. When including the Planck HFI PR4 maps, but fitting $\beta$ separately for dust-dominated, $\beta_{>70\,\mathrm{GHz}}$, and synchrotron-dominated channels, $\beta_{\leq 70\,\mathrm{GHz}}$, we find $\beta_{\leq 70\,\mathrm{GHz}}=0.53^{\circ}\pm0.28^\circ$. This differs from zero with a statistical significance of $1.9\sigma$, and the main contribution to this value comes from the LFI 70 GHz channel. While the statistical significances of these results are low on their own, the measurement derived from the LFI and WMAP synchrotron-dominated maps agrees with the previously reported HFI-dominated constraints, despite the very different astrophysical and instrumental systematics involved in all these experiments., Comment: 10 pages, 7 figures, 2 tables. Submitted to A&A

We present Cosmoglobe Data Release 1, which implements the first joint analysis of WMAP and Planck LFI time-ordered data, processed within a single Bayesian end-to-end framework. This framework builds directly on a similar analysis of the LFI measurements by the BeyondPlanck collaboration, and approaches the CMB analysis challenge through Gibbs sampling of a global posterior distribution, simultaneously accounting for calibration, mapmaking, and component separation. The computational cost of producing one complete WMAP+LFI Gibbs sample is 812 CPU-hr, of which 603 CPU-hrs are spent on WMAP low-level processing; this demonstrates that end-to-end Bayesian analysis of the WMAP data is computationally feasible. We find that our WMAP posterior mean temperature sky maps and CMB temperature power spectrum are largely consistent with the official WMAP9 results. Perhaps the most notable difference is that our CMB dipole amplitude is $3366.2 \pm 1.4\ \mathrm{\mu K}$, which is $11\ \mathrm{\mu K}$ higher than the WMAP9 estimate and $2.5\ {\sigma}$ higher than BeyondPlanck; however, it is in perfect agreement with the HFI-dominated Planck PR4 result. In contrast, our WMAP polarization maps differ more notably from the WMAP9 results, and in general exhibit significantly lower large-scale residuals. We attribute this to a better constrained gain and transmission imbalance model. It is particularly noteworthy that the W-band polarization sky map, which was excluded from the official WMAP cosmological analysis, for the first time appears visually consistent with the V-band sky map. Similarly, the long standing discrepancy between the WMAP K-band and LFI 30 GHz maps is finally resolved, and the difference between the two maps appears consistent with instrumental noise at high Galactic latitudes. All maps and the associated code are made publicly available through the Cosmoglobe web page., Comment: 65 pages, 61 figures. Data available at cosmoglobe.uio.no. Submitted to A&A

End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any other means. In this paper, we address an important issue regarding such simulations, namely how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data, or as a random realization independent from the data. We refer to these as Bayesian and frequentist simulations, respectively. We show that the two options lead to significantly different correlation structures, as frequentist simulations, contrary to Bayesian simulations, effectively include cosmic variance, but exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties, and we argue that they therefore also have different and complementary scientific uses, even if this dichotomy is not absolute. Before BeyondPlanck, most pipelines have used a mix of constrained and random inputs, and used the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BeyondPlanck represents the first end-to-end CMB simulation framework that is able to generate both types of simulations, and these new capabilities have brought this topic to the forefront. The Bayesian BeyondPlanck simulations and their uses are described extensively in a suite of companion papers. In this paper we consider one important applications of the corresponding frequentist simulations, namely code validation. That is, we generate a set of 1-year LFI 30 GHz frequentist simulations with known inputs, and use these to validate the core low-level BeyondPlanck algorithms; gain estimation, correlated noise estimation, and mapmaking.

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.), Comment: 32 pages, 23 figures, data available from https://www.cosmoglobe.uio.no/

We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations derived through global end-to-end Bayesian processing. We use these samples to study correlations between CMB, foreground, and instrumental parameters, and we identify a particularly strong degeneracy between CMB temperature fluctuations and free-free emission on intermediate angular scales, which is mitigated through model reduction, masking, and resampling. We compare our posterior-based CMB results with previous Planck products, and find generally good agreement, but with higher noise due to exclusion of HFI data. We find a best-fit CMB dipole amplitude of $3362.7\pm1.4{\mu}K$, in excellent agreement with previous Planck results. The quoted uncertainty is derived directly from the sampled posterior distribution, and does not involve any ad hoc contribution for systematic effects. Similarly, we find a temperature quadrupole amplitude of $\sigma^{TT}_2=229\pm97{\mu}K^2$, in good agreement with previous results in terms of the amplitude, but the uncertainty is an order of magnitude larger than the diagonal Fisher uncertainty. Relatedly, we find lower evidence for a possible alignment between $\ell = 2$ and $\ell = 3$ than previously reported due to a much larger scatter in the individual quadrupole coefficients, caused both by marginalizing over a more complete set of systematic effects, and by our more conservative analysis mask. For higher multipoles, we find that the angular temperature power spectrum is generally in good agreement with both Planck and WMAP. This is the first time the sample-based asymptotically exact Blackwell-Rao estimator has been successfully established for multipoles up to $\ell\le600$, and it now accounts for the majority of the cosmologically important information. Cosmological parameter constraints are presented in a companion paper. (Abriged), Comment: 26 pages, 24 figures. Submitted to A&A. Part of the BeyondPlanck paper suite

The BeyondPlanck and Cosmoglobe collaborations have implemented the first integrated Bayesian end-to-end analysis pipeline for CMB experiments. The primary long-term motivation for this work is to develop a common analysis platform that supports efficient global joint analysis of complementary radio, microwave, and sub-millimeter experiments. A strict prerequisite for this to succeed is broad participation from the CMB community, and two foundational aspects of the program are therefore reproducibility and Open Science. In this paper, we discuss our efforts toward this aim. We also discuss measures toward facilitating easy code and data distribution, community-based code documentation, user-friendly compilation procedures, etc. This work represents the first publicly released end-to-end CMB analysis pipeline that includes raw data, source code, parameter files, and documentation. We argue that such a complete pipeline release should be a requirement for all major future and publicly-funded CMB experiments, noting that a full public release significantly increases data longevity by ensuring that the data quality can be improved whenever better processing techniques, complementary datasets, or more computing power become available, and thereby also taxpayers' value for money; providing only raw data and final products is not sufficient to guarantee full reproducibility in the future.

We present cosmological parameter constraints as estimated using the Bayesian BeyondPlanck (BP) analysis framework. This method supports seamless end-to-end error propagation from raw time-ordered data to final cosmological parameters. As a first demonstration of the method, we analyze time-ordered Planck LFI observations, combined with selected external data (WMAP 33-61GHz, Planck HFI DR4 353 and 857GHz, and Haslam 408MHz) in the form of pixelized maps which are used to break critical astrophysical degeneracies. Overall, all results are generally in good agreement with previously reported values from Planck 2018 and WMAP, with the largest relative difference for any parameter of about 1 sigma when considering only temperature multipoles between 29

We describe the correction procedure for Analog-to-Digital Converter (ADC) differential non-linearities (DNL) adopted in the Bayesian end-to-end BeyondPlanck analysis framework. This method is nearly identical to that developed for the official LFI Data Processing Center (DPC) analysis, and relies on the binned rms noise profile of each detector data stream. However, rather than building the correction profile directly from the raw rms profile, we first fit a Gaussian to each significant ADC-induced rms decrement, and then derive the corresponding correction model from this smooth model. The main advange of this approach is that only samples which are significantly affected by ADC DNLs are corrected. The new corrections are only applied to data for which there is a clear detection of the non-linearities, and for which they perform at least comparably with the DPC corrections. Out of a total of 88 LFI data streams (sky and reference load for each of the 44 detectors) we apply the new minimal ADC corrections in 25 cases, and maintain the DPC corrections in 8 cases. All these correctsion are applited to 44 or 70 GHz channels, while, as in previous analyses, none of the 30 GHz ADCs show significant evidence of non-linearity. By comparing the BeyondPlanck and DPC ADC correction methods, we estimate that the residual ADC uncertainty is about two orders of magnitude below the total noise of both the 44 and 70 GHz channels, and their impact on current cosmological parameter estimation is small. However, we also show that non-idealities in the ADC corrections can generate sharp stripes in the final frequency maps, and these could be important for future joint analyses with HFI, WMAP, or other datasets. We therefore conclude that, although the existing corrections are adequate for LFI-based cosmological parameter analysis, further work on LFI ADC corrections is still warranted., Comment: 9 pages, 8 figures, mild language edits

We present the first application of the Cosmoglobe analysis framework by analyzing 9-year $\mathit{WMAP}$ time-ordered observations using similar machinery as BeyondPlanck utilizes for $\mathit{Planck}$ LFI. We analyze only the $\mathit Q$-band (41 GHz) data and report on the low-level analysis process from uncalibrated time-ordered data to calibrated maps. Most of the existing BeyondPlanck pipeline may be reused for $\mathit{WMAP}$ analysis with minimal changes to the existing codebase. The main modification is the implementation of the same preconditioned biconjugate gradient mapmaker used by the $\mathit{WMAP}$ team. Producing a single $\mathit{WMAP}$ $\mathit Q$1-band sample requires 22 CPU-hrs, which is slightly more than the cost of a $\mathit{Planck}$ 44 GHz sample of 17 CPU-hrs; this demonstrates that full end-to-end Bayesian processing of the $\mathit{WMAP}$ data is computationally feasible. In general, our recovered maps are very similar to the maps released by the $\mathit{WMAP}$ team, although with two notable differences. In temperature we find a $\sim2\,\mathrm{\mu K}$ quadrupole difference that most likely is caused by different gain modeling, while in polarization we find a distinct $2.5\,\mathrm{\mu K}$ signal that has been previously called poorly-measured modes by the $\mathit{WMAP}$ team. In the Cosmoglobe processing, this pattern arises from temperature-to-polarization leakage from the coupling between the CMB Solar dipole, transmission imbalance, and sidelobes. No traces of this pattern are found in either the frequency map or TOD residual map, suggesting that the current processing has succeeded in modelling these poorly measured modes within the assumed parametric model by using $\mathit{Planck}$ information to break the sky-synchronous degeneracies inherent in the $\mathit{WMAP}$ scanning strategy., Comment: 11 figures, submitted to A&A. Includes updated instrument model and changes addressing referee comments

We present the intensity foreground algorithms and model employed within the BeyondPlanck analysis framework. The BeyondPlanck analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the $Planck$ Low Frequency Instrument (LFI) data analysis. Given the scope of the BeyondPlanck analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous $\texttt{Commander}$ component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: 1) joint foreground spectral parameter and amplitude sampling, building on ideas from Miramare; 2) component-based monopole determination; 3) joint spectral parameter and monopole sampling; and 4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BeyondPlanck data set is the peak frequency of the anomalous microwave emission component, for which we find $\nu_{\mathrm{p}}=25.3\pm0.5$ GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects., Comment: 27 pages, 23 figures, 3 tables, part 13 of the BeyondPlanck release. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science. Paper version as accepted by A&A

We constrain the level of polarized anomalous microwave emission (AME) on large angular scales using $\textit{Planck}$ LFI and $\textit{WMAP}$ polarization data within a Bayesian CMB analysis framework. We model synchrotron emission with a power-law spectral energy distribution, and the sum of AME and thermal dust emission through linear regression with the $\textit{Planck}$ HFI 353 GHz data. This template-based dust emission model allows us to constrain the level of polarized AME while making minimal assumptions on its frequency dependence. We neglect cosmic microwave background fluctuations, but show through simulations that these have a minor impact on the results. We find that the resulting AME polarization fraction confidence limit is sensitive to the polarized synchrotron spectral index prior, and for priors steeper than $\beta_{\mathrm{s}} = -3.1\pm0.1$ we find an upper limit of $p_{\mathrm{AME}}^{\rm max}\lesssim 0.6\,\%$ ($95\,\%$ confidence). In contrast, for $\beta_{\mathrm{s}}=-3.0\pm0.1$, we find a nominal detection of $p_{\mathrm{AME}}=2.5\pm1.0\,\%$ ($95\,\%$ confidence). These data are thus not strong enough to simultaneously and robustly constrain both polarized synchrotron emission and AME, and our main result is therefore a constraint on the AME polarization fraction explicitly as a function of $\beta_\mathrm{s}$. Combining the current $\textit{Planck}$ and $\textit{WMAP}$ observations with measurements from high-sensitivity low-frequency experiments such as C-BASS and QUIJOTE will be critical to improve these limits further., Comment: 10 pages, 9 figures, part 15 of the BeyondPlanck release. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science. Refereed, edited, and accepted by A&A. Added references, added arxiv IDs to BeyondPlanck papers. Figure update. Expanded discussion on AME models. Moved title from BeyondPlanck XV to BeyondPlanck XVI due to internal reordering

We describe the computational infrastructure for end-to-end Bayesian CMB analysis implemented by the BeyondPlanck collaboration. This code is called commander3, and provides a statistically consistent framework for global analysis of CMB and microwave observations, and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs, or to reimplement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, FFT optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BeyondPlanck analysis, and find that a total of 1.5 TB of RAM is required for efficient analysis, and the total cost of a full Gibbs sample is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license., Comment: 16 Pages, 7 Figures. Part of the BeyondPlanck paper suite

We introduce a new formulation of the Conviqt convolution algorithm in terms of spin harmonics, and apply this to the problem of sidelobe correction for BeyondPlanck, the first end-to-end Bayesian Gibbs sampling framework for CMB analysis. We compare our implementation to the previous Planck LevelS implementation, and find good agreement between the two codes in terms of accuracy, but with a speed-up reaching a factor of 3--10, depending on the frequency bandlimits, $l_{\textrm{max}}$ and $m_{\textrm{max}}$. The new algorithm is significantly simpler to implement and maintain, since all low-level calculations are handled through an external spherical harmonic transform library. We find that our mean sidelobe estimates for Planck LFI agree well with previous efforts. Additionally, we present novel sidelobe rms maps that quantify the uncertainty in the sidelobe corrections due to variations in the sky model., Comment: 9 pages, 8 figures. Part of the BeyondPlanck paper suite

We discuss the treatment of bandpass and beam leakage corrections in the Bayesian BeyondPlanck CMB analysis pipeline as applied to the Planck LFI measurements. As a preparatory step, we first apply three corrections to the nominal LFI bandpass profiles including removal of a known systematic effect in the ground measuring equipment at 61 GHz; smoothing of standing wave ripples; and edge regularization. The main net impact of these modifications is an overall shift in the 70 GHz bandpass of +0.6 GHz; we argue that any analysis of LFI data products, either from Planck or BeyondPlanck, should use these new bandpasses. In addition, we fit a single free bandpass parameter for each radiometer of the form $\Delta_i = \Delta_0 + \delta_i$, where $\Delta_0$ represents an absolute frequency shift per frequency band and $\delta_i$ is a relative shift per detector. The absolute correction is only fitted at 30 GHz with a full $\chi^2$-based likelihood, resulting in a correction of $\Delta_{30}=0.24\pm0.03\,$GHz. The relative corrections are fitted using a spurious map approach, fundamentally similar to the method pioneered by the WMAP team, but without introducing many additional degrees of freedom. All bandpass parameters are sampled using a standard Metropolis sampler within the main BeyondPlanck Gibbs chain, and bandpass uncertainties are thus propagated to all other data products in the analysis. In total, we find that our bandpass model significantly reduces leakage effects. For beam leakage corrections, we adopt the official Planck LFI beam estimates without additional degrees of freedom, and only marginalize over the underlying sky model. We note that this is the first time leakage from beam mismatch has been included for Planck LFI maps., Comment: 14 pages, 11 figures, this is part 10 in the BeyondPlanck release. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science. Submitted to A&A

We constrain polarized foreground emission between 30 and 70 GHz with the Planck Low Frequency Instrument (LFI) and WMAP data within the global Bayesian BeyondPlanck framework. We combine for the first time full-resolution Planck LFI time-ordered data with low-resolution WMAP sky maps at 33, 40 and 61 GHz. Spectral parameters are fit with a likelihood defined at the native resolution of each frequency channel. This analysis represents the first implementation of true multi-resolution component separation applied to CMB observations for both amplitude and spectral energy distribution (SED) parameters. For synchrotron emission, we approximate the SED as a power-law in frequency and find that the low signal-to-noise ratio of the current data strongly limits the number of free parameters that may be robustly constrained. We partition the sky into four large disjoint regions (High Latitude; Galactic Spur; Galactic Plane; and Galactic Center), each associated with its own power-law index. We find that the High Latitude region is prior-dominated, while the Galactic Center region is contaminated by residual instrumental systematics. The two remaining regions appear to be signal-dominated, and for these we derive spectral indices of $\beta_{\mathrm s}^{\mathrm{Spur}}=-3.17\pm0.06$ and $\beta_{\mathrm s}^{\mathrm{Plane}}=-3.03\pm0.07$, in good agreement with previous results. For thermal dust emission we assume a modified blackbody model and we fit a single power-law index across the full sky. We find $\beta_{\mathrm{d}}=1.64\pm0.03$, which is slightly steeper than reported from Planck HFI data, but still statistically consistent at the 2$\sigma$ confidence level., Comment: 18 pages, 15 figures. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science. This paper has been submitted to A&A. Major revision, matches submitted version

We present a Bayesian calibration algorithm for CMB observations as implemented within the global end-to-end BeyondPlanck (BP) framework, and apply this to the Planck Low Frequency Instrument (LFI) data. Following the most recent Planck analysis, we decompose the full time-dependent gain into a sum of three orthogonal components: One absolute calibration term, common to all detectors; one time-independent term that can vary between detectors; and one time-dependent component that is allowed to vary between one-hour pointing periods. Each term is then sampled conditionally on all other parameters in the global signal model through Gibbs sampling. The absolute calibration is sampled using only the orbital dipole as a reference source, while the two relative gain components are sampled using the full sky signal, including the orbital and Solar CMB dipoles, CMB fluctuations, and foreground contributions. We discuss various aspects of the data that influence gain estimation, including the dipole/polarization quadrupole degeneracy and anomalous jumps in the instrumental gain. Comparing our solution to previous pipelines, we find good agreement in general, with relative deviations of -0.67% (-0.84%) for 30 GHz, 0.12% (-0.04%) for 44 GHz and -0.03% (-0.64%) for 70 GHz, compared to Planck DR4 (Planck 2018). The deviations we find are within expected error bounds, and we attribute them to differences in data usage and general approach between the pipelines. In particular, the BP calibration is performed globally, resulting in better inter-frequency consistency. Additionally, WMAP observations are used actively in the BP analysis, which breaks degeneracies in the Planck data set and results in better agreement with WMAP. Although our presentation and algorithm are currently oriented toward LFI processing, the procedure is fully generalizable to other experiments., Comment: 19 pages, 18 figures. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science

We present a Bayesian method for estimating instrumental noise parameters and propagating noise uncertainties within the global BeyondPlanck Gibbs sampling framework, and apply this to Planck Low Frequency Instrument (LFI) time-ordered data. Following previous literature, we initially adopt a $1/f$ model for the noise power spectral density (PSD), but find the need for an additional lognormal component in the noise model for the 30 and 44\,GHz bands. We implement an optimal Wiener-filter (or constrained realization) gap-filling procedure to account for masked data. We then use this procedure to both estimate the gapless correlated noise in the time-domain, $n_\mathrm{corr}$, and to sample the noise PSD parameters, $\xi^n = \{\sigma_0, f_\mathrm{knee}, \alpha, A_\mathrm{p}\}$. In contrast to previous \textit{Planck} analyses, we assume piecewise stationary noise only within each pointing period (PID), not throughout the full mission, but we adopt the LFI Data Processing Center (DPC) results as priors on $\alpha$ and $f_\mathrm{knee}$. On average, we find best-fit correlated noise parameters that are mostly consistent with previous results, with a few notable exceptions. However, a detailed inspection of the time-dependent results reveals many important findings. First and foremost, we find strong evidence for statistically significant temporal variations in all noise PSD parameters, many of which are directly correlated with satellite housekeeping data. Second, while the simple $1/f$ model appears to be an excellent fit for the LFI 70 GHz channel, there is evidence for additional correlated noise not described by a $1/f$ model in the 30 and 44 GHz channels, including within the primary science frequency range of 0.1--1 Hz. (Abridged), Comment: 26 pages, 29 figures, as accepted in A&A

We present a Gibbs sampling solution to the map-making problem for CMB measurements, building on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps; noise filtering and map binning. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods, and allows us for the first time to bring the destriping baseline length to a single sample. We apply the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we may compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction, and this methodology forms the conceptual basis for the map-making algorithm employed in the BeyondPlanck framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations., Comment: 11 pages, 10 figures. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science during the online release conference (November 18-20, 2020). Connection details will be made available at the same website. Registration is mandatory for the online tutorial, but optional for the conference

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.), Comment: 61 pages, 31 figures, submitted to A&A. Major revision: Previously reported unresolved effects are now understood and mitigated. This paper version concludes the BeyondPlanck project. All BeyondPlanck products and software are available at https://cosmoglobe.uio.no

We explore the fundamental limits to which reionization histories can be constrained using only large-scale cosmic microwave background (CMB) anisotropy measurements. The redshift distribution of the fractional ionization $x_e(z)$ affects the angular distribution of CMB polarization. We project constraints on the reionization history of the universe using low-noise full-sky temperature and E-mode measurements of the CMB. We show that the measured TE power spectrum, $\hat C_\ell^\mathrm{TE}$, has roughly one quarter of the constraining power of $\hat C_\ell^\mathrm{EE}$ on the reionization optical depth $\tau$, and its addition improves the precision on $\tau$ by 20% over using $\hat C_\ell^\mathrm{EE}$ only. We also use a two-step reionization model with an additional high redshift step, parametrized by an early ionization fraction $x_e^\mathrm{min}$, and a late reionization step at $z_\mathrm{re}$. We find that future high signal-to-noise measurements of the multipoles $10\leqslant\ell<20$ are especially important for breaking the degeneracy between $x_e^\mathrm{min}$ and $z_\mathrm{re}$. In addition, we show that the uncertainties on these parameters determined from a map with sensitivity $10\,\mathrm{\mu K\,arcmin}$ are less than 5% larger than the uncertainties in the noiseless case, making this noise level a natural target for future large sky area E-mode measurements., Comment: 13 pages, 10 figures, matches version accepted by ApJ, corrected author information

The reionization optical depth is the most poorly determined of the six $\Lambda$CDM parameters fit to CMB anisotropy data. Instrumental noise and systematics have prevented uncertainties from reaching their cosmic variance limit. At present, the datasets providing the most statistical constraining power are the WMAP, Planck LFI, and Planck HFI full-sky polarization maps. As the reprocessed HFI data with reduced systematics are not yet publicly unavailable, we examine determinations of $\tau$ using 9-year WMAP and 2015 Planck LFI data, with an emphasis on characterizing potential systematic bias resulting from foreground template and masking choices. We find evidence for a low-level systematic in the LFI polarization data with a roughly common-mode morphology across the LFI frequencies and a spectrum consistent with leakage of intensity signal into the polarization channels. We demonstrate significant bias in the optical depth derived when using the LFI 30 GHz map as a template to clean synchrotron from WMAP data, and recommend against use of the 2015 LFI 30 GHz polarization data as a foreground template for non-LFI datasets. We find an inconsistency between versions of the 2015 polarized 353 GHz dust templates reconstructed from the Planck likelihood and those from delivered maps, which can affect $\tau$ at the 1$\sigma$ level. The spread in $\tau$ values over the ensemble of data combinations we study suggests that systematic uncertainties still contribute significantly to the current uncertainty in $\tau$, but all values are consistent with the range of $\tau$ = 0.07 +/- 0.02., Comment: 13 pages, 7 figures, accepted for publication by ApJ

We examine the impact of baryon acoustic oscillation (BAO) scale measurements on the discrepancy between the value of the Hubble constant ($H_0$) inferred from the local distance ladder and from Planck cosmic microwave background (CMB) data. While the BAO data alone cannot constrain $H_0$, we show that combining the latest BAO results with WMAP, Atacama Cosmology Telescope (ACT), or South Pole Telescope (SPT) CMB data produces values of $H_0$ that are $2.4-3.1\sigma$ lower than the distance ladder, independent of Planck, and that this downward pull was less apparent in some earlier analyses that used only angle-averaged BAO scale constraints rather than full anisotropic information. At the same time, the combination of BAO and CMB data also disfavors the lower values of $H_0$ preferred by the Planck high-multipole temperature power spectrum. Combining galaxy and Lyman-$\alpha$ forest (Ly$\alpha$) BAO with a precise estimate of the primordial deuterium abundance produces $H_0=66.98\pm1.18$ km s$^{-1}$ Mpc$^{-1}$ for the flat $\Lambda$CDM model. This value is completely independent of CMB anisotropy constraints and is $3.0\sigma$ lower than the latest distance ladder constraint, although $2.4\sigma$ tension also exists between the galaxy BAO and Ly$\alpha$ BAO. These results show that it is not possible to explain the $H_0$ disagreement solely with a systematic error specific to the Planck data. The fact that tensions remain even after the removal of any single data set makes this intriguing puzzle all the more challenging to resolve., Comment: 13 pages, 4 figures, updated to match version accepted by ApJ (extra panel in Fig 3, some additional text, no changes to results or conclusions)

We examine the internal consistency of the Planck 2015 cosmic microwave background (CMB) temperature anisotropy power spectrum. We show that tension exists between cosmological constant cold dark matter (LCDM) model parameters inferred from multipoles l<1000 (roughly those accessible to Wilkinson Microwave Anisotropy Probe), and from l>=1000, particularly the CDM density, Omega_ch^2, which is discrepant at 2.5 sigma for a Planck-motivated prior on the optical depth, tau=0.07+/-0.02. We find some parameter tensions to be larger than previously reported because of inaccuracy in the code used by the Planck Collaboration to generate model spectra. The Planck l>=1000 constraints are also in tension with low-redshift data sets, including Planck's own measurement of the CMB lensing power spectrum (2.4 sigma), and the most precise baryon acoustic oscillation (BAO) scale determination (2.5 sigma). The Hubble constant predicted by Planck from l>=1000, H_0=64.1+/-1.7 km/s/Mpc, disagrees with the most precise local distance ladder measurement of 73.0+/-2.4 km/s/Mpc at the 3.0 sigma level, while the Planck value from l<1000, 69.7+/-1.7 km/s/Mpc, is consistent within 1 sigma. A discrepancy between the Planck and South Pole Telescope (SPT) high-multipole CMB spectra disfavors interpreting these tensions as evidence for new physics. We conclude that the parameters from the Planck high-multipole spectrum probably differ from the underlying values due to either an unlikely statistical fluctuation or unaccounted-for systematics persisting in the Planck data., Comment: 8 pages, 7 figures, updated to match version accepted by ApJ

Variable-delay Polarization Modulators (VPMs) are currently being implemented in experiments designed to measure the polarization of the cosmic microwave background on large angular scales because of their capability for providing rapid, front-end polarization modulation and control over systematic errors. Despite the advantages provided by the VPM, it is important to identify and mitigate any time-varying effects that leak into the synchronously modulated component of the signal. In this paper, the effect of emission from a $300$ K VPM on the system performance is considered and addressed. Though instrument design can greatly reduce the influence of modulated VPM emission, some residual modulated signal is expected. VPM emission is treated in the presence of rotational misalignments and temperature variation. Simulations of time-ordered data are used to evaluate the effect of these residual errors on the power spectrum. The analysis and modeling in this paper guides experimentalists on the critical aspects of observations using VPMs as front-end modulators. By implementing the characterizations and controls as described, front-end VPM modulation can be very powerful for mitigating $1/f$ noise in large angular scale polarimetric surveys. None of the systematic errors studied fundamentally limit the detection and characterization of B-modes on large scales for a tensor-to-scalar ratio of $r=0.01$. Indeed, $r<0.01$ is achievable with commensurately improved characterizations and controls., Comment: 13 pages, 13 figures, 1 table, matches published version

Models of contagion arise broadly both in the biological and social sciences, with applications ranging from the transmission of infectious diseases to the diffusion of innovations and the spread of cultural fads. In this Letter, we introduce a general model of contagion which, by explicitly incorporating memory of past exposures to, for example, an infectious agent, rumor, or new product, includes the main features of existing contagion models and interpolates between them. We obtain exact solutions for a simple version of the model, finding that under general conditions only three classes of collective dynamics exist, two of which correspond to familiar epidemic threshold and critical mass dynamics, while the third is a distinct intermediate case. We find that for a given length of memory, the class into which a particular system falls is determined by two parameters, each of which ought to be measurable empirically. Our model suggests novel measures for assessing the susceptibility of a population to large contagion events, and also a possible strategy for inhibiting or facilitating them., Comment: 5 pages, 2 figures; to appear in Phys. Rev. Lett., 2004

Social networks have the surprising property of being "searchable": Ordinary people are capable of directing messages through their network of acquaintances to reach a specific but distant target person in only a few steps. We present a model that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions. Our model defines a class of searchable networks and a method for searching them that may be applicable to many network search problems, including the location of data files in peer-to-peer networks, pages on the World Wide Web, and information in distributed databases., Comment: 4 page, 3 figures, revtex

Recent work on the internet, social networks, and the power grid has addressed the resilience of these networks to either random or targeted deletion of network nodes. Such deletions include, for example, the failure of internet routers or power transmission lines. Percolation models on random graphs provide a simple representation of this process, but have typically been limited to graphs with Poisson degree distribution at their vertices. Such graphs are quite unlike real world networks, which often possess power-law or other highly skewed degree distributions. In this paper we study percolation on graphs with completely general degree distribution, giving exact solutions for a variety of cases, including site percolation, bond percolation, and models in which occupation probabilities depend on vertex degree. We discuss the application of our theory to the understanding of network resilience., Comment: 4 pages, 2 figures

Recent work on the structure of social networks and the internet has focussed attention on graphs with distributions of vertex degree that are significantly different from the Poisson degree distributions that have been widely studied in the past. In this paper we develop in detail the theory of random graphs with arbitrary degree distributions. In addition to simple undirected, unipartite graphs, we examine the properties of directed and bipartite graphs. Among other results, we derive exact expressions for the position of the phase transition at which a giant component first forms, the mean component size, the size of the giant component if there is one, the mean number of vertices a certain distance away from a randomly chosen vertex, and the average vertex-vertex distance within a graph. We apply our theory to some real-world graphs, including the world-wide web and collaboration graphs of scientists and Fortune 1000 company directors. We demonstrate that in some cases random graphs with appropriate distributions of vertex degree predict with surprising accuracy the behavior of the real world, while in others there is a measurable discrepancy between theory and reality, perhaps indicating the presence of additional social structure in the network that is not captured by the random graph., Comment: 19 pages, 11 figures, some new material added in this version along with minor updates and corrections

The small-world network model is a simple model of the structure of social networks, which simultaneously possesses characteristics of both regular lattices and random graphs. The model consists of a one-dimensional lattice with a low density of shortcuts added between randomly selected pairs of points. These shortcuts greatly reduce the typical path length between any two points on the lattice. We present a mean-field solution for the average path length and for the distribution of path lengths in the model. This solution is exact in the limit of large system size and either large or small number of shortcuts., Comment: 14 pages, 2 postscript figures

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one non-trivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the cross-over from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Pade approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model., Comment: 12 pages including 9 postscript figures, minor corrections and additions made in this version

We study the small-world network model, which mimics the transition between regular-lattice and random-lattice behavior in social networks of increasing size. We contend that the model displays a normal continuous phase transition with a divergent correlation length as the degree of randomness tends to zero. We propose a real-space renormalization group transformation for the model and demonstrate that the transformation is exact in the limit of large system size. We use this result to calculate the exact value of the single critical exponent for the system, and to derive the scaling form for the average number of "degrees of separation" between two nodes on the network as a function of the three independent variables. We confirm our results by extensive numerical simulation., Comment: 4 pages including 3 postscript figures