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S. Paradiso

Publications and source records attributed to S. Paradiso.

At least 19 recordsLinked to original sources

Implementation of frequency-correlated noise in CMB component separation: Method, Validation, and Early Applications

Parametric component separation methods used in cosmic microwave background (CMB) analyses commonly assume instrumental noise to be uncorrelated between frequency channels. This approximation may become insufficient for experiments whose design naturally introduces cross-channel correlations, such as interferometric or multi-band bolometric systems. This work aims to provide a consistent framework to include frequency-correlated noise in Commander2 and to quantify its impact on component separation in controlled and instrument-motivated simulations. We generalized the amplitude sampling of the Commander2 framework to consistently handle dense frequency-frequency noise covariance matrices, modifying the likelihood evaluation and parallel architecture. The implementation is validated on low-resolution simulations of a simplified CMB-S4-like configuration. We applied the generalized framework to instrument-motivated simulations of the QUBIC bolometric interferometer, using representative noise models derived from end-to-end simulations. Validation tests show excellent convergence and agreement between sampled parameters and analytical maximum-likelihood estimates. Accounting for frequency correlations reduces the width of the maximum-likelihood residual distributions by up to 8% on average, and up to 11% for individual parameters, relative to the diagonal-noise approximation. In QUBIC-based simulations, accounting for an anti-correlated noise produces posterior widths reduced by about 60%, while a positive-correlation test increases them by about 40%. This shows that neglecting cross-channel correlations can lead to incorrect posterior estimates in either direction. The generalized implementation presented here enables the Commander2 software to consistently propagate such correlations into parameter estimation, providing a framework for assessing their impact in future CMB analyses.

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Planck constraints on the scale dependence of isotropic cosmic birefringence

The rotation of the linear polarisation plane of photons during propagation, also known as cosmic birefringence, is a powerful probe of parity-violating extensions of standard electromagnetism. Using Planck legacy data, we confirm previous estimates of the isotropic birefringence angle, finding $\beta \simeq 0.30 \pm 0.05$ [deg] at 68% CL, not including the systematic error from the instrumental polarisation angle. If this is a genuine signal, it could be explained by theories of Chern--Simons-type coupled to electromagnetism, which could lead to a harmonic scale-dependent birefringence signal, if the hypothesis of an ultra-light (pseudo) scalar field does not hold. To investigate these models, we pursue two complementary approaches: first, we fit the birefringence angle estimated at different multipoles, $\beta_{\ell}$, with a power-law model and second, we perform a non-parametric Bayesian reconstruction of it. Both methods yield results consistent with a non-vanishing constant birefringence angle. The first method shows no significant dependence on the harmonic scale (up to $1.8\sigma$ CL), while the second method demonstrates that a constant model is favored by Bayesian evidence. This conclusion is robust across all four published Planck CMB solutions. Finally, we forecast that upcoming CMB observations by Simons Observatory, LiteBIRD and a wishful CMB-Stage 4 experiment could reduce current uncertainties by a factor of approximately 7.

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Reducing nuisance prior sensitivity via non-linear reparameterization, with application to EFT analyses of large-scale structure

Many physical models contain nuisance parameters that quantify unknown properties of an experiment that are not of primary relevance. Typically, these cannot be measured except by fitting the models to the data from the experiment, requiring simultaneous measurement of interesting parameters that are our target of inference and nuisance terms that are not directly of interest. A recent example of this is fitting Effective Field Theory (EFT) models to large-scale structure (LSS) data to make cosmological inferences. These models have a large number of nuisance parameters that are typically correlated with cosmological parameters in the posterior, leading to strong dependence on the nuisance parameter priors. We introduce a reparametrization method that leverages Generalized Additive Models (GAMs) to decorrelate nuisance parameters from the parameters of interest in the likelihood, even in the presence of non-linear relationships. This reparametrization forms a natural basis within which to define priors that are independent between nuisance and target parameters: the separation means that the marginal posterior for cosmological parameters does not depend on simple priors placed on nuisance terms. In application to EFT models using LSS data, we demonstrate that the proposed approach leads to robust cosmological inference.

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Evaluating extensions to LCDM: an application of Bayesian model averaging and selection

We employ Bayesian Model Averaging (BMA) as a powerful statistical framework to address key cosmological questions about the universe's fundamental properties. We explore extensions beyond the standard $\Lambda$CDM model, considering a varying curvature density parameter $\Omega_{\rm k}$, a spectral index $\mathrm{n}_{\rm s}=1$ and a varying $n_{\rm run}$, a constant dark energy equation of state (EOS) $w_0$CDM and a time-dependent one $w_0w_a$CDM. We also test cosmological data against a varying effective number of neutrino species $N_{\rm eff}$. Data from different combinations of cosmic microwave background (CMB) data from the last Planck PR4 analysis, CMB lensing from Planck 2018, baryonic acoustic oscillations (BAO) and the Bicep-KECK 2018 results, are used. We find that the standard $\Lambda$CDM model is favoured when combining CMB data with CMB lensing, BAO and Bicep-KECK 2018 data against $K-\Lambda$CDM model $N_{\rm eff}-\Lambda$CDM with a probability $> 80\%$. When investigating the dark energy EOS, we find that this dataset is not able to express a strong preference between the standard $\Lambda$CDM model and the constant dark energy EOS model $w_0$CDM, with an approximately split model posterior probability of $\approx 60\%:40\%$ in favour of $\Lambda$CDM, whereas the time-varying dark energy EOS model is ruled out. Finally, we find that the CMB data alone show a strong preference for a model that includes the running of the spectral index $n_{\rm run}$, with a probability $\approx 90\%$, when compared to the $n_{\rm s}=1$ model and the standard $\Lambda$CDM. Overall, we find that including the model uncertainty in the considered cases does not significantly impact the Hubble tension.

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LSPE-STRIP on-sky calibration strategy using bright celestial sources

In this paper we describe the global on-sky calibration strategy of the LSPE-Strip instrument. Strip is a microwave telescope operating in the Q- and W-bands (central frequencies of 43 and 95 GHz respectively) from the Observatorio del Teide in Tenerife, with the goal to observe and characterise the polarised Galactic foreground emission, and complement the observations of the polarisation of the cosmic microwave background to be performed by the LSPE-SWIPE instrument and other similar experiments operating at higher frequencies to target the detection of the B-mode signal from the inflationary epoch of the Universe. Starting from basic assumptions on some of the instrument parameters (NET, 1/f noise knee frequency, beam properties, observing efficiency) we perform realistic simulations to study the level of accuracy that can be achieved through observations of bright celestial calibrators in the Strip footprint (sky fraction of 30 %) on the determination and characterisation of the main instrument parameters: global and relative gain factors (in intensity and in polarisation), polarisation direction, polarisation efficiency, leakage from intensity to polarisation, beams, window functions and pointing model.

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Measuring the CMB primordial B-modes with Bolometric Interferometry

The Q&U Bolometric Interferometer for Cosmology (QUBIC) is the first bolometric interferometer designed to measure the primordial B-mode polarization of the Cosmic Microwave Background (CMB). Bolometric interferometry is a novel technique that combines the sensitivity of bolometric detectors with the control of systematic effects that is typical of interferometry, both key features in the quest for the faint signal of the primordial B-modes. A unique feature is the so-called "spectral imaging", i.e., the ability to recover the sky signal in several sub-bands within the physical band during data analysis. This feature provides an in-band spectral resolution of \Delta{\nu}/{\nu} \sim 0.04 that is unattainable by a traditional imager. This is a key tool for controlling the Galactic foregrounds contamination. In this paper, we describe the principles of bolometric interferometry, the current status of the QUBIC experiment and future prospects.

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The advantage of Bolometric Interferometry for controlling Galactic foreground contamination in CMB primordial B-modes measurements

In the quest for the faint primordial B-mode polarization of the Cosmic Microwave Background, three are the key requirements for any present or future experiment: an utmost sensitivity, excellent control over instrumental systematic effects and over Galactic foreground contamination. Bolometric Interferometry (BI) is a novel technique that matches them all by combining the sensitivity of bolometric detectors, the control of instrumental systematics from interferometry and a software-based, tunable, in-band spectral resolution due to its ability to perform band-splitting during data analysis (spectral imaging). In this paper, we investigate how the spectral imaging capability of BI can help in detecting residual contamination in case an over-simplified model of foreground emission is assumed in the analysis. To mimic this situation, we focus on the next generation of ground-based CMB experiment, CMB-S4, and compare its anticipated sensitivities, frequency and sky coverage with a hypothetical version of the same experiment based on BI, CMB-S4/BI, assuming that line-of-sight (LOS) frequency decorrelation is present in dust emission but is not accounted for during component separation. We show results from a Monte-Carlo analysis based on a parametric component separation method (FGBuster), highlighting how BI has the potential to diagnose the presence of foreground residuals in estimates of the tensor-to-scalar ratio $r$ in the case of unaccounted Galactic dust LOS frequency decorrelation.

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A convenient approach to characterizing model uncertainty with application to early dark energy solutions of the Hubble tension

Despite increasingly precise observations and sophisticated theoretical models, the discrepancy between measurements of H0 from the cosmic microwave background or from Baryon Acoustic Oscillations combined with Big-Bang Nucleosynthesis versus those from local distance ladder probes -- commonly known as the $H_0$ tension -- continues to perplex the scientific community. To address this tension, Early Dark Energy (EDE) models have been proposed as alternatives to $\Lambda$CDM, as they can change the observed sound horizon and the inferred Hubble constant from measurements based on this. In this paper, we investigate the use of Bayesian Model Averaging (BMA) to evaluate EDE as a solution to the H0 tension. BMA consists of assigning a prior to the model and deriving a posterior as for any other unknown parameter in a Bayesian analysis. BMA can be computationally challenging in that one must approximate the joint posterior of both model and parameters. Here we present a computational strategy for BMA that exploits existing MCMC software and combines model-specific posteriors post-hoc. In application to a comprehensive analysis of cosmological datasets, we quantify the impact of EDE on the H0 discrepancy. We find an EDE model probability of $\sim$90% whenever we include the H0 measurement from Type Ia Supernovae in the analysis, whereas the other data show a strong preference for the standard cosmological model. We finally present constraints on common parameters marginalized over both cosmological models. For reasonable priors on models with and without EDE, the H0 tension is reduced by at least 20%.

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Identifying frequency decorrelated dust residuals in B-mode maps by exploiting the spectral capability of bolometric interferometry

Astrophysical polarized foregrounds represent the most critical challenge in Cosmic Microwave Background (CMB) B-mode experiments. Multi-frequency observations can be used to constrain astrophysical foregrounds to isolate the CMB contribution. However, recent observations indicate that foreground emission may be more complex than anticipated. We investigate how the increased spectral resolution provided by band splitting in Bolometric Interferometry (BI) through a technique called spectral imaging can help control the foreground contamination in the case of unaccounted Galactic dust frequency decorrelation along the line-of-sight. We focus on the next generation ground-based CMB experiment CMB-S4, and compare its anticipated sensitivities, frequency and sky coverage with a hypothetical version of the same experiment based on BI. We perform a Monte-Carlo analysis based on parametric component separation methods (FGBuster and Commander) and compute the likelihood on the recovered tensor-to-scalar ratio. The main result of this analysis is that spectral imaging allows us to detect systematic uncertainties on r from frequency decorrelation when this effect is not accounted for in component separation. Conversely, an imager would detect a biased value of r and would be unable to spot the presence of a systematic effect. We find a similar result in the reconstruction of the dust spectral index, where we show that with BI we can measure more precisely the dust spectral index also when frequency decorrelation is present. The in-band frequency resolution provided by BI allows us to identify dust LOS frequency decorrelation residuals where an imager of similar performance would fail. This opens the prospect to exploit this potential in the context of future CMB polarization experiments that will be challenged by complex foregrounds in their quest for B-modes detection.

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Cosmoglobe: Towards end-to-end CMB cosmological parameter estimation without likelihood approximations

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.

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Cosmoglobe DR1 results. II. Constraints on isotropic cosmic birefringence from reprocessed WMAP and Planck LFI data

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.

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Cosmoglobe DR1 results. I. Improved Wilkinson Microwave Anisotropy Probe maps through Bayesian end-to-end analysis

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.

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Status of QUBIC, the Q&U Bolometer for Cosmology

The Q&U Bolometric Interferometer for Cosmology (QUBIC) is a novel kind of polarimeter optimized for the measurement of the B-mode polarization of the Cosmic Microwave Back-ground (CMB), which is one of the major challenges of observational cosmology. The signal is expected to be of the order of a few tens of nK, prone to instrumental systematic effects and polluted by various astrophysical foregrounds which can only be controlled through multichroic observations. QUBIC is designed to address these observational issues with a novel approach that combines the advantages of interferometry in terms of control of instrumental systematics with those of bolometric detectors in terms of wide-band, background-limited sensitivity.

astro-ph.IM

BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics

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.

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BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation

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)

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BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation

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.)

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From BeyondPlanck to Cosmoglobe: Open Science, Reproducibility, and Data Longevity

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.

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BeyondPlanck XII. Cosmological parameter constraints with end-to-end error propagation

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<l<601. In cases where there are differences, we note that the BP results are generally slightly closer to the high-l HFI-dominated Planck 2018 results than previous analyses, suggesting slightly less tension between low and high multipoles. Using low-l polarization information from LFI and WMAP, we find a best-fit value of tau=0.066 +/- 0.013, which is higher than the low value of tau=0.051 +/- 0.006 derived from Planck 2018 and slightly lower than the value of 0.069 +/- 0.011 derived from joint analysis of official LFI and WMAP products. Most importantly, however, we find that the uncertainty derived in the BP processing is about 30% larger than when analyzing the official products, after taking into account the different sky coverage. We argue that this is due to marginalizing over a more complete model of instrumental and astrophysical parameters, and this results in both more reliable and more rigorously defined uncertainties. We find that about 2000 Monte Carlo samples are required to achieve robust convergence for low-resolution CMB covariance matrix with 225 independent modes.

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