arXiv subjects

M. San

Publications and source records attributed to M. San.

18 recordsLinked to original sources

arXiv2026

Cosmoglobe DR2. VI. Disentangling hot and cold thermal dust emission with Planck HFI

We present a four-component high-resolution model of thermal dust emission for microwave and sub-mm frequencies derived from Planck HFI, WHAM and Gaia. The resulting high-resolution model derived here forms the basis for the thermal dust model employed in the Cosmoglobe DR2 reanalysis of COBE-DIRBE. The four dust components are called ``cold dust'', ``hot dust'', ``nearby dust'', and ``Ha correlated dust'', respectively, and trace different physical environments. The spatial distributions of the nearby dust and Ha dust components are defined by the Edenhofer et al. Gaia 3D extinction model and the WHAM survey, respectively, while the hot and cold dust components are fit freely pixel-by-pixel to the Planck HFI data. We use a global parameter grid search coupled to an amplitude map Gibbs sampler to fit this model to Planck HFI data. In agreement with the companion low-resolution analysis, we find that the hot dust component is strongly correlated with the FIRAS Cii map, while the cold dust component is strongly correlated with the HI4PI Hi map. Despite its fewer degrees of freedom per pixel compared to the Planck 2015 legacy dust model, we find that this new model performs competitively in terms of overall residuals, capturing over 98% of the full-sky dust variance for all channels. When fitting a spatially varying 3-parameter MBB model to the new dust model with isotropic SEDs, we find very similar spatial distributions to those of the official Planck analysis, and this new model thus represents an economical decomposition of previously published spatially varying spectral parameter maps. We conclude that this new model represents both a statistically more efficient summary of thermal dust in the microwave and far-infrared regimes and a physically more realistic decomposition of the sky compared to the traditional 3-parameter MBB model. (abridged)

astro-ph.CO↗

arXiv2026

Cosmoglobe DR2. V. Spatial correlations between thermal dust and ionized carbon emission in Planck HFI and COBE-DIRBE

We fit five tracers of thermal dust emission to ten Planck HFI and COBE-DIRBE frequency maps between 353 GHz and 25 THz, aiming to map the relative importance of each physical host environment as a function of frequency and position on the sky. Four of these correspond to classic thermal dust tracers, namely H i (HI4PI), CO (Dame et al. 2001a), H{\alpha} (WHAM, Haffner et al. (2003a, 2016)), and dust extinction (Gaia; Edenhofer et al. 2024), while the fifth is ionized carbon (C ii) emission as observed by COBE- FIRAS. We jointly fit these five templates to each frequency channel through standard multi-variate linear regression. At frequencies higher than 1 THz, we find that the dominant tracer is in fact C ii, and above 10 THz this component accounts for almost the entire fitted signal; at frequencies below 1 THz, its importance is second only to H i. We further find that all five components are well described by a modified blackbody spectral energy density (SED) up to some component-dependent maximum frequency ranging between 1 and 5 THz. In this interpretation, the C ii-correlated component is the hottest among all five, with an effective temperature of about 25 K. The H{\alpha} component has a temperature of 18 K, and, unlike the other four, is observed in absorption rather than emission. Despite the simplicity of this model, which relies only on external templates coupled to spatially isotropic SEDs, we find that it captures 98 % of the full signal root mean squared (RMS) below 1 THz. This high efficiency suggests that spatial variations in the thermal dust SED, as for instance reported by Planck and other experiments, may be more economically modelled on large angular scales in terms of a spatial mixing of individually isotropic physical components.

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arXiv2026

Cosmoglobe DR2. VII. Towards a concordance model of large-scale thermal dust emission for microwave and infrared frequencies

We fit a four-component thermal dust model to COBE-DIRBE data between 3.5 and 240 micron within the global Bayesian end-to-end Cosmoglobe DR2 reanalysis. Following a companion analysis of Planck HFI, the four components of this model correspond to "hot dust", "cold dust", "nearby dust", and "Halpha correlated dust", respectively, and each component is modelled in terms of a fixed spatial template and a spatially isotropic spectral energy density (SED) defined by an overall free amplitude for each DIRBE channel. Except for the cold dust amplitude, which is only robustly detected in the 240 micron channel, we measure statistically significant template amplitudes for all components in all DIRBE channels between 12 and 240 micron. In the 3.5 and 4.9 micron channels, only the hot component is detected, while the 1.25 and 2.2 micron channels are too dominated by starlight emission to allow robust dust detections. The total number of DIRBE-specific degrees of freedom in this model is 25. Despite this low dimensionality, the resulting total SED agrees well with recent astrodust predictions. At both low and high frequencies, more than 95 % of the frequency map variance is captured by the model, while at 60 and 100 micron about 70 % of the signal variance is successfully accounted for. The hot dust component, which in a companion paper has been found to correlate strongly with C ii emission, has the highest absolute amplitude in all DIRBE frequency channels; in particular, at 3.5 micron, which is known to be dominated by polycyclic aromatic hydrocarbon emission, this component accounts for at least 80 % of the total signal. This analysis represents an important step towards establishing a joint concordance model of thermal dust emission applicable to both the microwave and infrared regimes.

astro-ph.CO↗

arXiv2026

Cosmoglobe DR2. IV. Modelling starlight in DIRBE with Gaia and WISE

We present a model of starlight emission in the Diffuse Infrared Background Explorer (DIRBE) data between 1.25 and 25$\,\mu$m based on \textit{Gaia} and WISE measurements. We include two classes of compact objects, namely bright stars with individual spectral energy densities (SEDs) measured by \textit{Gaia}, and a combined diffuse background of dim point source emission. Of the 424\ 829 bright sources that we fit, the number of stars with a flux density detected by WISE at Galactic latitudes $|b|>20^{\circ}$ at more than $5\,\sigma$ is 94\,680, for an average of 1.36~stars per DIRBE beam area. For each star, we adopt physical parameters ($T_{\mathrm{eff}}$, $\log g$, and [M/H]) from \textit{Gaia}; use these to identify a best-fit effective SED with the PHOENIX stellar model library; convolve with the respective DIRBE bandpass; and fit an overall free amplitude per star within the Bayesian end-to-end \texttt{Cosmoglobe} DR2 framework. The contributions from faint sources are accounted for by coadding all 710\ 825\ 587 WISE sources not included as bright stars, and fit one single overall amplitude per DIRBE band. Based on this model we find that total star emission accounts for 91\,\% of the observed flux density at 2.2\,$\mu$m; 54\,\% at 4.9$\,\mu$m; and 1\,\% at 25\,$\mu$m. As shown in companion papers, this new model is sufficiently accurate to support high-precision measurements of both the Cosmic Infrared Background monopole and zodiacal light emission in the three highest DIRBE frequencies.

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arXiv2024

Cosmoglobe DR2. I. Global Bayesian analysis of COBE-DIRBE

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.

astro-ph.CO↗

arXiv2024

Cosmoglobe DR2. III. Improved modelling of zodiacal light with COBE-DIRBE through global Bayesian analysis

We present an improved zodiacal light (ZL) model for COBE-DIRBE derived through global Bayesian analysis within the Cosmoglobe Data Release 2 framework. The parametric form of the ZL model is inspired by the original DIRBE model by Kelsall et al. (K98), 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 $\lesssim 3\%$ 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 ZL Subtracted Mission Average maps by $\sim 30$ 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. At high Galactic latitudes, the total RMS of each DR2 map is lower than the corresponding DIRBE ZSMA map of $\sim$ 80 \% at wavelengths 4.9--25 $\mu\mathrm{m}$. Still, obvious ZL residuals can be seen in several of the DR2 maps, and further work is required to mitigate these. Joint analysis with 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. (abridged)

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arXiv2024

Cosmoglobe DR2. II. CIB monopole measurements from COBE-DIRBE through global Bayesian analysis

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.

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arXiv2023

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.

astro-ph.CO↗

arXiv2023

Cosmoglobe DR1. III. First full-sky model of polarized synchrotron emission from all WMAP and Planck LFI data

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.

astro-ph.CO↗

arXiv2023

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 $β$ since its emission. This has recently been measured to be non-zero at a statistical significance of $3.6σ$ in the official Planck PR4 and 9-year WMAP data. In this work, we constrain $β$ 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 $β$, 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 $β$ and the polarization miscalibration angle, $α$, of each channel, we find a best-fit value of $β=0.35^{\circ}\pm0.70^{\circ}$ with LFI and WMAP data only. When including the Planck HFI PR4 maps, but fitting $β$ separately for dust-dominated, $β_{>70\,\mathrm{GHz}}$, and synchrotron-dominated channels, $β_{\leq 70\,\mathrm{GHz}}$, we find $β_{\leq 70\,\mathrm{GHz}}=0.53^{\circ}\pm0.28^\circ$. This differs from zero with a statistical significance of $1.9σ$, 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.

astro-ph.CO↗

arXiv2023

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.

astro-ph.IM↗

arXiv2023

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 $3366.2 \pm 1.4\ \mathrm{μK}$, which is $11\ \mathrm{μK}$ higher than the WMAP9 estimate and $2.5\ σ$ 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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arXiv2022

BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors

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 $ν_{\mathrm{p}}=25.3\pm0.5$ 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.

astro-ph.CO↗

arXiv2022

BeyondPlanck I. Global Bayesian analysis of the Planck Low Frequency Instrument data

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 $P(ω|d)$, where $ω$ 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 $Λ$CDM model, and we constrain the reionization optical depth to $τ=0.066\pm0.013$, with a low-resolution $χ^2$ 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 $3362.7\pm1.4μ\mathrm{K}$, 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.)

astro-ph.CO↗

arXiv2022

Cosmoglobe: Simulating zodiacal emission with ZodiPy

We present ZodiPy, a modern and easy-to-use Python package for modeling the zodiacal emission seen by an arbitrary Solar System observer, which can be used for the removal of both thermal emission and scattered sunlight from interplanetary dust in astrophysical data. The code implements the COBE Diffuse Infrared Background Experiment (DIRBE) interplanetary dust model and the Planck extension, which allows for zodiacal emission predictions at infrared wavelengths in the 1.25-240 $μ$m range and at microwave frequencies in the 30-857 GHz range. The predicted zodiacal emission may be extrapolated to frequencies and wavelengths not covered by the built-in models to produce forecasts for future experiments. ZodiPy attempts to enable the development of new interplanetary dust models by providing the community with an easy-to-use interface for testing both current and future models. We demonstrate how the software can be used by creating simulated zodiacal emission timestreams for the DIRBE experiment and show that these agree with corresponding timestreams produced with the DIRBE Zodiacal Light Prediction Software. We also make binned maps of the zodiacal emission as predicted to be observed by DIRBE and compare them with the DIRBE calibrated individual observations (CIO).

astro-ph.EP↗

arXiv2022

BeyondPlanck VI. Noise characterization and modelling

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, $ξ^n = \{σ_0, f_\mathrm{knee}, α, A_\mathrm{p}\}$. 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 $α$ 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)

astro-ph.CO↗

arXiv2022

From BeyondPlanck to Cosmoglobe: Preliminary $\mathit{WMAP}$ $\mathit Q$-band analysis

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 $\sim2\,\mathrm{μK}$ quadrupole difference that most likely is caused by different gain modeling, while in polarization we find a distinct $2.5\,\mathrm{μK}$ 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.

astro-ph.CO↗

arXiv2022

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.

astro-ph.CO↗