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H. T. Ihle

Publications and source records attributed to H. T. Ihle.

At least 19 recordsLinked to original sources

Three-Dimensional Stacking as a Line Intensity Mapping Statistic

Line-intensity mapping (LIM) is a growing technique that measures the integrated spectral-line emission from unresolved galaxies over a three-dimensional region of the Universe. Although LIM experiments ultimately aim to provide powerful cosmological constraints via auto-correlation, many LIM experiments are also designed to take advantage of overlapping galaxy surveys, enabling joint analyses of the two datasets. We introduce a flexible simulation pipeline that can generate mock galaxy surveys and mock LIM data simultaneously for the same population of simulated galaxies. Using this pipeline, we explore a simple joint analysis technique: three-dimensional co-addition (stacking) of LIM data on the positions of galaxies from a traditional galaxy catalogue. We test how the output of this technique reacts to changes in experimental design of both the LIM experiment and the galaxy survey, its sensitivity to various astrophysical parameters, and its susceptibility to common systematic errors. We find that an ideal catalogue for a stacking analysis targets as many high-mass dark matter halos as possible. We also find that the signal in a LIM stacking analysis originates almost entirely from the large-scale clustering of halos around the catalogue objects, rather than the catalogue objects themselves. While stacking is a sensitive and conceptually simple way to achieve a LIM detection, thus providing a valuable way to validate a LIM auto-correlation detection, it will likely require a full cross-correlation to achieve further characterization of the galaxy tracers involved, as the cosmological and astrophysical parameters we explore here have degenerate effects on the stack.

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Separation of gain fluctuations and continuum signals in total power spectrometers with application to COMAP

We describe a time-domain technique for separating $1/f$ gain fluctuations and continuum signal for a total power spectrometer, such as the CO Mapping Array Project (COMAP) Pathfinder instrument. The $1/f$ gain fluctuations of such a system are expected to be common-mode across frequency channels. If the instrument's system temperature is not constant across channels, a continuum signal will exhibit a frequency dependence different from that of common-mode gain fluctuations. Our technique leverages this difference to fit a three-parameter frequency model to each time sample in the time-domain data, separating gain and continuum. We show that this technique can be applied to the COMAP Pathfinder instrument, which exhibits a series of temporally stable resonant noise spikes that effectively act as calibrators, breaking the gain degeneracy with continuum signals. Using both simulations and observations of Jupiter, we explore the effect of a $1/f$ prior for the gain model. We show that the model is capable of cleanly separating Jupiter, a bright continuum source, from the gain fluctuations in the scan. The technique has two applications to COMAP. For the COMAP observations performing line intensity mapping (LIM), the technique better suppresses atmospheric fluctuations and foregrounds than the COMAP LIM pipeline. For the Galactic COMAP observations, which map Galactic continuum signals, the technique can suppress $1/f$ gain fluctuations while retaining all continuum signals. This is demonstrated by the latest COMAP observations of $λ$-Orionis, where our method produces far cleaner maps than a destriper alone, typically reducing the noise power by a factor of 7 on beam scales and up to 15 on larger scales.

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COMAP Pathfinder -- Season 2 results I. Improved data selection and processing

The CO Mapping Array Project (COMAP) Pathfinder is performing line intensity mapping of CO emission to trace the distribution of unresolved galaxies at redshift $z \sim 3$. We present an improved version of the COMAP data processing pipeline and apply this to the first two seasons of observations. This analysis improves on the COMAP Early Science (ES) results in several key aspects. On the observational side, all second season scans were made in constant-elevation mode, after noting that the previous Lissajous scans were associated with increased systematic errors; those scans accounted for 50% of the total Season 1 data volume. Secondly, all new observations were restricted to an elevation range of 35-65 degrees, to minimize sidelobe ground pickup. On the data processing side, more effective data cleaning in both the time- and map-domain has allowed us to eliminate all data-driven power spectrum-based cuts. This increases the overall data retention and reduces the risk of signal subtraction bias. On the other hand, due to the increased sensitivity, two new pointing-correlated systematic errors have emerged, and we introduce a new map-domain PCA filter to suppress these. Subtracting only 5 out of 256 PCA modes, we find that the standard deviation of the cleaned maps decreases by 67% on large angular scales, and after applying this filter, the maps appear consistent with instrumental noise. Combining all these improvements, we find that each hour of raw Season 2 observations yields on average 3.2 times more cleaned data compared to ES analysis. Combining this with the increase in raw observational hours, the effective amount of data available for high-level analysis is a factor of 8 higher than in ES. The resulting maps have reached an uncertainty of $25$-$50\,μK$ per voxel, providing by far the strongest constraints on cosmological CO line emission published to date.

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COMAP Pathfinder -- Season 2 results II. Updated constraints on the CO(1-0) power spectrum

We present updated constraints on the cosmological 3D power spectrum of carbon monoxide CO(1-0) emission in the redshift range $2.4$-$3.4$. The constraints are derived from the two first seasons of Carbon monOxide Mapping Array Project (COMAP) Pathfinder line-intensity mapping observations aiming to trace star-formation during the Epoch of Galaxy Assembly. These results improve on the previous Early Science (ES) results through both increased data volume and improved data processing methodology. On the methodological side, we now perform cross-correlations between groups of detectors (''feed-groups''), as opposed to cross-correlations between single feeds, and this new feed-group pseudo power spectrum (FGPXS) is constructed to be more robust against systematic effects. In terms of data volume, the effective mapping speed is significantly increased due to an improved observational strategy as well as better data selection methodology. The updated spherically- and field-averaged FGPXS, $\tilde{C}(k)$, is consistent with zero, at a probability-to-exceed of around $34\,\%$, with an excess of $2.7\,σ$ in the most sensitive bin. Our power spectrum estimate is about an order of magnitude more sensitive in our six deepest bins across ${0.09\,\mathrm{Mpc}^{-1} < k < 0.73\,\mathrm{Mpc}^{-1}}$, as compared to the feed-feed pseudo power spectrum (FPXS) of COMAP ES. Each of these bins individually constrains the CO power spectrum to ${kP_\mathrm{CO}(k)< 2400-4900\,\mathrm{μK^2 Mpc^{2}}}$ at $95\,\%$ confidence. To monitor potential contamination from residual systematic effects, we analyze a set of 312 difference-map null tests and find that these are consistent with the instrumental noise prediction. In sum, these results provide the strongest direct constraints on the cosmological 3D CO(1-0) power spectrum published to date.

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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 $\mathrm{μm}$). For the 2.2 $μ$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 $μ\mathrm{m}$ 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 $μ\mathrm{m}$, 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 $μ\mathrm{m}$ 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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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 $μ$m. A novel aspect of this processing is the characterization and removal of excess radiation between 4.9 and 60$\,μ$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 $μ$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$\,μ$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.

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COMAP Pathfinder -- Season 2 results III. Implications for cosmic molecular gas content at "Cosmic Half-past Eleven"

The Carbon monOxide Mapping Array Project (COMAP) Pathfinder survey continues to demonstrate the feasibility of line-intensity mapping using high-redshift carbon monoxide (CO) line emission traced at cosmological scales. The latest COMAP Pathfinder power spectrum analysis is based on observations through the end of Season 2, covering the first three years of Pathfinder operations. We use our latest constraints on the CO(1-0) line-intensity power spectrum at $z\sim3$ to update corresponding constraints on the cosmological clustering of CO line emission and thus the cosmic molecular gas content at a key epoch of galaxy assembly. We first mirror the COMAP Early Science interpretation, considering how Season 2 results translate to limits on the shot noise power of CO fluctuations and the bias of CO emission as a tracer of the underlying dark matter distribution. The COMAP Season 2 results place the most stringent limits on the CO tracer bias to date, at $\langle{Tb}\rangle<4.8$ $μ$K. These limits narrow the model space significantly compared to previous CO line-intensity mapping results while maintaining consistency with small-volume interferometric surveys of resolved line candidates. The results also express a weak preference for CO emission models used to guide fiducial forecasts from COMAP Early Science, including our data-driven priors. We also consider directly constraining a model of the halo-CO connection, and show qualitative hints of capturing the total contribution of faint CO emitters through the improved sensitivity of COMAP data. With continued observations and matching improvements in analysis, the COMAP Pathfinder remains on track for a detection of cosmological clustering of CO emission.

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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 $β$ 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.

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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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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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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.

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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.)

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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 $3362.7\pm1.4μK$, 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 $σ^{TT}_2=229\pm97μK^2$, 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 $δg_{0}/g_{0} =5 \cdot 10^{-5}$, 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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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)

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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.

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