Beyondplanck

Ihle, H. T.; Bersanelli, M.; Franceschet, C.; Gjerløw, E.; Andersen, K. J.; Aurlien, R.; Banerji, R.; Bertocco, S.; Brilenkov, M.; Carbone, M.; Colombo, L. P. L.; Eriksen, H. K.; Eskilt, J. R.; Foss, M. K.; Fuskeland, U.; Galeotta, S.; Galloway, M.; Gerakakis, S.

doi:10.1051/0004-6361/202243619

Cited by 15 publications

(9 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the amplitude of the primordial gravitational wave signal is expected to be smaller than 10-100 nK on large angular scales (Tristram et al 2021). This, combined with a plethora of confounding instrumental effects, such as temperature-topolarization leakage (Paradiso et al 2023), correlated noise (Ihle et al 2023), and calibration uncertainties (Gjerløw et al 2023), makes high-precision CMB polarization science a particularly difficult challenge. Furthermore, as summarized by the Planck team in a document (titled "Lessons learned from Planck" 1 ) the quality of current state-of-the-art CMB observations is limited by the interplay between instrumental and foreground effects.…”

Section: Introductionmentioning

confidence: 99%

Beyondplanck

Svalheim¹,

Andersen²,

Aurlien³

et al. 2023

A&A

Self Cite

View full text Add to dashboard Cite

Using the Planck Low Frequency Instrument (LFI) and WMAP data within the global Bayesian BEYONDPLANCK framework, we constrained the polarized foreground emission between 30 and 70 GHz. We combined, for the first time, full-resolution Planck LFI time-ordered data with low-resolution WMAP sky maps at 33, 40, and 61 GHz. The spectral parameters were fit with a likelihood defined at the native resolution of each frequency channel. This analysis represents the first implementation of true multi-resolution component separation applied to CMB observations for both amplitude and spectral energy distribution (SED) parameters. For the synchrotron emission, we approximated the SED as a power-law in frequency and we find that the low signal-to-noise ratio of the current data strongly limits the number of free parameters that can be robustly constrained. We partitioned the sky into four large disjoint regions (High Latitude; Galactic Spur; Galactic Plane; and Galactic Center), each associated with its own power-law index. We find that the High Latitude region is prior-dominated, while the Galactic Center region is contaminated by residual instrumental systematics. The two remaining regions appear to be signal-dominated, and for these we derive spectral indices of βsSpur = −3.17 ± 0.06 and βsPlane = −3.03 ± 0.07, which is in good agreement with previous results. For the thermal dust emission, we assumed a modified blackbody model and we fit a single power-law index across the full sky. We find βd = 1.64 ± 0.03, which is slightly steeper than the value reported in Planck HFI data, but still statistically consistent at the 2σ confidence level.

show abstract

Section: Introductionmentioning

confidence: 99%

Beyondplanck

Svalheim¹,

Andersen²,

Aurlien³

et al. 2023

A&A

Self Cite

View full text Add to dashboard Cite

show abstract

“…The maps a represent the Stokes parameters for each astrophysical component, while s orb is the orbital dipole induced by the motion of the telescope with respect to the Sun, and s fsl is the time-dependent far sidelobe signal. Following Ihle et al (2023), we model the correlated noise component n corr in terms of a 1/ f power spectral density (PSD), which explicitly takes the form P n ( f ) = σ 2 0 (1+( f / f knee ) α ), where σ 0 denotes the white noise amplitude, f knee is the so-called 1/ f knee frequency, and α is a free power law slope. For notational purposes, we denote the set of all correlated noise parameters by ξ n = {σ 0 , f knee , α}.…”

Section: Cosmoglobe Instrument Modelmentioning

confidence: 99%

“…Noise estimation and calibration are described by Ihle et al (2023) and Gjerløw et al (2023), respectively. As noted in those works, these two steps are strongly correlated, simply because the timestream…”

Section: Review Of Sampling Algorithmsmentioning

confidence: 99%

“…The correlated noise sampling, described by Ihle et al (2023), follows a similar procedure, except this now conditions upon the previous gain estimate, which is sampled immediately before the correlated noise component in the code. Similar to the gain case, we can write a generative model for the data,…”

Section: Review Of Sampling Algorithmsmentioning

confidence: 99%

“…The main driver of this model failure lies in the fact that our current noise estimation algorithm fits the white noise level by computing the standard deviation of pairwise signal-subtracted sample differences. The motivation for this is to prevent slowly varying model failures from contaminating the white level, which worked very well for Planck LFI (Ihle et al 2023). However, the WMAP time-ordered data exhibit a low level of colored noise at very high temporal frequencies, and is not supported by a rigid 1/ f model.…”

Section: Noise Modelingmentioning

confidence: 99%

See 2 more Smart Citations

COSMOGLOBE DR1 results

Watts,

Basyrov,

Eskilt

et al. 2023

A&A

Self Cite

View full text Add to dashboard Cite

We present COSMOGLOBEData Release 1, which implements the first joint analysis of WMAP andPlanckLFI time-ordered data, processed within a single Bayesian end-to-end framework. This framework directly builds on a similar analysis of the LFI measurements by the BEYONDPLANCKcollaboration, and approaches the cosmic microwave background (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-h, of which 603 CPU-h 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 ± 1.4 μK, which is 11 μK higher than the WMAP9 estimate and 2.5σhigher than BEYONDPLANCK; however, it is in perfect agreement with the HFI-dominatedPlanckPR4 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 theW-band polarization sky map, which was excluded from the official WMAP cosmological analysis, for the first time appears visually consistent with theV-band sky map. Similarly, the long standing discrepancy between the WMAPK-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. Relatedly, these updated maps allowed us for the first time to combine WMAP and LFI polarization data into a single coherent model of large-scale polarized synchrotron emission. Still, we identified a few issues that require additional work, including (1) low-level noise modeling; (2) large-scale temperature residuals at the 1–2 μK level; and (3) a strong degeneracy between the absoluteK-band calibration and the dipole of the anomalous microwave emission component. We conclude that leveraging the complementary strengths of WMAP and LFI has allowed the mitigation of both experiments’ weaknesses, and resulted in new state-of-the-art WMAP sky maps. All maps and the associated code are made publicly available through the COSMOGLOBEweb page.

show abstract

Beyondplanck

Keihänen¹,

Suur-Uski²

2023

A&A

View full text Add to dashboard Cite

We present a Gibbs sampling solution to the mapmaking problem for cosmic microwave background (CMB) measurements that builds on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps: noise filtering and map binning. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods and it allows us, for the first time, to bring the destriping baseline length to a single sample. Here, we applied the Gibbs procedure to simulated Planck 30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them in with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we are able to compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without the need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of the total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction. This methodology thus forms the conceptual basis for the mapmaking algorithm employed in the BeyondPlanck framework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations.

show abstract

Beyondplanck

Cited by 15 publications

References 52 publications

Beyondplanck

Beyondplanck

COSMOGLOBE DR1 results

Beyondplanck

Contact Info

Product

Resources

About