LiteBIRD science goals and forecasts: constraining isotropic cosmic birefringence
Bibliographic record
Abstract
Abstract Cosmic birefringence (CB) is the rotation of the photons' linear polarisation plane during propagation. Such an effect is a tracer of parity-violating extensions of standard electromagnetism and would probe the existence of a new cosmological field acting as dark matter or dark energy. It has become customary to employ cosmic microwave background (CMB) polarised data to probe such a phenomenon. Recent analyses on Planck and WMAP data provide a hint of detection of the isotropic CB angle with an amplitude of around 0.3° at the level of 2.4 to 3.6σ. In this work, we explore the LiteBIRD capabilities in constraining such an effect, accounting for the impact of the more relevant systematic effects, namely foreground emission and instrumental polarisation angles. We build five semi-independent pipelines and test these against four different simulation sets with increasing complexity in terms of non-idealities. All the pipelines are shown to be robust and capable of returning the expected values of the CB angle within statistical fluctuations for all the cases considered. We find that the uncertainties in the CB estimates increase with more complex simulations. However, the trend is less pronounced for pipelines that account for the instrumental polarisation angles. For the most complex case analysed, we find that LiteBIRD will be able to detect a CB angle of 0.3° with a statistical significance ranging from 5 to 13σ, depending on the pipeline employed, where the latter uncertainty corresponds to a total error budget of the order of 0.02°.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".