Systematic error mitigation for the PIXIE Fourier transform spectrometer
Bibliographic record
Abstract
Abstract The Primordial Inflation Explorer (PIXIE) is an Explorer-class mission concept to measure the spectrum and polarization of the cosmic microwave background. Cosmological signals are small compared to the instantaneous instrument noise, requiring strict control of instrumental signals. The instrument design provides multiple levels of null operation, signal modulation, and signal differences, with only few-percent systematic error suppression required at each level. Jackknife tests based on discrete instrument symmetries provide an independent means to identify, model, and remove remaining instrumental signals. We use detailed time-ordered simulations, including realistic performance and tolerance parameters, to evaluate the instrument response to broad classes of systematic errors for both spectral distortions and polarization. The largest systematic errors contribute additional white noise at the few-percent level compared to the dominant photon noise. Coherent instrumental effects which do not integrate down are smaller still, and remain several orders of magnitude below the targeted cosmological signals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".