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Record W2767675395 · doi:10.3847/1538-4357/ab0f36

Intensity-coupled Polarization in Instruments with a Continuously Rotating Half-wave Plate

2019· article· en· W2767675395 on OpenAlexaff
Joy Didier, Amber Miller, Derek Araujo, François Aubin, Christopher Geach, Bradley R. Johnson, Andrei Korotkov, Kate Raach, Benjamin Westbrook, Karl Young, Asad M. Aboobaker, P. A. R. Ade, C. Baccigalupi, Chaoyun Bao, Daniel Chapman, M. Dobbs, W. Grainger, Shaul Hanany, Kyle Helson, Seth Hillbrand, Johannes Hubmayr, A. H. Jaffe, T. J. Jones, Jeff Klein, Adrian V. Lee, M. Limon, Kevin MacDermid, Michael Milligan, E. Pascale, Britt Reichborn-Kjennerud, Ilan Sagiv, C. Tucker, Gregory S. Tucker, Kyle Zilic

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCosmology and Gravitation Theories
Canadian institutionsCanadian Institute for Advanced ResearchMcGill University
FundersScience and Technology Facilities CouncilNational Aeronautics and Space Administration
KeywordsPolarization (electrochemistry)PhysicsCosmic microwave backgroundLinearityOpticsWaveplateDetectorLinear polarizationBrewster's angleRadial polarizationChemistryLaser beams

Abstract

fetched live from OpenAlex

Abstract We discuss a systematic effect associated with measuring polarization with a continuously rotating half-wave plate (HWP). The effect was identified with the data from the E and B Experiment, which was a balloon-borne instrument designed to measure the polarization of the cosmic microwave background (CMB) as well as that from Galactic dust. The data show polarization fractions larger than 10%, while less than 3% were expected from instrumental polarization. We give evidence that the excess polarization is due to detector nonlinearity in the presence of a continuously rotating HWP. The nonlinearity couples intensity signals to polarization. We develop a map-based method to remove the excess polarization. Applying this method to the 150 (250) GHz band data, we find that 81% (92%) of the excess polarization was removed. Characterization and mitigation of this effect are important for future experiments aiming to measure the CMB B-modes with a continuously rotating HWP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.006
GPT teacher head0.210
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2019
Admission routes1
Has abstractyes

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