Gemini planet imager observational calibrations VII: on-sky polarimetric performance of the Gemini planet imager
Bibliographic record
Abstract
We present on-sky polarimetric observations with the Gemini Planet Imager (GPI) obtained at straight Cassegrain focus on the Gemini South 8-m telescope. Observations of polarimetric calibrator stars, ranging from nearly un- polarized to strongly polarized, enable determination of the combined telescope and instrumental polarization. We find the conversion of Stokes I to linear and circular instrumental polarization in the instrument frame to be I → (QIP, UIP, PIP, VIP) = (-0.037 ± 0.010%, +0.4338 ± 0.0075%, 0.4354 ± 0.0075%, -6.64 ± 0.56%). Such precise measurement of instrumental polarization enables ~0.1% absolute accuracy in measurements of linear polarization, which together with GPI’s high contrast will allow GPI to explore scattered light from circumstellar disk in unprecedented detail, conduct observations of a range of other astronomical bodies, and potentially even study polarized thermal emission from young exoplanets. Observations of unpolarized standard stars also let us quantify how well GPI's differential polarimetry mode can suppress the stellar PSF halo. We show that GPI polarimetry achieves cancellation of unpolarized starlight by factors of 100-200, reaching the photon noise limit for sensitivity to circumstellar scattered light for all but the smallest separations at which the calibration for instrumental polarization currently sets the limit.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".