The NANOGrav 11 yr Data Set: Arecibo Observatory Polarimetry and Pulse Microcomponents
Bibliographic record
Abstract
Abstract We present the polarization pulse profiles for 28 pulsars observed with the Arecibo Observatory by the North American Nanohertz Observatory for Gravitational Waves timing project at 2.1 GHz, 1.4 GHz, and 430 MHz. These profiles represent some of the most sensitive polarimetric millisecond pulsar profiles to date, revealing the existence of microcomponents (that is, pulse components with peak intensities much lower than the total pulse peak intensity). Although microcomponents have been detected in some pulsars previously, we present microcomponents for PSR B1937+21, PSR J1713+0747, and PSR J2234+0944 for the first time. These microcomponents can have an impact on pulsar timing, geometry, and flux density determination. We present rotation measures for all 28 pulsars, determined independently at different observation frequencies and epochs, and find the Galactic magnetic fields derived from these rotation measures to be consistent with current models. These polarization profiles were made using measurement equation template matching, which allows us to generate the polarimetric response of the Arecibo Observatory on an epoch-by-epoch basis. We use this method to describe its time variability and find that the polarimetric responses of the Arecibo Observatory's 1.4 and 2.1 GHz receivers vary significantly with time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".