The NANOGrav 12.5 yr Data Set: Observations and Narrowband Timing of 47 Millisecond Pulsars
Bibliographic record
Abstract
Abstract We present time-of-arrival (TOA) measurements and timing models of 47 millisecond pulsars observed from 2004 to 2017 at the Arecibo Observatory and the Green Bank Telescope by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). The observing cadence was three to four weeks for most pulsars over most of this time span, with weekly observations of six sources. These data were collected for use in low-frequency gravitational wave searches and for other astrophysical purposes. We detail our observational methods and present a set of TOA measurements, based on “narrowband” analysis, in which many TOAs are calculated within narrow radio-frequency bands for data collected simultaneously across a wide bandwidth. A separate set of “wideband” TOAs will be presented in a companion paper. We detail a number of methodological changes, compared to our previous work, which yield a cleaner and more uniformly processed data set. Our timing models include several new astrometric and binary pulsar measurements, including previously unpublished values for the parallaxes of PSRs J1832−0836 and J2322+2057, the secular derivatives of the projected semimajor orbital axes of PSRs J0613−0200 and J2229+2643, and the first detection of the Shapiro delay in PSR J2145−0750. We report detectable levels of red noise in the time series for 14 pulsars. As a check on timing model reliability, we investigate the stability of astrometric parameters across data sets of different lengths. We also report flux density measurements for all pulsars observed. Searches for stochastic and continuous gravitational waves using these data will be subjects of forthcoming publications.
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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 | 0.003 |
| 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) | 0.002 | 0.002 |
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".