DISCOVERY OF AN ENERGETIC PULSAR ASSOCIATED WITH SNR G76.9+1.0
Bibliographic record
Abstract
We report the discovery of PSR J2022+3842, a 24 ms radio and X-ray pulsar in the supernova remnant G76.9+1.0, in observations with the Chandra X-ray Observatory , the Robert C. Byrd Green Bank Radio Telescope, and the Rossi X-ray Timing Explorer ( RXTE ). The pulsar's spin-down rate implies a rotation-powered luminosity erg s −1 , a surface dipole magnetic field strength B s = 1.0 × 10 12 G, and a characteristic age of 8.9 kyr. PSR J2022+3842 is thus the second-most energetic Galactic pulsar known, after the Crab pulsar, as well as the most rapidly rotating young, radio-bright pulsar known. The radio pulsations are highly dispersed and broadened by interstellar scattering, and we find that a large (δ f / f ≈ 1.9 × 10 −6 ) spin glitch must have occurred between our discovery and confirmation observations. The X-ray pulses are narrow (0.06 cycles FWHM) and visible up to 20 keV, consistent with magnetospheric emission from a rotation-powered pulsar. The Chandra X-ray image identifies the pulsar with a hard, unresolved source at the midpoint of the double-lobed radio morphology of G76.9+1.0 and embedded within faint, compact X-ray nebulosity. The spatial relationship of the X-ray and radio emissions is remarkably similar to the extended structure seen around the Vela pulsar. The combined Chandra and RXTE pulsar spectrum is well fitted by an absorbed power-law model with column density N H = (1.7 ± 0.3) × 10 22 cm −2 and photon index Γ = 1.0 ± 0.2; this implies that the Chandra point-source flux is virtually 100% pulsed. For a distance of 10 kpc, the X-ray luminosity of PSR J2022+3842 is L X (2–10 keV) = 7.0 × 10 33 erg s −1 . Despite being extraordinarily energetic, PSR J2022+3842 lacks a bright X-ray wind nebula and has an unusually low conversion efficiency of spin-down power to X-ray luminosity, .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".