A 1.05<i>M</i><sub>☉</sub>COMPANION TO PSR J2222–0137: THE COOLEST KNOWN WHITE DWARF?
Bibliographic record
Abstract
The recycled pulsar PSR J2222−0137 is one of the closest known neutron stars (NSs) with a parallax distance of pc and an edge-on orbit. We measure the Shapiro delay in the system through pulsar timing with the Green Bank Telescope, deriving a low pulsar mass (1.20 ± 0.14 M ☉ ) and a high companion mass (1.05 ± 0.06 M ☉ ) consistent with either a low-mass NS or a high-mass white dwarf. We can largely reject the NS hypothesis on the basis of the system's extremely low eccentricity (3 × 10 −4 )—too low to have been the product of two supernovae under normal circumstances. However, despite deep optical and near-infrared searches with Southern Astrophysical Research and the Keck telescopes we have not discovered the optical counterpart of the system. This is consistent with the white dwarf hypothesis only if the effective temperature is <3000 K, a limit that is robust to distance, mass, and atmosphere uncertainties. This would make the companion to PSR J2222−0137 one of the coolest white dwarfs ever observed. For the implied age to be consistent with the age of the Milky Way requires the white dwarf to have already crystallized and entered the faster Debye-cooling regime.
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 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".