PSR J1012+5307: a millisecond pulsar with an extremely low-mass white dwarf companion
Bibliographic record
Abstract
ABSTRACT Binaries harbouring millisecond pulsars (MSPs) enable a unique path to determine neutron star (NS) masses: radio pulsations reveal the motion of the NS, while that of the companion can be characterized through studies in the optical range. PSR J1012+5307 is an MSP in a 14.5-h orbit with a helium-core white dwarf (WD) companion. In this work we present the analysis of an optical spectroscopic campaign, where the companion star absorption features reveal one of the lightest known WDs. We determine a WD radial velocity semi-amplitude of $K_2 = 218.9 \pm 2.2\, \rm km\, s^{-1}$, which combined with that of the pulsar derived from the precise radio timing, yields a mass ratio of q = 10.44 ± 0.11. We also attempt to infer the WD mass from observational constraints using new binary evolution models for extremely low-mass (ELM) WDs, but find that they cannot reproduce all observed parameters simultaneously. In particular, we cannot reconcile the radius predicted from binary evolution with the measurement from the photometric analysis ($R_{\rm WD}=0.047_{-0.002}^{+0.003}\, \mathrm{ R}_{\odot }$). Our limited understanding of ELM WD evolution, which results from binary interaction, therefore comes as the main factor limiting the precision with which we can measure the mass of the WD in this system. Our conservative WD mass estimate of $M_{\rm WD} = 0.165 \pm 0.015\, \mathrm{ M}_{\rm \odot }$, along with the mass ratio enables us to infer a pulsar mass of $M_{\rm NS} = 1.72 \pm 0.16\, \mathrm{ M}_{\rm \odot }$. This value is clearly above the canonical $\sim 1.4\, \mathrm{ M}_{\rm \odot }$, therefore adding PSR J1012+5307 to the growing list of massive MSPs.
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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 | 0.001 |
| 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) | 0.001 | 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".