Studying the Solar system with the International Pulsar Timing Array
Bibliographic record
Abstract
Pulsar-timing analyses are sensitive to errors in the Solar-system ephemerides (SSEs) that timing models utilize to estimate the location of the Solar-system barycentre, the quasi-inertial reference frame to which all recorded pulse times-of-arrival are referred. Any error in the SSE will affect all pulsars, therefore pulsar timing arrays (PTAs) are a suitable tool to search for such errors and impose independent constraints on relevant physical parameters. We employ the first data release of the International Pulsar Timing Array to constrain the masses of the planet–moons systems and to search for possible unmodelled objects (UMOs) in the Solar system. We employ 10 SSEs from two independent research groups, derive and compare mass constraints of planetary systems, and derive the first PTA mass constraints on asteroid-belt objects. Constraints on planetary-system masses have been improved by factors of up to 20 from the previous relevant study using the same assumptions, with the mass of the Jovian system measured at 9.5479189(3) × 10−4 M⊙. The mass of the dwarf planet Ceres is measured at 4.7(4) × 10−10 M⊙. We also present the first sensitivity curves using real data that place generic limits on the masses of UMOs, which can also be used as upper limits on the mass of putative exotic objects. For example, upper limits on dark-matter clumps are comparable to published limits using independent methods. While the constraints on planetary masses derived with all employed SSEs are consistent, we note and discuss differences in the associated timing residuals and UMO sensitivity curves.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".