Planet Mass Function around M Stars at 1–10 au: A Plethora of Sub-Earth Mass Objects
Bibliographic record
Abstract
Abstract Small planets (≲1 M ⊕) at intermediate orbital distances (∼1 au) represent an uncharted territory in exoplanetary science. The upcoming microlensing survey by the Nancy Grace Roman Space Telescope will be sensitive to objects as light as Ganymede and unveil the small planet population at 1–10 au. Instrumental sensitivity to such planets is low, and the number of objects we will discover is strongly dependent on the underlying planet mass function. In this work, we provide a physically motivated planet mass function by combining the efficiency of planet formation by pebble accretion with the observed disk mass function. Because the disk mass function for M dwarfs (0.4–0.6 M ⊙) is bottom heavy, the initial planet mass function is also expected to be bottom heavy, skewing toward Ganymede and Mars mass objects, more so for heavier initial planetary seeds. We follow the subsequent dynamical evolution of planetary systems over ∼100 Myr varying the initial eccentricity and orbital spacing. For initial planet separations of ≥3 local disk scale heights, we find that Ganymede and Mars mass planets do not grow significantly by mergers. However, Earth-like planets undergo vigorous merging and turn into super-Earths, potentially creating a gap in the planet mass function at ∼1 M ⊕. Our results demonstrate that the slope of the mass function and the location of the potential gap in the mass function can probe the initial architecture of multiplanet systems. We close by discussing implications on the expected difference between bound and free-floating planet mass functions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".