Radial Velocity Detectability of Low‐Mass Extrasolar Planets in Close Orbits
Bibliographic record
Abstract
Detection of Jupiter-mass companions to nearby solar-type stars with precise radial velocity measurements is now routine, and Doppler surveys are moving toward lower velocity amplitudes. The detection of several Neptune-mass planets with orbital periods of less than a week has been reported. The drive toward the search for close-in, Earth-mass planets is on the agenda. Successful detection or meaningful upper limits will place important constraints on the process of planet formation. In this paper, we quantify the statistics of detection of low-mass planets in close orbits, showing how the detection threshold depends on the number and timing of the observations. In particular, we consider the case of a low-mass planet close to but not on the 2 : 1 mean motion resonance with a hot Jupiter. This scenario is a likely product of the core-accretion hypothesis for planet formation coupled with migration of Jupiters in the protoplanetary disk. It is also advantageous for detection because the orbital period is well constrained. We show that the minimum detectable mass is ≈4 M ⊕ ( N /20) -1/2 (σ/m s -1 )( P /days) 1/3 ( M * / M ☉ ) 2/3 for N ≥ 20, where N is the number of observations, P is the orbital period, σ is the quadrature sum of Doppler velocity measurement errors and stellar jitter, and M * is the stellar mass. Detection of few Earth-mass rocky cores will require ~1 m s -1 velocity precision and, most important, a better understanding of stellar radial velocity "jitter."
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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 | 0.002 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".