Transit Timing Variations for AU Microscopii b & c
Bibliographic record
Abstract
AU Mic is a relatively bright, nearby (9.7 pc), young (22 Myr) M1V pre-main sequence star hosting two transiting exoplanets AU Mic b and c and a spatially-resolved outer dusty debris disk. This research explores the transit timing variations (TTVs) of AU Mic b and c. For AU Mic b, we present three Spitzer/IRAC (4.5 μm) transits (two new), five TESS Cycle 1 and 3 transits, 11 LCO transits, one PEST-0.30m transit, one Brierfield-0.36m transit, and two transit timing measurements from Rossiter-McLaughlin observations; for AU Mic c, we present three TESS Cycle 1 and 3 transits. We use EXOFASTv2 to jointly model the transits and to obtain the midpoint transit times. We then construct an O-C diagram to map the TTVs. We model the TTVs for AU Mic b and c with Exo-Striker to recover constraints on the mass for AU Mic c. We compare the TTV-derived constraints to a recent radial-velocity mass determination. The results demonstrate that the AU Mic planetary system is dynamically interacting producing detectable TTVs, and the implied orbital dynamics may inform future constraints on the formation mechanisms for this young planetary system. However, stellar activity from flares and rotational spot modulation complicate our analysis of this young system. We recommend future TTV observations of AU Mic b and c to further constrain the dynamical masses and to search for additional planets in the system.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".