MACHOs in M 31? Absence of evidence but notevidence of absence
Bibliographic record
Abstract
We present results of a microlensing survey toward the Andromeda Galaxy (M 31) carried out during four observing seasons at the Isaac Newton Telescope (INT). This survey is part of the larger microlensing survey toward M 31 performed by the Microlensing Exploration of the Galaxy and Andromeda (MEGA) collaboration. Using a fully automated search algorithm, we identify 14 candidate microlensing events, three of which are reported here for the first time. Observations obtained at the Mayall telescope are combined with the INT data to produce composite lightcurves for these candidates. The results from the survey are compared with theoretical predictions for the number and distribution of events. These predictions are based on a Monte Carlo calculation of the detection efficiency and disk-bulge-halo models for M 31. The models provide the full phase-space distribution functions (DFs) for the lens and source populations and are motivated by dynamical and observational considerations. They include differential extinction and span a wide range of parameter space characterised primarily by the mass-to-light ratios for the disk and bulge. For most models, the observed event rate is consistent with the rate predicted for self-lensing – a MACHO halo fraction of 30% or higher can be ruled at the 95% confidence level. The event distribution does show a large near-far asymmetry hinting at a halo contribution to the microlensing signal. Two candidate events are located at particularly large projected radii on the far side of the disk. These events are difficult to explain by self lensing and only somewhat easier to explain by MACHO lensing. A possibility is that one of these is due to a lens in a giant stellar stream.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".