OGLE-2017-BLG-0537: A Microlensing Event with a Resolvable Lens in ≲5 years from High-resolution Follow-up Observations
Bibliographic record
Abstract
Abstract We present an analysis of the binary-lens microlensing event OGLE-2017-BLG-0537. The light curve of the event exhibits two strong caustic-crossing spikes among which the second caustic crossing was resolved by high-cadence surveys. It is found that the lens components with a mass ratio ∼0.5 are separated in projection by , where θ E is the angular Einstein radius. Analysis of the caustic-crossing part yields mas and a lens-source relative proper motion of μ = 12.4 ± 1.1 mas yr−1. The measured μ is the third highest value among the events with measured proper motions and is ∼3 times higher than the value of typical Galactic bulge events, making the event a strong candidate for follow-up observations to directly image the lens by separating it from the source. From the angular Einstein radius combined with the microlens parallax, it is estimated that the lens is composed of two main-sequence stars with masses M 1 ∼ 0.4 M ⊙ and M 2 ∼ 0.2 M ⊙ located at a distance of D L ∼ 1.2 kpc. However, the physical lens parameters are not very secure due to the weak microlens-parallax signal, thus we cross-check the parameters by conducting a Bayesian analysis based on the measured Einstein radius and event timescale, combined with the blending constraint. From this, we find that the physical parameters estimated from the Bayesian analysis are consistent with those based on the measured microlens parallax. Resolving the lens from the source can be done in about 5 years from high-resolution follow-up observations and this will provide a rare opportunity to test and refine the microlensing model.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".