Validate Unclassified TESS Microlensing Candidates

Determine whether the TESS sources classified as stars or not found in SIMBAD represent genuine microlensing signals by conducting further analysis.

Background

Microlensify identified numerous high-confidence, microlensing-like signals in TESS light curves extracted by the Eleanor, TESS-SPOC, and QLP pipelines. Cross-matching with SIMBAD revealed that many candidates were false positives associated with long-period variables, cataclysmic variables, stellar types, systematics, blending, or asteroid crossings.

The authors designate sources classified as stars and sources without SIMBAD classifications as the remaining microlensing candidates. These objects have not yet been confirmed as genuine microlensing events and require additional investigation, including the precise point-source point-lens fitting mentioned immediately afterward in the conclusions.

References

Our final microlensing candidates are sources classified as stars or those that have not yet been classified, which require further analysis to confirm whether they represent real microlensing signals.

— Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves  (2608.19419 - Kalantari et al., 19 Aug 2026) in Section Summary and Conclusions, Section 6