Microlensing planets in the light of the second data release of Gaia

TL;DR

This paper uses Gaia DR2 data to verify and refine the physical parameters of 20 microlensing exoplanet candidates, improving the reliability of their distance and source star measurements.

Contribution

It provides a systematic consistency check of microlensing planets with Gaia DR2 data, offering a reference for future observational efforts.

Findings

19 of 20 events are consistent within 2 sigma of Gaia data

9 events match published source magnitudes within 0.2 mag

One event shows significant discrepancy but is well-constrained

Abstract

Extrasolar planets found by gravitational microlensing often require assumptions on the source star distance and relative proper motion. Only in a few cases has it been possible to confirm these findings with space-based observations or high-resolution follow-up. 20 planetary microlensing events can be positionally cross-matched with the second Gaia data release containing parallax and proper motion measurements. In this work we subject all microlensing planets listed in NASA's Exoplanet Archive to an initial consistency check by comparing them with Gaia data release 2 measurements. The resulting list is supposed to serve as a reference for the observers in the microlensing community. Gravitational microlensing can constrain the physical parameters lens mass and lens distance based on fit parameters, such as the event timescale, the microlensing parallax, and the source star crossing time. If some of these parameters are not available, one needs to resort to indirect means of assessing the events, often involving a Galactic model. In this work, we seek to make an initial assessment of those parameters solely based on Gaia DR2. We find that 19 of 20 planetary events are consistent within $2\,\sigma$ of their published lens and source distances, whereas 9 of them agree with their published source magnitude within $0.2\,\mathrm{mag}$. The only event that does not seem to be compatible with the reported distance, is well-constrained and provides plausible distance estimates.