Contamination in the MACHO data set and the puzzle of Large Magellanic Cloud microlensing

Abstract

In a recent series of three papers, Belokurov, Evans & Le Du and Evans & Belokurov reanalysed the MACHO collaboration data and gave alternative sets of microlensing events and an alternative optical depth to microlensing towards the Large Magellanic Cloud (LMC). Although these authors examined less than 0.2 per cent of the data, they reported that by using a neural net program they had reliably selected a better (and smaller) set of microlensing candidates. Estimating the optical depth from this smaller set, they claimed that the MACHO collaboration overestimated the optical depth by a significant factor and that the MACHO microlensing experiment is consistent with lensing by known stars in the Milky Way and LMC. As we show below, the analysis by these authors contains several errors, and as a result their conclusions are incorrect. Their efficiency analysis is in error, and since they did not search through the entire MACHO data set, they do not know how many microlensing events their neural net would find in the data nor what optical depth their method would give. Examination of their selected events suggests that their method misses low signal-to-noise ratio events and thus would have lower efficiency than the MACHO selection criteria. In addition, their method is likely to give many more false positives (non-lensing events identified as lensing). Both effects would increase their estimated optical depth. Finally, we note that the EROS discovery that LMC event 23 is a variable star reduces the MACHO collaboration estimates of optical depth and the Macho halo fraction by around 8 per cent, and does open the question of additional contamination. Ke yw ords: gravitational lensing ‐ Galaxy: halo ‐ Magellanic Clouds ‐ dark matter.