Testing LMC Microlensing Scenarios: The Discrimination Power of the SuperMACHO Microlensing Survey

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Abstract

Characterizing the nature and spatial distribution of the lensing objects that produce the previously measured microlensing optical depth toward the Large Magellanic Cloud (LMC) remains an open problem. We present an appraisal of the ability of the SuperMACHO Project, a next-generation microlensing survey directed toward the LMC, to discriminate between various proposed lensing populations. We consider two scenarios: lensing by a uniform foreground screen of objects and self-lensing by LMC stars. The optical depth for ''screen lensing'' is essentially constant across the face of the LMC, whereas the optical depth for self-lensing shows a strong spatial dependence. We have carried out extensive simulations, based on data obtained during the first year of the project, to assess the SuperMACHO survey's ability to discriminate between these two scenarios. In our simulations we predict the expected number of observed microlensing events for various LMC models for each of our fields by adding artificial stars to the images and estimating the spatial and temporal efficiency of detecting microlensing events using Monte Carlo methods. We find that the event rate itself shows significant sensitivity to the choice of the LMC luminosity function, limiting the conclusions that can be drawn from the absolute rate. If instead we determine the differential event rate across the LMC, we will decrease the impact of these systematic biases and render our conclusions more robust. With this approach the SuperMACHO Project should be able to distinguish between the two categories of lens populations. This will provide important constraints on the nature of the lensing objects and their contributions to the Galactic dark matter halo.

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