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arXiv · 1912.04510

PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events

Abstract

We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times ($t_E>120$ days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~85% by selecting events with both $t_E>120$ days and a microlensing parallax of $π_E<0.08$. Unfortunately, such a selection criterion cannot be applied during the event as $π_E$ requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of $\mathcal{O}(100-1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions.

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BibTeXRIS

Casey Y. Lam, Jessica R. Lu, Matthew W. Hosek, Jr., William A. Dawson, Nathan R. Golovich. 2019-12-10. PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events. https://doi.org/10.3847/1538-4357%2Fab5fd3

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