Microlensing of dark matter models in the Milky Way

We investigate constraints on the abundance of primordial black holes (PBHs) as dark matter (DM) candidates using five years of microlensing data from the OGLE survey. While the majority of OGLE's $\sim\!2000$ microlensing events are well-explained by stellar populations such as brown dwarfs, main-sequence stars, and compact remnants, a subset of six ultrashort-timescale events ($t_E \sim 0.1\text{--}0.3~\mathrm{days}$) may signal the presence of PBHs. Building upon prior work that adopted the Navarro-Frenk-White (NFW) DM profile, we examine how alternative DM halo models -- specifically the Einasto and Burkert profiles, affect microlensing predictions and the constraints on PBH abundance. In light of kinematic data of Milky Way, we could obtain the range of ($r_s, \rho_s$) for both profiles. We computed differential microlensing event rates for both profiles, using the main-sequence star rate as an observational benchmark. Our results show that neither the Einasto nor Burkert profiles reproduce the distribution of main-sequence star events, yet both allow for viable explanations of the ultrashort-timescale events with PBH masses $M_{\mathrm{PBH}} \sim 10^{-5} M_\odot$. Using a Poisson likelihood analysis under the null hypothesis that no PBH is observed in OGLE dataset, we derive $95\%~\text{C.L.}$ upper and lower bounds on $f_{\mathrm{PBH}}$ for both profiles, finding that the constraints are significantly relaxed under Burkert profiles compared to the NFW case. These results show the sensitivity of PBH constraints to the assumed DM halo structure and highlight the importance of accurately modeling the inner Galactic density profile to robustly assess PBH dark matter scenarios.