A Reanalysis of Public Galactic Bulge Gravitational Microlensing Events from OGLE-III and -IV

被引:12
|
作者
Golovich, Nathan [1 ]
Dawson, William [1 ]
Bartolic, Fran [2 ,3 ]
Lam, Casey Y. [4 ]
Lu, Jessica R. [4 ]
Medford, Michael S. [4 ,5 ]
Schneider, Michael D. [1 ]
Chapline, George [1 ]
Schlafly, Edward F. [1 ]
Drlica-Wagner, Alex [6 ,7 ]
Pruett, Kerianne [1 ]
机构
[1] Lawrence Livermore Natl Lab, 7000 East Ave, Livermore, CA 94550 USA
[2] Univ St Andrews, Ctr Exoplanet Sci, Sch Phys & Astron, St Andrews KY16 9SS, Fife, Scotland
[3] Flatiron Inst, Ctr Computat Astrophys, 162 5th Ave,6th Floor, New York, NY 10010 USA
[4] Univ Calif Berkeley, Dept Astron, Berkeley, CA 94720 USA
[5] Lawrence Berkeley Natl Lab, 1 Cyclotron Rd, Berkeley, CA 94720 USA
[6] Fermilab Natl Accelerator Lab, Kirk Rd & Pine St, Batavia, IL 60510 USA
[7] Univ Chicago, Dept Astron & Astrophys, 5640 South Ellis Ave, Chicago, IL 60637 USA
来源
基金
美国国家航空航天局; 英国科学技术设施理事会;
关键词
MACHO PROJECT LIMITS; MASS DARK-MATTER; LENSING EXPERIMENT; BLACK-HOLE; GAUSSIAN-PROCESSES; OPTICAL DEPTH; PARALLAX; DEGENERACIES; EFFICIENT; ASTROPY;
D O I
10.3847/1538-4365/ac5969
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Modern surveys of gravitational microlensing events have progressed to detecting thousands per year, and surveys are capable of probing Galactic structure, stellar evolution, lens populations, black hole physics, and the nature of dark matter. One of the key avenues for doing this is the microlensing Einstein radius crossing time (t (E)) distribution. However, systematics in individual light curves as well as oversimplistic modeling can lead to biased results. To address this, we developed a model to simultaneously handle the microlensing parallax due to Earth's motion, systematic instrumental effects, and unlensed stellar variability with a Gaussian process model. We used light curves for nearly 10,000 OGLE-III and -IV Milky Way bulge microlensing events and fit each with our model. We also developed a forward model approach to infer the t (E) distribution by forward modeling from the data rather than using point estimates from individual events. We find that modeling the variability in the baseline removes a source of significant bias in individual events, and the previous analyses overestimated the number of t (E) > 100 day events due to their oversimplistic model ignoring parallax effects. We use our fits to identify the hundreds filling a regime in the microlensing parameter space that are 50% pure of black holes. Finally, we have released the largest-ever catalog of Markov Chain Monte Carlo parameter estimates for microlensing events.
引用
收藏
页数:25
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