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Modeling Binary Lenses and Sources with the BAGLE Python Package
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DOI：10.3847/1538-4357/ae5701.png)
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Abstract
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Gravitational microlensing is a powerful tool that can be used to find and measure the mass of isolated and dark compact objects. In many microlensing events, the lens, the source, or both may be binary systems. In this work, we introduce binary source and lens models into the gravitational lensing formalism encoded in the Bayesian Analysis of Gravitational Lensing Events (BAGLE) Python software package. These new binary models in BAGLE account for Keplerian orbits. We also add binary models with fewer parameters that describe the binary orbital motion as acceleration, linear, or stationary motion of the secondary companion; these are useful when the orbit has a very low eccentricity or the orbital period is much longer than the microlensing timescale. The model parameterizations based on these binary lensing equations enable joint fitting of photometric and astrometric data sets. These binary models will be used to fit microlensing event data from the Vera C. Rubin Observatory, the Nancy Grace Roman Telescope, and other surveys.
Keywords:
gravitational microlensing
binary lens
binary source
Bayesian Analysis of Gravitational Lensing Events
astrometric data
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