Modeling Binary Lenses and Sources with the BAGLE Python Package

TL;DR

This paper introduces new binary lens and source models into the BAGLE Python package, enabling joint-fitting of microlensing data for binary systems with various orbital configurations.

Contribution

The authors extend the BAGLE software to include binary lens and source models with Keplerian and simplified orbital motions, enhancing microlensing analysis capabilities.

Findings

Binary models account for Keplerian orbits in BAGLE.

Simplified binary models describe low-eccentricity or long-period orbits.

Models facilitate joint photometric and astrometric data fitting.

Abstract

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 a binary system. 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 datasets. 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.