Finding Habitable Exoplanets with Binary Relative Astrometry: Planet Detection and Characterization with the Microarcsecond Astrometric Retrieval Algorithm (MARA)

Abstract

Binary relative astrometry is a technique to search for rocky planets in the habitable zone of nearby binary stars using 1D relative astrometry at the microarcsecond level. This unprecedented precision would allow a custom-designed space telescope to directly measure the occurrence rate of these planets. The success of such a mission depends on our ability to recover and characterize planets from the unique format of extreme precision binary relative astrometry data. We present MARA, the Microarcsecond Astrometric Retrieval Algorithm, specifically designed for these data. We describe the design and format of the MARA pipeline, and demonstrate its accuracy and performance with a series of validation tests on simulated data, using the SHERA SMEx mission concept as an example. Our injection/recovery tests show that with these data, MARA is able to detect and characterize rocky planets in the habitable zone of alpha Cen A, down to a coplanar mass of about 1 Earth mass in 1 year orbits. Expanding to a range of input planet masses and periods for the same example mission, we find that the results from these injection/recovery tests generally agree with the analytic predictions of binary relative astrometry sensitivity. We use MARA to map out the expected completeness as a function of planet mass and period, which in this case reaches down to about 0.5 M Earth masses at 3 year orbits around alpha Cen A. These depth-of-search calculations will be a vital ingredient in demographics calculations from the final data from a binary relative astrometry mission.