Optimal starshade observation scheduling

Abstract

An exoplanet direct imaging mission using an external occulter for starlight suppression could potentially achieve higher contrasts and throughputs than an equivalently sized telescope with an internal coronagraph.We consider a formation flying mission where the starshade must station-keep with a telescope, assumed to be on a halo orbit about the Sun-Earth L2 point, during observations and slew between observations as the telescope re-orients to target the next star. We use a parameterization of the slew fuel cost calculation based on interpolation of exact solutions of boundary value problem in the circular restricted three body formalism. Time constraints are imposed based on when stars are observable due to the motion of bright sources in the solar system, integration times, and mission lifetime constraints. Finally, we present a comprehensive cost function incorporating star completeness values as a reward heuristic and retargeting fuel costs to sequentially select the next best star to observe. Ensembles of simulations are conducted for different selection schemes; for a 3 year mission, taking two steps of the linear cost function produces the most unique detections with an average of 7.08± 2.55.

Optimal scheduling of exoplanet direct imaging single-visit observations of a blind search survey

“…(38) from period (P) space to a space using Eqs. (39) and (40) assuming a solar mass star to arrive at Eq. (41).…”

“…The histogram and cumulative distribution of visibility of all targets is shown (b). Minimum target visibility is 28% 38,39.…”

Parameterizing the Search Space of Starshade Fuel Costs for Optimal Observation Schedules

“…The starshade begins the retargeting trajectory at a distance d along the LOS to target star i at time t i ; it ends at a distance d along the LOS to target j at time t j t i Δt, where Δt is the slew time [7,8]. More details can be found in the work of Soto et al [9].…”

“…The retargeting or slewing process creates a vast search space of trajectories: we can choose from any star on a target list and achieve alignment after an arbitrary slew time. At each decision step, the simulation scheduler must select the next best star to observe based on costs and the constraints of required integration times, evolving keepout regions, and mission goals [4,5,7,9,10].…”

Exoplanet imaging scheduling optimization for an orbiting starshade working with Extremely Large Telescopes

“…Previous work 7 in optimizing starshade science deliverables has focused on space-telescope coupled configurations in L2 halo orbits, requiring sophisticated techniques to define stars with maximal completeness curves leading to estimating overall exoplanet yield. [8][9][10] We focus here on developing adaptable mission planning tools, which will inform subsequent developments to the R-O's mission architecture. This paper develops algorithmic processes to find and present optimized observation schedules for the R-O mission over various operational conditions.…”