Dmitry Savranskyhttps://orcid.org/0000-0002-8711-7206,1 Russell Knight,2 Michael Turmon,2 Corey Spohn,1 Rhonda Morgan,2 Mario Damiano,2 Grace Genszler,1 Jackson Kulik1
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NASA is currently responding to the recommendations of the astrophysics decadal survey via its Great Observatories Maturation Program and preparing for the maturation of the Habitable Worlds Observatory, which will have a key science goal of exoplanet detection and characterization. An important element of this process is the evaluation of the impact of mission design decisions on mission science outcomes. One approach to such science yield modeling is via Monte Carlo Mission Simulation (MCMS) - the generation of ensembles of simulated mission schedules from which performance metric statistics can be derived. MCMS requires the ability to automatically schedule such observing sequences based on a mission concept’s stated operating rules. However, inefficiencies in the scheduler can lead to suboptimal performance and decreases in expected science yield that are not driven by any design decisions. Here, we discuss approaches to quantifying the impacts of schedulability and scheduling inefficiencies on science yields, and present a new method for validating scheduler efficiency.
Conference Presentation
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Dmitry Savransky,Russell Knight,Michael Turmon,Corey Spohn,Rhonda Morgan,Mario Damiano,Grace Genszler, andJackson Kulik
"Quantifying the impacts of schedulability on science yield of exoplanet imaging missions", Proc. SPIE 12680, Techniques and Instrumentation for Detection of Exoplanets XI, 126801K (5 October 2023); https://doi.org/10.1117/12.2677102
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Dmitry Savransky, Russell Knight, Michael Turmon, Corey Spohn, Rhonda Morgan, Mario Damiano, Grace Genszler, Jackson Kulik, "Quantifying the impacts of schedulability on science yield of exoplanet imaging missions," Proc. SPIE 12680, Techniques and Instrumentation for Detection of Exoplanets XI, 126801K (5 October 2023); https://doi.org/10.1117/12.2677102