Paper
4 August 2014 Have confidence in your coronagraph: statistical analysis of high-contrast coronagraph dynamics error budgets
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Abstract
We have combined our Excel-based coronagraph dynamics error budget spreadsheets with DAKOTA scripts to perform statistical analyses of the predicted dark-hole contrast. Whereas in the past we have reported the expected contrast level for an input set of allocated parameters, we now generate confidence intervals for the predicted contrast. Further, we explore the sensitivity to individual or groups of parameters and model uncertainty factors through aleatory-epistemic simulations based on a surrogate model fitted to the error budget. We show example results for a generic high-contrast coronagraph.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stuart B. Shaklan, Luis Marchen, Lee Peterson, and Marie B. Levine "Have confidence in your coronagraph: statistical analysis of high-contrast coronagraph dynamics error budgets", Proc. SPIE 9150, Modeling, Systems Engineering, and Project Management for Astronomy VI, 915018 (4 August 2014); https://doi.org/10.1117/12.2054960
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Cited by 1 scholarly publication.
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KEYWORDS
Coronagraphy

Error analysis

Performance modeling

Statistical analysis

James Webb Space Telescope

Mirrors

Systems modeling

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