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StraKLIP: A novel pipeline for detection and characterization of close-in faint companions through Karhunen-Lo\^eve Image Processing algorithm

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arxiv 2208.06719 v1 pith:N2GGSVFH submitted 2022-08-13 astro-ph.IM astro-ph.EPastro-ph.SR

StraKLIP: A novel pipeline for detection and characterization of close-in faint companions through Karhunen-Lo\^eve Image Processing algorithm

classification astro-ph.IM astro-ph.EPastro-ph.SR
keywords pipelinecompanionsdetectimagingablealgorithmanalysischaracterization
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We present a new pipeline developed to detect and characterize faint astronomical companions at small angular separation from the host star using sets of wide-field imaging observations not specifically designed for High Contrast Imaging analysis. The core of the pipeline relies on Karhunen-Lo\^eve truncated transformation of the reference PSF library to perform PSF subtraction and identify candidates. Tests of reliability of detections and characterization of companions are made through simulation of binaries and generation of Receiver Operating Characteristic curves for false positive/true positive analysis. The algorithm has been successfully tested on large HST/ACS and WFC3 datasets acquired for two HST Treasury Programs on the Orion Nebula Cluster. Based on these extensive numerical experiments we find that, despite being based on methods designed for observations of single star at a time, our pipeline performs very well on mosaic space based data. In fact, we are able to detect brown dwarf-mass companions almost down to the planetary mass limit. The pipeline is able to reliably detect signals at separations as close as $\gtrsim 0.1 "$ with a completeness of $\gtrsim 10\%$, or $\sim 0.2"$ with a completeness of $\sim 30\%$. This approach can potentially be applied to a wide variety of space based imaging surveys, starting with data in the existing HST archive, near-future JWST mosaics, and future wide-field Roman images.

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