More data than you want, less data than you need: machine learning approaches to starlight subtraction with MagAO-X

High-contrast imaging data analysis depends on removing residual starlight from the host star to reveal planets and disks. Most observers do this with principal components analysis (i.e. KLIP) using modes computed from the science images themselves. These modes may not be orthogonal to planet and di...

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Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Long, Joseph D, Males, Jared R, Close, Laird M, Guyon, Olivier, Haffert, Sebastiaan Y, Weinberger, Alycia J, Kueny, Jay, Kyle Van Gorkom, McEwen, Eden, Pearce, Logan, Kautz, Maggie, Li, Jialin, Lumbres, Jennifer, Hedglen, Alexander, Schatz, Lauren, McLeod, Avalon, Doty, Isabella, Foster, Warren B, Roberts, Roswell, Twitchell, Katie
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive optics Data analysis Disks Image contrast Machine learning Point spread functions Principal components analysis Sensors Terrestrial planets Wave front sensors Wave fronts
Online-Zugang:	Volltext
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