Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 1, 2020 | Accepted Version + Published
Journal Article Open

Using Data Imputation for Signal Separation in High-contrast Imaging


To characterize circumstellar systems in high-contrast imaging, the fundamental step is to construct a best point-spread function (PSF) template for the noncircumstellar signals (i.e., starlight and speckles) and separate it from the observation. With existing PSF construction methods, the circumstellar signals (e.g., planets, circumstellar disks) are unavoidably altered by overfitting and/or self-subtraction, making forward modeling a necessity to recover these signals. We present a forward modeling–free solution to these problems with data imputation using sequential nonnegative matrix factorization (DI-sNMF), which first converts this signal separation problem to a "missing data" problem in statistics by flagging the regions that host circumstellar signals as missing data, then attributes PSF signals to these regions. We mathematically prove it to have negligible alteration to circumstellar signals when the imputation region is relatively small, which thus enables precise measurement of these circumstellar objects. We apply it to simulated point-source and circumstellar disk observations to demonstrate its proper recovery of them. We apply it to Gemini Planet Imager K1-band observations of the debris disk surrounding HR 4796A, finding a tentative trend that the dust is more forward scattering as the wavelength increases. We expect DI-sNMF to be applicable to other general scenarios where the separation of signals is needed.

Additional Information

© 2020 The American Astronomical Society. Received 2019 August 19; revised 2020 January 20; accepted 2020 January 25; published 2020 March 31. We appreciate the suggestions in both the mathematical expressions and main text from the anonymous referee that improved this paper. B.R. thanks Nicolas Charon and Bingxiao Xu for useful discussions and Christophe Pinte for sharing the MCFOST software and commenting on this paper. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the data archive at the Space Telescope Science Institute. STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), Ministério da Ciência, Tecnologia e Inovação (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). This research project (or part of this research project) was conducted using computational resources (and/or scientific computing services) at the Maryland Advanced Research Computing Center (MARCC; https://www.marcc.jhu.edu). This work was in part funded by contract 61362448-122362 from WFIRST NASA project office via a subcontract through Stanford. Facilities: HST (STIS) - , Gemini:South (Gemini Planet Imager). - Software: MCFOST (Pinte et al. 2006, 2009), nmf_imaging (Ren 2018), TinyTim (Krist et al. 2011).

Attached Files

Published - Ren_2020_ApJ_892_74.pdf

Accepted Version - 2001.00563.pdf


Files (10.0 MB)
Name Size Download all
6.9 MB Preview Download
3.1 MB Preview Download

Additional details

August 22, 2023
October 19, 2023