Using Data Imputation for Signal Separation in High Contrast Imaging

التفاصيل البيبلوغرافية
العنوان: Using Data Imputation for Signal Separation in High Contrast Imaging
المؤلفون: Ren, Bin, Pueyo, Laurent, Chen, Christine, Choquet, Élodie, Debes, John H., Duchêne, Gaspard, Ménard, François, Perrin, Marshall D.
المصدر: ApJ 892 (2020) 74
سنة النشر: 2020
المجموعة: Astrophysics
Statistics
مصطلحات موضوعية: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Statistics - Machine Learning
الوصف: To characterize circumstellar systems in high contrast imaging, the fundamental step is to construct a best point spread function (PSF) template for the non-circumstellar signals (i.e., star light 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 over-fitting 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 non-negative matrix factorization (DI-sNMF). DI-sNMF first converts this signal separation problem to a "missing data" problem in statistics by flagging the regions which 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 for 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 (GPI) 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.
Comment: 18 pages, 9 figures, ApJ published. Modified AASTeX template at https://github.com/seawander/aastex_pwnedTest
نوع الوثيقة: Working Paper
DOI: 10.3847/1538-4357/ab7024
الوصول الحر: http://arxiv.org/abs/2001.00563Test
رقم الانضمام: edsarx.2001.00563
قاعدة البيانات: arXiv