Multiband Polarimetric Imaging of HR 4796A with the Gemini Planet Imager

Arriaga, Pauline; Fitzgerald, Michael P.; Duchêne, Gaspard; Kalas, Paul; Millar‐Blanchaer, Maxwell A.; Perrin, Marshall D.; Chen, Christine; Mazoyer, J.; Ammons, Mark; Bailey, Vanessa P.; Barman, Trafis S.; Bulger, J.; Chilcote, Jeffrey; Cotten, Tara; Rosa, Robert J. De; Doyon, René; Espósito, Thomas M.; Follette, Katherine B.; Gerard, Benjamin L.; Goodsell, Stephen J.; Graham, James R.; Greenbaum, Alexandra Z.; Hibon, Pascale; Hom, Justin; Hung, Li Wei; Ingraham, Patrick; Konopacky, Quinn; Macintosh, Bruce; Maire, Jérôme; Marchis, Franck; Marley, Mark S.; Marois, Christian; Metchev, Stanimir; Nielsen, Eric L.; Oppenheimer, Rebecca; Palmer, David; Patience, J.; Poyneer, Lisa; Pueyo, Laurent; Rajan, Abhijith; Rameau, Julien; Rantakyrö, Fredrik T.; Ruffio, Jean Baptiste; Savransky, Dmitry; Schneider, Adam C.; Sivaramakrishnan, Anand; Song, Inseok; Soummer, Rémi; Thomas, Sandrine; Wang, Jason; Ward-Duong, Kimberly; Wolff, Schuyler

doi:10.3847/1538-3881/ab91b1

Cited by 28 publications

(23 citation statements)

References 41 publications

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“…Simultaneous analysis of photometric and polarimetric observations of light scattered by dust grains at various wavelengths provide important constraints on the physical properties of the scattering particles. The use of an adequate model particle is mandatory for the proper interpretation of remotely observed photopolarimetric observations (see, e.g., Arriaga et al 2020;Calcino et al 2020;Duchêne et al 2020). As shown in the previous section, the use of the spherical particle model for analyzing the light scattered by a cloud of irregularly shaped nonabsorbing dust particles produces significant errors in the retrieved grain parameters.…”

Section: Discussionmentioning

confidence: 99%

“…Regarding circumstellar regions, the arrival of high-contrast imaging observations broke new ground in characterizing grain size evolution by analyzing the scattered phase function and/or DLP curves (Canovas et al 2015;Kataoka et al 2015Kataoka et al , 2017Milli et al 2017;Birnstiel et al 2018;Ren et al 2019;Arriaga et al 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is important to know the effects of the adopted particle shape model on the retrieved dust parameters such as dust grain and the refractive index. For instance, the simultaneous analysis of the observed phase function and DLP curves places emphasis on the limitations of the spherical particle model for characterizing real dust particles in debris disks (Graham et al 2007;Arriaga et al 2020;Engler et al 2020). Further, the simultaneous analysis of the OSIRIS data set combined with ground-based DLP observations of comet 67P/ Churyumov-Gerasimenko has exposed challenging contradictions in the retrieved physical properties of cometary dust (Hadamcik et al 2016;Markkanen et al 2018;Moreno et al 2018;Muñoz et al 2020).…”

Section: Introductionmentioning

confidence: 99%

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Retrieving Dust Grain Sizes from Photopolarimetry: An Experimental Approach

Muñoz

Frattin

Jardiel

et al. 2021

ApJS

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We present the experimental phase function, degree of linear polarization (DLP), and linear depolarization (δ L ) curves of a set of forsterite samples representative of low-absorbing cosmic dust particles. The samples are prepared using state-of-the-art size-segregating techniques to obtain narrow size distributions spanning a broad range of the scattering size parameter domain. We conclude that the behavior of the phase function at the side-and back-scattering regions provides information on the size regime, the position and magnitude of the maximum of the DLP curve are strongly dependent on particle size, the negative polarization branch is mainly produced by particles with size parameters in the ∼6 to ∼20 range, and the δ L is strongly dependent on particle size at all measured phase angles except for the exact backward direction. From a direct comparison of the experimental data with computations for spherical particles, it becomes clear that the use of the spherical model for simulating the phase function and DLP curves of irregular dust produces dramatic errors in the retrieved composition and size of the scattering particles: The experimental phase functions are reproduced by assuming unrealistically high values of the imaginary part of the refractive index. The spherical model does not reproduce the bell-shaped DLP curve of dust particles with sizes in the resonance and/or geometric optics size domain. Thus, the use of the Mie model for analyzing polarimetric observations might prevent locating dust particles with sizes of the order of or larger than the wavelength of the incident light.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Retrieving Dust Grain Sizes from Photopolarimetry: An Experimental Approach

Muñoz

Frattin

Jardiel

et al. 2021

ApJS

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“…DiskFM has currently been used for SPHERE/IRDIS data, GPI IFS mode data 18 and GPI pol mode data. 19 pyKLIP supports data from various instruments and DiskFM should work without change with SPHERE/IFS and SCEXAO/CHARIS. 35 A main goal has been to optimize the speed of this algorithm for ADI or RDI so that it can be incorporated in an MCMC or Chi-square wrapper.…”

Section: Implementation Detailsmentioning

confidence: 99%

“…This algorithm was successfully used to analyze the HR 4796 A disk for GPI and SPHERE/IRDIS data. 18,19 This algorithm is now publicly available, included in the python based pyKLIP * package. 20 This package has been originally designed to be multi-instrument and most features (including DiskFM) are readily available for GPI, SPHERE, SCExAO coronagraphic instruments.…”

Section: Introductionmentioning

confidence: 99%

DiskFM: A forward modeling tool for disk analysis with coronagraphic instruments

Mazoyer

Arriaga

Hom

et al. 2020

Ground-Based and Airborne Instrumentation for Astronomy VIII

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Because of bright starlight leakage in coronagraphic raw images, faint astrophysical objects such as exoplanets can only be detected using powerful point spread function (PSF) subtraction algorithms. However, these algorithms have strong effects on faint objects of interest, and often prevent precise spectroscopic analysis and scattering property measurements of circumstellar disks. For this reason, PSF-subtraction effects is currently the main limitations to the precise characterization of exoplanetary dust with scattered-light imaging.Forward modeling techniques have long been developed for point source objects (Pueyo 2016). However, Forward Modeling with disks is complicated by the fact that the disk cannot be simplified using a simple point source convolved by the PSF as the astrophysical model; all hypothetical disk morphologies must be explored to understand the subtle and non-linear effects of the PSF subtraction algorithm on the shape and local geometry of these systems. Because of their complex geometries, the forward-modeling process has to be repeated tens or hundred of thousands of times on disks with slightly different physical properties. All of these geometries are then compared to the PSF-subtracted image of the data, within an MCMC or a Chi-square wrapper.In this paper, we present here DiskFM, a new open-source algorithm included in the PSF subtraction algorithms package pyKLIP. This code allows to produce fast forward-modeling for a variety of observation strategies (ADI, SDI, ADI+SDI, RDI). pyKLIP has already been used for SPHERE/IRDIS and GPI data. It is readily available on all instruments supported by pyKLIP (SPHERE/IFS, SCExAO/CHARIS), and can be quickly adapted for other coronagraphic instruments.

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