Regularized Maximum Likelihood Image Synthesis and Validation for ALMA Continuum Observations of Protoplanetary Disks

Abstract

Regularized Maximum Likelihood (RML) techniques are a class of image synthesis methods that achieve better angular resolution and image fidelity than traditional methods like CLEAN for sub-mm interferometric observations. To identify best practices for RML imaging, we used the GPU-accelerated open source Python package MPoL, a machine learning-based RML approach, to explore the influence of common RML regularizers (maximum entropy, sparsity, total variation, and total squared variation) on images reconstructed from real and synthetic ALMA continuum observations of protoplanetary disks. We tested two different cross-validation (CV) procedures to characterize their performance and determine optimal prior strengths, and found that CV over a coarse grid of regularization strengths easily identifies a range of models with comparably strong predictive power. To evaluate the performance of RML techniques against a ground truth image, we used MPoL on a synthetic protoplanetary disk dataset and found that RML methods successfully resolve structures at fine spatial scales present in the original simulation. We used ALMA DSHARP observations of the protoplanetary disk around HD 143006 to compare the performance of MPoL and CLEAN, finding that RML imaging improved the spatial resolution of the image by up to a factor of 3 without sacrificing sensitivity. We provide general recommendations for building an RML workflow for image synthesis of ALMA protoplanetary disk observations, including effective use of CV. Using these techniques to improve the imaging resolution of protoplanetary disk observations will enable new science, including the detection of protoplanets embedded in disks.

27 pages, 12 figures, accepted for publication in PASP

References in corpus (20)

• First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole
• CASA, the Common Astronomy Software Applications for Radio Astronomy
• Multi-Scale CLEAN deconvolution of radio synthesis images
• Compressed sensing imaging techniques for radio interferometry
• A Circumplanetary Disk Around PDS70c
• Imaging the water-snow line during a protostellar outburst
• Imaging the Schwarzschild-radius-scale Structure of M87 with the Event Horizon Telescope using Sparse Modeling
• Sparsity Averaging Reweighted Analysis (SARA): a novel algorithm for radio-interferometric imaging
• Super-resolution Full Polarimetric Imaging for Radio Interferometry with Sparse Modeling
• Dust unveils the formation of a mini-Neptune planet in a protoplanetary ring
• Frankenstein: Protoplanetary disc brightness profile reconstruction at sub-beam resolution with a rapid Gaussian process
• MORESANE: MOdel REconstruction by Synthesis-ANalysis Estimators. A sparse deconvolution algorithm for radio interferometric imaging
• Molecules with ALMA at Planet-forming Scales (MAPS). A Circumplanetary Disk Candidate in Molecular Line Emission in the AS 209 Disk
• A dusty filament and turbulent CO spirals in HD135344B-SAO206462
• Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers
• ALMA observations of Elias 2-24: a protoplanetary disk with multiple gaps in the Ophiuchus Molecular Cloud
• First AI for deep super-resolution wide-field imaging in radio astronomy: unveiling structure in ESO 137--006
• Super-resolution Imaging of the Protoplanetary Disk HD 142527 Using Sparse Modeling
• 3D Detection and Characterisation of ALMA Sources through Deep Learning
• Neural network based image reconstruction with astrophysical priors

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• Seeing the unseen: a method to detect unresolved rings in protoplanetary disks