exoALMA. IX. Regularized Maximum Likelihood Imaging of Non-Keplerian Features
The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼ 0 . ″ 15 angular resolution and ∼100 m s −1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) i...
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| Published in: | Astrophysical journal. Letters Vol. 984; no. 1; p. L14 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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The American Astronomical Society
01.05.2025
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| ISSN: | 2041-8205, 2041-8213 |
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| Abstract | The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼ 0 . ″ 15 angular resolution and ∼100 m s −1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) in the gas emission. As these features are often small and low-contrast, robust imaging procedures are critical for identifying and characterizing NKFs, including determining which features may be signatures of young planets. The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. This Letter presents the exoALMA RML images, obtained by maximizing the likelihood of the visibility data given a model image and subject to regularizer penalties. Crucially, in the context of exoALMA, RML images serve as an independent verification of marginal features seen in the fiducial CLEAN images. However, best practices for synthesizing RML images of multichanneled (i.e., velocity-resolved) data remain undefined, as prior work on RML imaging for protoplanetary disk data has primarily addressed single-image cases. We used the open-source Python package MPoL to explore RML image validation methods for multichanneled data and synthesize RML images from the exoALMA observations of seven protoplanetary disks with apparent NKFs in the 12 CO J = 3–2 CLEAN images. We find that RML imaging methods independently reproduce the NKFs seen in the CLEAN images of these sources, suggesting that the NKFs are robust features rather than artifacts from a specific imaging procedure. |
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| AbstractList | The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at angular resolution and ∼100 m s‑1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) in the gas emission. As these features are often small and low-contrast, robust imaging procedures are critical for identifying and characterizing NKFs, including determining which features may be signatures of young planets. The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. This Letter presents the exoALMA RML images, obtained by maximizing the likelihood of the visibility data given a model image and subject to regularizer penalties. Crucially, in the context of exoALMA, RML images serve as an independent verification of marginal features seen in the fiducial CLEAN images. However, best practices for synthesizing RML images of multichanneled (i.e., velocity-resolved) data remain undefined, as prior work on RML imaging for protoplanetary disk data has primarily addressed single-image cases. We used the open-source Python package MPoL to explore RML image validation methods for multichanneled data and synthesize RML images from the exoALMA observations of seven protoplanetary disks with apparent NKFs in the 12CO J = 3–2 CLEAN images. We find that RML imaging methods independently reproduce the NKFs seen in the CLEAN images of these sources, suggesting that the NKFs are robust features rather than artifacts from a specific imaging procedure. The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼0.″15 angular resolution and ∼100 m s−1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) in the gas emission. As these features are often small and low-contrast, robust imaging procedures are critical for identifying and characterizing NKFs, including determining which features may be signatures of young planets. The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. This Letter presents the exoALMA RML images, obtained by maximizing the likelihood of the visibility data given a model image and subject to regularizer penalties. Crucially, in the context of exoALMA, RML images serve as an independent verification of marginal features seen in the fiducial CLEAN images. However, best practices for synthesizing RML images of multichanneled (i.e., velocity-resolved) data remain undefined, as prior work on RML imaging for protoplanetary disk data has primarily addressed single-image cases. We used the open-source Python package MPoL to explore RML image validation methods for multichanneled data and synthesize RML images from the exoALMA observations of seven protoplanetary disks with apparent NKFs in the 12CO J = 3–2 CLEAN images. We find that RML imaging methods independently reproduce the NKFs seen in the CLEAN images of these sources, suggesting that the NKFs are robust features rather than artifacts from a specific imaging procedure. The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at $\sim 0\mathop{.}\limits^{^{\prime\prime} }15$ angular resolution and ∼100 m s ^−1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) in the gas emission. As these features are often small and low-contrast, robust imaging procedures are critical for identifying and characterizing NKFs, including determining which features may be signatures of young planets. The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. This Letter presents the exoALMA RML images, obtained by maximizing the likelihood of the visibility data given a model image and subject to regularizer penalties. Crucially, in the context of exoALMA, RML images serve as an independent verification of marginal features seen in the fiducial CLEAN images. However, best practices for synthesizing RML images of multichanneled (i.e., velocity-resolved) data remain undefined, as prior work on RML imaging for protoplanetary disk data has primarily addressed single-image cases. We used the open-source Python package MPoL to explore RML image validation methods for multichanneled data and synthesize RML images from the exoALMA observations of seven protoplanetary disks with apparent NKFs in the ^12 CO J = 3–2 CLEAN images. We find that RML imaging methods independently reproduce the NKFs seen in the CLEAN images of these sources, suggesting that the NKFs are robust features rather than artifacts from a specific imaging procedure. The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼ 0 . ″ 15 angular resolution and ∼100 m s −1 spectral resolution, characterizing disk structures and kinematics in enough detail to detect non-Keplerian features (NKFs) in the gas emission. As these features are often small and low-contrast, robust imaging procedures are critical for identifying and characterizing NKFs, including determining which features may be signatures of young planets. The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. This Letter presents the exoALMA RML images, obtained by maximizing the likelihood of the visibility data given a model image and subject to regularizer penalties. Crucially, in the context of exoALMA, RML images serve as an independent verification of marginal features seen in the fiducial CLEAN images. However, best practices for synthesizing RML images of multichanneled (i.e., velocity-resolved) data remain undefined, as prior work on RML imaging for protoplanetary disk data has primarily addressed single-image cases. We used the open-source Python package MPoL to explore RML image validation methods for multichanneled data and synthesize RML images from the exoALMA observations of seven protoplanetary disks with apparent NKFs in the 12 CO J = 3–2 CLEAN images. We find that RML imaging methods independently reproduce the NKFs seen in the CLEAN images of these sources, suggesting that the NKFs are robust features rather than artifacts from a specific imaging procedure. |
| Author | Hilder, Thomas Ilee, John D. Curone, Pietro Kanagawa, Kazuhiro Flock, Mario Fasano, Daniele Bae, Jaehan Barraza-Alfaro, Marcelo Longarini, Cristiano Yoshida, Tomohiro C. Zawadzki, Brianna Yen, Hsi-Wei Pinte, Christophe Garg, Himanshi Hall, Cassandra Huang, Jane Winter, Andrew J. Orihara, Ryuta Rosotti, Giovanni Wilner, David J. Lesur, Geoffroy Facchini, Stefano Isella, Andrea Teague, Richard Benisty, Myriam Czekala, Ian Loomis, Ryan A. Wafflard-Fernandez, Gaylor Fukagawa, Misato Price, Daniel J. Wölfer, Lisa Stadler, Jochen Galloway-Sprietsma, Maria Cataldi, Gianni Izquierdo, Andrés F. |
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organization: Massachusetts Institute of Technology Department of Earth, Atmospheric, and Planetary Sciences, Cambridge, MA 02139, USA – sequence: 6 givenname: Myriam orcidid: 0000-0002-7695-7605 surname: Benisty fullname: Benisty, Myriam organization: Université Côte d’Azur , Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, 06304, France – sequence: 7 givenname: Gianni orcidid: 0000-0002-2700-9676 surname: Cataldi fullname: Cataldi, Gianni organization: National Astronomical Observatory of Japan , Osawa 2-21-1, Mitaka, Tokyo 181-8588, Japan – sequence: 8 givenname: Pietro orcidid: 0000-0003-2045-2154 surname: Curone fullname: Curone, Pietro organization: Universidad de Chile Departamento de Astronomía, Camino El Observatorio 1515, Las Condes, Santiago, Chile – sequence: 9 givenname: Stefano orcidid: 0000-0003-4689-2684 surname: Facchini fullname: Facchini, Stefano organization: Università degli Studi di Milano Dipartimento di Fisica, Via Celoria 16, 20133 Milano, Italy – 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Technology Department of Earth, Atmospheric, and Planetary Sciences, Cambridge, MA 02139, USA – sequence: 30 givenname: Hsi-Wei orcidid: 0000-0003-1412-893X surname: Yen fullname: Yen, Hsi-Wei organization: Academia Sinica Institute of Astronomy & Astrophysics , 11F of Astronomy-Mathematics Building, AS/NTU, No.1, Sec. 4, Roosevelt Rd, Taipei 10617, Taiwan – sequence: 31 givenname: Gaylor orcidid: 0000-0002-3468-9577 surname: Wafflard-Fernandez fullname: Wafflard-Fernandez, Gaylor organization: Université Grenoble Alpes , CNRS, IPAG, 38000 Grenoble, France – sequence: 32 givenname: David J. orcidid: 0000-0003-1526-7587 surname: Wilner fullname: Wilner, David J. organization: Center for Astrophysics—Harvard & Smithsonian , Cambridge, MA 02138, USA – sequence: 33 givenname: Andrew J. orcidid: 0000-0002-7501-9801 surname: Winter fullname: Winter, Andrew J. organization: Université Côte d’Azur , Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, 06304, France – sequence: 34 givenname: Lisa orcidid: 0000-0002-7212-2416 surname: Wölfer fullname: Wölfer, Lisa organization: Massachusetts Institute of Technology Department of Earth, Atmospheric, and Planetary Sciences, Cambridge, MA 02139, USA – sequence: 35 givenname: Tomohiro C. orcidid: 0000-0001-8002-8473 surname: Yoshida fullname: Yoshida, Tomohiro C. organization: The Graduate University for Advanced Studies Department of Astronomical Science, SOKENDAI, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan |
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| Keywords | Deconvolution Computational methods Instrumentation and Methods for Astrophysics Submillimeter astronomy Protoplanetary disks Planet formation Earth and Planetary Astrophysics |
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| Snippet | The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼ 0 . ″ 15 angular resolution... The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at ∼0.″15 angular resolution and... The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at angular resolution and ∼100 m... The planet-hunting Atacama Large Millimeter/submillimeter Array (ALMA) large program exoALMA observed 15 protoplanetary disks at $\sim... |
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| SubjectTerms | Angular resolution Best practice Computational methods Deconvolution Emissions Imaging Kinematics Planet formation Protoplanetary disks Radio telescopes Robustness Sciences of the Universe Spectral resolution Submillimeter astronomy Synthesis Visibility |
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| Title | exoALMA. IX. Regularized Maximum Likelihood Imaging of Non-Keplerian Features |
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