Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering
Debris disks, which consist of dust, planetesimals, planets, and gas, offer a unique window into the mineralogical composition of their parent bodies, especially during the critical phase of terrestrial planet formation spanning 10 yr to a few hundred million years. Observations from the Spitzer Spa...
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2025-01-01
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| Online Access: | https://doi.org/10.3847/1538-4365/ada0ba |
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| author | Cicero X. Lu Tushar Mittal Christine H. Chen Alexis Y. Li Kadin Worthen B. A. Sargent Carey M. Lisse G. C. Sloan Dean C. Hines Dan M. Watson Isabel Rebollido Bin B. Ren Joel D. Green |
| author_facet | Cicero X. Lu Tushar Mittal Christine H. Chen Alexis Y. Li Kadin Worthen B. A. Sargent Carey M. Lisse G. C. Sloan Dean C. Hines Dan M. Watson Isabel Rebollido Bin B. Ren Joel D. Green |
| author_sort | Cicero X. Lu |
| collection | DOAJ |
| description | Debris disks, which consist of dust, planetesimals, planets, and gas, offer a unique window into the mineralogical composition of their parent bodies, especially during the critical phase of terrestrial planet formation spanning 10 yr to a few hundred million years. Observations from the Spitzer Space Telescope have unveiled thousands of debris disks, yet systematic studies remain scarce, let alone those with unsupervised clustering techniques. This study introduces CLustering UnsupErvised with Sequencer (CLUES), a novel, nonparametric, fully interpretable machine learning spectral analysis tool designed to analyze and classify the spectral data of debris disks. CLUES combines multiple unsupervised clustering methods with multiscale distance measures to discern new groupings and trends, offering insights into compositional diversity and geophysical processes within these disks. Our analysis allows us to explore a vast parameter space in debris disk mineralogy and also offers broader applications in fields such as protoplanetary disks and solar system objects. This paper details the methodology, implementation, and initial results of CLUES , setting the stage for more detailed follow-up studies focusing on debris disk mineralogy and demographics. |
| format | Article |
| id | doaj-art-905ce65cbcfa41a0b33d2348666f0148 |
| institution | Kabale University |
| issn | 0067-0049 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astrophysical Journal Supplement Series |
| spelling | doaj-art-905ce65cbcfa41a0b33d2348666f01482025-02-04T12:17:31ZengIOP PublishingThe Astrophysical Journal Supplement Series0067-00492025-01-0127626510.3847/1538-4365/ada0baSequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised ClusteringCicero X. Lu0https://orcid.org/0000-0001-9352-0248Tushar Mittal1https://orcid.org/0000-0002-8026-0018Christine H. Chen2https://orcid.org/0000-0002-8382-0447Alexis Y. Li3https://orcid.org/0009-0001-7058-8538Kadin Worthen4https://orcid.org/0000-0002-5885-5779B. A. Sargent5https://orcid.org/0000-0001-9855-8261Carey M. Lisse6https://orcid.org/0000-0002-9548-1526G. C. Sloan7https://orcid.org/0000-0003-4520-1044Dean C. Hines8https://orcid.org/0000-0003-4653-6161Dan M. Watson9https://orcid.org/0000-0001-8302-0530Isabel Rebollido10https://orcid.org/0000-0002-4388-6417Bin B. Ren11https://orcid.org/0000-0003-1698-9696Joel D. Green12https://orcid.org/0000-0003-1665-5709Gemini Observatory/NSF NOIRLab , 670 N. A’ohoku Pl., Hilo, HI 96720, USA ; cicero.lu@noirlab.edu; Department of Physics and Astronomy , The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USADepartment of Geosciences , Pennsylvania State University, 309 Deike Building, State College, PA 16801, USADepartment of Physics and Astronomy , The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA; Space Telescope Science Institute , 3700 San Martin Dr., Baltimore, MD 21218, USADepartment of Physics and Astronomy , The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USADepartment of Physics and Astronomy , The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USADepartment of Physics and Astronomy , The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA; Space Telescope Science Institute , 3700 San Martin Dr., Baltimore, MD 21218, USAJohns Hopkins University Applied Physics Laboratory , 11100 Johns Hopkins Rd., Laurel, MD 20723, USASpace Telescope Science Institute , 3700 San Martin Dr., Baltimore, MD 21218, USA; Department of Physics and Astronomy , University of North Carolina, Chapel Hill, NC 27599-3255, USASpace Telescope Science Institute , 3700 San Martin Dr., Baltimore, MD 21218, USADepartment of Physics and Astronomy , University of Rochester, 500 Wilson Blvd., Rochester, NY 14627, USAEuropean Space Astronomy Centre (ESAC) , Camino bajo del Castillo, s/n Urbanización Villafranca del Castillo, Villanueva de la Cañada, E-28692 Madrid, SpainUniversité Côte d’Azur , Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, Bd de l’Observatoire, CS 34229, 06304 Nice cedex 4, France; Max-Planck-Institut für Astronomie (MPIA) , Königstuhl 17, D-69117 Heidelberg, GermanySpace Telescope Science Institute , 3700 San Martin Dr., Baltimore, MD 21218, USADebris disks, which consist of dust, planetesimals, planets, and gas, offer a unique window into the mineralogical composition of their parent bodies, especially during the critical phase of terrestrial planet formation spanning 10 yr to a few hundred million years. Observations from the Spitzer Space Telescope have unveiled thousands of debris disks, yet systematic studies remain scarce, let alone those with unsupervised clustering techniques. This study introduces CLustering UnsupErvised with Sequencer (CLUES), a novel, nonparametric, fully interpretable machine learning spectral analysis tool designed to analyze and classify the spectral data of debris disks. CLUES combines multiple unsupervised clustering methods with multiscale distance measures to discern new groupings and trends, offering insights into compositional diversity and geophysical processes within these disks. Our analysis allows us to explore a vast parameter space in debris disk mineralogy and also offers broader applications in fields such as protoplanetary disks and solar system objects. This paper details the methodology, implementation, and initial results of CLUES , setting the stage for more detailed follow-up studies focusing on debris disk mineralogy and demographics.https://doi.org/10.3847/1538-4365/ada0baDebris disksPlanetary system formationClusteringSilicate grainsInfrared spectroscopySpectroscopy |
| spellingShingle | Cicero X. Lu Tushar Mittal Christine H. Chen Alexis Y. Li Kadin Worthen B. A. Sargent Carey M. Lisse G. C. Sloan Dean C. Hines Dan M. Watson Isabel Rebollido Bin B. Ren Joel D. Green Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering The Astrophysical Journal Supplement Series Debris disks Planetary system formation Clustering Silicate grains Infrared spectroscopy Spectroscopy |
| title | Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering |
| title_full | Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering |
| title_fullStr | Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering |
| title_full_unstemmed | Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering |
| title_short | Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering |
| title_sort | sequencing silicates in the spitzer infrared spectrograph debris disk catalog i methodology for unsupervised clustering |
| topic | Debris disks Planetary system formation Clustering Silicate grains Infrared spectroscopy Spectroscopy |
| url | https://doi.org/10.3847/1538-4365/ada0ba |
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