A machine-learning compositional study of exoplanetary material accreted onto five helium-atmosphere white dwarfs with cecilia 

1,2,3Mariona Badenas-Agusti,4Siyi Xu (许偲艺),2Andrew Vanderburg,2Kishalay De,5Patrick Dufour,1,4Laura K Rogers,2,6Susana Hoyos,7Simon Blouin,2Javier Viaña,1Amy Bonsor,6Ben Zuckerman
Monthly Notices of the Royal Astronomical Society 540, 746-773 Open Access Link to Article [https://doi.org/10.1093/mnras/staf777]
1Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK
2Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3Department of Physics and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
4Gemini Observatory/NSF’s NOIRLab, 950 North Cherry Avenue, Tucson, AZ 85719, USA
5Département de Physique, Université de Montréal, Montréal, Québec H3C 3J7, Canada
6Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, CA 90095-1567, USA
7Department of Physics and Astronomy, University of Victoria, Victoria, BC V8W 2Y2, Canad

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What falls versus what we recover: Quantifying search and recovery bias for orbital meteorites

1,2Patrick M. Shober,2Jeremie Vaubaillon,3,4Hadrien A. R. Devillepoix,3,4Eleanor K. Sansom,3,4Sophie E. Deam,2,5Simon Anghel,2Francois Colas,6Pierre Vernazza,7Brigitte Zanda
Meteoritics & Planetary Science (in Press) Link to Article [https://doi.org/10.1111/maps.70041]
1Astromaterials Research and Exploration Science Directorate (ARES), NASA Johnson Space Center, Houston, Texas, USA
2LTE, Observatoire de Paris, Université PSL, Sorbonne Université, Université de Lille, LNE, CNRS, Paris, France
3Space Science and Technology Centre, School of Earth and Planetary Sciences, Curtin University, Perth, WA, Australia
4International Centre for Radio Astronomy Research, Curtin University, Perth, WA, Australia
5Astronomical Institute of the Romanian Academy, Bucharest, Romania
6Institut de Minéralogie, Physique des Matériaux et Cosmochimie, Muséum National d’Histoire Naturelle, CNRS, Paris, France
7Laboratoire d’Astrophysique de Marseille, Aix Marseille Université, Aix-Marseille University, CNRS, CNES, LAM, Institut Origines, Marseille, France
Published by arrangement with John Wiley & Sons

Instrumentally determined pre-atmospheric orbits of meteorites offer crucial constraints on the provenance of extraterrestrial material and the dynamical pathways that deliver it to Earth. However, recovery efforts are focused on larger and slower impacts due to their higher survival probabilities and ease of detection. In this study, we investigate the prevalence of these biases in the population of recovered meteorites with known orbits. We compiled a data set of 75 meteorites with triangulated trajectories and compared their orbits to 538 potential 1 g meteorite-dropping fireballs detected by the Global Fireball Observatory, the European Fireball Network, and the Fireball Recovery and InterPlanetary Observation Network. Our results reveal that objects with small semi-major axis values (a1.8 au) appear 2–3 more often than expected. The current sample of meteorites with known orbits does not reflect the sources of meteorites in our collections, and it is essential to account for search and recovery biases to obtain a more representative understanding of meteorite source contributions.