2026/05/19 by Julien de Wit, Andrew S. Rivkin, Marco Micheli +12 · 2 voices
Engineering · Physics and Astronomy · #Astro and Planetary Science #Planetary Science and Exploration #Space Satellite Systems and Control #astro-ph.EP #astro-ph.IM
paper · pdf · doi:10.3847/2041-8213/ae6a95
openalex created_date 2026/05/19 · openalex publication_date 2026/05/19 · openalex updated_date 2026/07/28
Abstract At the end of its discovery apparition, the ∼60 m near-Earth object 2024 YR4 was associated with a nonzero probability of lunar impact during its 2032 December 22 close approach. While posing no threat to Earth, a lunar impact of this scale could have consequences for Earth-orbiting infrastructure, as well as for human exploration on and around the Moon. We present new JWST/NIRCam observations from 2026 February 18 and 26 that extend the observational arc by 8 months, reduce the uncertainty in the 2032 lunar encounter by a factor >30, and constitute the faintest detection of a near-Earth object to date, reaching V ∼ 30.5—beyond the V ∼ 27 ground-based limit. The updated orbit solution yields a predicted miss distance of 22,900 ± 800 km (1 σ ) from the center of the Moon, thus ruling out a lunar impact. Despite challenges due to the limited number of reference stars and saturation and trailing effects, we derive astrometric positions with three independent analysis methods, demonstrating consistency at the ≲50 mas level. These observations extend the orbital arc at epochs when the object is not accessible from the ground, advancing the timeline for hazard assessment by 2 yr relative to the next feasible ground-based recovery. This capability is critical in an emerging regime of planetary defense characterized by the discovery of decameter-scale objects by next-generation surveys. These objects are far more common but rapidly become inaccessible to ground-based follow-up. In this regime, hazard assessment can become follow-up limited, requiring targeted space-based observations, such as those demonstrated here, to reliably constrain impact probabilities on operationally relevant timescales.