Predictions of the LSST Solar System Yield: Neptune Trojans

Abstract The NSF-DOE Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), beginning full operations in late 2025, will dramatically transform solar system science by vastly expanding discoveries and providing detailed characterization opportunities across all small-body populations. This includes the co-orbiting 1:1 resonant Neptune Trojans (NTs), which are thought to be dynamically hot captures from the protoplanetary disk. Using the survey simulator Sorcha , combined with the latest LSST cadence simulations, we present the very first predictions for the NT yield within the LSST. We forecast a model-dependent median number of ∼130–300 discovered NTs, and infer a notable 2:1 detection bias toward the recently emerged L5 cloud near the Galactic plane versus the L4 cloud, reflecting the lower-cadence coverage in the Northern Ecliptic Spur region that suppresses L4 detections. The additionally simulated Science Validation survey will offer the very first early insights into this understudied cloud. Around 60% of detected main survey NTs will meet stringent color light-curve quality criteria, increasing the sample size more than fourfold compared to existing datasets. This enhanced sample will enable robust statistical analyses of NT color and size distributions, crucial for understanding their origins and relationship to the broader trans-Neptunian population. These comprehensive color measurements represent a major step forward in characterizing the NT population and will facilitate future targeted spectroscopic observations.

Authors

Publication Details

Journal
The Astronomical Journal
Published
2026-01-20
DOI
https://doi.org/10.3847/1538-3881/ae27bd
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictions of the LSST Solar System Yield: Neptune Trojans

Samuel Cornwall, Peter Yoachim, Mario Jurić, Joachim Moeyens et al.
The Astronomical Journal
Astro and Planetary Science
article

Predictions of the LSST Solar System Yield: Neptune Trojans

Samuel Cornwall, Peter Yoachim, Mario Jurić, Joachim Moeyens, Jeremy Kubica, Maxine West, J Murtagh, Drew Oldag, Grigori Fedorets, Colin Orion Chandler, Hsing Wen 省 文 Lin 林, Matthew J. Holman, Megan E. Schwamb, Stephanie R. Merritt, Pedro H. Bernardinelli, Jacob A. Kurlander, R. Lynne Jones
article en

Abstract

Abstract The NSF-DOE Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), beginning full operations in late 2025, will dramatically transform solar system science by vastly expanding discoveries and providing detailed characterization opportunities across all small-body populations. This includes the co-orbiting 1:1 resonant Neptune Trojans (NTs), which are thought to be dynamically hot captures from the protoplanetary disk. Using the survey simulator Sorcha , combined with the latest LSST cadence simulations, we present the very first predictions for the NT yield within the LSST. We forecast a model-dependent median number of ∼130–300 discovered NTs, and infer a notable 2:1 detection bias toward the recently emerged L5 cloud near the Galactic plane versus the L4 cloud, reflecting the lower-cadence coverage in the Northern Ecliptic Spur region that suppresses L4 detections. The additionally simulated Science Validation survey will offer the very first early insights into this understudied cloud. Around 60% of detected main survey NTs will meet stringent color light-curve quality criteria, increasing the sample size more than fourfold compared to existing datasets. This enhanced sample will enable robust statistical analyses of NT color and size distributions, crucial for understanding their origins and relationship to the broader trans-Neptunian population. These comprehensive color measurements represent a major step forward in characterizing the NT population and will facilitate future targeted spectroscopic observations.

The Astronomical JournalVol. 171(2)
Openalex Percentile: Top 80%
Astro and Planetary Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.