HackerPapers

arXiv:2508.09167physics.pop-ph

The Loeb Scale: Astronomical Classification of Interstellar Objects

Omer Eldadi, Gershon Tenenbaum, Abraham Loeb

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

The Vera C. Rubin Observatory is expected to increase interstellar object (ISO) detections from a few over the past decade to potentially one per few months, demanding a systematic classification scheme. We present the Loeb Scale, formally the Interstellar Object Significance Scale (IOSS), a 0-10 classification system extending the proven Torino Scale framework, to address ISOs' unique anomalies, including potential technosignatures. The scale provides quantitative thresholds for natural phenomena (Levels 0-3) and graduated protocols for increasingly anomalous characteristics (Levels 4-7), with Levels 8-10 reserved for confirmed artificial origin. Each level specifies observable criteria and response protocols. We demonstrate the scale's application using 1I/'Oumuamua (Level 4), 2I/Borisov (Level 0), and 3I/ATLAS (Level 4) as test cases. The Loeb Scale provides the astronomical community with a standardized framework for consistent, evidence-based and dynamic evaluation while maintaining scientific rigor across the full spectrum of possibilities as we enter an era of routine ISO encounters.

arXiv comments
19 pages, 1 table
Journal reference
DOI
Subjects
physics.pop-phPopular Physics astro-ph.EPEarth and Planetary Astrophysics astro-ph.GAAstrophysics of Galaxies astro-ph.IMInstrumentation and Methods for Astrophysics

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Aug 2025 to Aug 2025. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.