A Pre-Registered Convergence Test for the Planet Nine Hypothesis Using LSST Data Preview 2

The Planet Nine hypothesis predicts that extreme trans-Neptunian objects (ETNOs) exhibit orbital clustering. Current evidence spans p-values from 7e-5 to 0.18 depending on the choice of bias-correction method. Chen (2026, MNRAS, submitted) proposed a convergence framework: if clustering is real, a single statistical test applied with different survey-weighting schemes should agree with an independent non-parametric reference; if it is noise, they will disagree. LSST Data Preview 2 (DP2), expected mid-2026, provides the first opportunity to test this prediction with an independent dataset. This Research Note pre-registers the analysis protocol before DP2 data become available. I will apply the Rayleigh test in six variants -- one unweighted, four survey-weighted (Pan-STARRS, DES, OSSOS, Kuiper), and one Monte Carlo reference -- to the DP2 ETNO sample and report the full set of p-values, convergence tier, and method correlation matrix, irrespective of outcome. This test provides a critical, independent check on whether the ETNO clustering signal reflects a genuine physical phenomenon or an artifact of heterogeneous survey selection.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-25
DOI
https://doi.org/10.5281/zenodo.20849444
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
0.00
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article

A Pre-Registered Convergence Test for the Planet Nine Hypothesis Using LSST Data Preview 2

Zhilei Chen
Zenodo (CERN European Organization for Nuclear Research)
Astro and Planetary Science
article

A Pre-Registered Convergence Test for the Planet Nine Hypothesis Using LSST Data Preview 2

Zhilei Chen
article en

Abstract

The Planet Nine hypothesis predicts that extreme trans-Neptunian objects (ETNOs) exhibit orbital clustering. Current evidence spans p-values from 7e-5 to 0.18 depending on the choice of bias-correction method. Chen (2026, MNRAS, submitted) proposed a convergence framework: if clustering is real, a single statistical test applied with different survey-weighting schemes should agree with an independent non-parametric reference; if it is noise, they will disagree. LSST Data Preview 2 (DP2), expected mid-2026, provides the first opportunity to test this prediction with an independent dataset. This Research Note pre-registers the analysis protocol before DP2 data become available. I will apply the Rayleigh test in six variants -- one unweighted, four survey-weighted (Pan-STARRS, DES, OSSOS, Kuiper), and one Monte Carlo reference -- to the DP2 ETNO sample and report the full set of p-values, convergence tier, and method correlation matrix, irrespective of outcome. This test provides a critical, independent check on whether the ETNO clustering signal reflects a genuine physical phenomenon or an artifact of heterogeneous survey selection.

Zenodo (CERN European Organization for Nuclear Research)
Guangdong Peizheng College
Openalex Percentile: Top 7%
Astro and Planetary Science
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