Dissecting Multi-Model Posterior Landscapes of GW231123: Unveiling Intrinsic Degeneracies via Mode-Finding and Shared Manifold Analysis

Abstract: Astrophysical inference from gravitational-wave observations is challenged by inherent parameter degeneracies and the choice of waveform models. For the high-mass binary black hole merger GW231123, we conduct a multi-model analysis of its 14-dimensional posterior distributions, comparing five distinct waveform models: NRSur7dq4, IMRPhenomXO4a, SEOBNRv5PHM, IMRPhenomXPHM, and IMRPhenomTPHM. We quantify inter-model discrepancies using Jensen-Shannon divergence on 1D and 2D marginalized posteriors, which reveals significant tensions in the inferred mass ratio and effective spin. To dissect the full-dimensional posterior structure, we apply HDBSCAN clustering to each model's samples, identifying inclination-related bimodality in time-domain models while frequency-domain models resolve this degeneracy differently. Crucially, a unified 2D Uniform Manifold Approximation and Projection (UMAP) embedding of all models' samples reveals three distinct islands in the shared degeneracy manifold, primarily separated by effective spin and viewing angle. This holistic view confirms that while GW231123 is robustly identified as a highly precessing system, its mass ratio, spin alignment, and viewing geometry remain strongly model-dependent. Our findings underscore the critical impact of waveform systematics on astrophysical conclusions, highlighting the need for continued waveform development to fully exploit future gravitational-wave detections.

Subjects:	astro-ph.CO; cs.LG
Cite as:	PX:2508.00010