Ensemble-Based Residual Tests of GW231123 across Waveform Models

Abstract

GW231123 is an exceptional gravitational wave event for which different waveform models yield significantly different inferred source parameters. Residual tests provide a direct way to assess whether each waveform model gives an adequate description of the observed signal. In this work, we extend the conventional residual-test methods by subtracting the 100 highest likelihood waveforms, rather than only the maximum likelihood waveform for each model, thereby propagating waveform reconstruction uncertainty into the residual analysis. This ensemble-based approach turns the residual test from a single waveform diagnostic into a robustness test over the local high likelihood waveform manifold. We further perform injection tests to quantify the detectability of cross-model waveform discrepancies in realistic detector noise. The large-scale implementation of these analyses is made possible by the high speed and low computational cost of our residual testing framework, which is based on three goodness-of-fit tests: the Kolmogorov-Smirnov test, the Anderson-Darling test, and Pearson's chi-squared test.