arXiv · 2606.26436
Massive boson stars: Waveform-based branch diagnosis with neural reconstruction
Abstract
We investigate whether gravitational waveforms from massive boson-star mergers can be used to diagnose the underlying merger outcome. Using an existing numerical-relativity catalogue, we construct a branch-conditioned neural reconstruction model and infer the outcome by comparing the reconstruction quality of candidate waveform hypotheses. This makes the diagnosis waveform-based rather than a direct classification in the initial parameter space. We compare a supervised baseline model with a distilled student model and find that the merger outcome is encoded in the waveform morphology and can be recovered through branch-conditioned reconstruction. Our results provide a first step toward waveform-based classification of exotic compact-object mergers with multiple possible final states.
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Bo-Xuan Ge. 2026-06-24. Massive boson stars: Waveform-based branch diagnosis with neural reconstruction. https://arxiv.org/abs/2606.26436
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