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PreprintarXiv licencearXiv

Massive boson stars: Waveform-based branch diagnosis with neural reconstruction

  • Bo-Xuan Ge
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Abstract

We investigate whether the dynamical merger branch of massive boson-star collisions can be inferred from the gravitational waveform without supplying the intrinsic source parameters. Using an existing equal-mass, head-on numerical-relativity catalogue, we construct branch-conditioned reduced-basis surrogates for the real (2,0) and (4,0) modes and perform parameter-blind waveform inference. On a frozen test set of 60 held-out samples, the correct branch is recovered for all samples using either mode, showing that the branch information is not confined to the dominant (2,0) channel. The inference also recovers |ϕc| with a mean relative error of 4.30% and selects the correct λ from {10,50,100,300} in 68.3% of the test samples. These results demonstrate waveform-based branch and source-parameter inference within the present noiseless numerical-relativity catalogue.

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Cite

BibTeXRIS
BibTeX
@misc{ge2026massive,
  title = {{Massive boson stars: Waveform-based branch diagnosis with neural reconstruction}},
  author = {Bo-Xuan Ge},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2606.26436},
  eprint = {2606.26436},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.26436},
}
RIS
TY  - UNPB
TI  - Massive boson stars: Waveform-based branch diagnosis with neural reconstruction
AU  - Bo-Xuan Ge
PY  - 2026
DA  - 2026/10/24
PB  - arXiv
DO  - 10.48550/arxiv.2606.26436
UR  - https://arxiv.org/abs/2606.26436
AB  - We investigate whether the dynamical merger branch of massive boson-star collisions can be inferred from the gravitational waveform without supplying the intrinsic source parameters. Using an existing equal-mass, head-on numerical-relativity catalogue, we construct branch-conditioned reduced-basis surrogates for the real (2,0) and (4,0) modes and perform parameter-blind waveform inference. On a frozen test set of 60 held-out samples, the correct branch is recovered for all samples using either mode, showing that the branch information is not confined to the dominant (2,0) channel. The inference also recovers |ϕ_c| with a mean relative error of 4.30% and selects the correct λ from {10,50,100,300} in 68.3% of the test samples. These results demonstrate waveform-based branch and source-parameter inference within the present noiseless numerical-relativity catalogue.
ER  -