Reanalysis of GW170817 and GW190425 under the Goldilocks Prior
Abstract
Gravitational waves from binary neutron star mergers encode the properties of the densest matter in the universe, but recovering them accurately requires controlling biases introduced by the inference framework. The recently developed Goldilocks Prior incorporates correlations predicted by a large ensemble of candidate equations of state and broadens them according to the expected detector sensitivity. We apply this framework to GW170817 and GW190425 and find that the inferred component tidal deformabilities differ substantially from standard analyses. For GW170817, we infer both neutron stars to be more tidally deformable than previously reported, with the most probable value for the lighter star nearly doubling from Λ2≃215 to Λ2≃443 relative to the uniform-prior analysis. For GW190425, the Goldilocks Prior considerably reduces the range of allowed tidal deformabilities. We propagate the resulting event likelihoods to the dense matter equation of state using two complementary hierarchical methods, a strongly parametrized spectral representation and a broader semi-parametric Gaussian-process ensemble. For GW170817, both prior treatments yield consistent EoS constraints despite substantial differences in the inferred properties of the individual neutron stars. For GW190425, however, the EoS constraints differ beyond numerical scatter even after removing the source-level priors, showing that prior choice affects likelihood recovery for low-SNR events. The joint EoS constraints nevertheless remain largely unchanged because GW170817 dominates the inference.
Related
- The Goldilocks Prior: Physically Consistent Inference of Neutron Star Properties from Gravitational Wave Observations
- A first-principles binary neutron star merger model of GW170817, GRB170817A, and AT2017gfo
- New Constraints on r-process Nucleosynthesis in Neutron Star Mergers from GW170817 Late-phase Spectra
- Updated estimates of post-merger gravitational wave energy released in GW170817 and the maximum neutron star mass
- New Constraints on r-process Nucleosynthesis in Neutron Star Mergers from GW170817 Late-Phase Spectra
BibTeX
@misc{khadkikar2026reanalysis,
title = {{Reanalysis of GW170817 and GW190425 under the Goldilocks Prior}},
author = {Sanika Khadkikar and B. S. Sathyaprakash},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.07147},
eprint = {2611.07147},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.07147},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Reanalysis of GW170817 and GW190425 under the Goldilocks Prior
AU - Sanika Khadkikar
AU - B. S. Sathyaprakash
PY - 2026
DA - 2026/11/04
PB - arXiv
DO - 10.48550/arxiv.2611.07147
UR - https://arxiv.org/abs/2611.07147
AB - Gravitational waves from binary neutron star mergers encode the properties of the densest matter in the universe, but recovering them accurately requires controlling biases introduced by the inference framework. The recently developed Goldilocks Prior incorporates correlations predicted by a large ensemble of candidate equations of state and broadens them according to the expected detector sensitivity. We apply this framework to GW170817 and GW190425 and find that the inferred component tidal deformabilities differ substantially from standard analyses. For GW170817, we infer both neutron stars to be more tidally deformable than previously reported, with the most probable value for the lighter star nearly doubling from Λ_2≃215 to Λ_2≃443 relative to the uniform-prior analysis. For GW190425, the Goldilocks Prior considerably reduces the range of allowed tidal deformabilities. We propagate the resulting event likelihoods to the dense matter equation of state using two complementary hierarchical methods, a strongly parametrized spectral representation and a broader semi-parametric Gaussian-process ensemble. For GW170817, both prior treatments yield consistent EoS constraints despite substantial differences in the inferred properties of the individual neutron stars. For GW190425, however, the EoS constraints differ beyond numerical scatter even after removing the source-level priors, showing that prior choice affects likelihood recovery for low-SNR events. The joint EoS constraints nevertheless remain largely unchanged because GW170817 dominates the inference.
ER -