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A weakly modelled view of the joint compact-binary mass plane: population structure and spectral-siren cosmology

Published 7 Oct 2026 in gr-qc | (2610.10535v1)

Abstract: We introduce a flexible mixture model for the joint source-frame component-mass distribution of compact binaries, inferred simultaneously with cosmology, together with a framework that identifies structures in the reconstructed density, quantifying their posterior stability, local prominence, and cosmological relevance. Applied to GWTC-5.0, the workflow clarifies several familiar and emergent structures. The ∼35 M⊙\sim35~M_\odot feature is classified as a clear near-equal-mass peak despite an ambiguous interpretation in the primary-mass projection. A weaker unequal-mass concentration near (21,12) M⊙(21,12)~M_\odot is recovered frequently but with lower prominence. A tentative joint transition near 60 M⊙60~M_\odot appears at mildly unequal masses, with a more robust manifestation in the primary-mass projection. For cosmology, the two-dimensional mass model constraint on H0H_0 is 33%33\% narrower than a model that flexibly reconstructs only the primary mass, and only ∼ 10%\sim~10\% wider than analyses based on strongly parameterized one-dimensional spectral structure. At the feature level, we show that the ∼10 M⊙\sim10~M_\odot and ∼35 M⊙\sim35~M_\odot concentrations depend on H0H_0 mainly through a common scale which captures the entire ∼ (1+z)\sim~(1+z) cosmological rescaling of both masses; the intermediate unequal-mass feature instead retains residual dependence in the orthogonal mass-ratio direction. More generally, we argue that population prominence, formal inclusion in an astrophysical feature catalogue, and cosmological relevance need not coincide. These results suggest that a genuinely two-dimensional view may be required to fully exploit spectral-siren information. Our workflow provides a reproducible way to detect population structure and identify which aspects of its geometry are associated with spectral-siren constraints. The feature finder is directly applicable to other population reconstructions.

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