Measurement prospects for the pair-instability mass cutoff with gravitational waves

TL;DR

This paper assesses the ability of gravitational-wave observations to detect the predicted black-hole mass gap caused by pair-instability supernovae, analyzing current and future data with Bayesian methods.

Contribution

It evaluates the robustness of identifying a black-hole mass cutoff in gravitational-wave data using Bayesian population models and simulations.

Findings

Current data may not confidently identify the mass cutoff.

Future data will reduce uncertainty in the cutoff mass by over 20%.

Parametric models are effective in detecting the cutoff, while nonparametric models show more features.

Abstract

Pair-instability supernovae leave behind no compact remnants, resulting in a predicted gap in the distribution of stellar black-hole masses. Gravitational waves from binary black-hole mergers probe the relevant mass range and analyses of the LIGO-Virgo-KAGRA catalog (GWTC-4) indicate a possible mass cutoff at $40$-$50\,M_\odot$. However, the robustness of this result remains unclear. To this end, using full Bayesian parameter estimation, we simulate gravitational-wave catalogs with and without such a mass cutoff, then test whether its presence or absence is correctly inferred with parametric population models. For catalogs similar to GWTC-4, confident identification of a cutoff is not guaranteed, but the best constraints among our simulations are compatible with results from GWTC-4 when the model includes a cutoff. Conversely, spurious identification of a cutoff is unlikely. For catalogs expected by the end of the O4 observing run, uncertainty in the cutoff mass is reduced by $\gtrsim20\,\%$, but a cutoff at 40-50$M_\odot$ yields only a lower bound on the $^{12}\mathrm{C}(\alpha,\gamma)^{16}\mathrm{O}$ reaction rate, our most stringent constraints on the S-factor at $300\,\mathrm{keV}$ being $S_{300}\gtrsim125\,\mathrm{keV}\,\mathrm{b}$ at $90\,\%$ credibility. Relative uncertainties on the Hubble parameter $H_0$ from gravitational-wave data alone can still be up to $100\,\%$. We also analyze GWTC-4 with the nonparametric PixelPop population model, finding that some mass features are more prominent than in parametric models but a sharp cutoff is not required. However, the parametric model passes a likelihood-based predictive test in GWTC-4 and the PixelPop results are consistent with those from our simulated catalogs with a cutoff. Such tests are necessary to make astrophysical claims from gravitational-wave catalogs.