Guesswork in the gap: the impact of uncertainty in the compact binary population on source classification

TL;DR

This work investigates how population-level assumptions and EOS constraints shape the classification of compact objects as neutron stars or black holes near the lower mass gap in gravitational-wave observations. Using a hierarchical Bayesian framework with the FullPop-4.0 model and 66 events from GWTC-3, the authors compute event-level NS probabilities $P(\text{NS})$ by marginalizing over population hyperparameters and EOS, revealing strong sensitivity to parameters such as the equal-mass pairing tendency $\beta_{\rm LL}$ and the NS spin distributions. They show that degeneracies in mass ratios and spins propagate into NS classifications, with notable variability for low-SNR events (e.g., GW230529) but robustness for high-SNR events (e.g., GW190814). The study also contrasts population-only and EOS-informed analyses and discusses prospects for reducing $P(\text{NS})$ uncertainty as more high-SNR, low-mass detections become available, while advocating explicit uncertainty budgets when reporting NS classifications. Overall, reliable NS classifications will require confronting population-model dependencies and exploring multiple EOS prescriptions in tandem with forthcoming gravitational-wave data.

Abstract

The nature of the compact objects within the supposed "lower mass gap" remains uncertain. Observations of GW190814 and GW230529 highlight the challenges gravitational waves face in distinguishing neutron stars from black holes. Interpreting these systems is especially difficult because classifications depend simultaneously on measurement noise, compact binary population models, and equation of state (EOS) constraints on the maximum neutron star mass. We analyze 66 confident events from GWTC-3 to quantify how the probability of a component being a neutron star, P(NS), varies across the population. The effects are substantial, the dominant drivers of classification are the pairing preferences of neutron stars with other compact objects, and the neutron star spin distributions. The data reveals that P(NS) varies between 1% - 67% for GW230529's primary and between 51% - 100% for GW190425's primary. By contrast, P(NS) for GW190814's secondary varies by <10%, demonstrating robustness from its high signal-to-noise ratio and small mass ratio. Analysis using EOS information tends to affect P(NS) through the inferred maximum neutron star mass rather than the maximum spin. As it stands, P(NS) remains sensitive to numerous population parameters, limiting its reliability and potentially leading to ambiguous classifications of future GW events.

Figures (12)

• Figure 1: The pairing of low mass compact objects ($\beta_{\rm LL}$) effect on classification of GW230529's primary. Here, “pairing” refers to the low-mass population hyperparameter $\beta_{\rm LL}$ that governs how strongly binaries prefer near-equal component masses. (Top) Joint BNS mass distribution $p(m_1,m_2|\beta_{\rm LL},\textsc{GWTC-3})$ evaluated across pairing functions with comparable posterior support. Strong pairing ($\beta_{\rm LL} = 5$) favors near equal masses, while weak pairing ($\beta_{\rm LL} = -0.5$) skews toward more asymmetric binaries. (Middle) The probability of classifying GW230529's primary as a NS for various $\beta_{\rm LL}$; $\gamma_{\text{low}}$ represents the start of the NS-BH boundary. The shaded region represents the 90% symmetric credible interval around the mean. $P(\text{NS})$ varies by up to 32% for equally likely $\beta_{\rm LL}$ and between $6$% -- $53$% in total. (Bottom) Hyperposterior $p(\beta_{\rm LL}|\rm{GWTC-}3)$. A wide range of $\beta_{\rm LL}$ values have comparable probabilities. $\beta_{\rm LL}$ spans values that meaningfully affect the mass distribution; for larger $\beta_{\rm LL}$, the inferred $p(m_1,m_2|\beta_{\rm LL},\textsc{GWTC-3})$ changes very little.
• Figure 2: Inferred latent mass distribution $p(m)$ from GWTC-3.0. The solid curve shows the mean, while the shaded band denotes the 90% symmetric credible interval. A clear dip appears across the putative NS–BH gap, with BBH peaks near $m \sim 10M_\odot$ and $m \sim 30M_\odot$.
• Figure 3: Population spin distributions inferred from GWTC-3. (Top) Spin magnitude distributions for components below and above $3\,M_\odot$. (Bottom) Corresponding spin tilt ($\cos\theta$) distributions. The solid curve shows the mean, while the shaded band denotes the 90% symmetric credible interval.
• Figure 4: Using default priors (uniform component masses in the detector frame and spins that are uniform in magnitude and isotropic in orientation), we show the inferred parameters for three events, GW170817 (red), GW190425 (green), and GW230529 (blue). Off-diagonal panels show 90% symmetric credible intervals. Gray shading indicates regions that are incompatible with NSs (masses above the NS cutoff, $\gamma_{\text{low}}$, or $m^{\text{EOS}}_{\text{max}}$ in our case) and the associated uncertainty band. Degeneracies appear between $q$, $\chi_{\text{eff}}$, $m_1$, and $m_2$. Overall, the $q-\chi_{\text{eff}}$, $q-m_1$, and $q-m_2$ couplings control whether the probability crosses into the "NS" or "Not NS" demarcations.
• Figure 5: The BNS pairing function's ($\beta_{\rm LL}$) effect on classification $P(\text{NS})$. (Top) Population-only, $P(m<\gamma_{\text{low}})$. (Bottom) EOS-informed, $P(m<m^{\text{EOS}}_{\text{max}})$. Increasing $\beta_{\rm LL}$ strengthens equal mass pairing ($q \rightarrow 1$). This is most apparent in GW230529's primary (top blue, shifting by $46$%) and GW190425 $m_1$ EOS case (bottom green, shifting by $37$%). The shaded region represents 90% credible interval around the mean. Primaries are solid lines and secondaries are dotted lines.