The Missing Massive Sector: Massive Boson Stars -- Stability and GW Emission in Head-on Mergers
Bo-Xuan Ge
TL;DR
The study investigates stability and gravitational-wave signatures of quartically self-interacting massive boson stars in head-on mergers. It constructs equilibrium sequences $M(|\phi_c|)$ for several $\lambda$ and evolves them using a 2D Cartoon reduction in GRChombo, analyzing stability and collision outcomes through $E_{\rm GW}$ and compactness $\mathcal{C}$. Key findings include stability changes only at the first mass maximum, absence of a second stable window, and a rich collision phenomenology with BS post-merger, BH post-merger, and BH pre-merger channels; high-$\lambda$ cases exhibit a non-monotonic $E_{\rm GW}/M_{\rm TOT}$ in the BH pre-merger branch linked to near-critical dynamics. The work provides an extensive waveform catalogue to enable AI-assisted initial-data improvements and rapid surrogate models across an extended parameter space, advancing gravitational-wave searches for exotic compact objects.
Abstract
We investigate quartically self-interacting massive boson stars by constructing equilibrium sequences and performing dynamical evolutions. The mass curve $M(|φ_c|)$ along these sequences develops multiple extrema, yet stability changes only at the first maximum; configurations beyond it become highly compact and collapse under numerically induced perturbations, with near-critical models displaying a short-lived double-dive behaviour. Head-on collisions of equal-mass stars yield three distinct outcomes - boson star remnants, black hole formation at contact, and collapse of each star to a black hole prior to contact. The associated gravitational-wave energies reflect the competition between increasing compactness and decreasing tidal deformability, and at large self-interaction strengths the collapse-before-contact branch exhibits a pronounced non-monotonic structure. The simulations reported here constitute a substantial catalogue of initial conditions and waveforms, providing a natural basis for neural-network techniques aimed at improving boson star initial data and constructing surrogate models capable of rapidly predicting gravitational-wave signals across an extended parameter space.
