Mapping Domain-Wall Bayesian Reconstruction with LISA

Abstract

We study the Bayesian reconstruction of peaked domain-wall gravitational-wave signals at LISA and construct reconstruction maps over the signal-parameter plane. These maps identify the regions in which the signal can be probed with minimal posterior uncertainty and parameter degeneracy. Our analysis employs a two-parameter domain-wall spectral template and includes isotropic, unmodulated astrophysical foregrounds from Galactic double white-dwarf binaries and extra-galactic compact binaries, together with LISA instrumental noise. The inference is performed for 64 injection points distributed on an equidistant grid using nested sampling, and the resulting posterior quantities are interpolated with the Clough--Tocher method to generate smooth maps over the full parameter plane. We find that LISA reconstructs domain-wall signals most effectively when the annihilation temperature lies approximately in the range $10^3\text{--}10^6\,\mathrm{GeV}$. In this regime, the posterior becomes both tighter and less degenerate, enabling genuine two-parameter reconstruction. The most favorable region corresponds to signals with ${\rm SNR}\gtrsim 50$, while signals with ${\rm SNR}\sim 10$ can still be reconstructed effectively only in a narrower part of parameter space concentrated near $T_*\lesssim 10^5\,\mathrm{GeV}$. In terms of the observable spectrum, this weaker-signal region corresponds approximately to peak amplitudes $Ω_{\rm GW}^{\rm peak}h^2 \gtrsim 4\times10^{-11}$ and peak frequencies typically satisfying $f_p\lesssim 10\text{--}20\,{\rm mHz}$. Our results provide a quantitative reconstruction forecast for peaked domain-wall signals in the LISA band and a useful guide for particle-physics realizations of domain walls that predict peaked gravitational-wave spectra in the milli-Hz range.