Data-driven exploration of the neutron $^3\text{P}_2$ pairing gap using Cassiopeia A neutron star observational data: Direct $\chi^2$ minimization
Abstract
The rapid cooling observed in the Cassiopeia~A neutron star (Cas~A NS) is one of the most stringent tests for neutron-star cooling theory. While Cooper-pair breaking and formation (PBF) neutrino emission is a leading candidate, uncertainties remain regarding the PBF efficiency factor and the neutron pairing gap. This work explores in a data-driven manner how the optimized gap shape responds to variations of the PBF emissivity parameter within a fixed cooling setup. We introduce a novel gap parametrization, in which each parameter carries direct physical meaning and controls the gap amplitude, peak location, width, and asymmetry. Using a Fortran-based cooling code and the BSk24 equation of state, we perform parameter-space exploration guided by the Cas~A NS data. Global optimization is carried out with Optuna's tree-structured Parzen estimator, followed by local refinement using the Nelder--Mead method. The optimized solutions yield physically reasonable gaps with peak amplitudes --. Although the multi-objective formulation explores the parameter space more broadly, the single-objective -only optimization achieves the lowest . For , increasing drives the optimized gap and critical-temperature profiles toward smoother and more localized shapes, improving consistency with the observed trend. Models with reproduce the decline rate within the confidence interval, whereas the baseline case lies near the level. Our results suggest larger effective PBF emissivities than the baseline estimate, although robust constraints on require future Bayesian inference including uncertainties in mass, envelope composition, equation of state, pairing microphysics, and age offset. (Shortened due to the arXiv abstract length limit.)
Keywords
Cite
@article{arxiv.2510.20353,
title = {Data-driven exploration of the neutron $^3\text{P}_2$ pairing gap using Cassiopeia A neutron star observational data: Direct $\chi^2$ minimization},
author = {Yoonhak Nam and Kazuyuki Sekizawa},
journal= {arXiv preprint arXiv:2510.20353},
year = {2026}
}
Comments
19 pages, 13 figures, 3 tables; v2 - Version accepted for publication in Physical Review C