Vetting quark-star models with gravitational waves in the hierarchical Bayesian framework

Kavli Affiliate: Lijing Shao

| First 5 Authors: Ziming Wang, Yong Gao, Dicong Liang, Junjie Zhao, Lijing Shao

| Summary:

The recent discovery of gravitational waves (GWs) has opened a new avenue for
investigating the equation of state (EOS) of dense matter in compact stars,
which is an outstanding problem in astronomy and nuclear physics. In the
future, next-generation (XG) GW detectors will be constructed, deemed to
provide a large number of high-precision observations. We investigate the
potential of constraining the EOS of quark stars (QSs) with high-precision
measurements of mass $m$ and tidal deformability $Lambda$ from the XG GW
observatories. We adopt the widely-used bag model for QSs, consisting of four
microscopic parameters: the effective bag constant $B_{rm eff}$, the
perturbative quantum chromodynamics correction parameter $a_4$, the strange
quark mass $m_s$, and the pairing energy gap $Delta$. With the help of
hierarchical Bayesian inference, for the first time we are able to infer the
EOS of QSs combining multiple GW observations. Using the top 25 loudest GW
events in our simulation, we find that, the constraints on $B_{rm eff}$ and
$Delta$ are tightened by several times, while $a_4$ and $m_s$ are still poorly
constrained. We also study a simplified 2-dimensional (2-d) EOS model which was
recently proposed in literature. The 2-d model is found to exhibit significant
parameter-estimation biases as more GW events are analyzed, while the predicted
$m$-$Lambda$ relation remains consistent with the full model.

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