Abstract

# Introduction

As we enter the advanced-detector era of ground-based gravitational-wave (GW) astronomy, it is critical that we understand the abilities and limitations of the analyses we are prepared to conduct. Of the many predicted sources of GWs, binary neutron-star (BNS) coalescences are paramount; their progenitors have been directly observed (Lorimer 2008), and the advanced detectors will be sensitive to their GW emission up to $$\sim 400~\mathrm{Mpc}$$ away (Abbott et al., 2016).

When analyzing a GW signal from a circularized compact binary merger, strong degeneracies exist between parameters describing the binary (e.g., distance and inclination). To properly estimate any particular parameter(s) of interest, the marginal distribution is estimated by integrating the joint posterior probability density function (PDF) over all other parameters. In this work, we sample the posterior PDF using software implemented in the LALInference library (Veitch et al., 2015). Specifically we use results from LALInfernce_nest (Veitch et al., 2010), a nest sampling algorithm (Skilling, 2006), and LALInference_MCMC (Christensen et al., 2004; Röver et al., 2006; van der Sluys et al., 2008), a Markov-chain Monte Carlo algorithm (chapter 12 Gregory, 2005).

Previous studies of BNS signals have largely assessed parameter constraints assuming negligible neutron-star (NS) spin, restricting models to nine parameters. This simplification has largely been due to computational constraints, but the slow spin of NSs in short-period BNS systems observed to date (e.g., Mandel et al., 2010) has also been used as justification. However, proper characterization of compact binary sources must account for the possibility of non-negligible spin; otherwise parameter estimates will be biased (Buonanno et al., 2009; Berry et al., 2015). This bias can potentially lead to incorrect conclusions about source properties and even misidentification of source classes.

Numerous studies have looked at the BNS parameter estimation abilities of ground-based GW detectors such as the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO; Aasi et al., 2015) and Advanced Virgo (AdV; Acernese et al., 2015) detectors. Nissanke et al. (2010); Nissanke et al. (2011) assessed localization abilities on a simulated non-spinning BNS population. Veitch et al. (2012) looked at several potential advanced-detector networks and quantified the parameter-estimation abilities of each network for a signal from a fiducial BNS with non-spinning NSs. Aasi et al. (2013) demonstrat