For CBC events, we calculate a number of quantities that are inferred from the signal. In preliminary alerts, these quantities are based on the candidate significance and the matched-filter estimates of the source parameters. Once parameter estimation has been completed, updated values will be provided based on samples drawn from the posterior probability distribution.


The classification consists of four numbers, summing to unity, that give the probability that the source is either a BNS, NSBH, BBH merger, or is of Terrestrial (i.e. a background fluctuation or a glitch) origin. See the figure in the alert contents section for the boundaries of the source classification categories in the \((m_1,m_2)\) plane. The boundary between NSs and BHs is set to \(3 M_{\odot}\).

This assumes that terrestrial and astrophysical events occur as independent Poisson processes. A source-dependent weighting of matched-filter templates is used to compute the mean values of expected counts associated with each of these four categories. The mean values are updated weekly based on observed matched-filter count rates. They are then used to predict the category for new triggers uploaded by search pipelines.

For details, see [1], especially Section II E. and Equation 18 therein.


The source properties consist of a set of numbers, each between zero and unity, that give the probabilities that the source satisfies certain conditions. These conditions are:

HasNS: At least one of the compact objects in the binary (that is, the less massive or secondary compact object) has a mass that is consistent with a neutron star. Specifically, we define this as the probability that the secondary mass satisfies \(m_2 \leq M_{\mathrm{max}}\), where \(M_{\mathrm{max}}\) is the maximum mass allowed by the neutron star equation of state (EOS). Several NS EOSs are considered and the value is marginalized by weighting using the Bayes factors reported in [2].

HasRemnant: The source formed a nonzero mass outside the final remnant compact object. Specifically, the probability is calculated using the disk mass fitting formula from [3] (Equation 4). Several neutron star EOSs are considered to compute the remnant mass. The value is marginalized by weighting based on Bayes factors in reference mentioned above.

HasMassGap: At least one of the compact objects in the binary has a mass in the hypothetical “mass gap” between neutron stars and black holes, defined here as \(3 M_{\odot} \leq m \leq 5 M_{\odot}\).

The mass values mentioned in this section are source-frame mass. The value reported in the preliminary alert is calculated using a supervised machine learning classifier on a feature space consisting of the masses, spins, and SNR of the best-matching template, described in [4]. This is to account for the uncertainty in the reported template parameters compared to the true parameters. The value reported in the update alerts uses the online parameter estimation to compute the value.