Inference
=========

For :term:`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.

Classification
--------------

The classification consists of five numbers, summing to unity, that give the
probability that the source is either a :term:`BNS`, :term:`NSBH`, :term:`BBH`
merger, contains at least one :term:`MassGap <MassGap>` component, or is of
:term:`terrestrial` (i.e. a background fluctuation or a glitch) origin. See the
:ref:`figure in the alert contents section <classification-diagram>` for the
boundaries of the source classification categories in the :math:`(m_1, m_2)`
plane.

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 five 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 :doc:`search pipelines </analysis/searches>`.

For details, see [#Pastro]_, especially Section II E. and Equation 18 therein.

Properties
----------

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 :math:`m_2 \leq 3 M_{\odot}`.

**HasRemnant**: The probability that the source ejected a nonzero mass outside
the final remnant compact object. This is calculated using the disk mass
fitting formula from [#DiskMass]_ (Equation 4).

For preliminary estimates based on the matched-filter pipeline results, the
source properties are calculated using a supervised learning technique;
mass-dependent rates are the same as those used for the classification. For
parameter estimation, updated properties are calculated from posterior samples.

.. |prd| replace:: *Phys. Rev. D*

.. [#Pastro]
   Kapadia, S. J., Caudill, S., Creighton, J. D. E., et al., 2019.
   :arxiv:`1903.06881`

.. [#DiskMass]
   Foucart, F., Hinderer, T. & Nissanke, S. 2018, |prd|, 98, 081501.
   :doi:`10.1103/PhysRevD.98.081501`