Commit bf7773b6 authored by Deep Chatterjee's avatar Deep Chatterjee

provide ref to source properties methods paper

parent 068b9154
Pipeline #130943 passed with stage
in 2 minutes and 29 seconds
......@@ -43,10 +43,21 @@ secondary mass satisfies :math:`m_2 \leq 3 M_{\odot}`.
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.
The way that these probabilities are calculated for preliminary alerts differs
for different search pipelines:
- For GstLAL, the probabilities consider the uncertainty in the
matched-filter estimates of the template parameters. The probabilities are
calculated using supervised machine learning on a feature space consisting of
the masses, spins, and :term:`SNR` of the best-matching template, described
in [#MLEMBright]_.
- For all other pipelines, the source property probabilities are reported as
exactly 0 or exactly 1 depending on whether the corresponding condition is
satisfied by the best-matching template. **In this case, these probabilities
do not capture uncertainty in the matched-filter estimates of the template
parameters, and should be interpreted with caution.**
.. include:: /journals.rst
......@@ -57,3 +68,7 @@ parameter estimation, updated properties are calculated from posterior samples.
.. [#DiskMass]
Foucart, F., Hinderer, T. & Nissanke, S. 2018, |PRD|, 98, 081501.
:doi:`10.1103/PhysRevD.98.081501`
.. [#MLEMBright]
Chatterjee, D., Ghosh, S., Brady, P. R., et al. 2020, |ApJ|,
:arXiv:`1911.00116`
......@@ -12,6 +12,9 @@ Version 17 (unreleased)
.. rubric:: Data Analysis
* Add the reference to the source properties methods paper.
Provide details on the cases where the above method is used.
.. rubric:: Alert Contents
.. rubric:: Sample Code
......
......@@ -19,6 +19,7 @@ capabilities
carée
Cascina
Caudill
Chatterjee
Chu
coalescences
comoving
......@@ -43,6 +44,7 @@ Fortran
Foucart
geocenter
Germain
Ghosh
glitching
gnomonic
Górski
......
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