Calibrating semi-analytic VT's against reweighted injection VT's

Document #:

LIGO-T1800427-v2

Document type:

T - Technical notes

Abstract:

The semi-analytic approach to computing VT is advantageous in its speed and its ability to compute VT anywhere in parameter space. On the other hand, re-weighted injections are much more accurate, but they only compute an average VT over an assumed population, and Monte Carlo error prevents the estimate from being accurate when considering narrow populations where few/no injections lie.

We present a method and results of calibrating semi-analytic VT's against pyCBC reweighted injection VT's. The method relies on assuming a relationship between the injection and semi-analytic VT's that can be expressed via basis functions.

Files in Document:

• Slides to present (2018-10-01--wysocki-oshaughnessy-vt-calibration-slides.pdf, file is not accessible)
• Technical description of work, including example of how to use the results. (technical_notes.pdf, file is not accessible)

Other Files:

• Calibration results assuming a very simple model. (calibration_linear.json, file is not accessible)
• Calibration results assuming our most complicated current model, and what we currently recommend using. (calibration_quadratic.json, file is not accessible)
• Calibration results assuming the simplest possible correction -- included mainly for completeness. (calibration_scalar.json, file is not accessible)
• Example of using the results. (coeff_example.py, file is not accessible)

Topics:

• Compact Binaries
• Data Analysis
• Astrophysics / Multi-messenger

Authors:

• Daniel Wysocki
• Richard O'Shaughnessy

Referenced by:

• LIGO-T2000432-v1: Calibrating semi-analytic VT's to injections in O3a