Expanding RIFT
ORAL
Abstract
The RIFT parameter inference engine provides a low-coast, iterative, scalable method to infer parameters of gravitational wave sources. In this talk, we describe and assess several updates to RIFT, several of which have already been widely applied to interpret gravitational wave observations. We discuss challenges and opportunities in using RIFT within the larger software ecosystem of gravitational wave science, including low-latency analysis, multi-stage analyses with revised data and/or multiple models, and population inference. We comment on ongoing improvements being developed in preparation for the next observing run.
–
Presenters
-
Richard W O'Shaughnessy
Rochester Institute of Technology
Authors
-
Richard W O'Shaughnessy
Rochester Institute of Technology
-
Jacob A Lange
University of Texas at Austin
-
Jared Wofford
Rochester Institute of Technology
-
Daniel Wysocki
Rochester Institute of Technology
-
Elizabeth Champion
University of Rochester
-
Vera E Delfavero
Rochester Institute of Technology
-
Hannah M Gallagher
Rochester Institute of Technology