APS Logo

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