Year: 2024
Type: article
Abstract: orbitize! is a package for Bayesian modeling of the orbital parameters of resolved binary objects from time series measurements.It was developed with the needs of the high-contrast imaging community in mind, and has since also become widely used in the binary star community.A generic orbitize!use case involves translating relative astrometric time series, optionally combined with radial velocity or astrometric time series, into a set of derived orbital posteriors.This paper is published alongside the release of orbitize!version 3.0, which has seen significant enhancements in functionality and accessibility since the release of version 1.0 (Blunt et al., 2020).
DOI: 10.21105/joss.06756
Authors: Sarah Blunt, Jason Jinfei Wang, Lea Hirsch, Roberto Tejada, Vighnesh Nagpal, Tirth Dharmesh Surti, Sofia Covarrubias, Thea McKenna, Rodrigo Ferrer Chávez, Jorge Llop-Sayson, Mireya Arora, Amanda Chavez, Devin Cody, Saanika Choudhary, Adam J. R. W. Smith, William Balmer, Tomas Stolker, Hannah Gallamore, Clarissa R. Do Ó, Eric L. Nielsen, Robert J. De Rosa
Institutions: Northwestern University, California Institute of Technology, University of Toronto, Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Jet Propulsion Laboratory, University of Michigan, Google (United States), New Mexico State University, Johns Hopkins University, Leiden University, Leiden Observatory, European Southern Observatory, European Southern Observatory
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: diamond
Awards: G2678255669, G2909838935
OpenAlex ID: W4402708153