Nii: a Bayesian orbit retrieval code applied to differential astrometry

Author:

Jin Sheng12ORCID,Ding Xiaojian3,Wang Su12ORCID,Dong Yao12,Ji Jianghui12ORCID

Affiliation:

1. CAS Key Laboratory of Planetary Sciences, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China

2. CAS Center for Excellence in Comparative Planetology, Hefei 230026, China

3. College of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210007, China

Abstract

ABSTRACT Here, we present an open source python-based Bayesian orbit retrieval code (Nii) that implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) strategy. Nii provides a module to simulate the observations of a space-based astrometry mission in the search for exoplanets, a signal extraction process for differential astrometric measurements using multiple reference stars, and an orbital parameter retrieval framework using APT-MCMC. We further verify the orbit retrieval ability of the code through two examples corresponding to a single-planet system and a dual-planet system. In both cases, efficient convergence on the posterior probability distribution can be achieved. Although this code specifically focuses on the orbital parameter retrieval problem of differential astrometry, Nii can also be widely used in other Bayesian analysis applications.

Funder

Chinese Academy of Sciences

National Natural Science Foundation of China

Youth Innovation Promotion Association CAS

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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