Analysing weak orbital signals in Gaia data

TL;DR

This paper investigates the detection of weak orbital signals in Gaia data, identifying anomalous orbits caused by measurement errors, and proposes a Bayesian method with a Copernican prior to improve orbit estimation.

Contribution

It introduces a Bayesian approach with a Copernican prior to mitigate anomalous orbit solutions in Gaia data analysis.

Findings

Anomalous orbits are linked to measurement errors in Gaia data.

A Bayesian method with a Copernican prior reduces anomalous orbit solutions.

The approach improves detection of weak orbital signals in astrometric binaries.

Abstract

Anomalous orbits are found when minimum-chi^{2} estimation is applied to synthetic Gaia data for orbits with astrometric signatures comparable to the single-scan measurement error (Pourbaix 2002). These orbits are nearly parabolic, edge-on, and their major axes align with the line-of-sight to the observer. Such orbits violate the Copernican principle (CPr) and as such could be rejected. However, the preferred alternative is to develop a statistical technique that incorporates the CPr as a fundamental postulate. This can be achieved in a Bayesian context by defining a Copernican prior. Pourbaix's anomalous orbits then no longer arise. Instead, the selected orbits have a somewhat higher chi^{2} but do not violate the CPr. The problem of detecting a weak additional orbit in an astrometric binary with a well-determined orbit is also treated.