On the Proper 3D Modeling of Orbits in Wide Binary Gravity Tests
A gravitationally-bound system of wide binary stars with precise 3D relative displacement $\mathbf{r}$ and velocity $\mathbf{v}$ can allow a Keplerian orbit reconstruction for an assumed gravitational parameter $G$. A sufficiently large sample of such systems can also be used to directly infer $G$ specific to the sample. A recent study argued that treating the semi-major axis ($a$) explicitly free with an empirical prior imposed on it can dramatically change the inference of $G$ in the Chae et al. sample of 36 wide binaries. Here we introduce and test a Bayesian Markov chain Monte Carlo algorithm that allows $a$ to be explicitly free (with or without a prior on $a$), and find using the $α$-Cen AB - proxima system and the Chae et al. sample that the explicit-$a$ algorithm with an observational constraint is fully equivalent to the implicit-$a$ algorithm with an internal consistency relation involving the sky-projected separation $s$. For the $α$-Cen AB - proxima system, we present orbits in Milgromian (MOND) as well as Newtonian gravity models. We show that a recent claim of Newtonian gravity from the Chae et al. sample is a consequence of a fatal error in the code or arbitrarily enlarged errors. We discuss how wide binaries can be properly analyzed and modeled to probe gravity at low acceleration and test gravity models, including the necessity of deriving individual-specific parameters, the importance of follow-up observations for anomalous systems, and the relevance of Bayesian MCMC approaches.