Bayesian Inference of Gravity through Realistic 3D Modeling of Wide Binary Orbits: General Algorithm and a Pilot Study with HARPS Radial Velocities

When 3D relative displacement r and velocity v between the pair in a gravitationally-bound system are precisely measured, the six measured quantities at one phase can allow elliptical orbit solutions at a given gravitational parameter G. Due to degeneracies between orbital-geometric parameters and G, individual Bayesian inferences and their statistical consolidation are needed to infer G as recently suggested by a Bayesian 3D modeling algorithm. Here I present a fully general Bayesian algorithm suitable for wide binaries with two (almost) exact sky-projected relative positions (as in the Gaia data release 3) and the other four sufficiently precise quantities. Wide binaries meeting the requirements of the general algorithm to allow for its full potential are rare at present, largely because the measurement uncertainty of the line-of-sight (radial) separation is usually larger than the true separation. As a pilot study, the algorithm is applied to 32 Gaia binaries for which precise HARPS radial velocities are available. The value of Γ≡ log₁₀√G/GN (where GN is Newton's constant) is -0.002-0.018+0.012 supporting Newton for a combination of 24 binaries with Newtonian acceleration gN>10⁻⁹m s⁻², while it is Γ=0.063-0.047+0.058 or 0.134-0.040+0.050 for 7 or 8 binaries with gN<10⁻⁹m s⁻² (depending on one system) showing tension with Newton. The Newtonian ``outlier'' is at the boundary set by the Newtonian escape velocity, but can be consistent with modified gravity. The pilot study demonstrates the potential of the algorithm in measuring gravity at low acceleration with future samples of wide binaries.