PROBABILISTIC FORECASTING OF THE MASSES AND RADII OF OTHER WORLDS

Mass and radius are two of the most fundamental properties of an astronomical object. Increasingly, new planet discoveries are being announced with a measurement of one of these quantities, but not both. This has led to a growing need to forecast the missing quantity using the other, especially when predicting the detectability of certain follow-up observations. We present an unbiased forecasting model built upon a probabilistic mass-radius relation conditioned on a sample of 316 well-constrained objects. Our publicly available code, Forecaster, accounts for observational errors, hyper-parameter uncertainties, and the intrinsic dispersions observed in the calibration sample. By conditioning our model on a sample spanning dwarf planets to late-type stars, Forecaster can predict the mass (or radius) from the radius (or mass) for objects covering nine orders of magnitude in mass. Classification is naturally performed by our model, which uses four classes we label as Terran worlds, Neptunian worlds, Jovian worlds, and stars. Our classification identifies dwarf planets as merely low-mass Terrans (like the Earth) and brown dwarfs as merely high-mass Jovians (like Jupiter). We detect a transition in the mass-radius relation at 2.0(-0.6)(+0.7) M-circle plus, which we associate with the divide between solid, Terran worlds and Neptunian worlds. This independent analysis adds further weight to the emerging consensus that rocky super-Earths represent a narrower region of parameter space than originally thought. Effectively, then, the Earth is the super-Earth we have been looking for.