Improving estimates of msini by expanding RV datasets

We develop new techniques for estimating the fractional uncertainty (F) in the projected planetary mass (msini) resulting from Keplerian fits to radial-velocity (RV) datasets of known Jupiter-class exoplanets. The techniques include (1) estimating the distribution of msini using Monte Carlo projection, (2) detecting and mitigating chimeras, a source of systematic error, and (3) estimating the reduction in the uncertainty in msini if hypothetical observations were made in the future. We demonstrate the techniques on a representative set of RV exoplanets, known as the Gang of 27, which are candidates for detection and characterization by a future astrometric direct imaging (ADI) mission. We estimate the improvements (reductions) in F due to additional, hypothetical RV measurements (RVMs) obtained in the future. We encounter and address a source of systematic error, chimeras, which can appear when multiple types of Keplerian solutions are compatible with a single dataset. We find that for n = 10 new, hypothetical RVMs obtained in the last planetary year before 2025, with the same accuracy as the current available RVMs, F is reduced by ~18%. From there, each plus-one increase in 2 log n - log q , where q is the factor by which RVM measurement uncertainty is reduced, further reduces F by factor 0.18.