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Population studies of Keplers multi-planet systems have revealed a surprising degree of structure in their underlying architectures. Information from a detected transiting planet can be combined with a population model to make predictions about the presence and properties of additional planets in the system. Using a statistical model for the distribution of planetary systems (He et al. 2020; arXiv:2007.14473), we compute the conditional occurrence of planets as a function of the period and radius of Kepler--detectable planets. About half ($0.52 pm 0.03$) of the time, the detected planet is not the planet with the largest semi-amplitude $K$ in the system, so efforts to measure the mass of the transiting planet with RV follow-up will have to contend with additional planetary signals in the data. We simulate RV observations to show that assuming a single--planet model to measure the $K$ of the transiting planet often requires significantly more observations than in the ideal case with no additional planets, due to the systematic errors from unseen planet companions. Our results show that planets around 10-day periods with $K$ close to the single--measurement RV precision ($sigma_{1,rm obs}$) typically require $sim 100$ observations to measure their $K$ to within 20% error. For a next generation RV instrument achieving $sigma_{1,rm obs} = 10$ cm/s, about $sim 200$ ($600$) observations are needed to measure the $K$ of a transiting Venus in a Kepler--like system to better than 20% (10%) error, which is $sim 2.3$ times as many as what would be necessary for a Venus without any planetary companions.
We present an extension of the formalism recently proposed by Pepper & Gaudi to evaluate the yield of transit surveys in homogeneous stellar systems, incorporating the impact of correlated noise on transit time-scales on the detectability of transits
Radial Velocity follow-up is essential to establish or exclude the planetary nature of a transiting companion as well as to accurately determine its mass. Here we present some elements of an efficient Doppler follow-up strategy, based on high-resolut
We infer the number of planets-per-star as a function of orbital period and planet size using $Kepler$ archival data products with updated stellar properties from the $Gaia$ Data Release 2. Using hierarchical Bayesian modeling and Hamiltonian Monte C
There is mounting evidence for the binary nature of the progenitors of gamma-ray bursts (GRBs). For a long GRB, the induced gravitational collapse (IGC) paradigm proposes as progenitor, or in-state, a tight binary system composed of a carbon-oxygen c
Close binaries suppress the formation of circumstellar (S-type) planets and therefore significantly bias the inferred planet occurrence rates and statistical trends. After compiling various radial velocity and high-resolution imaging surveys, we dete