Hidden Worlds: Dynamical Architecture Predictions of Undetected Planets in Multi-planet Systems and Applications to TESS Systems

TL;DR

This paper introduces a statistical model to predict undetected planets in multi-planet systems, enhancing our understanding of planetary architectures and guiding future observations, especially in TESS systems.

Contribution

The paper presents a novel population-based model capable of predicting multiple undetected planets, including non-transiting ones, in multi-planet systems.

Findings

Model's orbital period predictions are robust to perturbations of a few percent.

Application to TESS systems yields prioritized targets for follow-up searches.

Predictions improve detection strategies for hidden exoplanets.

Abstract

Multi-planet systems produce a wealth of information for exoplanet science, but our understanding of planetary architectures is incomplete. Probing these systems further will provide insight into orbital architectures and formation pathways. Here we present a model to predict previously undetected planets in these systems via population statistics. The model considers both transiting and non-transiting planets, and can test the addition of more than one planet. Our tests show the model's orbital period predictions are robust to perturbations in system architectures on the order of a few percent, much larger than current uncertainties. Applying it to the multi-planet systems from TESS provides a prioritized list of targets, based on predicted transit depth and probability, for archival searches and for guiding ground-based follow-up observations hunting for hidden planets.