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Published December 2020 | Accepted Version
Journal Article Open

Resonance Hopping Effect in the Neptune-planet Nine System

Abstract

The observed physical clustering of the orbits of small bodies in the distant Kuiper Belt (TNOs) has recently prompted the prediction of an additional planet in the outer solar system. Since the initial posing of the hypothesis, the effects of Planet Nine on the dynamics of the main cluster of TNOs—the objects anti-aligned with its orbit—have been well-studied. In particular, numerical simulations have revealed a fascinating phenomenon, referred to as "resonance hopping," in which these objects abruptly transition between different mean-motion commensurabilities with Planet Nine. In this work, we explore this effect in greater detail, with the goal of understanding what mechanism prompts the hopping events to occur. In the process, we elucidate the often underestimated role of Neptune scattering interactions, which leads to diffusion in the semimajor axes of these distant TNOs. In addition, we demonstrate that although some resonant interactions with Planet Nine do occur, the anti-aligned objects are able to survive without the resonances, confirming that the dynamics of the TNOs are predominantly driven by secular, rather than resonant, interactions with Planet Nine.

Additional Information

© 2020 The Astronomical Society of the Pacific. Received 2020 July 2; accepted 2020 October 1; published 2020 October 29. We thank Konstantin Batygin for useful discussions and suggestions. The computations for this work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant No. ACI-1548562. This research was done using resources provided by the Open Science Grid, which is supported by the National Science Foundation and the U.S. Department of Energy's Office of Science, through allocation number TG-AST190031. J.C.B. has been supported by the Heising–Simons 51 Pegasi b postdoctoral fellowship. Software: pandas (McKinney 2010), IPython (Pérez & Granger 2007), matplotlib (Hunter 2007), scipy (Jones et al. 2001), numpy (Oliphant 2006), Jupyter (Kluyver et al. 2016).

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August 20, 2023
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