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Catastrophic tidal disruption of heterogeneous rubble piles: a tale of two regimes

John Wimarsson, Eric Frizzell, Martin Jutzi, Fabio Ferrari

astro-ph.EParXiv:2608.27131

Abstract

The way a rubble-pile body deforms or disrupts under the influence of tidal forces can be directly tied to its internal strength and configuration. Computational modelling of such tidal disruption events provides an indispensable numerical laboratory for constraining the origin and evolution of small bodies in the Solar System. A majority of previous investigations into tidal disruption of rubble piles have mainly considered progenitors consisting of same-sized, spherical elements. Our study attempts to fill the existing gap in studies analysing the effect of aggregate heterogeneity on tidal disruption outcomes by varying element shape and size frequency distribution. Such heterogeneities have been shown to strongly influence rubble pile dynamics for impacts and rotational failure. We performed numerical simulations of parabolic and hyperbolic tidal encounters between six unique rubble-pile progenitors and the Earth using the N-body code GRAINS. The resulting mass distributions of generated fragments and tidal chain morphologies for the different progenitors were further tied to the internal strength of rubble piles. Two regimes of tidal disruption are identified. In the first regime, closest to the planet, the dynamic evolution is dominated by tidal forces. Here, particle shape, size distribution and resolution appear to have little importance for the resulting distribution of fragment masses. In the second, shear-controlled regime, the internal structure of the progenitor begins to strongly influence the resulting tidal chain morphology and properties of the surviving fragments. Heterogeneity originating from the shape and size frequency distribution of elements in rubble pile models has a substantial effect on the outcomes of tidal disruption events. These parameters must be carefully taken into account when future studies attempt to tie results from numerical models to observations.

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