Role of dark matter haloes on the predictability of computed orbits

Abstract

Aims. The predictability of a system indicates how often a computed orbit is close to a real orbit of the system, independent of its stability or chaotic nature. We explore the effect of dark halo shapes on the predictability of computed orbits in a Milky Way mean field model. We also present the sources for the low predictability found in some orbits. Methods. We derived a predictability index from the distributions of the finite-time Lyapunov exponents. We computed those distributions and analysed the evolution of their shapes when the finite-time interval sizes are varied. The predictability index can be computed using the interval lengths corresponding to the timescales when the flow dynamics leaves the local regime and enters the global regime. Results. These analyses reveal that not all chaotic orbits have the same predictability and that the predictability of some orbits is more affected than others by the orientation and shape of the dark halo. We show that the lowest predictability may be linked to strong unstable dimension variability.

Effects of chaos on the detectability of stellar streams

“…Thus, we can apply tools and theorems that were built in the past for Hamiltonian systems with few degrees of freedom. Among them, chaos theory (Contopoulos 2002) is a well developed branch of study that has played a big role in many astrophysical theories, such as in Solar System dynamics (Morbidelli 2010;Tsiganis et al 2005), multi-planet extrasolar systems (Martí et al 2013;Beaugé et al 2012), barred spiral galaxies (Contopoulos & Harsoula 2012;Voglis et al 2006) and galaxy haloes (Zhu et al 2017;Vallejo & Sanjuan 2016;Carpintero et al 2014;Efthymiopoulos et al 2007;Siopis & Kandrup 2000;Valluri & Merritt 1998;Merritt & Valluri 1996). And the field of stellar streams belongs to this group since the early works of Hunter (2005), Fux (2001) and Dehnen (2000).…”