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We study behaviour of ionized region of a Keplerian disk orbiting aSchwarzschild black hole immersed in an asymptotically uniform magnetic field.In dependence on the magnetic parameter ${\cal B}$, and inclination angle$\theta$ of the disk plane with respect to the magnetic field direction, thecharged particles of the ionized disk can enter three regimes: a) regularoscillatory motion, b) destruction due to capture by the magnetized black hole,c) chaotic regime of the motion. In order to study transition between theregular and chaotic type of the charged particle motion, we generate timeseries of the solution of equations of motion under various conditions, andstudy them by non-linear (box counting, correlation dimension, Lyapunovexponent, recurrence analysis, machine learning) methods of chaosdetermination. We demonstrate that the machine learning method appears to bethe most efficient in determining the chaotic region of the $\theta-r$ space.We show that the chaotic character of the ionized particle motion increaseswith the inclination angle. For the inclination angles $\theta \sim 0$ wholethe ionized internal part of the Keplerian disk is captured by the black hole.

Determination of chaotic behaviour in time series generated by charged particle motion around magnetized Schwarzschild black holes