MOTS Finder version 1.5

• Main Authors: Pook-Kolb, Daniel, Birnholtz, Ofek, Booth, Ivan, Hennigar, Robie A., Jaramillo, José Luis, Krishnan, Badri, Schnetter, Erik, Zhang, Victor
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2021
• Subjects: North Pole; South pole
• Online Access: https://doi.org/10.5281/zenodo.4687700

Main changes in this update include: Add an implementation of a shooting method for finding MOT(O)S (see the new tutorial on the shooting method) Enable the representation (and search) of toroidal MOTSs Implement predicting the MOTS location by tracking either the north pole, south pole, locally minimal x-location (useful for neck-like features) and coordinate center (default) Smaller changes: Add a smarter line search. To use it, add the <code>step_mult="auto"</code> option to the <code>find_mots()</code> call (or to the configuration object). New example metric for a slice of Schwarzschild in Painleve-Gullstrand coordinates Make computing properties more robust for initial data Allow most properties to be computed for toroidal MOTSs New MOTS properties: <code>"ricci_difference_integral"</code>, <code>"ricci_interp"</code> (see the documentation of the <code>axisym.trackmots.props.compute_props()</code> function for details) New MOTT properties via functions of the form <code>"compute_*"</code> in module <code>axisym.trackmots.props</code> Optionally save all interim Newton steps Many small plotting optimizations and options Fix compatibility with more recent Python and SciPy/NumPy versions Research at Perimeter Institute is supported in part by the Government of Canada through the Department of Innovation, Science and Economic Development Canada and by the Province of Ontario through the Ministry of Colleges and Universities. We also thank the French EIPHI Graduate School (ANR-17-EURE-0002) and the Spanish FIS2017-86497-C2-1 project (with FEDER contribution) for support. IB was supported by the Natural Science and Engineering Research Council of Canada Discovery Grant 2018-0473. The work of RAH was supported by the Natural Science and Engineering Research Council of Canada through the Banting Postdoctoral Fellowship program.