Event Horizon Detection for Five Dimensional Stationary Black Holes

Abstract

n this thesis we show how to locate the event horizons for five dimensional (5D) stationary black holes. We present the Cartan algorithm in an arbitrary number of dimensions and apply it in 4D and 5D. To facilitate the algorithm in 5D, we classifiy the Weyl tensor using its boost weight decomposition. We also consider the Lorentz frame transformations in 5D. We present the algorithm explicitly for the 4D Kerr metric. For 5D, computations by hand are not feasible. Thus we show how to perform the algorithm on Maple 2016 and illustrate it with four 5D examples: the singly rotating Myers-Perry metric, the Kerr-NUTT-(Anti)-de Sitter metric, the Reissner-Nordstrom-(Anti)-de Sitter metric, and the singly rotating static black ring.