Quasinormal modes of dS and AdS black holes: Feedforward neural network method

Abstract

network method Ali Övgün,1, ∗ İzzet Sakallı,1, † and Halil Mutuk2, ‡ 1Physics Department, Eastern Mediterranean University, Famagusta, 99628 North Cyprus, via Mersin 10, Turkey. 2Physics Department, Faculty of Arts and Sciences, Ondokuz Mayis University, 55139, Samsun, Turkey. (Dated: May 18, 2021) Abstract In this paper, we show how the quasinormal modes (QNMs) arise from the perturbations of massive scalar fields propagating in the curved background by using the artificial neural networks. To this end, we architect a special algorithm for the feedforward neural network method (FNNM) to compute the QNMs complying with the certain types of boundary conditions. To test the reliability of the method, we consider two black hole spacetimes whose QNMs are wellknown: 4D pure de Sitter (dS ) and five-dimensional Schwarzschild anti-de Sitter (AdS ) black holes. Using the FNNM, the QNMs of are computed numerically. It is shown that the obtained QNMs via the FNNM are in good agreement with their former QNM results resulting from the other methods. Therefore, our method of finding the QNMs can be used for other curved spacetimes that obey the same boundary conditions.