TY - JOUR
T1 - Quasinormal modes of dS and AdS black holes
T2 - Feedforward neural network method
AU - OVGUN, ALI
AU - Sakalll, Izzet
AU - Mutuk, Halil
N1 - Publisher Copyright:
© 2021 World Scientific Publishing Company.
PY - 2021
Y1 - 2021
N2 - 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 well known: 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.
AB - 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 well known: 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.
KW - anti-de Sitter
KW - black hole
KW - de Sitter
KW - feedforward neural network
KW - Quasinormal modes
UR - http://www.scopus.com/inward/record.url?scp=85108193371&partnerID=8YFLogxK
U2 - 10.1142/S0219887821501541
DO - 10.1142/S0219887821501541
M3 - Article
AN - SCOPUS:85108193371
JO - International Journal of Geometric Methods in Modern Physics
JF - International Journal of Geometric Methods in Modern Physics
SN - 0219-8878
M1 - 2150154
ER -