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Modeling the Central Supermassive Black Holes Mass of Quasars via LSTM Approach | Seyed Sajad Tabasi
; Reyhaneh Vojoudi Salmani
; Pouriya Khaliliyan
; Javad T. Firouzjaee
; | Date: |
4 Jan 2023 | Abstract: | One of the fundamental questions about quasars is related to their central
supermassive black holes. The reason for the existence of these black holes
with such a huge mass is still unclear and various models have been proposed to
explain them. However, there is still no comprehensive explanation that is
accepted by the community. The only thing we are sure of is that these black
holes were not created by the collapse of giant stars, nor by the accretion of
matter around them. Moreover, another important question is the mass
distribution of these black holes over time. Observations have shown that if we
go back through redshift, we see black holes with more masses, and after
passing the peak of star formation redshift, this procedure decreases.
Nevertheless, the exact redshift of this peak is still controversial. In this
paper, with the help of deep learning and the LSTM algorithm, we tried to find
a suitable model for the mass of central black holes of quasars over time by
considering QuasarNET data. Our model was built with these data reported from
redshift 3 to 7 and for two redshift intervals 0 to 3 and 7 to 10, it predicted
the mass of the quasar’s central supermassive black holes. We have also tested
our model for the specified intervals with observed data from central black
holes and discussed the results. | Source: | arXiv, 2301.01459 | Services: | Forum | Review | PDF | Favorites |
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