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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

HAWKING-PENROSE BLACK HOLE MODEL. LARGE EMISSION REGIME

Author(s):
Pechersky, E. [1] ; Pirogov, S. [1] ; Yambartsev, A. [2]
Total Authors: 3
Affiliation:
[1] Inst Informat Transmiss Problems, 19 Bolshoj Karetny, Moscow 127994 - Russia
[2] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: REPORTS ON MATHEMATICAL PHYSICS; v. 87, n. 1, p. 1-14, FEB 2021.
Web of Science Citations: 0
Abstract

In this paper, we propose a stochastic version of the Hawking-Penrose black hole model. We describe the dynamics of the stochastic model as a continuous-time Markov jump process of quanta out and in the black hole. The average of the random process satisfies the deterministic picture accepted in the physical literature. Assuming that the number of quanta is finite the proposed Markov process consists of two componentes: the number of the quanta in the black hole and the amount of the quanta outside. The stochastic representation allows us to apply large deviation theory to study the asymptotics of probabilities of rare events when the number of quanta grows to infinity. The theory provides explicitly the rate functional for the process. Its infimum over the set of all trajectories leading to large emission event is attained on the most probable trajectory. This trajectory is a solution of a highly nonlinear Hamiltonian system of equations. Under the condition of stationarity of the fraction of quanta in the black hole, we found the most probable trajectory corresponding to a large emission event. (AU)

FAPESP's process: 17/10555-0 - Stochastic modeling of interacting systems
Grantee:Fabio Prates Machado
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 19/08557-0 - Percolation models on the causal random graph and market microstructure models
Grantee:Anatoli Iambartsev
Support Opportunities: Regular Research Grants