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Atomic Fisher information and entanglement forecasting for quantum system based on artificial neural network and time series model
Author(s) -
Abdelkhalek S.,
Alhag Azhri,
Ragab Mahmoud,
AboDahab S. M.,
Algarni Ali,
Ahmad Hijaz
Publication year - 2021
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.26446
Subject(s) - statistical physics , fisher information , quantum entanglement , qubit , entropy (arrow of time) , quantum information , computer science , quantum mechanics , quantum , physics , machine learning
In this article, we apply a statistical model for forecasting the quantum entanglement between a two‐qubit and optical field in binomial distribution. We explore the link between the atomic Fisher information, quantum entropy, and the statistical properties of the field. The qubit‐qubit entanglement is investigated through concurrence during the interaction time. The dynamics of the statistical quantities will be forecasted using the time series and neural network models. The effect of the field distribution parameter (number of successes) is examined by the time series models and artificial neural network. We compare the accuracy of both modes from the perspective of the dynamic of the quantum entropy and atomic Fisher information. A statistical description for the data has been obtained and is discussed to show the statistical technique analysis the data of statistical quantities. The results obtained have several applications and are related with quantum statistics and quantum information processing.