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Home > Archives > Volume 20, No 8 (2022) > Article

DOI: 10.14704/nq.2022.20.8.NQ44634

The moment probability and impacts monitoring for electron cloud behavior of electronic computers by using quantum deep learning model

Dr. B.Gopi , J Logeshwaran, J Gowri, T. Kiruthiga

Abstract

Quantum theory is the most important part of quantum physics. In simple terms, this theory describes the movement, behavior and interaction of microscopic particles. The theory of quantum physics about the behavior and interaction of microscopic particles formed the basis for condensed matter physics, elementary particle physics, and high energy physics. Quantum theory explains to us the essence of many phenomena in our world - from the operation of electronic computers to the structure and behavior of celestial bodies. In this paper a quantum deep learning model was proposed to identify the moment of probability and impacts for electron cloud behavior of electronic computers. This method helps to understand the true essence of many things at the level of fundamental particles. In short, quantum field theory is a descriptive theory of microscopic particles, as well as their behavior in space, interactions with each other, and mutual transformations. This proposed model examines the behavior of quantum systems with so-called degrees of freedom. In a saturation tip the proposed model achieved 86.37% of the light interface management, 89.50% of the photon stream management, 89.52% of the superposition management, 91.30% of the quantum wave function management, 88.61% of the quantities management and 90.39% of the Experimental quantum structure management.

Keywords

Quantum theory, Quantum theory, microscopic particles, computers, deep learning

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