Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Computational Physics
Simulation of entanglement generation and variation in quantum computation
Journal of Computational Physics
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Quantum information theory is the new field of physics and electrical engineering that arose from the application of fundamental physics concepts in communications and computing. In this paper, aiming to calculate some properties of quantum communication systems and the quantum entanglement measure, for C2 ⊗ C2 systems, based on relative entropy, two numerical algorithms are presented. The first one is based on the codification of the possible solution in a binary string and in the application, in that string, of an assembly algorithm, such as one used in DNA construction. The second one is the construction of a genetic algorithm where a string of density matrices and quantum gates in the reproduction stage are used. Both algorithms are used in situations where the best solution needs to be found. Numerical simulations are presented and the advantages and disadvantages of the algorithms are discussed.