2023/05/30 by S.V. Ulyanov, Fabio Ghisi, Ulyanov, Sergey V. +5
Computer Science · #68T40 #81-05 #81-08 #93C85 #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2306.03233
openalex publication_date 2023/05/30 · openalex created_date 2023/06/09 · openalex updated_date 2026/07/28
There are important algorithms built upon a mixture of basic techniques described; for example, the Fast Fourier Transform (FFT) employs both Divide-and-Conquer and Transform-and-Conquer techniques. In this article, the evolution of a quantum algorithm (QA) is examined from an information theory viewpoint. The complex vector entering the quantum algorithmic gate - QAG is considered as an information source both from the classical and the quantum level. The analysis of the classical and quantum information flow in Deutsch-Jozsa, Shor and Grover algorithms is used. It is shown that QAG, based on superposition of states, quantum entanglement and interference, when acting on the input vector, stores information into the system state, minimizing the gap between classical Shannon entropy and quantum von Neumann entropy. Minimizing of the gap between Shannon and von Neumann entropies is considered as a termination criterion of QA computational intelligence measure.