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System Analysis in Science and Education

Quantum Software EngineeringSupremacy in Intelligent Robotics

V. Korenkov, Andrey G. Reshetnikov, Sergey Victorovich Ulyanov

Published Dec 30, 2020• 0 citations
Publisher

Abstract

A new approach for implementing quantum massive parallel computations is presented, using methods of circuit implementation of quantum algorithmic gates. Methods for designing fast quantum operators such as superposition, entanglement, andinterference are considered. The presented methodsallow you to reduce the number of actions that must be performed. The implementation is presented as a support tool for SW&HW supercomputer accelerator for modeling quantum algorithms. In particular, a newquantum-genetic and quantum-fuzzy inference algorithm for intelligent robotic control has been implemented. Also, a new method for performing Grover's inference without operations with the productis presented.

DOI
10.37005/2071-9612-2020-4-135-146

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A new approach to a circuit implementation design of quantum algorithm gates for quantum massive parallel fast computing implementation is presented. The main attention is focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed. SW & HW support sophisticated smart toolkit of supercomputing accelerator of quantum algorithm simulation is described. The method for performing Grover’s interference without product operations as Benchmark introduced. The background of developed information technology is the "Quantum / Soft Computing Optimizer" (QSCOptKBTM) software based on soft and quantum computational intelligence toolkit. Quantum genetic and quantum fuzzy inference algorithm gate design considered. The quantum information technology of imperfect knowledge base self-organization design of fuzzy robust controllers for the guaranteed achievement of intelligent autonomous robot the control goal in unpredicted control situations is described.
Principles and methodologies of quantum algorithmic gates design for master course and PhD students in computer science, control engineering and intelligent robotics described. The possibilities of quantum algorithmic gates simulation on classical computers discussed. Applications of quantum gate of nanotechnology in intelligent quantum control introduced. Anew approach to a circuit implementation design of quantum algorithm gates for fast quantum massive parallel computing presented. The main attention focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference, which are in general time-consuming operations due to the number of products that have performed. SW & HW support sophisticated smart toolkit of supercomputing accelerator of quantum algorithm simulation on small quantum programmable computer algorithm gate (that can program in SW to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates) described. As example, the method for performing Grover’s interference operator without product operations introduced. The background of developed information technology is the "Quantum / Soft Computing Optimizer" (QSCOptKBTM) SW based on soft and quantum computational intelligence toolkit.
Principles and methodologies of quantum algorithmic gate-based design on small quantum computer described. The possibilities of quantum algorithmic gates simulation on classical computers discussed. A new approach to a circuit implementation design of quantum algorithm gates for fast quantum massive parallel computing presented. SW & HW support sophisticated smart toolkit of supercomputing accelerator of quantum algorithm simulation on small quantum programmable computer algorithm gate (that can program in SW to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates) described
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This paper introduces the first implementation of fuzzy rule-based systems for quantum computers. Quantum computers are incredibly powerful machines that use principles of quantum mechanics, such as superposition and entanglement, to process information in a more efficient way than classical computers. Currently, several companies and academic research groups are focusing their efforts on the development of quantum algorithms for artificial intelligence but, so far, no significant contribution in the area of the fuzzy inference for quantum machines has been proposed. This article bridges this gap by introducing a quantum implementation of a fuzzy rule-based system through a synergistic usage of the well-known Grover's algorithm and look-up tables. As shown by a case study, the behaviour of the quantum implementation of the fuzzy rule-based system is comparable to its classical version, but with a quadratic asymptotic speed-up than a fuzzy rule-based system implemented by a classical look-up table.