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Artificial Intelligence Advances

Quantum Fast Algorithm Computational Intelligence PT I: SW / HW Smart Toolkit

Sergey Victorovich Ulyanov

Published Jul 19, 2019• 18 citations
Publisher

Abstract

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.

DOI
10.30564/aia.v1i1.619

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A new approach to a circuit implementation design of quantum algorithmic gates for the realization of 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 to be performed. SW&HW support toolkit of supercomputing accelerator of quantum algorithm simulation on classical computer described. The method for performing Grover's interference without product operations introduced. New quantum genetic and quantum fuzzy inference algorithm gate design for intelligent robotic control considered. Quantum software engineering supremacy on Benchmarks demonstrated.
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.
The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered. Background of the model is a new model of quantum inference based on quantum genetic algorithm. Quantum genetic algorithm applied on line for the quantum correlation’s type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing. Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures (as new design laws) discussed in Part I. The smart control design with guaranteed achievement of these tradeoff interrelations is main goal for quantum self-organization algorithm of imperfect KB. Sophisticated synergetic quantum information effect in Part I (autonomous robot in unpredicted control situations) and II (swarm robots with imperfect KB exchanging between “master - slaves”) introduced: a new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation. Within the toolkit of classical intelligent control, the achievement of the similar synergetic information effect is impossible. Benchmarks of intelligent cognitive robotic control applications considered.
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
Strategy of intelligent cognitive control systems of ill-defined control objects based on quantum and soft computing presented. Quantum self-organization knowledge base synergetic effect extracted from intelligent fuzzy controller’s imperfect knowledge bases described. That technology improved of robustness of intelligent cognitive control systems in hazard control situations described with different types of robot cooperation. Examples demonstrated the introduction of quantum fuzzy inference gate design as prepared programmable algorithmic solution for board embedded control systems. The physical interpretation of the process of controlling self-organization at the quantum level is discussed on the basis of quantum information-thermodynamic models of exchange and extraction of quantum (hidden) valuable information from/between classical particle trajectories in the "swarm of interacting particles" model. The main physical and information-thermodynamic aspects of the model of quantum intelligent control of classical control objects are discussed and described. An approach is considered for constructing reference control models based on new laws of quantum deep machine learning applying neural networks in mega-science project NICA.