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Quantum Machine Learning

Quantum Software EngineeringSupremacy in Intelligent Robotics

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Authors: V. V. Korenkov, A. G. Reshetnikov, S.V. Ulyanov

Year

2020

Paper ID

5302

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

93

Citations

0

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.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2020 reference point for readers tracking recent quantum research.
  • A new approach for implementing quantum massive parallel computations is presented, using methods of circuit implementation of quantum algorithmic gates.

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References & Citation Signals

[1] DOI https://doi.org/10.37005/2071-9612-2020-4-135-146 [2] Publisher https://doi.org/10.37005/2071-9612-2020-4-135-146

Local Citation Graph (Related-Paper Links)

Current Paper #5302 #69034 Hardware-aware Low-latency Quan... #69025 Machine-Learning Optimization a... #69003 QBugLM: An Agentic Benchmarking... #68993 Tomography of quantum states wi...

External citation index: OpenAlex citation signal • updated 2026-06-17 05:10:56

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