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Quantum Entanglement and Quantum Algorithms

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".

Deadline for manuscript submissions: closed (30 December 2025) | Viewed by 1431

Special Issue Editors


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Guest Editor
Department of Computer Science, University of Hong Kong, Hong Kong, China
Interests: quantum simulation; quantum computing; resource theory; self-testing quantum information; entanglement detection

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Guest Editor
Department of Computer Science, University of Hong Kong, Hong Kong, China
Interests: quantum entanglement theory; quantum error-correcting codes; quantum states discrimination; Bell nonlocality; unextendible product bases

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Guest Editor
School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China
Interests: quantum entanglement; quantum coherence; resource theory; blind quantum computation; machine learning

Special Issue Information

Dear Colleagues,

The field of quantum information science has seen tremendous progress over the last several years, with advances in both hardware development and novel algorithms. Quantum entanglement and algorithms, in particular, represent some of the most captivating and rapidly advancing frontiers in modern physics and computer science, the former being the cornerstone of many quantum technologies, including quantum computing, cryptography, and communication.

This Special Issue seeks to explore quantum entanglement, quantum algorithms, and their connections, focusing on the role of entanglement in quantum algorithms and how it contributes to quantum advantages. Quantum entanglement is a critical resource that enables quantum computers to perform complex computations more efficiently than classical computers. Understanding the intricate relationship between entanglement and algorithmic performance is essential for advancing both theoretical and practical aspects of quantum computing.

Original unpublished papers and review articles are invited on the following topics: (1) advances in generating, manipulating, and detecting quantum entanglement, (2) novel quantum algorithms and their reliance on entanglement, (3) applications of entanglement in quantum error correction, teleportation, and communication, (4) the role of entanglement in achieving quantum computational advantage, (5) quantum networks and distributed quantum computing leveraging entanglement, and (6) investigations into the scalability and robustness of entanglement in various quantum hardware architectures.

Dr. Qi Zhao
Dr. Fei Shi
Dr. Banghai Wang
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • quantum entanglement
  • quantum algorithms
  • quantum computing
  • quantum simulation
  • quantum teleportation
  • quantum error correction
  • entanglement detection
  • quantum networks
  • quantum computational advantage
  • hybrid quantum-classical algorithms

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Published Papers (1 paper)

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Research

17 pages, 3006 KB  
Article
A New Quantum Video Processing Algorithm Based on the NEQR Technique
by Adrian Prodan, Alexandru-Gabriel Tudorache and Vasile Manta
Entropy 2026, 28(2), 168; https://doi.org/10.3390/e28020168 - 1 Feb 2026
Viewed by 637
Abstract
The main goal of this paper is to present a new way of processing a video file using a combination of multiple quantum methods. The design is built upon the novel enhanced quantum representation technique, NEQR, which is then expanded using ideas such [...] Read more.
The main goal of this paper is to present a new way of processing a video file using a combination of multiple quantum methods. The design is built upon the novel enhanced quantum representation technique, NEQR, which is then expanded using ideas such as image segmentation, implemented with the help of one or multiple comparators, binarization and cycle shift. This approach allows us to process all frames in parallel according to the desired parameters—one or more thresholds. A demonstration circuit for the proposed design, using a couple of frames, that sums together all the concepts is implemented using the Python programming language and Qiskit open-source framework, made available by IBM. The circuits are analyzed in the experimental section, using the Simulator component and configured using the noise properties of real devices, where we present different relevant metrics obtained by processing the simulation results. Full article
(This article belongs to the Special Issue Quantum Entanglement and Quantum Algorithms)
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