Special Issue "Quantum Computation and Its Applications"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Quantum Electronics".

Deadline for manuscript submissions: 15 December 2023 | Viewed by 593

Special Issue Editors

Department of Digital Systems, Faculty of Technology, University of Thessaly, 415000 Larissa, Greece
Interests: quantum computing (QML, QKD, post-quantum cryptography); parallel and distributed systems; computational clouds
Special Issues, Collections and Topics in MDPI journals
Department of Digital Systems, School of Technology, University of Thessaly, Geopolis, 41500 Larissa, Greece
Interests: wireless sensor networks; networks; wireless communications; cross-layer optimization; quantum communications; security and IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Quantum computers (QCs) base their computing functionalities on the phenomena and properties of quantum mechanics (QM) theories, such as superposition and entanglement. When super-powerful quantum computing devices, with large numbers of qubits, become reality, it will shake our world! A large variety of applications will appear, ranging from cryptography to chemistry, medicine and pharmacology. Additionally, powerful, quantum machine learning algorithms will be proposed and applied to solve complex, heterogeneous and multi-dimensional data, and the majority of scientific fields will flourish. In particular, within days or months QCs will propose solutions for vaccines and drugs, which currently take years to discover and test. Additionally, cryptography and current cryptographic algorithms will no longer have power. Codes and passwords will break within seconds. In addition, chemical, healthcare and drug development industries, security and so on, will take advantage of the new and revolutionary computing era. Therefore, new meta-quantum cryptographic algorithms will have to be devised and take the lead. However, the problem of QC reliability remains, especially as qubit number and circuit size escalate.

In this Special Issue, research works as well as practical applications are of interest. We invite authors from universities and research centers as well as independent researchers to contribute. The Special Issue will mainly focus on high-quality research works focused on, but not limited to, one or more of the following topics:

  • Quantum computing research and applications on chemistry and material science, blockchain and cybersecurity, logistics, healthcare, agriculture, finance, and so on;
  • Quantum machine learning (algorithms, applications, and techniques);
  • Quantum processing units (QPUs) and error correction;
  • Quantum drug development;
  • Parallel computations on quantum computing devices;
  • Algorithms and quantum computing in the NISQ (noisy intermediate-scale quantum) era;
  • Quantum key distribution;
  • Post-quantum cryptography;
  • Quantum annealing and adiabatic quantum computing;
  • Quantum telecommunications;
  • Quantum networking and quantum internet;
  • Benchmarking quantum computing devices;
  • Quantum computing and optimization (i.e., modelling and simulation);
  • Quantum information theory (i.e., entropy, information channels);
  • Classical shadows;
  • Future trends of quantum computing;
  • Quantum applications (i.e., medical, defense, energy system, smart grid etc.).

Prof. Dr. Ilias K. Savvas
Dr. Apostolos Xenakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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.



  • quantum key distribution
  • post-quantum cryptography
  • classical shadows
  • quantum telecommunications and networking
  • quantum processing units (QPUs) and error correction
  • quantum algorithms

Published Papers (1 paper)

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Unlocking the Potential of Quantum Machine Learning to Advance Drug Discovery
Electronics 2023, 12(11), 2402; https://doi.org/10.3390/electronics12112402 - 25 May 2023
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The drug discovery process is a rigorous and time-consuming endeavor, typically requiring several years of extensive research and development. Although classical machine learning (ML) has proven successful in this field, its computational demands in terms of speed and resources are significant. In recent [...] Read more.
The drug discovery process is a rigorous and time-consuming endeavor, typically requiring several years of extensive research and development. Although classical machine learning (ML) has proven successful in this field, its computational demands in terms of speed and resources are significant. In recent years, researchers have sought to explore the potential benefits of quantum computing (QC) in the context of machine learning (ML), leading to the emergence of quantum machine learning (QML) as a distinct research field. The objective of the current study is twofold: first, to present a review of the proposed QML algorithms for application in the drug discovery pipeline, and second, to compare QML algorithms with their classical and hybrid counterparts in terms of their efficiency. A query-based search of various databases took place, and five different categories of algorithms were identified in which QML was implemented. The majority of QML applications in drug discovery are primarily focused on the initial stages of the drug discovery pipeline, particularly with regard to the identification of novel drug-like molecules. Comparison results revealed that QML algorithms are strong rivals to the classical ones, and a hybrid solution is the recommended approach at present. Full article
(This article belongs to the Special Issue Quantum Computation and Its Applications)
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