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Electronics
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Quantum Computation and Its Applications
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Quantum Computation and Its Applications

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: 15 October 2024 | Viewed by 9462

Special Issue Editors

Prof. Dr. Ilias K. Savvas

E-Mail Website
Guest Editor
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
Dr. Apostolis Xenakis

E-Mail Website
Guest Editor
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; Physical Computing; STEM; Robotis
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 2400 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 key distribution
  • post-quantum cryptography
  • classical shadows
  • quantum telecommunications and networking
  • quantum processing units (QPUs) and error correction
  • quantum algorithms

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Published Papers (4 papers)

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Research

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12 pages, 570 KiB  
Article
Grover on Scrypt
by Gyeongju Song and Hwajeong Seo
Electronics 2024, 13(16), 3167; https://doi.org/10.3390/electronics13163167 - 10 Aug 2024
Viewed by 219
Abstract
This paper presents an optimized quantum circuit for the scrypt cryptographic algorithm. We applied various optimization techniques to reduce the DW cost, which is the product of the time and space complexity of quantum circuits. In our proposed [...] Read more.
This paper presents an optimized quantum circuit for the scrypt cryptographic algorithm. We applied various optimization techniques to reduce the DW cost, which is the product of the time and space complexity of quantum circuits. In our proposed method, the number of ancilla qubits was significantly reduced through the use of optimized inverse operations, while the depth was minimized by implementing parallel structures. For the SHA-256, we devised a structure that achieves a substantial reduction in the number of ancilla qubits with only a slight increase in quantum circuit depth. By cleaning the dirty ancilla qubits used in the previous round through inverse operations, we enabled their reuse in each subsequent round. Specifically, we reduced the number of 8128 ancilla qubits, achieving this with an increase of only 6 in the full depth of the quantum circuit. Additionally, within Salsa20/8 in SMix, we reused qubits through inverse operations and performed some operations in parallel to reduce both the number of qubits and the overall quantum circuit depth. Finally, our quantum circuit for scrypt demonstrates a significant reduction in the width (the number of qubits) with only a minimal increase in the full quantum circuit depth. Full article
(This article belongs to the Special Issue Quantum Computation and Its Applications)
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10 pages, 478 KiB  
Article
Adjusting Optical Polarization with Machine Learning for Enhancing Practical Security of Continuous-Variable Quantum Key Distribution
by Zicheng Zhou and Ying Guo
Electronics 2024, 13(8), 1410; https://doi.org/10.3390/electronics13081410 - 9 Apr 2024
Viewed by 666
Abstract
An available trick to mitigate the interference of environmental noise in quantum communications is to modulate signals with time-polarization multiplexing. Conversely, due to effects of the atmospheric turbulence in free space, the polarization of signals fluctuates randomly, resulting in feasible information leakage when [...] Read more.
An available trick to mitigate the interference of environmental noise in quantum communications is to modulate signals with time-polarization multiplexing. Conversely, due to effects of the atmospheric turbulence in free space, the polarization of signals fluctuates randomly, resulting in feasible information leakage when direct polarization demultiplexing is carried out at the receiver, drowning out the noise-contained signals. For enhancing the practical security of the continuous-variable quantum key distribution (CVQKD), we propose a machine learning (ML) approach for optimization of the dynamic polarization control (DPC) of signals transmitted through atmospheric turbulence. An optimal DPC scheme can be adaptively adjusted with ML algorithms, which is based on the received signals at the receiver for solving the loophole problem of information leakage since it provides an accurate response to the polarization changes regarding the anamorphic signals. The performance of the CVQKD system can be increased in terms of secret key rates and maximal transmission distance as well. Numerical simulation shows the positive effect of the ML-based DPC while taking into account the secret key rate of the CVQKD system. The ML-based DPC effectively reduces the feasibility of information leakage and hence results in an increased secret key rate of the practical CVQKD system. Full article
(This article belongs to the Special Issue Quantum Computation and Its Applications)
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25 pages, 389 KiB  
Article
Evaluation and Comparison of Lattice-Based Cryptosystems for a Secure Quantum Computing Era
by Maria E. Sabani, Ilias K. Savvas, Dimitrios Poulakis, Georgia Garani and Georgios C. Makris
Electronics 2023, 12(12), 2643; https://doi.org/10.3390/electronics12122643 - 12 Jun 2023
Cited by 3 | Viewed by 3808
Abstract
The rapid development of quantum computing devices promises powerful machines with the potential to confront a variety of problems that conventional computers cannot. Therefore, quantum computers generate new threats at unprecedented speed and scale and specifically pose an enormous threat to encryption. Lattice-based [...] Read more.
The rapid development of quantum computing devices promises powerful machines with the potential to confront a variety of problems that conventional computers cannot. Therefore, quantum computers generate new threats at unprecedented speed and scale and specifically pose an enormous threat to encryption. Lattice-based cryptography is regarded as the rival to a quantum computer attack and the future of post-quantum cryptography. So, cryptographic protocols based on lattices have a variety of benefits, such as security, efficiency, lower energy consumption, and speed. In this work, we study the most well-known lattice-based cryptosystems while a systematic evaluation and comparison is also presented. Full article
(This article belongs to the Special Issue Quantum Computation and Its Applications)
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Review

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26 pages, 3913 KiB  
Review
Unlocking the Potential of Quantum Machine Learning to Advance Drug Discovery
by Maria Avramouli, Ilias K. Savvas, Anna Vasilaki and Georgia Garani
Electronics 2023, 12(11), 2402; https://doi.org/10.3390/electronics12112402 - 25 May 2023
Cited by 6 | Viewed by 3805
Abstract
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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