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Applied Sciences
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Recent Trends in Quantum Computing, Quantum Information and Quantum Sensing
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Recent Trends in Quantum Computing, Quantum Information and Quantum Sensing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Quantum Science and Technology".

Deadline for manuscript submissions: closed (20 June 2024) | Viewed by 5658

Special Issue Editor

Dr. Sergio Pagano

E-Mail Website
Guest Editor
Dipartimento di Fisica "E.R. Caianiello", Università di Salerno, Via Giovanni Paolo II, n.132, 84084 Fisciano, SA, Italy
Interests: physics of Josephson junctions; semiconducting cryogenic detectors; superconducting active and quantum devices; transport properties and low-frequency noise in materials and devices; application of network and complexity theories to management and public health
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A (second) quantum revolution is engaging the arcane quantum world in order to develop practical applications, bringing about new concepts (quantum information), instruments (quantum computing) and devices (quantum sensing).

This is a multidisciplinary field that encompasses aspects of computer science, physics, engineering and mathematics with the following aims: to approach complex problems, to solve them much faster than conventional computers can, and to realize super-sensitive devices that can probe the smallest aspects of nature.

The purpose of this Special Issue is to bring together scientists, experts and engineers from across the world in order to present and share their recent research results and innovative ideas related to quantum computing, quantum information and quantum sensing.

We are particularly interested in contributions that cover front edge results in specific aspects of quantum technologies. Examples include: quantum algorithms, quantum computers, qubits architectures, quantum exploitable materials, quantum sensitive devices, and quantum sensing applications. Additionally, a broader discussion of current status and trends in specific quantum subfields will be appreciated.

Dr. Sergio Pagano
Guest Editor

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. Applied Sciences 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 computation
  • quantum information
  • quantum optimization
  • quantum measurement
  • quantum imaging
  • quantum communication
  • quantum networks
  • quantum sensing

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Published Papers (3 papers)

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Research

9 pages, 242 KiB  
Article
Improving Quantum Optimization Algorithms by Constraint Relaxation
by Tomasz Pecyna and Rafał Różycki
Appl. Sci. 2024, 14(18), 8099; https://doi.org/10.3390/app14188099 - 10 Sep 2024
Viewed by 919
Abstract
Quantum optimization is a significant area of quantum computing research with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational-Hamiltonian-based algorithms, struggle to present quantum devices due to noise and decoherence. Existing techniques attempt to mitigate these issues [...] Read more.
Quantum optimization is a significant area of quantum computing research with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational-Hamiltonian-based algorithms, struggle to present quantum devices due to noise and decoherence. Existing techniques attempt to mitigate these issues through employing different Hamiltonian encodings or Hamiltonian clause pruning, but they often rely on optimistic assumptions rather than a deep analysis of the problem structure. We demonstrate how to formulate the problem Hamiltonian for a quantum approximate optimization algorithm that satisfies all the requirements to correctly describe the considered tactical aircraft deconfliction problem, achieving higher probabilities for finding solutions compared to previous works. Our results indicate that constructing Hamiltonians from an unconventional, quantum-specific perspective with a high degree of entanglement results in a linear instead of exponential number of entanglement gates instead and superior performance compared to standard formulations. Specifically, we achieve a higher probability of finding feasible solutions: finding solutions in nine out of nine instances compared to standard Hamiltonian formulations and quadratic programming formulations known from quantum annealers, which only found solutions in seven out of nine instances. These findings suggest that there is substantial potential for further research in quantum Hamiltonian design and that gate-based approaches may offer superior optimization performance over quantum annealers in the future. Full article
(This article belongs to the Special Issue Recent Trends in Quantum Computing, Quantum Information and Quantum Sensing)
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21 pages, 5099 KiB  
Article
Characterization of a Transmon Qubit in a 3D Cavity for Quantum Machine Learning and Photon Counting
by Alessandro D’Elia, Boulos Alfakes, Anas Alkhazaleh, Leonardo Banchi, Matteo Beretta, Stefano Carrazza, Fabio Chiarello, Daniele Di Gioacchino, Andrea Giachero, Felix Henrich, Alex Stephane Piedjou Komnang, Carlo Ligi, Giovanni Maccarrone, Massimo Macucci, Emanuele Palumbo, Andrea Pasquale, Luca Piersanti, Florent Ravaux, Alessio Rettaroli, Matteo Robbiati, Simone Tocci and Claudio Gattiadd Show full author list remove Hide full author list
Appl. Sci. 2024, 14(4), 1478; https://doi.org/10.3390/app14041478 - 11 Feb 2024
Cited by 4 | Viewed by 2719
Abstract
In this paper, we report the use of a superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization and characterization of a transmon qubit coupled to a 3D resonator, providing a detailed [...] Read more.
In this paper, we report the use of a superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization and characterization of a transmon qubit coupled to a 3D resonator, providing a detailed description of the simulation framework and of the experimental measurement of important parameters, such as the dispersive shift and the qubit anharmonicity. We then report on a Quantum Machine Learning application implemented on a single-qubit device to fit the u-quark parton distribution function of the proton. In the final section of the manuscript, we present a new microwave photon detection scheme based on two qubits coupled to the same 3D resonator. This could in principle decrease the dark count rate, favoring applications like axion dark matter searches. Full article
(This article belongs to the Special Issue Recent Trends in Quantum Computing, Quantum Information and Quantum Sensing)
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18 pages, 8201 KiB  
Article
A Dynamic-Routing Algorithm Based on a Virtual Quantum Key Distribution Network
by Lin Bi, Minghui Miao and Xiaoqiang Di
Appl. Sci. 2023, 13(15), 8690; https://doi.org/10.3390/app13158690 - 27 Jul 2023
Cited by 3 | Viewed by 1478
Abstract
Quantum key distribution (QKD) is an encrypted communication technique based on the principles of quantum mechanics that ensures communication security by exploiting the properties of quantum states. Currently, the transmission efficiency of the QKD system is low. Trusted relay technology is used to [...] Read more.
Quantum key distribution (QKD) is an encrypted communication technique based on the principles of quantum mechanics that ensures communication security by exploiting the properties of quantum states. Currently, the transmission efficiency of the QKD system is low. Trusted relay technology is used to solve this problem and achieve long-distance transmission. However, trusted relaying alone cannot decrypt the issues of poor link stability and the low utilization of key resources. To further optimize the system performance, we propose a dynamic routing algorithm. One of the improvement schemes includes the following: firstly, an adjustable-size quantum key pool (QKP) is designed, which can dynamically adjust the size of the refreshing pool according to the actual demand. Secondly, the utilization of key resources is improved by using the residual quantum key model to dynamically obtain the remaining key amount in the QKP and set the key amount threshold. We calculate the link-blocking probability and track the blocking intensity and blocking entry by combining the Poisson process, thus realizing the evaluation of the link stability. Finally, the number of remaining keys in the QKP and the link-blocking probability combine with the random wandering model as the basis of the route selection for the QKD dynamic routing algorithm to achieve efficient key path selection. We validated the algorithm by comparing it with other algorithms on the Mininet simulation platform, and the algorithm proved to have a better performance in terms of congestion avoidance, delay reduction, and improved QKD efficiency. This scheme provides a novel and efficient way to solve the problems in existing QKD systems. It effectively improves the transmission efficiency and strengthens the system’s security by dynamically obtaining the critical volume, accurately evaluating the link state, and selecting the optimal critical path. Full article
(This article belongs to the Special Issue Recent Trends in Quantum Computing, Quantum Information and Quantum Sensing)
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