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Applied Sciences
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Quantum Computation in Quantum Science
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Quantum Computation in Quantum Science

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

Deadline for manuscript submissions: 20 May 2024 | Viewed by 2416

Special Issue Editor

Prof. Dr. Felix Jaetae Seo

E-Mail Website
Guest Editor
Department of Physics, Hampton University, Hampton, VA 23668, USA
Interests: nanophotonics; quantum optics; nanocrystals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is acknowledged that quantum computing has the ability to tackle the most challenging problems with fewer resources than traditional computing technologies and has the potential to resolve a wide range of complicated problems in less time and space. Both academia and industry have proven the quantum advantage of solving challenging and complicated problems in the fields of quantum information, quantum communication, quantum algorithms, quantum machine learning, quantum cryptography, quantum key distribution, quantum blockchain, quantum error correction, quantum image processing, quantum games, etc. Quantum computation research has significantly advanced over the past several years because of the availability of cloud-based quantum computers and quantum simulators, and the accessibility of real quantum computers. Furthermore, quantum software platforms significantly facilitate the designing, testing and execution of quantum circuits. Therefore, research articles on quantum computation in the areas of (but not limited to) quantum information, quantum communication, quantum algorithms, quantum machine learning, quantum cryptography, quantum key distribution, quantum blockchain, quantum error correction, quantum image processing and quantum games will demonstrate prospective quantum computation applications well.

Prof. Dr. Felix Jaetae Seo
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 information
  • quantum communication
  • quantum algorithms
  • quantum machine learning
  • quantum cryptography
  • quantum key distribution
  • quantum blockchain
  • quantum error correction
  • quantum image processing
  • quantum games

Published Papers (2 papers)

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Research

15 pages, 4692 KiB  
Article
Pairing Hamiltonians of Nearest-Neighbor Interacting Superconducting Qubits on an IBM Quantum Computer
by Shirshendu Chatterjee, Bikash K. Behera and Felix J. Seo
Appl. Sci. 2023, 13(21), 12075; https://doi.org/10.3390/app132112075 - 06 Nov 2023
Viewed by 848
Abstract
A quantum simulation experiment pairing Hamiltonians of nearest-neighbor interacting superconducting qubits was performed with a complete set of algorithms on an IBM Quantum Computer-IBMq Lima. The experiment revealed that the fidelity is a function of iteration using Suzuki–Trotter decomposition for four different types [...] Read more.
A quantum simulation experiment pairing Hamiltonians of nearest-neighbor interacting superconducting qubits was performed with a complete set of algorithms on an IBM Quantum Computer-IBMq Lima. The experiment revealed that the fidelity is a function of iteration using Suzuki–Trotter decomposition for four different types of nearest-neighbor Heisenberg, XY, transverse, and longitudinal Ising superconducting qubit couplings of Hamiltonians. The experiment displayed the models of how the experimental density matrices shift from the theoretical density matrices and how their behavior changes with different numbers of iterations. It also demonstrated the reconstruction of quantum states and how the states change as a function of iteration with the IBM Quantum Computer-IBMq Lima. The time evolutions of the states for different models were also shown to predict the dominance of each state. Full article
(This article belongs to the Special Issue Quantum Computation in Quantum Science)
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15 pages, 2968 KiB  
Article
Implementation of the HHL Algorithm for Solving the Poisson Equation on Quantum Simulators
by Beimbet Daribayev, Aksultan Mukhanbet and Timur Imankulov
Appl. Sci. 2023, 13(20), 11491; https://doi.org/10.3390/app132011491 - 20 Oct 2023
Viewed by 1272
Abstract
The Poisson equation is a fundamental equation of mathematical physics that describes the potential distribution in static fields. Solving the Poisson equation on a grid is computationally intensive and can be challenging for large grids. In recent years, quantum computing has emerged as [...] Read more.
The Poisson equation is a fundamental equation of mathematical physics that describes the potential distribution in static fields. Solving the Poisson equation on a grid is computationally intensive and can be challenging for large grids. In recent years, quantum computing has emerged as a potential approach to solving the Poisson equation more efficiently. This article uses quantum algorithms, particularly the Harrow–Hassidim–Lloyd (HHL) algorithm, to solve the 2D Poisson equation. This algorithm can solve systems of equations faster than classical algorithms when the matrix A is sparse. The main idea is to use a quantum algorithm to transform the state vector encoding the solution of a system of equations into a superposition of states corresponding to the significant components of this solution. This superposition is measured to obtain the solution of the system of equations. The article also presents the materials and methods used to solve the Poisson equation using the HHL algorithm and provides a quantum circuit diagram. The results demonstrate the low error rate of the quantum algorithm when solving the Poisson equation. Full article
(This article belongs to the Special Issue Quantum Computation in Quantum Science)
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