Quantum machine learning: from physics to software engineering

Article Properties
  • Language
    English
  • DOI (url)
    10.1080/23746149.2023.2165452
  • Publication Date
    2023/02/15
  • Journal
    Advances in Physics: X
  • Indian UGC (journal)
  • Refrences
    371
  • Citations
    13
  • Alexey Melnikov Terra Quantum AG, St. Gallen, Switzerland ORCID (unauthenticated)
  • Mohammad Kordzanganeh Terra Quantum AG, St. Gallen, Switzerland ORCID (unauthenticated)
  • Alexander Alodjants ITMO University, St. Petersburg, Russia ORCID (unauthenticated)
  • Ray-Kuang Lee Institute of Photonics Technologies, National Tsing Hua University, Hsinchu, TaiwanDepartment of Physics, National Tsing Hua University, Hsinchu, TaiwanPhysics Division, National Center for Theoretical Sciences, Taipei, TaiwanCenter for Quantum Technology, Hsinchu, Taiwan ORCID (unauthenticated)
Cite
Melnikov, Alexey, et al. “Quantum Machine Learning: From Physics to Software Engineering”. Advances in Physics: X, vol. 8, no. 1, 2023, https://doi.org/10.1080/23746149.2023.2165452.
Melnikov, A., Kordzanganeh, M., Alodjants, A., & Lee, R.-K. (2023). Quantum machine learning: from physics to software engineering. Advances in Physics: X, 8(1). https://doi.org/10.1080/23746149.2023.2165452
Melnikov A, Kordzanganeh M, Alodjants A, Lee RK. Quantum machine learning: from physics to software engineering. Advances in Physics: X. 2023;8(1).
Journal Category
Science
Physics
Refrences
Title Journal Journal Categories Citations Publication Date
Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms 2022
Automated design of quantum optical experiments for device-independent quantum key distribution 2022
Hierarchical text-conditional image generation with clip latents 2022
Is quantum advantage the right goal for quantum machine learning? 2022
Optimizing quantum circuits with Riemannian gradient flow 2022
Citations
Title Journal Journal Categories Citations Publication Date
A variational quantum perceptron with Grover’s algorithm for efficient classification

 Physica Scripta
  • Science: Physics
  • Science: Physics
 2024
Quantum machine learning for image classification

 Machine Learning: Science and Technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Science (General)
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
 1 2024
Quantum fidelity kernel with a trapped-ion simulation platform Physical Review A
  • Science: Physics: Optics. Light
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics
 2024
Experimental Property Reconstruction in a Photonic Quantum Extreme Learning Machine Physical Review Letters
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics
  • Science: Physics
 2024
Unleashing the potential: AI empowered advanced metasurface research

 Nanophotonics
  • Science: Physics
  • Technology: Chemical technology
  • Science: Chemistry
  • Science: Physics: Optics. Light
  • Science: Physics
  • Science: Physics: Acoustics. Sound
  • Science: Physics: Optics. Light
  • Technology: Chemical technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
  • Science: Physics
 2024
Citations Analysis
Category Category Repetition
Science: Physics8
Science: Mathematics: Instruments and machines: Electronic computers. Computer science5
Science: Physics: Optics. Light3
Science: Chemistry: Physical and theoretical chemistry2
Technology: Engineering (General). Civil engineering (General)2
Science: Mathematics2
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks2
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware2
Science: Science (General)2
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software2
Science: Physics: Acoustics. Sound2
Science: Physics: Atomic physics. Constitution and properties of matter1
Technology: Ocean engineering1
Science: Physics: Geophysics. Cosmic physics1
Geography. Anthropology. Recreation: Geography (General)1
Technology: Photography1
Science: Geology1
Technology: Engineering (General). Civil engineering (General): Applied optics. Photonics1
Technology: Chemical technology1
Science: Chemistry1
Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials1
The category Science: Physics 8 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Quantum Machine Learning for Computational Methods in Engineering: A Systematic Review and was published in 2023. The most recent citation comes from a 2024 study titled Experimental Property Reconstruction in a Photonic Quantum Extreme Learning Machine. This article reached its peak citation in 2023, with 8 citations. It has been cited in 12 different journals, 33% of which are open access. Among related journals, the Machine Learning: Science and Technology cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year