Student review of innovations in quantum technologies. Part 6

• Autorzy: Potaszyński Jan , Buchwald Wojciech , Moszczyński Adam , Wasilewska Julita , Danieluk Daria , Magnuszewski Jan , Kaźmierczuk Adrian , Czarnomska-Wyżlic Monika , Żerański Przemysław , Staszkiewicz Richard , Kosiński Tymoteusz , Gołebiowska Aneta , Romaniuk Ryszard

Identyfikatory

DOI

10.24425/ijet.2025.153633

• Języki publikacji: EN

Abstrakty

EN

The aim of the paper is to show how graduated engineering students in classical ICT view practically the advent of the QIT. The students do their theses in El. Eng. and ICT and were asked how to implement now or in the future the QIT in their current or future work. Most of them have strictly defined research topics and in some cases the realization stage is advanced. Thus, most of the potential QIT application areas are defined and quite narrow. In such a case, the issue to be considered is the incorporation of QIT components and interfaces into the existing ICT infrastructure, software and hardware alike, and propose a solution as a reasonable functional hybrid system. The QIT components or circuits are not standalone in most cases, they should be somehow incorporated into existing environment, with a measurable added value. Not an easy task indeed. We have to excuse the students if the proposed solutions are not ripe enough. The exercise was proposed as an on-purpose publication workshop, related strictly to the fast and fascinating development of the QIT. The paper is a continuation of publishing exercises with previous groups of students participating in QIT lectures.

Słowa kluczowe

EN

QIT; cryptanalysis; differential equations; quantum materials; quantum radar; tomography; quantum dot; magnetometer; facial expression recognition; quantum sensors; atomic layer deposition

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2025
• Tom: Vol. 71, No. 3
• Strony: 27
• Opis fizyczny: Bibliogr. 44 poz., tab.

Twórcy

autor

Potaszyński Jan

• Warsaw University of Technology, Warsaw, Poland

autor

Buchwald Wojciech

• Warsaw University of Technology, Warsaw, Poland

autor

Moszczyński Adam

• Warsaw University of Technology, Warsaw, Poland

autor

Wasilewska Julita

• Warsaw University of Technology, Warsaw, Poland

autor

Danieluk Daria

• Warsaw University of Technology, Warsaw, Poland

autor

Magnuszewski Jan

• Warsaw University of Technology, Warsaw, Poland

autor

Kaźmierczuk Adrian

• Warsaw University of Technology, Warsaw, Poland

autor

Czarnomska-Wyżlic Monika

• Warsaw University of Technology, Warsaw, Poland

autor

Żerański Przemysław

• Warsaw University of Technology, Warsaw, Poland

autor

Staszkiewicz Richard

• Warsaw University of Technology, Warsaw, Poland

autor

Kosiński Tymoteusz

• Warsaw University of Technology, Warsaw, Poland

autor

Gołebiowska Aneta

• Warsaw University of Technology, Warsaw, Poland

autor

Romaniuk Ryszard

• Warsaw University of Technology, Warsaw, Poland

Bibliografia

• [1] A. Abbas, D. Sutter, C. Zoufal, A. Lucchi, A. Figalli, and S. Woerner, “The power of quantum neural networks,” Nature Computational Science, vol. 1, no. 6, pp. 403-409, 2021. [Online]. Available: https://arxiv.org/abs/2011.00027
• [2] E. Farhi and H. Neven, “Classification with quantum neural networks on near term processors,” 2018. [Online]. Available: https://arxiv.org/abs/1802.06002
• [3] A. Mari, T. R. Bromley, J. Izaac, M. Schuld, and N. Killoran, “Transfer learning in hybrid classical-quantum neural networks,” Quantum, vol. 4, p. 340, 2020. [Online]. Available: https://arxiv.org/abs/1912.08278
• [4] M. K. Pasupuleti, Quantum Computing Chips: Advances in Superconducting and Topological Qubits, 03 2025.
• [5] E. Boldbaatar, D. Grant, S. Choy, S. Zaminpardaz, and L. Holden, “Evaluating optical clock performance for gnss positioning,” Sensors, vol. 23, no. 13, 2023.
• [6] S.-H. Ho, S. P. Chao, C.-H. Chou, and F.-L. Lin, “Decoherence patterns of topological qubits from majorana modes,” New Journal of Physics, vol. 16, 11 2014.
• [7] S. Li and W. Deng, “Deep facial expression recognition: A survey,” IEEE Transactions on Affective Computing, vol. 13, pp. 1195-1215, 2022.
• [8] A. R. Khan, “Facial emotion recognition using conventional machine learning and deep learning methods: Current achievements, analysis and remaining challenges,” Information (Switzerland), vol. 13, 6 2022.
• [9] S. Alsubai, A. Alqahtani, A. Alanazi, M. Sha, and A. Gumaei, “Facial emotion recognition using deep quantum and advanced transfer learning mechanism,” Frontiers in Computational Neuroscience, vol. 18, 2024.
• [10] Y. Li, R. G. Zhou, R. Xu, J. Luo, and W. Hu, “A quantum deep convolutional neural network for image recognition,” Quantum Science and Technology, vol. 5, 10 2020.
• [11] Q. Leng and L. Peng, “Medical image intelligent diagnosis system based on facial emotion recognition and convolutional neural network,” Applied and Computational Engineering, vol. 67, pp. 152-159, 7 2024.
• [12] P. Easom-Mccaldin, A. Bouridane, A. Belatreche, R. Jiang, and S. Al-Maadeed, “Efficient quantum image classification using single qubit encoding,” IEEE Transactions on Neural Networks and Learning Systems, vol. 35, pp. 1472-1486, 2 2024.
• [13] S. Hossain, S. Umer, R. K. Rout, and H. A. Marzouqi, “A deep quantum convolutional neural network based facial expression recognition for mental health analysis,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 1556-1565, 2024.
• [14] A. Bhatt, T. Alam, K. P. Rane, R. Nandal, M. Malik, R. Neware, and S. Goel, “Quantum-inspired meta-heuristic algorithms with deep learning for facial expression recognition under varying yaw angles,” International Journal of Modern Physics C, vol. 33, 4 2022.
• [15] I.-H. Baek, J. J. Pyeon, S. H. Han, G.-Y. Lee, B. J. Choi, J. H. Han, T.-M. Chung, C. S. Hwang, and S. K. Kim, “High-performance thin-film transistors of quaternary indium-zinc-tin oxide films grown by atomic layer deposition,” ACS applied materials interfaces, vol. 11, no. 16, pp. 14 892-14 901, 2019.
• [16] “Atomic layer deposition.”
• [17] A. A. Marth, R. P. Marcus, G. C. Feuerriegel, D. Nanz, and R. Sutter, “Photon-counting detector ct versus energy-integrating detector ct of the lumbar spine: Comparison of radiation dose and image quality,” American Journal of Roentgenology, 2023.
• [18] A. M. El-Ali, N. Strubel, L. Pinkney, C. Xue, B. Dane, and S. V. Lala, “Pediatric contrast-enhanced chest ct on a photon-counting detector ct: radiation dose and image quality compared to energy-integrated detector ct,” Pediatric Radiology, 2024.
• [19] L. Ren, Z. Zhou, Z. Ahmed, K. Rajendran, J. G. Fletcher, C. H. McCollough, and L. Yu, “Performance evaluation of single- and dual- contrast spectral imaging on a photon-counting-detector ct,” Medical Physics, vol. 51, no. 11, pp. 8034-8046, 2024.
• [20] A. W. Harrow, A. Hassidim, and S. Lloyd, “Quantum algorithm for linear systems of equations,” Phys. Rev. Lett., vol. 103, p. 150502, Oct 2009.
• [21] J. Kyungtaek, “A highly accurate quantum optimization algorithm for ct image reconstruction based on sinogram patterns,” Scientific Reports, 2023.
• [22] H. Li and M. A. Buckingham, “Silicon quantum dots inlaid micron graphite anode for fast chargeable and high energy density li-ion batteries,” Frontiers in Chemistry, vol. 10, 2022. [Online]. Available: https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2022.1091268
• [23] S. Brahma, C.-Y. Wang, Y.-H. Huang, W.-F. Lin, and J.-L. Huang, “One-pot bottom-up synthesis of sio2 quantum dots and reduced graphene oxide (rgo) nanocomposite as anode materials in lithium-ion batteries,” C, vol. 11, no. 1, p. 23, 2025. [Online]. Available: https://www.mdpi.com/2311-5629/11/1/23
• [24] Z. Wang, H. Che, W. Lu, Y. Chao, L. Wang, B. Liang, J. Liu, Q. Xu, and X. Cui, “Application of inorganic quantum dots in advanced lithium-sulfur batteries,” Advanced Science, vol. 10, no. 19, p. 2301355, 2023. [Online]. Available: https://advanced.onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301355
• [25] M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information. Cambridge University Press, 2002.
• [26] P. W. Shor, “Algorithms for quantum computation: Discrete logarithms and factoring,” Proceedings 35th Annual Symposium on Foundations of Computer Science, pp. 124-134, 1994.
• [27] L. K. Grover, “A fast quantum mechanical algorithm for database search,” Proceedings of the 28th Annual ACM Symposium on Theory of Computing, pp. 212-219, 1996.
• [28] National Institute of Standards and Technology (NIST), “Post-quantum cryptography standardization: Fourth round candidate algorithms,” On-line, 2024, https://csrc.nist.gov/projects/post-quantum-cryptography.
• [29] F. Giustino, J. H. Lee, F. Trier, M. Bibes, S. Winter, R. Valentí, Y.-W. Son, L. Taillefer, C. Heil, A. Figueroa, B. Plac¸ais, Q.-S. Wu, O. Yazyev, E. Bakkers, J. Nyg˚ard, P. Forn-Diaz, S. Franceschi, J. McIver, L. Foa Torres, and S. Roche, “The 2021 quantum materials roadmap,” 02 2021.
• [30] M. Dickmann, L. Mathes, R. Helm, V. Burwitz, W. Egger, J. Mitteneder, C. Hugenschmidt, P. Sperr, M. Butterling, M. Liedke, A. Wagner, J. Dorner, T. Schwarz-Selinger, and G. Dollinger, “Identification and reversible optical switching of nv centers in diamond,” Advanced Functional Materials, 03 2025.
• [31] D. Irber, F. Poggiali, F. Kong, M. Kieschnick, T. Lühmann, D. Kwiatkowski, J. Meijer, J. Du, F. Shi, and F. Reinhard, “Robust all-optical single-shot readout of nv centers in diamond,” 06 2020.
• [32] K. Khazen and H. J. von Bardeleben, “Nv-centers in sic: A solution for quantum computing technology?” Frontiers in Quantum Science and Technology, vol. Volume 2 - 2023, 2023. [Online]. Available: https://www.frontiersin.org/journals/quantum-science-and-technology/articles/10.3389/frqst.2023.1115039
• [33] Y. Zhu, B. Kovos, M. Onizhuk, D. Awschalom, and G. Galli, “Theoretical and experimental study of the nitrogen-vacancy center in 4h-sic,” Phys. Rev. Mater., vol. 5, p. 074602, Jul 2021. [Online]. Available: https://link.aps.org/doi/10.1103/PhysRevMaterials.5.074602
• [34] J. Adamowski, S. Bednarek, and B. Szafran, “Quantum computing with quantum dots,” vol. 14, 01 2005.
• [35] G. Miao, “Promising single-photon emitters with reconfined ingan/gannanowire quantum dots,” Quantum Engineering, vol. 1, 06 2019.
• [36] C. S. Noah Linden, Ashely Montanaro, “Quantum vs. classical algorithms for solving the heat equation,” Springer Nature, 2022.
• [37] J. C. J. X. I. A. L. L. X. K. D. L. E. S. G. L. Tao Xin, Shijie Wei, “A quantum algorithm for solving linear differential equations: Theory and experiment,” Cornell University, 2018.
• [38] N. W. A. A.-G. Mohsen Bagherimehrab, Kouhei Nakaji, “Fast quantum algorithm for differential equations,” Cornell University, 2023.
• [39] K. Wu and R. He, “Perspective: magnetic quantum sensors for biomedical applications,” Nanotechnol., 2025.
• [40] M. Alalili, M. B. Ali, Q. Nasir, and M. A. Talib, “Quantum radar: Overview on technology, limitations and opportunities,” in 2024 17th International Conference on Development in eSystem Engineering (DeSE), 2024, pp. 180-186.
• [41] G. Pavan, G. Galati, and F. Daum, “Lessons learnt from the rise and fall of quantum radar research,” Academia Quantum, vol. 2, no. 1, 2025.
• [42] D. Luong, A. Damini, B. Balaji, C. W. Sandbo Chang, A. M. Vadiraj, and C. Wilson, “A quantum-enhanced radar prototype,” in 2019 IEEE Radar Conference (RadarConf), 2019, pp. 1-6.
• [43] D. Luong, B. Balaji, and S. Rajan, “Quantum radar: Challenges and outlook: An overview of the state of the art,” IEEE Microwave Magazine, vol. 24, no. 9, pp. 61-67, 2023.
• [44] K. Lukin, “Quantum radar and noise radar concepts,” in 2021 IEEE Radar Conference (RadarConf21), 2021, pp. 1-4.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).