- 1School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, China
- 2Department of Physics & Astronomy, Louisiana State University, Baton Rouge, LA,United States
- 3Centro de Ciências Exatas e das Tecnologias, Universidade Federal do Oeste daBahia - Campus Reitor Edgard Santos, Barreiras, Brasil
Editorial on the Research Topic
Advancements and challenges in quantum technologies using low-dimensional systems
Background
The study of low-dimensional systems for quantum technologies has garnered significant attention in the past few years due to their potential in developing the next generation of quantum devices such as quantum batteries [1], sensors [2, 3], and quantum heat engines [4]. In this scenario, some materials like two-dimensional structures [5, 6], quantum dots [7], nanowires [8], and molecular magnetic systems [9, 10] offer distinctive platforms to study and utilize quantum phenomena [11, 12]. Recent advances have highlighted the potential of these low-dimensional quantum systems in developing more efficient quantum devices [1, 4, 13, 14]. These devices promise improvements in computational speed, sensing precision, and energy efficiency [2, 12]. Nevertheless, there are several challenges to overcome, including decoherence, noisy environments, and the difficulty of scaling quantum systems for real-world applications [15–17].
In this context, low-dimensional quantum materials are intriguing platforms providing opportunities for fundamental research. Therefore, to contextualize the advancements and challenges in this area, this Research Topic brings together different studies addressing some advancements, challenges, and directions in the research of quantum technologies that benefit from the useful features of low-dimensional systems.
Key contributions and insights
Each paper contributed original findings demonstrating innovative approaches to leveraging quantum technologies in various contexts.
Quantum magnetism in low-dimensional systems
Sivý et al. studied the magnetic properties of a molecular magnetic system
Quantum thermodynamics and heat engines
In the same way, Rastegar-Sedehi and Cruz explored a low-dimensional interaction predominant in metal complexes systems to analyze the performance of a quantum Stirling heat engine. The model includes a two-particle Heisenberg model with Dzyaloshinskii–Moriya interaction. The study demonstrates how quantum features such as quantum entanglement can be used to enhance thermodynamic efficiency. These results not only expand the understanding of the performance of quantum thermodynamics devices, but also suggest practical applications in designing efficient quantum-based energy harvesting systems.
Quantum cryptography and secure communication
On the other hand, Hou et al. introduced a quantum computing application. The authors proposed a quantum private comparison protocol to solve the socialist millionaire problem, employing rotation operations and Bell states, ensuring robust security by preventing information leakage. The results depend on quantum features such as entanglement and Bell states. These features play a crucial role in utilizing low-dimensional systems as platforms for quantum information processing [18, 19]. Therefore, this highlights the potential for low-dimensional quantum systems to be applied in cryptographic applications.
Quantum machine learning and sensing
Following the quantum computing results, Dong et al. developed a hybrid (quantum-classical) neural network optimized with a quantum activation function. The proposed approach demonstrates how integrating quantum activation functions into machine learning models potentially enhances the performance across different predictive tasks. Therefore, the integration of quantum neural networks aligns well with the characterization of low-dimensional quantum systems, where local interactions and spatial correlations can play a significant role. In this regard, quantum energy devices, such as quantum heat engines based on low-dimensional systems, could benefit from these approaches, predicting their performance, and understanding energy fluctuations and the dynamics of their quantum correlations over time.
Quantum information security and image processing
On the other hand, Zeng et al. introduced a color watermarking algorithm utilizing the quantum discrete cosine transform and a sinusoidal-tent map. By using quantum features such as entanglement, the algorithm enhances resistance to tampering, addressing critical issues regarding digital content protection and intellectual property rights. In this regard, the efficient quantum operations proposed for this algorithm can provide insights into the manipulation of quantum states, which can be applied in the research of low-dimensional systems, with potential applications in future developments in quantum sensing and secure quantum communication protocols based on these systems.
Concluding remarks
The presented Research Topic highlighted the fundamental role of the study of low-dimensional quantum systems in advancing emerging quantum technologies. The papers cover from quantum magnetism and thermodynamics to practical applications in machine learning and information security. The collected works demonstrate how key quantum properties, such as entanglement and coherence, can be harnessed to improve quantum devices and protocols. The continued progress in this research area requires interdisciplinary efforts, focusing on themes related to scalability, noise mitigation, and integration with current classical technologies, making low-dimensional systems essential building blocks for next-generation quantum technologies.
Author contributions
NZ: Writing–review and editing. OM-L: Writing–review and editing. CC: Writing–original draft, Writing–review and editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
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References
1. Campaioli F, Gherardini S, Quach JQ, Polini M, Andolina GM. Colloquium: quantum batteries. Rev Mod Phys (2024) 96:031001. doi:10.1103/revmodphys.96.031001
2. Tawffaq MR, Khani HI, Ali AHSA, Kanbar A, Mahdi S, Electron transport mechanisms in low-dimensional semiconductor structures: a review (2024) 16, 731, 44. doi:10.17725/j.rensit.2024.16.731
3. Yu C-J, von Kugelgen S, Laorenza D, Freedman D. A molecular approach to quantum sensing. ACS Cent Sci (2021) 7:712–23. doi:10.1021/acscentsci.0c00737
4. Myers NM, Abah O, Deffner S, Quantum thermodynamic devices: from theoretical proposals to experimental reality, AVS Quantum Sci, 4 (2022), doi:10.1116/5.0083192
5. Arbiol J, Mata M, Eickhoff M, Morral AF. Mater Today (2013) 16:213. doi:10.1016/j.mattod.2013.06.006
6. Cai K, Huang H-Y, Hsieh M-L, Chen P-W, Chiang S-E, Chang S-H, et al. Two-dimensional self-assembly of boric acid-functionalized graphene quantum dots: tunable and superior optical properties for efficient eco-friendly luminescent solar concentrators. ACS Nano (2022) 16:3994–4003. doi:10.1021/acsnano.1c09582
7. Escott C, Zwanenburg F, Morello A. Resonant tunnelling features in quantum dots. Nanotechnology (2010) 21:274018. doi:10.1088/0957-4484/21/27/274018
8. Leandro L, Gunnarsson CP, Reznik R, Jöns KD, Shtrom I, Khrebtov A, et al. Nanowire quantum dots tuned to atomic resonances. Nano Lett (2018) 18:7217–21. doi:10.1021/acs.nanolett.8b03363
9. Moreno-Pineda E, Wernsdorfer W. Measuring molecular magnets for quantum technologies. Nat Rev Phys (2021) 3:645–59. doi:10.1038/s42254-021-00340-3
10. Gaita-Ariño A, Luis F, Hill S, Coronado E. Molecular spins for quantum computation. Nat Chem (2019) 11:301–9. doi:10.1038/s41557-019-0232-y
11. Liu R, Hu X, Xu M, Ren H, Yu H. Layered low-dimensional ruddlesden-popper and dion-jacobson perovskites: from material properties to photovoltaic device performance. ChemSusChem (2023) 16:e202300736. doi:10.1002/cssc.202300736
12. Su C, Gao X, Liu K, Wang S, Dai Y, Dong H, et al. An intellectual property analysis: advances and commercialization of low-dimensional carbon materials in batteries. Energy Mater (2024) 4. doi:10.20517/energymater.2023.98
13. Zhang Z, Ouyang Y, Cheng Y, Chen J, Li N, Zhang G. Size-dependent phononic thermal transport in low-dimensional nanomaterials. Phys Rep (2020) 860:1–26. doi:10.1016/j.physrep.2020.03.001
14. Garewal IK, Mahamuni C, Jha S, Emerging applications and challenges in quantum computing: a literature survey, (2024) 1, 12. doi:10.1109/icABCD62167.2024.10645271
16. Gyongyosi L, Imre S. Scalable distributed gate-model quantum computers. Scientific Rep (2021) 11:5172. doi:10.1038/s41598-020-76728-5
17. de Leon ND, Itoh K, Kim D, Mehta K, Northup T, Paik H, et al. Materials challenges and opportunities for quantum computing hardware. Science (2021) 372:eabb2823. doi:10.1126/science.abb2823
18. Nandy A, Duan C, Taylor MG, Liu F, Steeves A, Kulik H. Computational discovery of transition-metal complexes: from high-throughput screening to machine learning. Chem Rev (2021) 121:9927–10000. doi:10.1021/acs.chemrev.1c00347
Keywords: quantum technologies, quantum computing, low-dimensional systems, quantum thermodynamics, metal complexes
Citation: Zhou N, Magana-Loaiza O and Cruz C (2025) Editorial: Advancements and challenges in quantum technologies using low-dimensional systems. Front. Phys. 13:1580425. doi: 10.3389/fphy.2025.1580425
Received: 20 February 2025; Accepted: 10 March 2025;
Published: 19 March 2025.
Edited and reviewed by:
Alexandre M. Zagoskin, Loughborough University, United KingdomCopyright © 2025 Zhou, Magana-Loaiza and Cruz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Clebson Cruz, Y2xlYnNvbi5jcnV6QHVmb2IuZWR1LmJy