Advancements in Quantum Computing—Viewpoint: Building Adoption and Competency in Industry

Pfaendler, Sieglinde M. -L.; Konson, Konstantin; Greinert, Franziska

doi:10.1007/s13222-024-00467-4

Datenbank Spektrum

2024

DOI: 10.1007/s13222-024-00467-4

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Advancements in Quantum Computing—Viewpoint: Building Adoption and Competency in Industry

Sieglinde M. -L. Pfaendler,

Konstantin Konson,

Franziska Greinert

Abstract: The narrative around quantum computing is evolving quickly. First reports of quantum computers able to solve certain scientific problems on-par with the precision of High-Performance Computers are persuading end-users and industry leaders to shift from passive observation to active exploration. Insights are provided here to enable organization and technology leaders in the database and data science community an entry into the field of quantum computing. This article provides an introduction of key concepts, in… Show more

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Cited by 4 publications

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Introducing quantum physics concepts and Dirac notation at the secondary school level: Insights into student reasoning from an acceptance survey

Hennig,

Tóth,

Veith

et al. 2024

Phys. Rev. Phys. Educ. Res.

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Evidence from physics education research suggests that the introduction of a formalistic description of quantum phenomena can be beneficial to student learning, particularly in terms of helping students move away from naive realist views of quanta or space-time descriptions of quantum phenomena. However, the mathematical requirements for mastering quantum formalism are typically far beyond the scope of secondary school education. Therefore, in previous research, we have proposed a reduced Dirac notation tailored to the capabilities of secondary school students, which is included in a novel teaching-learning sequence. However, the cognitive processes of students when confronted with an introduction to quantum physics via a reduced Dirac notation have not been thoroughly investigated: In particular, it seems important to investigate whether this approach is actually beneficial to students’ learning and to explore the learning difficulties students are likely to encounter in such a setting. This paper contributes to this research gap by reporting the findings of an acceptance survey: N=14 learners participated in one-on-one interviews following a protocol consisting of four cyclical phases (information phase, acceptance evaluation, paraphrasing phase, and application phase). The findings of our study indicate that the instructional elements within our new teaching-learning sequence were generally well accepted by students but also revealed learning difficulties that students may encounter. Thus, on the one hand, the findings of this study pave the way for future research on students’ learning of quantum physics using Dirac notation. On the other hand, the in-depth findings reported here may guide teachers in designing learning environments that introduce Dirac notation at the upper secondary school and introductory university levels. Published by the American Physical Society 2024

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Introducing quantum physics concepts and Dirac notation at the secondary school level: Insights into student reasoning from an acceptance survey

Hennig,

Tóth,

Veith

et al. 2024

Phys. Rev. Phys. Educ. Res.

View full text Add to dashboard Cite

show abstract

Convergence of Nanotechnology and Machine Learning: The State of the Art, Challenges, and Perspectives

Tripathy,

Patne,

Mohapatra

et al. 2024

IJMS

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Nanotechnology and machine learning (ML) are rapidly emerging fields with numerous real-world applications in medicine, materials science, computer engineering, and data processing. ML enhances nanotechnology by facilitating the processing of dataset in nanomaterial synthesis, characterization, and optimization of nanoscale properties. Conversely, nanotechnology improves the speed and efficiency of computing power, which is crucial for ML algorithms. Although the capabilities of nanotechnology and ML are still in their infancy, a review of the research literature provides insights into the exciting frontiers of these fields and suggests that their integration can be transformative. Future research directions include developing tools for manipulating nanomaterials and ensuring ethical and unbiased data collection for ML models. This review emphasizes the importance of the coevolution of these technologies and their mutual reinforcement to advance scientific and societal goals.

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QCA: Quantum Computational Approach for Internet of Things with 5G Connectivity

Selvarajan,

Manoharan,

Khadidos

et al. 2024

Information

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In this paper, the need for a quantum computing approach is analyzed for IoT applications using the 5G resource spectrum. Most of the IoT devices are connected for data transmission to end users with remote monitoring units, but there are no sufficient data storage units, and more data cannot be processed at minimized time periods. Hence, in the proposed method, quantum information processing protocols and quantum algorithms are integrated where data transmissions are maximized. Further, the system model is designed in such a way for checking the external influence factors that prevent the IoT device from transmitting data to end users. Therefore, with corresponding signal and noise power, it is essential to process the transmissions, thereby increasing data proportions at end connectivity. Once quantum computations are performed, then it is crucial to normalize IoT data units, thus establishing control over entire connected nodes that create a gateway for achieving maximum throughput. The combined system model is tested under four cases where the comparative outcomes prove that with reduced queue reductions of 12%, it is possible to achieve a maximum throughput of 99%.

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Advancements in Quantum Computing—Viewpoint: Building Adoption and Competency in Industry

Cited by 4 publications

References 69 publications

Introducing quantum physics concepts and Dirac notation at the secondary school level: Insights into student reasoning from an acceptance survey

Introducing quantum physics concepts and Dirac notation at the secondary school level: Insights into student reasoning from an acceptance survey

Convergence of Nanotechnology and Machine Learning: The State of the Art, Challenges, and Perspectives

QCA: Quantum Computational Approach for Internet of Things with 5G Connectivity

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