Applications of quantum computing technology

Hafiz Md. Hasan Babu

Muhammad Azeem Akbar, Arif Ali Khan, Sami Hyrynsalmi

The emergence of 6 G technology heralds a groundbreaking era in digital connectivity, envisaging universal and seamless links. To address the intricate computational and security requirements of this revolution, the integration of quantum computing (QC) into these networks is perceived as a promising solution. The objective this study presents a comprehensive investigation into the potential roles and implications of QC within the context of 6 G technology. To address the objectives of this study, firstly, we have conducted literature survey to identify the key applications of using QC in 6 G technology. Secondly, we performed interview study with industry experts to identify the best practices related to the key application of QC in 6 G technology. Our study unfolds in two distinct stages: firstly, we identify 15 key applications of QC in 6 G technology and segmented into 4 core areas. Secondly, the literature findings were empirically validated by conducting interview study and identified 49 best practices related to one of the identified key applications of QC in 6 G technology. The outcomes of this research lay a solid foundation for understanding both the pivotal applications of QC in 6 G technology and the effective practices for its implementation, thus providing valuable insights to both academics and industry practitioners.

Ganesh Nagaraj, Niraj Upadhayaya, Atheer A. Matroud +3 more

Quantum computing is an emerging technology (QC). Several groups and research institutions are working to make quantum computing applications a reality. Artificial Intelligence (AI) is another emerging field that is becoming more established over time. The main goal of this research is to figure out how the advancement of quantum computing technology will affect AI applications. Computational methods are used to explore the growing influence of quantum computing development for a specific AI application. This study also discusses about the impact and potential of Quantum Computing (QC) on Artificial Intelligence (AI). These can be accomplished by employing cutting-edge methods to deliver usable, economically viable, and scalable technology across a wide range of industries. On the other hand, the risk of committing errors in quantum algorithms, as well as the inability to function without being super-cooled, emerges as a major challenge. Macro-energy systems and the development of sustainable energy materials are just two areas of science and engineering that quantum computing has the potential to completely transform.

Seiki Akama

Don Roosan, Rubayat Islam Khan

Ashutosh Bhatia, Sainath Bitragunta, Kamlesh Tiwari

This paper presents a layered architecture QC-Stack for the quantum computing domain. It is a comprehensive framework explaining quantum computing systems by identifying three fundamental layers: the physical, system, and application layers. Each plays a crucial role in implementing quantum computing systems in practice. The physical layer evaluates quantum hardware technologies based on crucial performance parameters such as qubit quality, connectivity, and scalability. The system layer, which includes quantum firmware, compilers, operating systems, and software development tools, bridges the gap between the physical and application layers. The application layer incorporates Quantum Programming Languages and algorithms, emphasizing their significance in leveraging quantum computing potential across various domains. The paper provides a comparative analysis at a higher level of existing quantum algorithms, protocols, and hardware and software technologies within each sub-layer. It also highlights the strengths and weaknesses of different technologies at each layer. This holistic model can guide researchers and practitioners, offering insights into the ever-evolving landscape of quantum technology.