Quantum technology can improve the control level of a physical system to the quantum level by implementing functions and reaching a performance that are not possible using classical technologies. Quantum technology is evolving and showing an increasing impact on computing, communication, and sensing. It leverages the nature of basic science measuring with quantum-level phenomena and demands top engineering skills in various technical fields toward increasing the number of qubits and achieving simultaneous high-fidelity control of several qubits, which are essential to achieve a quantum advantage.

This special issue is intended to showcase the state of the art in various areas of quantum technology and related areas through contributions that involve theories, materials, devices, systems, and software. This Call for Papers welcomes original contributions that reflect the current state of research and trends. In addition, studies revealing the transverse and multidisciplinary nature of quantum technology are appreciated. This special issue covers various essential areas of quantum technology and recent research activities. The topics of interest include but are not limited to quantum technology and artificial intelligence (AI).

AI is pervasive in several fields and offers substantial practical benefits. Machine learning and deep learning enable machines to analyze large volumes of data, learn, offer recommendations, and make decisions. However, current AI and machine learning models are limited to solving specific problems in a narrow domain and present major limitations and diverse concerns. We look forward to receiving contributions in next-generation AI, which features better capabilities and addresses current limitations and concerns. To realize next-generation AI, researchers and developers are actively working in several areas, including enhanced explainability, improved trust and reliability, new AI paradigms (for example, federated learning, bio-inspired AI models, neuro-symbolic AI, and quantum AI), specialized AI hardware, software, and data models, enriched AI–human collaboration (that is, collaborative intelligence), and artificial general intelligence. Overall, next-generation AI is a highly capable, exciting, and challenging subject.

This special issue examines quantum technology and next-generation AI from the viewpoint of advances and applications that will shape the future:

• Quantum information, computing, simulation, and machine learning
• Quantum cryptography and networking
• Quantum sensing and metrology
• Quantum control based on classical engineering
• Quantum algorithms and software
• Quantum entanglement and teleportation
• Quantum materials
• Ultralow-power RISC-V processors
• Ultralow-power neuromorphic circuits and systems
• Human-body communication circuits and systems
• Advanced packaging technologies and system integration (including thermal management)
• Devices and accelerators for machine learning
• Processing-in-memory designs
• Architectures for efficient AI computing
• Domain-specific architectures of generative pretrained transformers
• Supercomputer-class system management for training and inference using generative pretrained transformers
• Ultralow-power computing to accelerate the execution of generative pretrained transformers on edge devices
• Floating-point unit architectures for efficient computation of generative pretrained transformers
• On-chip cache memory architectures for handling massive training data of generative pretrained transformers
• Parallel-qubit simulation methods for quantum computing
• Parallelization and optimization of quantum simulation using throughput processors (for example, GPU, NPU, GPT-NPU)


Important Dates (tentative)
- Paper submission: March 10, 2024
- First decision: May 20, 2024
- Final decision: July 20, 2024
- Publication: October 20, 2024

Paper Submission
- Papers should be submitted at https://mc.manuscriptcentral.com/etrij and adhere to the journal’s Author Guidelines.

Section Editor
- Ho-Young Cha, Hongik University, Republic of Korea; hcha@hongik.ac.kr

Guest Editors
- Shiho Kim, Yonsei University, Republic of Korea; shiho@yonsei.ac.kr
- Daewoong Kwon, Hanyang University, Republic of Korea; dw79kwon@hanyang.ac.kr
- Ji-Hoon Kim, Ewha Woman’s University, Republic of Korea; jihoonkim@ewha.ac.kr


The Editorial Office can be contacted at etrij@etri.re.kr.