Endohedral fullerenes as qubits: From synthesis to quantum computing applications
Jeong‐Seok Nam, Jiye Han, Jin‐Myung Choi, Franklin H. Cho, Daniel K. Park, Seong-Jin Park, Yoshifumi Hashikawa, Yasujiro Murata, Eunsang Kwon, Dong‐Hwan Kim, Junki Kim, Il Jeon
Abstract Since the 1980s, quantum computing has progressed significantly, evolving from theoretical models to early working devices. Due to their unique molecular structure, endohedral fullerenes offer long decoherence times, stable operation under ambient conditions, and cost‐effective fabrication, making them promising candidates for qubit implementation in quantum computing. In this review, we examine research efforts on endohedral fullerene‐based quantum computing across various platforms and molecular types, with a particular focus on the synthetic challenges that remain a critical bottleneck for practical device integration. This review classifies the different types of endohedral fullerene‐based quantum devices, explores their current limitations, and discusses future prospects. Endohedral fullerene‐based quantum technology has the potential to transform endohedral fullerene‐based quantum computing, enabling solutions to complex industrial problems and advancing the development of fault‐tolerant quantum technologies. image
Abstract Since the 1980s, quantum computing has progressed significantly, evolving from theoretical models to early working devices. Due to their unique molecular structure, endohedral fullerenes offer long decoherence times, stable operation under ambient conditions, and cost‐effective fabrication, making them promising candidates for qubit implementation in quantum computing. In this review, we examine research efforts on endohedral fullerene‐based quantum computing across various platforms and molecular types, with a particular focus on the synthetic challenges that remain a critical bottleneck for practical device integration. This review classifies the different types of endohedral fullerene‐based quantum devices, explores their current limitations, and discusses future prospects. Endohedral fullerene‐based quantum technology has the potential to transform endohedral fullerene‐based quantum computing, enabling solutions to complex industrial problems and advancing the development of fault‐tolerant quantum technologies. image
This chapter begins with a short introduction to the topic of quantum information processing. We presume only a very limited familiarity with quantum mechanics; in fact, all the really essential ideas, terminology and formalism will be introduced as we go along. The introductionwill discuss classical and quantum information, the qubit, entanglement, and the basic operations of quantum computer. It will include a brief look at how accelerated searching can be performed, and finally a discussion of the problem of decoherence and how to fight it. We will then introduce endohedral fullerenes, the key molecular building blocks that have been identified as promising components of a quantum technology. We will describe the synthesis of these structures, togetherwith the key experimental demonstrations of quantum phenomena.
Quantum computing has emerged as a transformative computational paradigm capable of addressing limitations increasingly encountered by classical computing systems as Moore’s law approaches physical and economic constraints. By leveraging quantum mechanical principles such as superposition, entanglement, and interference, quantum systems offer the potential for significant computational advantages in solving complex problems that are currently infeasible for conventional architectures. This review critically synthesizes recent advances in quantum computing by examining foundational principles, major algorithmic breakthroughs, evolving hardware platforms, and interdisciplinary real-world applications. A structured narrative literature review was conducted using major scientific databases, including PubMed, IEEE Xplore, Nature, ScienceDirect, and arXiv, with emphasis on peer-reviewed studies, landmark foundational research, and major industry developments published between 2018 and 2026. Key findings indicate substantial progress in superconducting, trapped ion, photonic, and topological quantum systems, alongside innovations in algorithms such as Shor’s, Grover’s, variational quantum methods, and quantum machine learning. Despite these advancements, major challenges including decoherence, noise, scalability limitations, and fault-tolerant error correction remain substantial barriers to commercial maturity. Future implications suggest quantum computing may profoundly influence artificial intelligence, cybersecurity, optimization, molecular simulation, and scientific discovery, particularly through hybrid classical-quantum systems and cloud-based democratization. Although practical deployment remains transitional, quantum computing is positioned to become a foundational technology with broad scientific, industrial, and societal implications.
ABSTRACT Solving quantum molecular systems presents a significant challenge for classical computation. The advent of early fault‐tolerant quantum computing devices offers a promising avenue to address these challenges, leveraging advanced quantum algorithms with reduced hardware requirements. This review surveys the latest developments in quantum computing algorithms for quantum molecular systems in the fault‐tolerant quantum computing era, covering encoding schemes, advanced Hamiltonian simulation techniques, and ground‐state energy estimation methods. We highlight recent progress in overcoming practical barriers, such as reducing circuit depth and minimizing the use of ancillary qubits. Special attention is given to the potential quantum advantages achievable through these algorithms, as well as the limitations imposed by dequantization and classical simulation techniques. The review concludes with a discussion of future directions, emphasizing the need for optimized algorithms and experimental validation to bridge the gap between theoretical developments and practical implementation for quantum molecular systems.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.
Quantum computing, grounded in the principles of superposition and entanglement, has emerged as a revolutionary paradigm with the potential to outperform classical systems in specific computational tasks. This paper presents a comprehensive survey of the foundational concepts, algorithmic developments, hardware architectures, and programming ecosystems in quantum computing. We analyze the current progress in key application areas such as cryptography, machine learning, optimization, and quantum chemistry. Furthermore, we review recent advances between 2023 and 2025, including developments in fault-tolerant architectures and quantum error correction. The paper also discusses the significant technical challenges that hinder large-scale practical deployment, including qubit scalability, decoherence, and programming limitations. By synthesizing literature across disciplines, this review aims to provide a holistic understanding of the quantum computing landscape and outline critical directions for future research and integration with classical systems.
Quantum computing (QC) has already entered the industrial landscape and several multinational corporations have initiated their own research efforts. So far, many of these efforts have been focusing on superconducting qubits, whose industrial progress is currently way ahead of all other qubit implementations. This paper briefly reviews the progress made on the silicon-based QC platform, which is highly promising to meet the scale-up challenges by leveraging the semiconductor industry. We look at different types of qubits, the advantages of silicon, and techniques for qubit manipulation in the solid state. Finally, we discuss the possibility of co-integrating silicon qubits with FET-based, cooled front-end electronics, and review the device physics of MOSFETs at deep cryogenic temperatures.