Superconducting and photonic qubits are the two promising platforms for quantum computation. This review investigates different materials that are being used to advance these platforms, detailing the structural, electrical, and thermal properties that influence qubit performance. The discussion on superconducting qubits covers material properties critical for achieving low-loss circuits, the impact of two-level system defects, and the engineering of Josephson junctions. In contrast, photonic qubits, which leverage light for quantum information processing, are examined through the lens of material platforms such as silicon-based photonics and III–V semiconductors. The chapter also highlights fabrication challenges, qubit coherence improvements, and recent advances in single-photon sources for scalable quantum systems. By analyzing the intersection of materials science, quantum mechanics, and device engineering, this review provides insights into the optimization of quantum hardware for future large-scale quantum computing applications.
Superconducting and photonic qubits are the two promising platforms for quantum computation. This review investigates different materials that are being used to advance these platforms, detailing the structural, electrical, and thermal properties that influence qubit performance. The discussion on superconducting qubits covers material properties critical for achieving low-loss circuits, the impact of two-level system defects, and the engineering of Josephson junctions. In contrast, photonic qubits, which leverage light for quantum information processing, are examined through the lens of material platforms such as silicon-based photonics and III–V semiconductors. The chapter also highlights fabrication challenges, qubit coherence improvements, and recent advances in single-photon sources for scalable quantum systems. By analyzing the intersection of materials science, quantum mechanics, and device engineering, this review provides insights into the optimization of quantum hardware for future large-scale quantum computing applications.
Superconducting qubits are a leading platform for quantum computation, yet decoherence and scalability challenges continue to limit progress toward fault-tolerant systems. This review synthesizes research on architectures, noise sources, and error correction to clarify performance trade-offs and guide development. The transition from Transmon to Fluxonium has dramatically improved qubit performance, achieving millisecond-scale coherence times. However, this success reveals a fundamental limit of coherence now being primarily restricted by the physical properties of the materials, specifically dielectric losses occurring at the Josephson junction leads and within the surrounding materials. As overcoming these material limits becomes increasingly difficult, system-level engineering determines whether high-coherence qubits can scale.Scaling quantum systems is difficult because current cooling and control systems create too much heat and this forces a shift to integrated digital superconducting circuits and cryogenic light-based links. While these hardware challenges restrict scaling, experiments in error correction show that logical qubits can already outperform physical ones. For example, a distance-7 surface code improved logical qubit lifetime by 2.4×. Achieving practical fault tolerance, however, requires moving beyond simple error models. Future systems must combine techniques like Dynamical Decoupling and Machine Learning-based Optimal Control with dynamic classical control capable of handling complex, correlated faults such as Multi-Bit Burst Errors. Progress in materials, cryogenic system integration for control, and adaptive error management must advance together to realize scalable, high-fidelity quantum hardware.
Quantum chips form the foundational hardware for quantum computing, promising transformative impacts across optimization, secure communications, and artificial intelligence. This paper surveys five leading qubit implementations—superconducting circuits, neutral-atom arrays, trapped ions, photonic systems, and silicon-based quantum dots—highlighting their distinct operating principles, recent milestones, and inherent trade-offs. Superconducting platforms leverage mature microfabrication to achieve hundreds to thousands of qubits with rapid gate times but require millikelvin environments and face millisecond-scale coherence limits. Neutral-atom and ion-trap architectures offer exceptionally long coherence (seconds to hours) and high-fidelity operations, making them ideal for quantum memory and precision simulation, yet scaling remains constrained by control complexity. Photonic chips excel at room-temperature operation and quantum networking via entangled photons, though deterministic two-qubit gates and on-chip integration pose challenges. Silicon quantum dots promise CMOS compatibility and sub-microsecond spin coherence, but demand atomic-scale fabrication precision and advanced cryogenic control. We analyze the tension between qubit count, error rates, and engineering practicality, and discuss emerging solutions such as hybrid integration, advanced error-correction codes, and novel materials. Looking ahead, coordinated optimization across these platforms—combining fast superconducting processors, long-lived atomic memories, photonic interconnects, and scalable silicon arrays—will be critical to transition quantum chips from research prototypes to industrially viable systems that redefine computing, communications, and AI.
Quantum information science is entering a second phase, the Quantum Evolution 2.0, in which the challenge has shifted from demonstrating coherent control of individual quantum states to building scalable multi-qubit processors and networks. This transition places materials science at the center of the field. Across superconducting circuits, quantum defects, quantum photonic devices, and emerging materials platforms, including two-dimensional materials and heterostructures, performance is now limited less by device design than by poorly controlled surfaces, buried interfaces, and defects whose atomic identities remain incompletely known. This review surveys the materials challenges of these quantum platforms together with the characterization methods needed to resolve them. For each platform we identify the dominant decoherence mechanisms, the current state of materials understanding, and the most pressing open materials problems. A cross-platform comparison then reveals a shared structure-coherence problem. The implicated material chemistry recurs across platforms, involving light elements in disordered or buried environments, yet no platform can quantitatively connect a specific atomic-scale structure to a measured change in coherence. We close by identifying three needs, mechanistic understanding of decoherence at the atomistic level, high-throughput proxy metrics predictive of device performance, and characterization tools built for quantum materials, whose resolution would advance coherence, scalability, and integration across all platforms.
Abstract Superconducting qubits are multilevel micro-fabricated artificial atoms based on superconducting materials. They are mainly operated in the low microwave frequency range (2–8 GHz) and require to be cooled below 20 mK to maintain quantum coherence. They enable precise engineering of transition frequencies and coupling strengths, facilitating advancements in quantum information processing and light-matter interactions. The field has evolved from early devices, characterized by short coherence times, to modern architectures with improved noise resilience, scalability, and fidelity. Better performances have been achieved through innovations in materials, fabrication, control electronics, and circuit design, enabling qubits with millisecond coherence times and gate fidelities exceeding 99.9%. However, challenges remain in mitigating two-level system defects, scaling devices, and addressing the cryogenic and infrastructure needs of larger quantum processing units. Current research focuses on modular and scalable architectures, error correction, and application. The field’s progress highlights the potential for superconducting qubits to drive advancements in quantum computation.
Superconducting materials have emerged as one of the most promising technologies for building quantum computers. These materials, characterized by their ability to conduct electricity without resistance at low temperatures, enable the creation of qubits, the fundamental units of quantum computation. This article explores the role of superconducting materials in quantum computing, focusing on their properties, applications in quantum systems, and the challenges faced in scaling quantum computers. We discuss the mechanisms behind superconductivity, the engineering advancements in superconducting qubits, and the future potential of this technology in the context of computational efficiency and scalability.
The superconducting qubit quantum computer is one of the most promising quantum computing architectures for large-scale integration due to its maturity and close proximity to the well-established semiconductor manufacturing infrastructure. From an education perspective, it also bridges classical microwave electronics and quantum electrodynamics. In this paper, we will review the basics of quantum computers, superconductivity, and Josephson junctions. We then introduce important technologies and concepts related to DiVincenzo's criteria, which are the necessary conditions for the superconducting qubits to work as a useful quantum computer. Firstly, we will discuss various types of superconducting qubits formed with Josephson junctions, from which we will understand the trade-off across multiple design parameters, including their noise immunity. Secondly, we will discuss different schemes to achieve entanglement gate operations, which are a major bottleneck in achieving more efficient fault-tolerant quantum computing. Thirdly, we will review readout engineering, including the implementations of the Purcell filters and quantum-limited amplifiers. Finally, we will discuss the nature and review the studies of two-level system defects, which are currently the limiting factor of qubit coherence time. DiVincenzo's criteria are only the necessary conditions for a technology to be eligible for quantum computing. To have a useful quantum computer, large-scale integration is required. We will review proposals and developments for the large-scale integration of superconducting qubit devices. By comparing with the application of electronic design automation (EDA) in semiconductors, we will also review the use of EDA in superconducting qubit quantum computer design, which is necessary for its large-scale integration.