Superconducting qubits have emerged as leading candidates for realizing quantum computers, which are particularly useful for solving computational problems that are beyond the capabilities of classical supercomputers. The performance of such systems critically depends on the precision and reliability of their control infrastructure. In this paper, we present an overview of state-of-the-art quantum control systems, including both closed- and open-source solutions, and discuss their respective advantages and limitations. While we review both categories, we focus more extensively on open-source control platforms and explore how their flexibility and programmability can support the research community and drive progress in the field. Lastly, we outline several promising research directions in quantum computing infrastructure, including scalable control, high-precision readout, and leakage suppression. We believe that these areas should be prioritized by the community, as they are critical to realizing fault-tolerant quantum computation.
Superconducting qubits have emerged as leading candidates for realizing quantum computers, which are particularly useful for solving computational problems that are beyond the capabilities of classical supercomputers. The performance of such systems critically depends on the precision and reliability of their control infrastructure. In this paper, we present an overview of state-of-the-art quantum control systems, including both closed- and open-source solutions, and discuss their respective advantages and limitations. While we review both categories, we focus more extensively on open-source control platforms and explore how their flexibility and programmability can support the research community and drive progress in the field. Lastly, we outline several promising research directions in quantum computing infrastructure, including scalable control, high-precision readout, and leakage suppression. We believe that these areas should be prioritized by the community, as they are critical to realizing fault-tolerant quantum computation.
Quantum computation has emerged as a prominent research field with the potential to revolutionize information processing. Recent advancements have focused on extending qubit coherence times and enhancing error correction and fault-tolerant protocols, achieving coherence time to gate time ratios as high as 10⁸ and reducing error rates to as low as 0.143% ± 0.003% per cycle for 101 qubit system. The next critical challenge lies in scaling up qubit systems to support large-scale quantum computation that exceeds the performance of classical supercomputer. In this study, we summarize the working mechanisms, physical properties, gate operations, and limitations of three leading qubit platforms—superconducting qubits, trapped-ion qubits, and neutral atom qubits. Through a systematic comparison, we identify the key challenges that hinder qubit system scalability. Finally, we outline future research directions to address these challenges, including exploring the fundamental physics underpinning long coherence times, improving control tools such as laser systems, enhancing material quality and fabrication precision, and investigating hybrid quantum architectures. We hope this study offers a valuable perspective for researchers working toward the development of scalable and reliable quantum computing systems.
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 computing has made significant strides, with hardware platforms now advanced enough to tackle the challenges of scaling up to larger and more robust systems. Central to this progression is the interface between quantum processors, comprising isolated qubits, and the classical systems required for their control and readout. As these systems transition from few-qubit devices to fault-tolerant architectures, the complexity of this quantum-classical interaction poses significant engineering challenges. Field-Programmable Gate Arrays (FPGAs) have emerged as an adaptable and efficient solution, offering realtime control, low-latency operations, and seamless integration. This review delves into current FPGA-based platforms, including commercial systems, as well as open-source solutions developed by academic research groups. The architecture, features, and contributions of these platforms to addressing scalability and integration issues are thoroughly examined. Additionally, the review highlights innovations in cryogeniccompatible controllers and explores the potential of Cryo-FPGAs to reduce noise and improve fidelity in quantum systems. By providing a comprehensive analysis of current technologies and identifying opportunities for advancement, this review offers valuable insights for researchers and engineers working to develop scalable quantum computing solutions.
Abstract Superconducting quantum computing has emerged as a leading platform in the pursuit of practical quantum computers, driven by rapid advances from industry, academia, and government initiatives. This review examines the state of superconducting quantum technology, with emphasis on qubit design, processor architecture, scalability, and supporting quantum software. We compare the hardware strategies and performance milestones of key players—including IBM Quantum, Google Quantum AI, Rigetti Computing, Intel Quantum, QuTech, and Oxford Quantum Circuits—highlighting innovations in qubit coherence, control, and system integration. Landmark demonstrations such as quantum supremacy experiments are discussed alongside progress toward real-world applications in the noisy intermediate-scale quantum (NISQ) era. Beyond hardware, attention is given to the broader software and service ecosystem, including quantum programming frameworks, operating environments, and cloud-accessible platforms such as Amazon Braket, Azure Quantum, and OriginQ Cloud, which enable remote access and algorithm development. Persistent challenges in superconducting quantum computing—such as error correction, system stability, and large-scale integration—are assessed in light of emerging approaches aimed at fault-tolerant quantum computing. As the field moves from the NISQ era toward fault-tolerant quantum computing, we capture the defining hardware achievements and characteristics of current superconducting processors, while examining the ongoing efforts and challenges in overcoming NISQ-era limitations. These developments offer critical insights into the path toward scalable quantum systems and their transformative impact on future technologies, while also underscoring the strategic and societal considerations that require balancing innovation with responsible oversight and thoughtful governance.
Quantum computation exploits superposition, entanglement, interference, and measurement to process information.Research has moved from theoretical algorithms to functional devices where the performance is not only limited by qubit physics, but also by the control, compilation, error mitigation, and error correction.This review considers quantum computing on various levels of abstraction, including physical qubits, quantum algorithms, system architecture, fault-tolerance, and emerging applications.Study-specific evidence regarding scale, operational quality, connectivity, control and suppression of errors is compared across the different types of superconducting circuits, trapped ions, semiconductor spin qubits, neutral atoms and photonic processors.The review of the fundamental algorithms, noisy intermediate-scale quantum computing, variational and hybrid quantum-classical approaches, quantum simulation, quantum machine learning, and security implications is also discussed.Measurable progress has been demonstrated in published experiments for logical-qubit operation, below-threshold surface-code memory, programmable photonic sampling and platformspecific scaling.However, the reported metrics are not directly interchangeable, and practical advantage remains task-and baseline-dependent.Further progress will need to be accompanied by coordinated developments in hardware reliability, error correction, classical control, estimates of algorithmic resources, and clear classical method comparisons.
Superconducting qubits are leading candidates in the race to build a quantum computer capable of realizing computations beyond the reach of modern supercomputers. The superconducting qubit modality has been used to demonstrate prototype algorithms in the noisy intermediate-scale quantum (NISQ) technology era, in which non-error-corrected qubits are used to implement quantum simulations and quantum algorithms. With the recent demonstrations of multiple high-fidelity, two-qubit gates as well as operations on logical qubits in extensible superconducting qubit systems, this modality also holds promise for the longer-term goal of building larger-scale error-corrected quantum computers. In this brief review, we discuss several of the recent experimental advances in qubit hardware, gate implementations, readout capabilities, early NISQ algorithm implementations, and quantum error correction using superconducting qubits. Although continued work on many aspects of this technology is certainly necessary, the pace of both conceptual and technical progress in recent years has been impressive, and here we hope to convey the excitement stemming from this progress.