Enabling Technologies for Scalable Superconducting Quantum Computing
Xanthe Croot, Kasra Nowrouzi, Christopher Spitzer, Carmen G. Almudever, Alexandre Blais, Malcolm Carroll, Jerry Chow, Daniel Friedman, Masao Tokunari, Edoardo Charbon, Vivek Chidambaram, Andrew N. Cleland, David Danovitch, Joseph Emerson, David Gunnarsson, Raymond Laflamme, John Martinis, Robert McDermott, William D. Oliver, Michel Pioro-Ladriere, Yoshiaki Sato, Hidenori Ohata, Kouichi Semba, Irfan Siddiqi
quant-phSubmitted Dec 17, 2025• Announced Dec 18, 2025• 0 citations
Experiments with superconducting quantum processors have successfully demonstrated the basic functions needed for quantum computation and evidence of utility, albeit without a sizable array of error-corrected qubits. The realization of the full potential of quantum computing centers on achieving large scale fault-tolerant quantum computers. Science, engineering and industry advances are needed to robustly generate, sustain, and efficiently manipulate an exponentially large computational (Hilbert) space as well as supply the number and quality components needed for such a scaled system. In this article, we suggest critical areas of quantum system and ecosystem development, with respect to the handling and transmission of quantum information within and out of a cryogenic environment, that would accelerate the development of quantum computers based on superconducting circuits.
Experiments with superconducting quantum processors have successfully demonstrated the basic functions needed for quantum computation and evidence of utility, albeit without a sizable array of error-corrected qubits. The realization of the full potential of quantum computing centers on achieving large scale fault-tolerant quantum computers. Science, engineering and industry advances are needed to robustly generate, sustain, and efficiently manipulate an exponentially large computational (Hilbert) space as well as supply the number and quality components needed for such a scaled system. In this article, we suggest critical areas of quantum system and ecosystem development, with respect to the handling and transmission of quantum information within and out of a cryogenic environment, that would accelerate the development of quantum computers based on superconducting circuits.
Quantum computing promises to revolutionize several scientific and technological domains through fundamentally new ways of processing information. Among its most compelling applications is digital quantum simulation, where quantum computers are used to replicate the behavior of other quantum systems. This could enable the study of problems that are otherwise intractable on classical computers, transforming fields such as quantum chemistry, condensed matter physics, and materials science. Despite this potential, realizations of practical quantum advantage for relevant problems are hindered by imperfections of current devices. This also affects quantum hardware based on superconducting circuits which is among the most advanced and scalable platforms. The envisaged long-term solution of fault-tolerant quantum computers that correct their own errors remains out of reach mainly due to the associated qubit number overhead. As a result, the field has developed strategies that combine quantum and classical resources, exploit hardware-native operations, and employ error mitigation techniques to extract meaningful results from noisy data. This doctoral thesis contributes to this broader effort by exploring methods for advancing quantum simulation across the full computational stack, including hardware-level innovations, refined techniques for noise modeling and error mitigation, and algorithmic improvements enabled by efficient measurement processing.
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.
Computational ecosystems in which classical supercomputers and general-purpose quantum computers provide a steady increase in value-creating computation capabilities have shown immense progress in recent years. Superconducting qubit technology, in particular, has emerged as a leading candidate for realizing a scalable quantum computing platform ready for paving the way to commercial quantum advantage. However, current academic approaches in fabrication and testing of quantum devices are not scalable and have already started to limit the rapid development of the field. Novel solutions are required to tackle the combined challenge of increasing the qubit count on a quantum processor and the need to further reduce the qubit’s error rates. This, in turn, will lead to a renewed acceleration in qubit manufacturing, test and diagnostics. Here we present aspects of how to move superconducting qubit manufacturing and testing from small-scale laboratory to large-scale fabrication facility environments. To enable this transfer, two key ingredients are demonstrated: (i) A foundry-compatible fabrication process of superconducting qubits that can benefit from the advanced process control in industry-scale CMOS fabrication facilities, and (ii) an acceleration of testing and cryogenic measurement throughput by using a milli-Kelvin cryo-CMOS signal multiplexer operating in near proximity to quantum devices and integrated qubit diagnostic and benchmarking tools with end-to-end data analytics. Although some of these elements have been explored independently, co-development is crucial to enable an efficient scalable development cycle for quantum computing technology. A full development cycle consisting of scalable manufacturing, testing, and benchmarking will enable the large-scale fabrication and control of quantum computing devices and thus pave the way to commercial quantum advantage.
Quantum computing is a novel paradigm for information processing that promises computational speedup for certain computational tasks while not being driven by Moore's law. Superconducting circuits based on Josephson junctions are one of the leading approaches for implementing the quantum bits, or qubits, in a quantum processor. Most superconducting qubit architectures involve circuit quantum electrodynamics, where the qubits are analogous to artificial atoms that are coupled to superconducting linear resonant cavities. This scheme allows for the readout of individual qubits, the manipulation of single-qubit states, and the generation of entanglement between qubits. The performance of current state-of-the-art systems is limited by decoherence of the qubits and associated gate errors. Nonetheless, experiments have been performed that already demonstrate a significant computational speedup compared to classical processing. Future implementations of fault-tolerant quantum computers will require the development of quantum error correction. Initial tests of elements of error correction in superconducting qubit arrays are underway.
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 holds the promise of solving problems that are intractable for classical computers, with applications ranging from optimization and materials simulation to cryptography. It achieves this by leveraging the exponentially scaling dimensionality of the space encoding quantum information and by executing algorithms on quantum registers in superposition states – a feature often referred to as quantum parallelism. However, while encoding information in computational units capable of exploring a continuous set of quantum states enables exponential scaling of computational power with system size, quantum systems are also more susceptible to errors than their classical counterparts. These errors take the form of both control errors, where miscalibration of the control pulses causes coherent errors on the qubit states, as well as incoherent errors due to energy relaxation and dephasing. Scaling quantum systems to run useful algorithms involving hundreds or thousands of logical qubits will require quantum error correction. In this approach, quantum information is redundantly encoded across an entangled state of many physical qubits. This has enabled experimental demonstrations across various platforms – including ion traps, superconducting circuits, and neutral atoms – showing that encoded quantum states can be preserved beyond the coherence times of the constituting physical qubits. However, quantum state preservation is only one component needed for scalable quantum computing. To execute algorithms, it is also necessary to implement quantum gates on and between encoded qubits, in a way that maintains fault tolerance by preserving the ability to correct errors as they occur during the computation. In the first part of this thesis, we demonstrate the implementation of an error-corrected quantum operation that entangles two logical qubits. This is achieved by performing lattice surgery on a distance-three surface code qubit, resulting in a logical Bell state encoded in distance-three repetition codes, which enable the correction of single bit-flip errors. We further introduce techniques to benchmark and characterize the performance of logical operations, including applying the protocol to arbitrary logical input states and performing logical quantum process tomography. Together, these results constitute one of the first realizations of error-corrected lattice surgery in superconducting circuits. While quantum error correction can correct errors provided they occur with sufficiently low frequency, it may fail when many qubits experience errors simultaneously. In the second part of this thesis, we therefore shift focus to a specific error mechanism known to cause correlated errors in superconducting circuits – quasiparticle-induced decoherence. In this case, various forms of energy deposition on the quantum device can break Cooper pairs into quasiparticles, which may subsequently diffuse to the tunnel junction and interact with the qubit state, thereby causing decoherence. In this thesis, we investigate the impact of quasiparticle tunneling on qubit performance, with a focus on infrared-induced quasiparticles. We compare the sensitivity of niobium-based qubits to those made from tantalum – a material that has gained interest in recent years following demonstrations of qubits with improved coherence times based on this material. Using a thermal radiator source, we show that the performance of tantalum qubits may be limited by infrared-induced quasiparticles in typical superconducting circuit experimental setups. By employing both ambient and in-line infrared filters, we investigate the effectiveness of different filtering strategies and develop best practices for engineering cryogenic environments for superconducting quantum processors. The results presented in this thesis contribute to the advancement of quantum computing based on superconducting circuits by implementing and characterizing quantum error-corrected operations, and by investigating quasiparticles as a source of decoherence, along with strategies to improve infrared filtering and signal conditioning in cryogenic environments for future fault-tolerant quantum computing.