Quantum Phase Machines argues that the central obstacle to scalable quantum computing is not noise, materials, or fabrication — but the unit of information itself.After two decades of engineering progress, superconducting quantum processors still rely on fragile single-particle quantum states protected by massive error-correction overheads. This book proposes a different approach: encode information in the collective phase of macroscopic superconducting domains rather than in individual qubits. By exploiting the intrinsic rigidity of phase-locked Cooper pair ensembles, it suggests that error suppression can be achieved natively at the hardware level, without the exponential overhead of quantum error-correcting codes.The argument is developed in four parts. Part I reframes the decoherence problem in engineering terms and introduces the dynamic impedance principle underlying collective robustness. Part II proposes a physical model of structured photons and electrons that reinterprets superconductivity, entanglement, and coherence as geometric properties of extended electromagnetic systems. Part III defines the Temporal Bit (T-bit) architecture and its gate operations using existing Josephson-junction technology. Part IV presents an experimental roadmap with falsifiable predictions and concrete device proposals.Written for physicists and engineers fluent in Maxwell’s equations and solid-state physics, Quantum Phase Machines offers a radical but testable alternative to orthodox quantum computing architectures. Whether ultimately confirmed or refuted, its central claim is precise: scalable quantum computation will require exploiting collective physical structure, not merely protecting fragile quantum states.
Quantum Phase Machines argues that the central obstacle to scalable quantum computing is not noise, materials, or fabrication — but the unit of information itself.After two decades of engineering progress, superconducting quantum processors still rely on fragile single-particle quantum states protected by massive error-correction overheads. This book proposes a different approach: encode information in the collective phase of macroscopic superconducting domains rather than in individual qubits. By exploiting the intrinsic rigidity of phase-locked Cooper pair ensembles, it suggests that error suppression can be achieved natively at the hardware level, without the exponential overhead of quantum error-correcting codes.The argument is developed in four parts. Part I reframes the decoherence problem in engineering terms and introduces the dynamic impedance principle underlying collective robustness. Part II proposes a physical model of structured photons and electrons that reinterprets superconductivity, entanglement, and coherence as geometric properties of extended electromagnetic systems. Part III defines the Temporal Bit (T-bit) architecture and its gate operations using existing Josephson-junction technology. Part IV presents an experimental roadmap with falsifiable predictions and concrete device proposals.Written for physicists and engineers fluent in Maxwell’s equations and solid-state physics, Quantum Phase Machines offers a radical but testable alternative to orthodox quantum computing architectures. Whether ultimately confirmed or refuted, its central claim is precise: scalable quantum computation will require exploiting collective physical structure, not merely protecting fragile quantum states.
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.
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.
Build quantum computers using superconducting qubits and microwave cavity technology Creating qubits with sufficiently long coherence times remains one of the central challenges in building practical quantum computers. Quantum Computing with Superconducting Qubits and Cavities unites the latest advances in superconducting qubits, ultra-high-Q microwave cavities, and cavity–transmon architectures that are emerging as one of the leading platforms for scalable, fault-tolerant quantum computing. By combining conceptual insight with practical implementation, the book equips readers to understand not only how these systems work, but why they are at the forefront of the quantum technology revolution. The book explores quantum computation using bosonic modes, Fock states, qudits, quantum memories, and modern bosonic error-correcting codes including cat, binomial, and GKP encodings. Fundamental concepts are developed through clear physical explanations, while rigorous mathematical treatments are introduced where needed to provide a deeper understanding. Dedicated reviews of the underlying principles of quantum physics make the material accessible to newcomers without sacrificing the depth expected by researchers and practicing engineers. Quantum Computing with Superconducting Qubits and Cavities also includes: Design principles and operation of superconducting transmon qubits integrated with high-coherence microwave cavities for scalable quantum architectures. Bosonic quantum error-correction strategies that dramatically extend coherence and move quantum computing closer to fault-tolerant operation. Applications of quantum computing, including integer factoring, database searching, quantum chemistry, condensed-matter physics, and materials science simulations beyond the reach of classical computers. Materials science, fabrication methods, and surface treatments that continue to drive record improvements in qubit and cavity coherence. The global race toward quantum computing, including major international investments and the rapidly expanding role of superconducting quantum technologies. Written for physicists, materials scientists, electrical engineers, computer scientists, graduate students, and researchers entering quantum information science, this book provides both the theoretical foundation and the practical knowledge needed to engage with one of the fastest-growing fields in modern science and engineering.
Quantum processing units (QPUs) built on superconducting Josephson junctions remain the most industrially mature route to fault-tolerant quantum computing, but the field has moved substantially since early 2025. This paper provides an updated overview of Josephson-junction QPUs, grounded in the quantum-mechanical principles, superposition, entanglement, and decoherence, that any qubit implementation must contend with, and in the physics of Cooper pairing and quantum tunneling that make a Josephson junction behave as a controllable qubit. We examine the engineering challenges of scaling these devices, including crosstalk, classical control-interface bottlenecks, and quantum error correction, and discuss the first below-threshold surface-code demonstrations on superconducting hardware. We survey recent materials advances, near-term computational results, and applications beyond computing, and compare Josephson-junction QPUs against trapped-ion, photonic, and neutral-atom alternatives, the latter having emerged as a serious fourth architecture since our original analysis. We close with the current public roadmaps toward fault-tolerant superconducting quantum computers and a calibrated assessment of how much progress those roadmaps still require.
The pursuit of a universal, fault-tolerant quantum computer has transformed quantum computing from a predominantly theoretical discipline into a rapidly diversifying hardware ecosystem. This review presents a comprehensive and technically grounded analysis of the principal physical qubit modalities: superconducting circuits, trapped ions, photonic platforms, neutral atoms, semiconductor spin qubits, and topological approaches, focusing on their underlying operating principles, performance characteristics, and system-level constraints. We examine how these qubit technologies are embedded within scalable quantum processor architectures, including control and readout infrastructures, connectivity topologies, and quantum error correction strategies. The review provides a comparative study of key performance metrics, such as coherence times, gate fidelities, error rates, and scalability, reveals fundamental trade-offs between speed, robustness, and operational complexity that shape distinct technological roadmaps and target applications. We further highlight the ongoing transition from noisy intermediate-scale quantum (NISQ) devices toward architectures centred on logical qubits, driven by advances in materials engineering, precision control, and quantum information theory. Together, these developments sketch the emerging routes toward fault-tolerant quantum computing and practical quantum advantage, while offering readers a coherent entry point and reference guide to the current quantum hardware landscape.
Quantum computers now show the promise of surpassing any possible classical machine. However, errors limit this ability and current machines do not have the ability to implement error correcting codes due to the limited number of qubits and limited control. Therefore, dynamical decoupling (DD) and encodings that limit noise with fewer qubits are more promising. For these reasons, we put forth a model of universal quantum computation that has many advantages over strategies that require a large overhead such as the standard quantum-error correcting codes. First, we separate collective noise from individual noises on physical qubits and use a decoherence-free subspace that uses just two qubits for its encoding to eliminate collective noise. Second, our bath model is very general as it uses a spin-boson-type bath but without any Markovian assumption. Third, we are able to either use a steady global magnetic field or to devise a set of DD pulses that remove much of the remaining noise and commute with the logical operations on the encoded qubit. This allows removal of noise while implementing gate operations. Numerical support is given for this hybrid protection strategy which provides an efficient approach to deal with the decoherence problems in quantum computation and is experimentally viable for several current quantum computing systems. This is emphasized by a recent experiment on superconducting qubits which shows promise for increasing the number of gates that can be implemented reliably with some realistic parameter assumptions.