Abstract The technological world is in the midst of a quantum computing and quantum information revolution. Since Richard Feynman’s famous ‘plenty of room at the bottom’ lecture (Feynman, Engineering and Science 23 , 22 (1960)), hinting at the notion of novel devices employing quantum mechanics, the quantum information community has taken gigantic strides in understanding the potential applications of a quantum computer and laid the foundational requirements for building one. We believe that the next significant step will be to demonstrate a quantum memory, in which a system of interacting qubits stores an encoded logical qubit state longer than the incorporated parts. Here, we describe the important route towards a logical memory with superconducting qubits, employing a rotated version of the surface code. The current status of technology with regards to interconnected superconducting-qubit networks will be described and near-term areas of focus to improve devices will be identified. Overall, the progress in this exciting field has been astounding, but we are at an important turning point, where it will be critical to incorporate engineering solutions with quantum architectural considerations, laying the foundation towards scalable fault-tolerant quantum computers in the near future.
Abstract The technological world is in the midst of a quantum computing and quantum information revolution. Since Richard Feynman’s famous ‘plenty of room at the bottom’ lecture (Feynman, Engineering and Science 23 , 22 (1960)), hinting at the notion of novel devices employing quantum mechanics, the quantum information community has taken gigantic strides in understanding the potential applications of a quantum computer and laid the foundational requirements for building one. We believe that the next significant step will be to demonstrate a quantum memory, in which a system of interacting qubits stores an encoded logical qubit state longer than the incorporated parts. Here, we describe the important route towards a logical memory with superconducting qubits, employing a rotated version of the surface code. The current status of technology with regards to interconnected superconducting-qubit networks will be described and near-term areas of focus to improve devices will be identified. Overall, the progress in this exciting field has been astounding, but we are at an important turning point, where it will be critical to incorporate engineering solutions with quantum architectural considerations, laying the foundation towards scalable fault-tolerant quantum computers in the near future.
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.
Few technological ideas in recent memory have stirred as much excitement—or skepticism—as quantum computing. The promise is genuine: for certain computational tasks, a quantum machine can do in seconds what would take a classical supercomputer longer than the age of the universe. At the heart of realising that promise is the qubit, the quantum analogue of a classical bit, and among the many physical systems that can host a qubit, superconducting circuits have quietly become the frontrunner. They can be fabricated in the same cleanrooms used to make conventional chips, controlled with ordinary microwave electronics, and scaled up in ways that other approaches cannot yet match. This thesis traces the full arc from first principles to working code. We start with the quantum mechanics a reader needs—superposition, entanglement, measurement—and build from therethrough the physics of superconductivity to the engineering of real qubit circuits. A key character in that story is the Josephson junction: a thin sandwich of metal and insulator whose quirky nonlinear behaviour is what makes the whole enterprise of superconducting qubits possible. A major focus of this work is the surface code, a topological quantum error-correcting code widely regarded as the most promising approach for achieving fault-tolerant quantum computation. We provide a rigorous analysis of the surface code’s lattice structure, stabilizer formalism, syndrome extraction, and decoding algorithms—in particular the minimum-weight perfect matching (MWPM) algorithm. A full Python/Qiskit implementation of a distance-3 surface code is presented, including qubit initialization, syndrome measurement circuits, error simulation, and decoding logic. We close by looking ahead. Modular processors, 3D circuit integration, and the long road to fault-tolerant machines are all on the horizon, and we try to give an honest assessment of where things stand and what the real obstacles are. Throughout, the goal has been to bridge theory and practice—to be precise enough to be useful, but grounded enough to stay connected to what is actually happening in laboratories today.
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.
Fault-tolerant quantum computing is required to execute many of the most promising quantum applications. In recent years, numerous error correcting codes, such as the surface code, have emerged which are well suited for current and future limited connectivity 2-D devices. We find quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5-D architecture, can efficiently implement surface codes with around 20× fewer transmons via this work. We virtualize 2-D memory addresses by storing the code in layers of qubit memories connected to each transmon. Distributing logical qubits across many memories has minimal impact on fault tolerance and results in substantially more efficient logical operations. Virtualized logical qubit (VLQ) systems can achieve fault tolerance comparable to conventional 2-D transmon-only architectures while putting within reach a proof-of-concept experimental demonstration of around ten logical qubits, requiring only 11 transmons and 9 attached cavities.
Quantum computing has reached a pivotal inflection point with the recent demonstration ofbelow-threshold quantum error correction and the emergence of logical qubits that outperformtheir physical counterparts. This review synthesizes the remarkable progress achieved between2024 and 2026 across multiple quantum hardware platforms, including superconducting circuits,trapped ions, and neutral atom arrays. We examine the theoretical foundations of quantumerror correction codes, with particular emphasis on surface codes and the rapidly advancingquantum low-density parity-check (qLDPC) codes. Key experimental milestones are analyzed,including Google’s Willow chip demonstration of exponential error suppression, IBM’s modularfault-tolerant roadmap culminating in the Starling system, IonQ’s achievement of 48 logicalqubits with a 2:1 encoding ratio, and QuEra’s record-efficiency neutral atom error correctionapproaching the Teraquop regime. The review further explores critical enabling technologiessuch as real-time decoding architectures, magic state distillation protocols, and fault-tolerant gateimplementations. We discuss the remaining challenges in scaling to hundreds of logical qubits,achieving practical logical error rates of 10−10 to 10−15, and realizing end-to-end fault-tolerantalgorithms. By synthesizing these developments, this article provides a comprehensive assessmentof the field’s trajectory toward practical fault-tolerant quantum computing and identifies the keymilestones that will define the next phase of progress.
To run a practical size of quantum program, computer architects have been making tremendous efforts to realize fault-tolerant quantum computing (FTQC) which constructs a fault-tolerant logical qubit by correcting many erroneous physical qubits during runtime. However, it is extremely challenging to build a full-stack FTQC system consisting of heterogeneous stacks, where each stack incurs unique challenges regarding the fault tolerance and the interplay of the challenges incurs very complicated overall design choice problem. Therefore, computer architects must fully understand stack-specific optimizations and their system-level trade-offs, and resolve all the challenges together. In this article, we first introduce critical design challenges in architecting an FTQC system built on the superconducting technology, and then present our research outcomes to resolve the challenges to build an FTQC system realizing thousands of logical qubits. We also outline near-future directions to resolve the remaining challenges and provide insights toward realizing more scalable future FTQC systems.