We review current status, prospects and challenges facing the realization of quantum processors based on silicon quantum dots. This platform represents an attractive pathway to full-scale quantum computing because of the long spin qubit coherence times available in silicon and its compatibility with CMOS manufacturing. Current benchmarks for qubit fidelity are discussed and processor architecture options presented. Key aspects determining the prospects for scaling to the millions of qubits required for fault-tolerant quantum computing are considered, including wiring overheads, quantum interconnects and processor operation temperature.
We review current status, prospects and challenges facing the realization of quantum processors based on silicon quantum dots. This platform represents an attractive pathway to full-scale quantum computing because of the long spin qubit coherence times available in silicon and its compatibility with CMOS manufacturing. Current benchmarks for qubit fidelity are discussed and processor architecture options presented. Key aspects determining the prospects for scaling to the millions of qubits required for fault-tolerant quantum computing are considered, including wiring overheads, quantum interconnects and processor operation temperature.
Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms give promise for the construction of a quantum computer based on millions of interacting qubits. However, the classical-quantum interface remains a nascent field of exploration. Here, we propose an architecture for a silicon-based quantum computer processor based on complementary metal-oxide-semiconductor (CMOS) technology. We show how a transistor-based control circuit together with charge-storage electrodes can be used to operate a dense and scalable two-dimensional qubit system. The qubits are defined by the spin state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.
Abstract Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms give promise for the construction of a quantum computer based on millions of interacting qubits. However, the classical-quantum interface remains a nascent field of exploration. Here, we propose an architecture for a silicon-based quantum computer processor based on complementary metal-oxide-semiconductor (CMOS) technology. We show how a transistor-based control circuit together with charge-storage electrodes can be used to operate a dense and scalable two-dimensional qubit system. The qubits are defined by the spin state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.
Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing. However, scaling to useful fault-tolerant processors will likely generate thermal loads that exceed the cooling power available at millikelvin temperatures. Raising the operating temperature eases cooling requirements but reduces gate fidelity, increasing the overhead of quantum error correction. Identifying the operating temperature that minimizes total power consumption is therefore a key challenge for commercially viable quantum computers. Here, we use gate set tomography to benchmark two-qubit silicon chips fabricated in both industrial and academic environments over a range of temperatures. Elevated temperatures substantially shorten coherence times and increase gate and state-preparation-and-measurement infidelities. Based on these measurements, we develop a general power model for silicon quantum computers that combines cryogenic cooling requirements with error-correction overheads. We show that a finite optimal operating temperature exists and is strongly influenced by a crossover temperature near 1 K in current devices, above which gate fidelity degrades rapidly. These results connect device-level fidelity limitations to system-level power requirements, providing design guidelines for large-scale silicon quantum computers.
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.
Qubits can be made out of a variety of experimental platforms, fig. 1. Small processors have already been demonstrated in trapped ions and superconductors but in both cases, the constraints for coherent manipulation and the effective large size of the qubits including all quantum functionalities are hardly compatible with very large-scale architecture. When it comes to the crucial issue of large-scale integration, Si spin qubits are well positioned due to their long coherence times and compatibility with semiconductor fabrication techniques. Indeed, dephasing times of the order of 1s have been achieved in Si-based spin qubits and single-qubit gate fidelities are high enough for scalable, fault-tolerant quantum computing.
Abstract Quantum computation (QC) is one of the most challenging quantum technologies that promise to revolutionize data computation in the long-term by outperforming the classical supercomputers in specific applications. Errors will hamper this quantum revolution if not sufficiently limited and corrected by quantum error correction codes thus avoiding quantum algorithm failures. In particular millions of highly-coherent qubits arranged in a two-dimensional array are required to implement the surface code, one of the most promising codes for quantum error correction. One of the most attractive technologies to fabricate such large number of almost identical high-quality devices is the well known metal-oxide-semiconductor technology. Silicon quantum processor manufacturing can leverage the technological developments achieved in the last 50 years in the semiconductor industry. Here, we review modeling, fabrication aspects and experimental figures of merit of qubits defined in the spin degree of freedom of charge carriers confined in quantum dots and donors in silicon devices along with classical electronics innovations for qubit control and readout. Furthermore, we discuss potential applications of the technology and finally we review the role of start-ups and companies in the silicon-based QC era.