The greatest challenge in quantum computing is achieving scalability. Classical computing previously faced a scalability issue, solved with silicon chips hosting billions of fin field-effect transistors (FinFETs). These FinFET devices are small enough for quantum applications: at low temperatures, an electron or hole trapped under the gate serves as a spin qubit. Such an approach potentially allows the quantum hardware and its classical control electronics to be integrated on the same chip. However, this requires qubit operation at temperatures above 1 K, where the cooling overcomes heat dissipation. Here, we show that silicon FinFETs can host spin qubits operating above 4 K. We achieve fast electrical control of hole spins with driving frequencies up to 150 MHz, single-qubit gate fidelities at the fault-tolerance threshold, and a Rabi oscillation quality factor greater than 87. Our devices feature both industry compatibility and quality, and are fabricated in a flexible and agile way that should accelerate further development.

Silicon quantum dot spin qubits have great potential for application in large-scale quantum circuits as they share many similarities with conventional transistors that represent the prototypical example for scalable electronic platforms. However, for quantum dot formation and control, additional gates are required, which add to device complexity and, thus, hinder upscaling. Here, we meet this challenge by demonstrating the scalable integration of a multilayer gate stack in silicon quantum dot devices using self-alignment, which allows for ultra-small gate lengths and intrinsically perfect layer-to-layer alignment. We explore the prospects of these devices as hosts for hole spin qubits that benefit from electrically driven spin control via spin–orbit interaction. Therefore, we study hole transport through a double quantum dot and observe current rectification due to the Pauli spin blockade. The application of a small magnetic field leads to lifting of the spin blockade and reveals the presence of spin–orbit interaction. From the magnitude of a singlet-triplet anticrossing at a high magnetic field, we estimate a spin–orbit energy of ∼37μeV, which corresponds to a spin–orbit length of ∼48 nm. This work paves the way for scalable spin-based quantum circuits with fast, all-electrical qubit control.

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Pauli spin blockade (PSB) can be employed as a great resource for spin qubit initialisation and readout even at elevated temperatures but it can be difficult to identify. We present a machine learning algorithm capable of automatically identifying PSB using charge transport measurements. The scarcity of PSB data is circumvented by training the algorithm with simulated data and by using cross-device validation. We demonstrate our approach on a silicon field-effect transistor device and report an accuracy of 96% on different test devices, giving evidence that the approach is robust to device variability. The approach is expected to be employable across all types of quantum dot devices.

Pauli spin blockade (PSB) can be employed as a great resource for spin qubit initialisation and readout even at elevated temperatures but it can be difficult to identify. We present a machine learning algorithm capable of automatically identifying PSB using charge transport measurements. The scarcity of PSB data is circumvented by training the algorithm with simulated data and by using cross-device validation. We demonstrate our approach on a silicon field-effect transistor device and report an accuracy of 96% on different test devices, giving evidence that the approach is robust to device variability. The approach is expected to be employable across all types of quantum dot devices.