Semiconductor spin qubits based on spin-orbit states are responsive to electric field excitation allowing for practical, fast and potentially scalable qubit control. Spinelectric susceptibility, however, renders these qubits generally vulnerable to electrical noise, which limits their coherence time. Here we report on a spin-orbit qubit consisting of a single hole electrostatically confined in a natural silicon metal-oxidesemiconductor device. By varying the magnetic field orientation, we reveal the existence of operation sweet spots where the impact of charge noise is minimized while preserving an efficient electric-dipole spin control. We correspondingly observe an extension of the Hahn-echo coherence time up to 88 µs, exceeding by an order of magnitude the best reported values for hole-spin qubits, and approaching the state-of-the-art for electron spin qubits with synthetic spin-orbit coupling in isotopically-purified silicon. This finding largely enhances the prospects of silicon-based hole spin qubits for scalable quantum information processing.

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A method to characterize the interface of InGaN/GaN quantum wells by X‐ray reflectivity is presented. The interface roughness can be obtained from the ratio of diffuse to specular scatterings obtained on a transverse ω‐scan. Rotation around the azimuthal φ angle allows for information about the directionality of the roughening mechanisms to be obtained. The method allows for quick identification of the presence or absence of gross well width fluctuations in the quantum well, providing that the interface is chemically sharp. When the interface exhibits chemical grading, compositional fluctuations across the terraced structure of the quantum well surface lead to aggravated roughness as the barrier is grown, which may be misinterpreted as gross well width fluctuations. This method carries promises for complementing analysis by transmission electron microscopy as it is non‐destructive, fast, and allows multi‐directional characterization of the roughness. It would therefore be particularly useful to detect process deviation in a production line, where prior knowledge of the sample is already available.