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Stefan Kubicek

Publications and source records attributed to Stefan Kubicek.

At least 19 recordsLinked to original sources

SiMOS quantum-dot spin qubits enabled by extreme-ultraviolet lithography

The realization of large-scale silicon quantum processors requires spin qubits compatible with advanced semiconductor manufacturing technologies, demanding lithographic processes that combine nanometer-scale precision with exceptional uniformity. Although the highest-performing silicon spin qubits demonstrated to date have relied on electron-beam (e-beam) lithography, its serial exposure process limits reproducibility studies and wafer-scale fabrication. Here, we demonstrate high-performance silicon metal-oxide-semiconductor (SiMOS) spin qubits fabricated using extreme-ultraviolet (EUV) lithography in a 300 mm semiconductor pilot line. We report wafer-scale quantum-dot uniformity metrics, including 100 % room-temperature gate-to-gate leakage yield and sub-nanometer control of critical gate dimensions. We characterize four double-dot systems realized in two triple-quantum-dot devices. Gate set tomography (GST) reveals consistently high fidelities across all four systems, with values up to 99.8 % for SPAM, 99.9 % for single-qubit gates, and 99.1 % for two-qubit gates. The devices exhibit highly reproducible exchange turn-on characteristics of 10-13 dec/V, indicating high fabrication uniformity enabled by EUV patterning. These results establish EUV lithography as a viable manufacturing technology for quantum processors based on high-fidelity SiMOS spin qubits.

cond-mat.mes-hall

Eight-Qubit Operation of a 300 mm SiMOS Foundry-Fabricated Device

Silicon spin qubits are a promising platform for quantum computing due to their high coherence, controllability, and CMOS manufacturability, yet scalable implementations have so far been limited to a few qubits. Here, to take a step towards larger qubit systems, we tune and coherently control an eight-dot linear array of silicon spin qubits fabricated in a 300~mm CMOS-compatible foundry process, establishing operational scalability beyond the two-qubit regime. All eight qubits are successfully tuned and characterized as four double-dot pairs, exhibiting Ramsey dephasing times $T_2^*$ up to 41(2)$~μ$s and Hahn-echo coherence times $T_2^{\mathrm{Hahn}}$ up to 1.31(4)$~$ms. Readout of the central four qubits is achieved via a cascaded charge-sensing protocol, enabling high-fidelity measurements of the entire multi-qubit array in a two step process. Additionally, we demonstrate a two-qubit gate operation between adjacent qubits with low phase noise. We show that silicon spin qubit arrays can be scaled to medium-sized arrays of 8 qubits while maintaining system coherence.

quant-ph

Concatenated continuous driving of silicon qubit by amplitude and phase modulation

The rate of coherence loss is lower for a qubit under the Rabi drive than a freely evolving qubit $T_{2}^{\rm{Rabi}}>T_{2}^*$. Building on this principle, concatenated continuous driving (CCD) keeps the qubit under continuous drive to suppress noise and manipulate dressed states by either phase or amplitude modulation. In this work, we propose a variant of CCD which simultaneously modulates both the amplitude and phase of the driving field to generate a circularly polarized field in the rotating frame of the carrier frequency. This circular-modulated CCD(CMCCD) cancels the counter-rotating term in the second rotating frame, eliminating a systematic pulse-area error that arises from an imperfect rotating wave approximation for fast gates. Numerical simulations demonstrate that the proposed CMCCD achieves higher gate fidelity than conventional CCD schemes. We further implement and compare different CCD protocols using an electron spin-qubit in an isotopically purified $^{28}$Si-MOS quantum dot and evaluate its robustness by applying static detuning and Rabi frequency errors. The robustness is significantly improved compared with the standard Rabi drive, showing the effectiveness of this scheme for qubit arrays with variation in qubit frequency, coupling to the Rabi drive, and low-frequency noise. The proposed scheme can be applied to various physical systems, including trapped atoms, cold atoms, superconducting qubits, and NV centers.

quant-ph

Understanding oxide-thickness-dependent variability in dense Si-MOS quantum dot arrays

Achieving uniform and scalable control of semiconductor spin qubits remains a key challenge for large scale quantum computing. In this work, we investigate how gate oxide thickness influences uniformity in dense two dimensional silicon quantum dot arrays. Using a 7 x 7 array fabricated in a 300 mm CMOS-process patterned by EUV lithography, we statistically characterize 392 quantum dots across four different oxide thicknesses. The threshold voltages, capacitances, lever arms, and charging energies are extracted using parallel row based measurements and we identify an optimal SiO2 thickness of 17 nm that minimizes threshold voltage variability below 63 mV standard deviation. Our observations illustrate how multiple sources of disorder can introduce competing oxide-thickness dependencies, resulting in non-monotonic trends. These results provide key design guidelines for dense, scalable silicon spin qubit architectures.

quant-ph

Valley enhanced Rabi frequency in n-type planar Silicon-MOS quantum dot

Electron spin resonance spectroscopy (ESR) of a single electron in planar Si-MOS quantum dot is reported in the vicinity of a valley level anti-crossing. A number of one and two-photon resonances are observed due to mixing of magnetic spin-flip and electric valley-flip transitions. This allows the reconstruction of the energy-level diagram of a four state system with two valley and two spin states. Near the anti-crossing, an enhancement of the Rabi frequency is observed. This is attributed to an electric-dipole transition activated by admixing of the upper energy level due to inter-valley spin coupling. The electric-dipole transition may be driven via capacitive coupling between the ESR antenna, and the confinement gate. To characterize spin-valley coupling responsible for the enhancement, we measure the anisotropy of the g-factor difference between the two valley states, the mean g-factor and the inter-valley spin coupling for both in and out-of-plane magnetic fields. The inter-valley spin coupling is strongly modulated by the direction of the B-field, and is strongest for out-of-plane B-field, consistent with an in-plane spin-valley field. In principle, this strong Electric dipole spin resonance (EDSR) effect could be utilized for fast all-electrical spin control in small-scale devices.

cond-mat.mes-hall

Radiofrequency cascade readout of coupled spin qubits

Silicon spin qubits based on metal-oxide-semiconductor (MOS) technology are compatible with semiconductor manufacturing and offer a route to scalable quantum processing. However, spin readout typically relies on proximal charge sensors, which add architectural complexity and limit qubit connectivity. In situ dispersive readout techniques are more compact, which can alleviate these constraints, but exhibit limited sensitivity. Here we report a radiofrequency electron-cascade readout method that enhances the dispersive signal through alternating-current electron co-tunnelling. With this approach, we achieve an enhancement in signal-to-noise ratio of more than $35~$dB, leading to a minimum integration time of $7.6 \pm 0.2~μ$s. We demonstrate singlet-triplet readout of two-electron spins in a natural silicon planar MOS quantum dot array, and coherent spin control using the exchange interaction, which forms the basis for entangling gates. We find dephasing times of up to $500~$ns and a gate quality factor that exceeds 10.

cond-mat.mes-hall

A current source with metrological precision made on a 300mm silicon MOS process

Although the measurement of current is now defined with respect to the electronic charge, producing a current standard based on a single-electron source remains challenging. The error rate of a source must be below 0.01 ppm, and many such sources must be operated in parallel to provide practically useful values of current in the nanoampere range. Achieving a single electron source using an industrial grade 300 mm wafer silicon metal oxide semiconductor (MOS) process could offer a powerful route for scaling, combined with the ability for integration with control and measurement electronics. Here, we present measurements of such a single-electron source indicating an error rate of 0.008 ppm, below the error threshold to satisfy the SI Ampere, and one of the lowest error rates reported, implemented using a gate-defined quantum dot device fabricated on an industry-grade silicon MOS process. Further evidence supporting the accuracy of the device is obtained by comparing the device performance to established models of quantum tunnelling, which reveal the mechanism of operation of our source at the single particle level. The low error rate observed in this device motivates the development of scaled arrays of parallel sources utilising Si MOS devices to realise a new generation of metrologically accurate current standards.

cond-mat.mes-hall

Long coherence silicon spin qubit fabricated in a 300 mm industrial foundry

Silicon spin qubits offer long coherence times, a compact footprint and compatibility with industrial CMOS manufacturing. Here, we investigate spin qubits hosted in quantum dots fabricated in a state-of-the-art 300 mm nanoelectronics foundry and demonstrate substantially enhanced coherence, achieving a Hahn-echo time of $T_2^{\text{Hahn}} = 4\,\mathrm{ms}$ for singlet--triplet oscillations. Employing noise spectroscopy and noise correlation measurements, we identify detuning noise with an amplitude of $δ\varepsilon_{\mathrm{rms}} = 2.2\,μ\mathrm{eV}$ (integrated over 90 s) and observe strong zero-phase correlations between two spatially separated spin qubits. The singlet--triplet basis intrinsically rejects these common-mode fluctuations, yielding a pronounced suppression of dephasing. Our results suggest that exploiting the versatility of silicon quantum dots to adapt the qubit encoding to the microscopic noise landscape represents a promising strategy for advancing scalable quantum information processing.

cond-mat.mes-hall

High Fidelity Qubit Control in a Natural Si-MOS Quantum Dot using a 300 mm Silicon on Insulator Wafer

We demonstrate high-fidelity single qubit control in a natural Si-MOS quantum dot fabricated in an industrial 300 mm wafer process on a silicon on insulator (SOI) wafer using electron spin resonance. A relatively high optimal Rabi frequency of 5 MHz is achieved, dynamically decoupling the electron spin from its 29-Si environment. Tracking the qubit frequency reduces the impact of low frequency noise in the qubit frequency and improves the $T^{Rabi}$ from 7 to 11 $μ$s at a Rabi frequency of 5 MHz, resulting in Q-factors exceeding 50. Randomized benchmarking returns an average single gate control fidelity of 99.5 $\pm$ 0.3%. As a result of pulse-area calibration, this fidelity is limited by the Rabi Q-factor. These results show that a fast Rabi frequency, low charge noise, and a feedback protocol enable high fidelity in these Si-MOS devices, despite the low-frequency magnetic noise.

cond-mat.mes-hall

Multimode RF Reflectometry for Spin Qubit Readout and Device Characterization

We introduce a multimode superconducting inductor architecture that enables radio-frequency reflectometry at multiple discrete frequencies up to 2 GHz, addressing limitations of conventional single-mode designs. The spiral inductor's distributed inter-turn capacitance yields distinct resonant modes with varied impedance-matching conditions. By probing a quantum dot across several modes, we extract tunneling rates over a broad frequency range and identify signatures of nearby charge defects. Using one of the higher-order modes, we demonstrate single-shot spin readout via a radio-frequency single-electron transistor (RF-SET), achieving singlet-triplet readout with an integration time of 8 us and a readout fidelity of 98%. These results establish multimode inductance as a scalable and flexible component for fast spin-qubit readout and device-quality characterization.

cond-mat.mes-hall

Hybrid Quantum Systems: Coupling Single-Molecule Magnet Qudits with Industrial Silicon Spin Qubits

Molecular spin qudits offer an attractive platform for quantum memory, combining long coherence times with rich multi-level spin structures. Terbium bis(phthalocyaninato) (TbPc$_2$) exemplifies such systems, with demonstrated quantum control and chemical reproducibility. In hybrid quantum architectures, TbPc$_2$ can act as the primary memory element, with semiconductor qubits providing scalable readout and coupling. Here we present a step toward such a hybrid system: using an industrially manufactured silicon metal-oxide-semiconductor (SiMOS) spin qubit to detect electronic spin transitions of an ensemble of TbPc$_2$ molecules. The readout is based on a compact and robust protocol that applies a microwave pulse while all gate voltages defining the qubit are held at a fixed operating point. This protocol, which combines simultaneous Rapid adiabatic Passage and Spin- Selective tunneling (RPSS), enables high-contrast resonance detection and avoids repeated $π$-pulse recalibration common in decoupling schemes. By demonstrating ensemble detection, we establish a foundation for integrating molecular quantum memories with industrial qubit platforms and mark an important step toward single-molecule hybrid quantum technologies.

cond-mat.mes-hall

Rapid Autotuning of a SiGe Quantum Dot into the Single-Electron Regime with Machine Learning and RF-Reflectometry FPGA-Based Measurements

Spin qubits need to operate within a very precise voltage space around charge state transitions to achieve high-fidelity gates. However, the stability diagrams that allow the identification of the desired charge states are long to acquire. Moreover, the voltage space to search for the desired charge state increases quickly with the number of qubits. Therefore, faster stability diagram acquisitions are needed to scale up a spin qubit quantum processor. Currently, most methods focus on more efficient data sampling. Our approach shows a significant speedup by combining measurement speedup and a reduction in the number of measurements needed to tune a quantum dot device. Using an autotuning algorithm based on a neural network and faster measurements by harnessing the FPGA embedded in Keysight's Quantum Engineering Toolkit (QET), the measurement time of stability diagrams has been reduced by a factor of 9.8. This led to an acceleration factor of 2.2 for the total initialization time of a SiGe quantum dot into the single-electron regime, which is limited by the Python code execution.

cond-mat.mes-hall

Precision high-speed quantum logic with holes on a natural silicon foundry platform

Silicon spin qubits in gate-defined quantum dots leverage established semiconductor infrastructure and offer a scalable path toward transformative quantum technologies. Holes spins in silicon offer compact all-electrical control, whilst retaining all the salient features of a quantum dot qubit architecture. However, silicon hole spin qubits are not as advanced as electrons, due to increased susceptibility to disorder and more complex spin physics. Here we demonstrate single-qubit gate fidelities up to 99.8% and a two-qubit gate quality factor of 240, indicating a physical fidelity limit of 99.7%. These results represent the highest performance reported in natural silicon to date, made possible by fast qubit control, exchange pulsing, and industrial-grade fabrication. Notably, we achieve these results in a near-identical device as used for highly reproducible, high-fidelity electron spin qubits. With isotopic purification and device-level optimisations in the future, our hole spin qubits are poised to unlock a new operation regime for quantum CMOS architectures.

cond-mat.mes-hall

High-fidelity dispersive spin sensing in a tuneable unit cell of silicon MOS quantum dots

Metal-oxide-semiconductor (MOS) technology is a promising platform for developing quantum computers based on spin qubits. Scaling this approach will benefit from compact and sensitive sensors that minimize constraints on qubit connectivity while being industrially manufacturable. Here, we demonstrate a compact dispersive spin-qubit sensor, a single-electron box (SEB), within a bilinear unit cell of planar MOS quantum dots (QDs) fabricated using an industrial grade 300 mm wafer process. By independent gate control of the SEB and double-quantum-dot tunnel rates, we optimize the sensor to achieve a readout fidelity of 99.92% in 340us (99% in 20us), fidelity values on a par with the best obtained with less compact sensors. Furthermore, we develop a Hidden Markov Model of the two-electron spin dynamics that enables a more accurate calculation of the measurement outcome and hence readout fidelity. Our results show how high-fidelity sensors can be introduced within silicon spin-qubit architectures while maintaining sufficient qubit connectivity as well as providing faster readout and more efficient initialisation schemes.

quant-ph

Experimental online quantum dots charge autotuning using neural networks

Spin-based semiconductor qubits hold promise for scalable quantum computing, yet they require reliable autonomous calibration procedures. This study presents an experimental demonstration of online single-dot charge autotuning using a convolutional neural network integrated into a closed-loop calibration system. The autotuning algorithm explores the gates' voltage space to localize charge transition lines, thereby isolating the one-electron regime without human intervention. This exploration leverages the model's uncertainty estimation to find the appropriate gate configuration with minimal measurements while reducing the risk of failures. In 20 experimental runs, our method achieved a success rate of 95% in locating the target electron regime, highlighting the robustness of this approach against noise and distribution shifts from the offline training set. Each tuning run lasted an average of 2 hours and 9 minutes, primarily due to the limited speed of the current measurement. This work validates the feasibility of machine learning-driven real-time charge autotuning for quantum dot devices, advancing the development toward the control of large qubit arrays.

cond-mat.mes-hall

Probing g-tensor reproducibility and spin-orbit effects in planar silicon hole quantum dots

In this work, we probe the sensitivity of hole-spin properties to hole occupation number in a planar silicon double-quantum dot device fabricated on a 300 mm integrated platform. Using DC transport measurements, we investigate the g-tensor and spin-relaxation induced leakage current within the Pauli spin-blockade regime as a function of magnetic-field orientation at three different hole occupation numbers. We find the g-tensor and spin-leakage current to be highly anisotropic due to light-hole/heavy-hole mixing and spin-orbit mixing, but discover the anisotropies to be relatively insensitive to the dot hole number. Furthermore, we extract the dominant inter-dot spin-orbit coupling mechanism as surface Dresselhaus, with an in-plane orientation parallel to transport and magnitude $\boldsymbol{t_{SO}}$ $\approx$ 300 neV. Finally, we observe a strong correlation between the g-factor difference ($δ$$\boldsymbol{g}$) between each dot and the spin-leakage current anisotropy, as a result of $δ$$\boldsymbol{g}$ providing an additional spin-relaxation pathway, and should be considered. ]Our findings indicate that hole-spin devices are not as sensitive to precise operating conditions as anticipated. This has important implications optimizing spin control and readout based on magnetic-field direction, together with tuning large arrays of QDs as spin-qubits.

cond-mat.mes-hall

Robust quantum dots charge autotuning using neural network uncertainty

This study presents a machine-learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention, addressing one of the significant challenges in scaling up quantum dot technologies. This method exploits artificial neural networks to identify noisy transition lines in stability diagrams, guiding a robust exploration strategy leveraging neural networks' uncertainty estimations. Tested across three distinct offline experimental datasets representing different single quantum dot technologies, the approach achieves over 99% tuning success rate in optimal cases, where more than 10% of the success is directly attributable to uncertainty exploitation. The challenging constraints of small training sets containing high diagram-to-diagram variability allowed us to evaluate the capabilities and limits of the proposed procedure.

quant-ph

Statistical Analysis of Spurious Dot Formation in SiMOS Single Electron Transistors

The spatial distribution of spurious dots in SiMOS single-electron transistors (SETs), fabricated on an industrial 300 mm process line, has been statistically analyzed. To have a deeper understanding of the origin of these spurious dots, we analyzed SETs with three different oxide thicknesses: 8 nm, 12 nm and 20 nm. By combining spurious dot triangulation cryo-measurement with simulations of strain, gate bias, and location of the electron wave function, we demonstrate that most spurious dots are formed through the combined effects of strain and gate bias, leading to variations in the conduction band energy. Despite the similar thermal expansion coefficients of polycrystalline silicon gates and single-crystalline silicon substrates, strain remains a crucial factor in spurious dots formation. This learning can be use to optimize the device design and the oxide thickness, to reduce the density of spurious dot while keeping quantum dot tunability.

cond-mat.mes-hall