Understanding scattering mechanisms in semiconductor heterostructures is crucial to reducing sources of disorder and ensuring high yield and uniformity in large spin qubit arrays. Disorder of the parent two-dimensional electron or hole gas is commonly estimated by the critical, percolation-driven density associated with the metal–insulator transition. However, a reliable estimation of the critical density within percolation theory is hindered by the need to measure conductivity with high precision at low carrier densities, where experiments are most difficult. Here, we connect experimentally percolation density and quantum Hall plateau width, in line with an earlier heuristic intuition, and offer an alternative method for characterizing semiconductor heterostructure disorder.

The scalability and power of quantum computing architectures depend critically on high-fidelity operations and robust and flexible qubit connectivity^{1, 2–3}. In this respect, mobile qubits are particularly attractive as they enable dynamic and reconfigurable qubit arrays. This approach allows quantum processors to adapt their connectivity patterns during operation, implement different quantum error correction codes on the same hardware and optimize resource use through dedicated functional zones for specific operations such as measurement or entanglement generation^{4, 5, 6–7}. Such flexibility also relieves architectural constraints, as recently demonstrated in atomic systems based on trapped ions^4,5 and neutral atoms manipulated with optical tweezers^6,7. In solid-state platforms, highly coherent shuttling of electron spins was recently reported^8,9. A key outstanding question is whether it may be possible to perform quantum gates directly on the mobile spins. Here we demonstrate two-qubit operations between two electron spins carried towards each other in separate travelling potential minima in a semiconductor device. We find that the interaction strength is highly tunable by their spatial separation. When we shuttle the two spins towards the centre by 120 nm each for a total displacement of 240 nm, we achieve an average two-qubit gate fidelity of about 99%. Furthermore, we implement conditional post-selected quantum state teleportation between qubits separated by 320 nm with an average gate fidelity of 87%, showcasing the potential of mobile spin qubits for non-local quantum information processing. We expect that operations on mobile qubits will become a universal feature of future large-scale semiconductor quantum processors.

Evaluation of the quantum lifetime in two-dimensional hole systems, together with band-structure parameters such as the effective mass and g factor, becomes challenging when competing energy scales shape Shubnnikov–de Haas oscillations in a magnetic field. Here, we overcome this challenge for holes with pseudospin J_z = ± ₂ ³, confined in low-disorder strained germanium quantum wells. We extract self-consistently the effective mass, g factor, and quantum lifetime, and estimate a maximum quantum mobility of 133(3) × 10³ cm²/V s, setting a benchmark for holes in group IV semiconductors. The high quality of the hole gas if further highlighted by observing clean fractional quantum Hall states at low magnetic field and density.

The large-scale integration of semiconductor spin qubits into quantum processors will require the characterization of quantum components at scale. However, such characterization is challenging and typically requires radio-frequency measurements at millikelvin temperatures and the presence of magnetic fields. Here we report a scalable architecture for characterizing spin qubits using a quantum dot crossbar array. The approach, which we term as the qubit-array research platform for engineering and testing, uses a crossbar array comprising tightly pitched spin-qubit tiles and is implemented in planar germanium, with the potential to host 1,058 single-hole spin qubits. We measure a subset of 40 tiles and demonstrate key device functionality at millikelvin temperatures, including tile addressability, threshold voltage and charge noise statistics, as well as the characterization of hole spin qubits and their coherence times in a single tile.

Germanium spin qubits offer high-fidelity control via strong spin-orbit interaction, but their magnetic field sensitivity typically requires bulky superconducting vector magnets that limit scalability. This study investigates replacing these with an external permanent magnet located outside the cryostat to reclaim internal sample space. By operating in a hybrid mode (internal and external magnets), we fine-tuned the field to an in-plane orientation, achieving a dephasing time T2*=13μs and single-qubit Clifford gate fidelities exceeding 99.9%. Remarkably, we demonstrate qubit operation even with the internal superconducting magnet deactivated. In this regime, we observed extended coherence times of T2*=31μs and T2H=266μs, on a natural Germanium heterostructure. These results demonstrate that room-temperature magnets allow for high qubit performance. This approach facilitates scaling by freeing cryogenic space for essential control circuitry and wiring, paving the way for large-scale quantum processors.

The simplicity of encoding a qubit in the state of a single electron spin and the potential for their integration into industry-standard microchips continue to drive the field of semiconductor-based quantum computing. After a series of key first-principles demonstrations validating universal gate operations, initialization and readout, three-qubit algorithms have already been realized with silicon-based quantum dots in past years. Devices containing more qubits have become available since then but experiments have not gone beyond meeting the DiVincenzo criteria. In this work, we fully exploit the capacity of a spin-qubit array and implement a six-qubit quantum circuit, the largest utilizing semiconductor quantum technology. By programming the quantum processor, we execute quantum circuits across all permutations of three, four, five, and six neighboring qubits, demonstrating successful programmable multi-qubit operation throughout the array. Using an error model that incorporates quasi-static noise allows us to qualitatively explain some key trends in our experimental results and highlight the necessity to minimize idling times through simultaneous operations, extending dephasing times, and consistently improving state preparation and measurement fidelities.

Electron spins in silicon offer a promising path toward scalable, fault-tolerant quantum computing, with the potential to host millions of qubits. However, scaling up dense quantum-dot arrays and enabling qubit interconnections through shuttling are hindered by uncontrolled lateral variations of the valley splitting energy E_VS. We map E_VS across a 40 nm × 400 nm region of a ²⁸Si/Si_0.7Ge_0.3 shuttle device and analyze the spin coherence of a single electron spin transported by conveyor-belt shuttling. We observe that the E_VS varies over a wide range from 1.5 μeV to 200 μeV and is dominated by SiGe alloy disorder. In regions of low E_VS and at spin-valley resonances, spin coherence is reduced and its dependence on shuttle velocity matches predictions. Rapid and frequent traversal of low-E_VS regions induces a regime of enhanced spin coherence explained by motional narrowing. By selecting shuttle trajectories that avoid problematic areas on the E_VS map, we achieve transport over tens of microns with coherence limited by the coupling to a static electron spin entangled with the mobile qubit. Our results provide experimental confirmation of the theory of spin decoherence of mobile electron spin-qubits and present practical strategies to integrate conveyor-mode qubit shuttling into silicon quantum chips.

Recent advances in coherent spin shuttling have made sparse semiconductor spin-qubit arrays an appealing solid-state platform to realize quantum processors^{1, 2, 3, 4, 5, 6–7}. The dynamic and long-range connectivity enabled by shuttling is also essential for many quantum error-correction schemes^{8, 9–10}. Here we demonstrate a silicon spin-qubit device comprising a shuttling bus for coherently transporting qubits that can interact at four isolated locations that we call bus stops. We dynamically populate the array and tune all single- and two-qubit operations using shuttling and quantum non-demolition spin measurements, without access to charge sensing in most of the device. We achieve universal control of the effective five-qubit processor and select the connectivity required to form a surface-code stabilizer plaquette that supports X- and Z-type parity checks up to weight four. We use the parity checks to generate multi-qubit entanglement between all qubit combinations in the array and report the genuine entanglement of a five-qubit Greenberger–Horne–Zeilinger state, constituting one of the largest such states constructed with gate-defined semiconductor spins. The protocols developed here lay the groundwork for modular calibration and operation of sparse spin-qubit arrays, and we highlight the feasibility of near-term quantum error-correction experiments with mobile spin qubits.

Quantum simulators enable studies of many-body phenomena, which are intractable with classical hardware. The manipulation of electronic spin states in devices based on semiconductor quantum dots promises precise electrical control and scalability advantages, but accessing many-body phenomena has so far been restricted by challenges in nanofabrication and simultaneous control of multiple interactions. in this study, we performed spectroscopy of up to eight interacting spins using a 2-×-4 array of gate-defined germanium quantum dots. The spectroscopy protocol is based on ramsey interferometry and adiabatic mapping of many-body eigenstates to single-spin eigenstates, enabling complete energy spectrum reconstruction. As the interaction strength exceeds magnetic disorder, we observed signatures of the crossover from localization to a chaotic phase marking a step toward the observation of many-body phenomena in quantum dot systems.

The optical generation of an out-of-equilibrium spin population is a keystone process for quantum technologies and spintronics alike. Although this is an established technique for studying direct band-gap semiconductors, it has been proven limited in materials that possess weak oscillator strengths for the optical transitions. We address the problem by presenting an all-optical analog of the spin-pumping method. By applying this concept to a Ge-on-Si heterostructure, we observe luminescence from Si with a polarization degree as high as 9%. The progressive etching of the absorbing layer, assisted by magneto-optic experiments, allows us to ascertain that the polarized emission is determined by effective spin injection aided by the carrier lifetime shortening due to extended defects. These findings can facilitate the use of highly promising spin-dependent phenomena of Si, whose optical exploitation has been hampered by fundamental limitations due to its peculiar electronic structure.

Constricting transport through a one-dimensional quantum point contact in the quantum Hall regime enables gate-tunable selection of the edge modes propagating between voltage probe electrodes. Here, we investigate the quantum Hall effect in a quantum point contact fabricated on low disorder strained germanium quantum wells. For increasing magnetic field, we observe Zeeman spin-split 1D ballistic hole transport evolving to integer quantum Hall states, with well-defined quantized conductance increasing in multiples of e ² / h down to the first integer filling factor ν = 1. These results establish strained germanium as a viable platform for complex experiments probing many-body states and quantum phase transitions.

Silicon-quantum-dot spin qubits have become a promising platform for scalable quantum computing because of their small size and compatibility with industrial semiconductor manufacturing processes. Although Si/SiGe heterostructures are commonly used to host spin qubits due to their high mobility and low percolation density, the SiGe spacer creates a gap between the qubits and control electrodes, which limits the ability to tune the exchange coupling. As a result, residual coupling leads to unwanted single-qubit phase shifts, making multi-qubit control more difficult. In this work, we explore swapping the roles of overlapping nanogates to overcome this issue. By reconfiguring the gate voltages, we demonstrate in situ role switching while maintaining multi-qubit control. Additionally, this method improves the tunability of the exchange coupling by up to 3.6 times. This strategy reduces unintended single-qubit phase shifts and minimizes the complexity of multi-qubit control, supporting scalable growth with minimal experimental overhead.

We investigate low-frequency noise in a spin-qubit device made in isotopically purified Si/Si-Ge. Observing sizable cross-correlations among energy fluctuations of different qubits, we conclude that these fluctuations are dominated by charge noise. At low frequencies, the noise spectra are not well described by a power law; instead, they reveal the presence of a few individual two-level fluctuators (TLFs). We demonstrate that the noise cross-correlations allow one to get information on the spatial location of such individual TLFs.

As quantum computing advances towards practical applications, reducing errors remains a crucial frontier for developing near-term devices. Errors in the quantum gates and quantum state readout result in noisy circuits, which would prevent the acquisition of the exact expectation values of the observables. Although ultimate robustness to errors is known to be achievable by quantum error correction-based fault-tolerant quantum computing, its successful implementation demands large-scale quantum processors with low average error rates that are not yet widely available. In contrast, quantum error mitigation offers more immediate and practical techniques, which do not require extensive resources and can be readily applied to existing quantum devices to improve the accuracy of the expectation values. Here, we report the implementation of a zero-noise extrapolation-based error mitigation technique on a silicon spin qubit platform. This technique has recently been successfully demonstrated for other platforms such as superconducting qubits, trapped-ion qubits, and photonic processors. We first explore three methods for amplifying noise on a silicon spin qubit: global folding, local folding, and pulse stretching, using a standard randomized benchmarking protocol. We then apply global folding-based zero-noise extrapolation to the state tomography and achieve a state fidelity of 99.96% (98.52%), compared to the unmitigated fidelity of 75.82% (82.16%) for different preparation states. These results show that the zero-noise extrapolation technique is a versatile approach that is generally adaptable to quantum computing platforms with different noise characteristics through appropriate noise amplification methods.

The rapidly growing number of qubits in semiconductor quantum computers requires a scalable control interface, including the efficient generation of dc bias voltages for gate electrodes. To avoid unrealistically complex wiring between any room-temperature electronics and the cryogenic qubits, this article presents an integrated cryogenic solution for the bias-voltage generation and distribution for large-scale semiconductor spin-qubit quantum processors. A dedicated cryogenic CMOS (cryo-CMOS) demultiplexer and a cryo-CMOS dc digital-to-analog converter (DAC) have been developed in a 22-nm fin field-effect transistor process to control a codeveloped 2-D array designed with 648 single-hole transistors. Thanks to the dissipation below 120 µ W, the whole system operates at temperatures below 70 mK in a custom-built electrical/mechanical infrastructure embedded in a standard single-pulse-tube dilution refrigerator. The bias voltages generated by the cryo-CMOS DAC are demultiplexed to sample-and-hold structures, allowing to store 96 unique bias voltages over a 3 V range with a voltage drift between 60 µ V / s and 18 mV/s. This work demonstrates a tight integration at mK temperatures of cryo-CMOS bias generation and distribution with a dedicated large-scale quantum device. This showcases how this approach simplifies the wiring to the electronics, thus facilitating the scaling up of quantum processors toward the large number of qubits required for a practical quantum computer.

Addressing and mitigating decoherence sources plays an essential role in the development of a scalable quantum computing system, which requires low gate errors to be consistently maintained throughout the circuit execution. While nuclear spin-free materials, such as isotopically purified silicon, exhibit intrinsically promising coherence properties for electron spin qubits, the omnipresent charge noise, when converted to magnetic noise under a strong magnetic field gradient, often hinders stable qubit operation within a time frame comparable to the data acquisition time. Here, we demonstrate both open- and closed-loop suppression techniques for the transduced noise in silicon spin qubits, resulting in a more than two-fold (ten-fold) improvement of the inhomogeneous coherence time (Rabi oscillation quality) that leads to a single-qubit gate fidelity of over 99.6% even in the presence of a strong decoherence field gradient. Utilizing gate set tomography, we show that adaptive qubit control also reduces the non-Markovian noise in the system, which validates the stability of the gate fidelity. The technique can be used to learn multiple Hamiltonian parameters and is useful for the intermittent calibration of the circuit parameters with affordable experimental overhead, providing a useful subroutine during the repeated execution of general quantum circuits.

Spin qubits in germanium gate-defined quantum dots have made considerable progress within the last few years, partially due to their strong spin-orbit coupling and site-dependent g-tensors. While this characteristic of the g-factors removes the need for micromagnets and allows for the possibility of all-electric qubit control, relying on these g-tensors necessitates the need to understand their sensitivity to the confinement potential that defines the quantum dots. Here, we demonstrate a S − T_ qubit whose frequency is a strong function of the voltage applied to the barrier gate shared by the quantum dots. We find a g-factor that can be approximately increased by an order of magnitude adjusting the barrier gate voltage only by 12 mV. We show how this strong dependence could potentially be attributed to the dots moving through a variable strain environment in our device. This work not only reinforces previous findings that site-dependent g-tensors in germanium can be utilized for qubit manipulation, but reveals the sensitivity and tunability these g-tensors have to the electrostatic confinement of the quantum dot.

The computational power and fault tolerance of future large-scale quantum processors derive in large part from the connectivity between the qubits. One approach to increase connectivity is to engineer qubit–qubit interactions at a distance. Alternatively, the connectivity can be increased by physically displacing the qubits. For semiconductor spin qubits, several studies have investigated spin coherent shuttling of individual electrons, but high-fidelity transport over extended distances remains to be demonstrated. Here we report shuttling of an electron inside an isotopically purified Si/SiGe heterostructure using electric gate potentials. In a first set of experiments, we form static quantum dots and study how spin coherence decays during bucket-brigade shuttling, where we repeatedly move a single electron between up to five dots. Next, for conveyor-mode shuttling, we create a travelling-wave potential, formed with either one or two sets of sine waves, to transport an electron in a moving quantum dot. This method shows a spin coherence an order of magnitude better than the bucket-brigade shuttling. It allows us to displace an electron over an effective distance of 10 μm in under 200 ns while preserving the spin state with a fidelity of 99.5% on average. These results will guide future efforts to realize large-scale semiconductor quantum processors, making use of electron shuttling both within and between qubit arrays.

(Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of devices due to its time-intensive nature. To address this, an analytical workflow is introduced for the holistic characterization, modelling, and simulation of device heterostructures. This workflow automates the experimental (S)TEM data analysis, providing an in-depth characterization of crystallographic information, 3D orientation, elemental composition, and strain distribution. It reduces a process that typically takes days for a trained human into an automatic routine solved in minutes. Utilizing a physics-guided artificial intelligence model, it generates representative descriptions of materials and samples. The workflow culminates in creating digital twins of systems limited with at least one axis of translational invariance –3D finite element and atomic models of millions of atoms–enabling simulations that provide crucial insights into device behavior in practical applications. Demonstrated with SiGe planar heterostructures for scalable spin qubits, the workflow links digital twins to theoretical properties, revealing how atomic structure impacts materials and functional properties such as spatially-resolved phononic or electronic characteristics, or (inverse) spin orbit lengths. The versatility of the workflow is demonstrated through its application to a wide array of materials systems, device configurations, and sample morphologies.