Significant advances have been made towards fault-tolerant operation of silicon spin qubits, with single qubit fidelities exceeding 99.9%, several demonstrations of two-qubit gates based on exchange coupling, and the achievement of coherent single spin-photon coupling. Coupling arbitrary pairs of spatially separated qubits in a quantum register poses a significant challenge as most qubit systems are constrained to two dimensions with nearest neighbor connectivity. For spins in silicon, new methods for quantum state transfer should be developed to achieve connectivity beyond nearest-neighbor exchange. Here we demonstrate shuttling of a single electron across a linear array of nine series-coupled silicon quantum dots in ~50 ns via a series of pairwise interdot charge transfers. By constructing more complex pulse sequences we perform parallel shuttling of two and three electrons at a time through the array. These experiments demonstrate a scalable approach to physically transporting single electrons across large silicon quantum dot arrays.

Silicon spin qubits satisfy the necessary criteria for quantum information processing. However, a demonstration of high-fidelity state preparation and readout combined with high-fidelity single- and two-qubit gates, all of which must be present for quantum error correction, has been lacking. We use a two-qubit Si/SiGe quantum processor to demonstrate state preparation and readout with fidelity greater than 97%, combined with both single- and two-qubit control fidelities exceeding 99%. The operation of the quantum processor is quantitatively characterized using gate set tomography and randomized benchmarking. Our results highlight the potential of silicon spin qubits to become a dominant technology in the development of intermediate-scale quantum processors.

As with any quantum computing platform, semiconductor quantum dot devices require sophisticated hardware and controls for operation. The increasing complexity of quantum dot devices necessitates the advancement of automated control software and image recognition techniques for rapidly evaluating charge stability diagrams. We use an image analysis toolbox developed in Python to automate the calibration of virtual gates, a process that previously involved a large amount of user intervention. Moreover, we show that straightforward feedback protocols can be used to simultaneously tune multiple tunnel couplings in a triple quantum dot in a computer automated fashion. Finally, we adopt the use of a 'tunnel coupling lever arm' to model the interdot barrier gate response and discuss how it can be used to more rapidly tune interdot tunnel couplings to the GHz values that are compatible with exchange gates.Quantum processors rely on classical hardware and controls in order to prepare, manipulate, and measure qubit states. For this reason, it is advantageous to develop tools to automate the operation of small quantum processors and routinely tune-up single qubit and two-qubit gates to maintain high performance 1-3 . Semiconductor spin qubits are a promising platform for realizing quantum computation largely due to their potential for scaling 4 . To tune up semiconductor quantum dots for operation as spin qubits requires control over the ground state charge occupation and chemical potential of each dot, as well as the interdot tunnel couplings 5 .Following the recent progress in constructing high-fidelity single-qubit and two-qubit gate operations with electron spins 6-11 , there are increasing efforts towards scaling to larger multi-qubit devices 12-15 . One of the key challenges in scaling up spin qubits is developing the software tools necessary to keep pace with increasingly complex devices. To date, approaches to implementing automated control software during tune-up of semiconductor qubits include training neural networks to identify the state of a device 16 , experimentally realizing automated control procedures for tuning double quantum dot (DQD) devices into the single-electron regime 17 , and automatically tuning the interdot tunnel coupling in a DQD [18][19][20] .In this Letter, we use an image analysis toolbox developed at Sandia National Laboratories to accurately analyze charge stability diagrams acquired from a triple quantum dot (TQD) unit cell of a 9-dot linear array 13,21 . Computer automated analysis of charge stability diagrams performs the inversion of the device capacitance matrix and the establishment of 'virtual gates'. Virtual gates compensate for cross-capacitances in the device and allow the chemical potential of each dot in the array to be independently controlled 13,22,23 . Furthermore, we use image analysis to locate interdot charge transitions and automatically perform measurements of the interdot tunnel coupling 24 . Using simple feedback protocols, we demonstrate simultaneous tune-up of the i...

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Atomically thin transition-metal dichalcogenides are of great interest due to their intriguing physical properties and potential applications. Here, we report our findings from scanning tunneling microscopy and spectroscopy investigations on molybdenum disulfide (MoS2) mono- to few-layers and pyramid nanostructures synthesized through chemical vapor deposition. On the few-layered MoS2 nanoplatelets grown on gallium nitride (GaN) and pyramid nanostructures on highly oriented pyrolytic graphite, we observed an intriguing curved region near the edge terminals. The measured band gap on these curved regions is 1.96 ± 0.10 eV, consistent with the value of the direct band gap in MoS2 monolayers. The curved features near the edge terminals and the associated electronic properties may contribute to the catalytic behaviors of MoS2 nanostructures and have potential applications in future electronic devices and energy-related products based on MoS2 nanostructures.