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Machine learning offers a largely unexplored avenue for improving noisy disordered devices in physics using automated algorithms. Through simulations that include disorder in physical devices, particularly quantum devices, there is…
Transformer models and end-to-end learning frameworks are rapidly revolutionizing the field of artificial intelligence. In this work, we apply object detection transformers to analyze charge stability diagrams in semiconductor quantum dot…
We investigate coherent control of a single electron trapped in a semiconductor quantum dot. Control is enabled with a strong laser field detuned with respect to the electron light-hole optical transitions. For a realistic experimental…
Charge noise is a major obstacle to improved gate fidelities in silicon spin qubits. Numerous methods exist to mitigate charge noise, including improving device fabrication, dynamical decoupling, and real-time parameter estimation. In this…
Semiconductor quantum dot arrays defined electrostatically in a 2D electron gas provide a scalable platform for quantum information processing and quantum simulations. For the operation of quantum dot arrays, appropriate voltages need to be…
We propose an all optical spin initialization and readout concept for single self assembled quantum dots and demonstrate its feasibility. Our approach is based on a gateable single dot photodiode structure that can be switched between…
Gate-defined semiconductor quantum dot (QD) arrays are a promising platform for quantum computing. However, presently, the large configuration spaces and inherent noise make tuning of QD devices a nontrivial task and with the increasing…
We have investigated coherent time evolution of pseudo-molecular states of an isolated (leadless) silicon double quantum-dot, where operations are carried out via capacitively-coupled elements. Manipulation is performed by short pulses…
Practical Quantum computing hinges on the ability to control large numbers of qubits with high fidelity. Quantum dots define a promising platform due to their compatibility with semiconductor manufacturing. Moreover, high-fidelity…
A crucial requirement for scalable quantum-information processing is the realization of multiple-qubit quantum gates. Universal multiple-qubit gates can be implemented by a set of universal single qubit gates and any one kind of two-qubit…
Semiconductor quantum dot arrays are a promising platform to perform spin-based error-corrected quantum computation with large numbers of qubits. However, due to the diverging number of possible charge configurations combined with the…
The gate fidelity and the coherence time of a qubit are important benchmarks for quantum computation. We construct a qubit using a single electron spin in a Si/SiGe quantum dot and control it electrically via an artificial spin-orbit field…
The remarkable properties of silicon have made it the central material for the fabrication of current microelectronic devices. Silicon's fundamental properties also make it an attractive option for the development of devices for spintronics…
The spin states of single electrons in gate-defined quantum dots satisfy crucial requirements for a practical quantum computer. These include extremely long coherence times, high-fidelity quantum operation, and the ability to shuttle…
The scaling up of electron spin qubit based nanocircuits has remained challenging up to date and involves the development of efficient charge control strategies. Here we report on the experimental realization of a linear triple quantum dot…
Electron charge qubits are compelling candidates for solid-state quantum computing because of their inherent simplicity in qubit design, fabrication, control, and readout. However, all existing electron charge qubits, built upon…
Recent demonstrations using electron spins stored in quantum dots array as qubits are promising for developing a scalable quantum computing platform. An ongoing effort is therefore aiming at the precise control of the quantum dots…
Solid-state quantum computer architectures with qubits encoded using single atoms are now feasible given recent advances in atomic doping of semiconductors. Here we present a charge qubit consisting of two dopant atoms in a semiconductor…
We propose the implementation of the Swap Test using a charge qubit in a double quantum dot. The Swap Test is a fundamental quantum subroutine in quantum machine learning and other applications for estimating the fidelity of two unknown…
Without resorting to spin-spin coupling, we propose a scalable spin quantum computing scheme assisted with a semiconductor multiple-quantum-dot structure. The techniques of single electron transitions and the nanostructure of quantum-dot…