Related papers: Noise-robust classification of single-shot electro…
Single electron spins confined in silicon quantum dots hold great promise as a quantum computing architecture with demonstrations of long coherence times, high-fidelity quantum logic gates, basic quantum algorithms and device scalability.…
Initialization and readout of coupled quantum systems are essential ingredients for the implementation of quantum algorithms. If the state of a multi-qubit register can be read out in a single shot, this enables further key resources such…
Electron spins in silicon quantum dots provide a promising route towards realising the large number of coupled qubits required for a useful quantum processor. At present, the requisite single-shot spin qubit measurements are performed using…
Proposals for large-scale semiconductor spin-based quantum computers require high-fidelity single-shot qubit readout to perform error correction and read out qubit registers at the end of a computation. However, as devices scale to larger…
Image sensors with nondestructive charge readout provide single-photon or single-electron sensitivity, but at the cost of long readout times. We present a smart readout technique to allow the use of these sensors in visible-light and other…
Solid-state systems which mimic two-level atoms are being actively developed. Improving the quantum coherence of these systems, for instance spin qubits or single photon emitters using semiconductor quantum dots, involves dealing with…
The radio frequency single electron transistor (rf-SET) possesses key requirements necessary for reading out a solid state quantum computer. This work explores the use of the rf-SET as a single-shot readout device in the presence of 1/f and…
The negatively charged tin-vacancy center in diamond (SnV$^-$) is an emerging platform for building the next generation of long-distance quantum networks. This is due to the SnV$^-$'s favorable optical and spin properties including bright…
Efficient optical readout of a single, solid-state electronic spin at room temperature is a key challenge for nanoscale quantum sensing. Here we apply the technique of spin-to-charge conversion to enhance the optical spin-state readout of a…
Spins in semiconductor quantum dots are a candidate for cryogenic quantum processors due to their exceptionally long coherence times. One major challenge to scaling quantum dot spin qubits is the dense wiring requirements, making it…
A first step is taken towards understanding often observed non-robustness phenomena of deep neural net (DNN) classifiers. This is done from the perspective of Boolean functions by asking if certain sequences of Boolean functions represented…
Deep Neural Networks (DNN) achieve human level performance in many image analytics tasks but DNNs are mostly deployed to GPU platforms that consume a considerable amount of power. New hardware platforms using lower precision arithmetic…
We demonstrate a new method for projective single-shot measurement of two electron spin states (singlet versus triplet) in an array of gate-defined lateral quantum dots in GaAs. The measurement has very high fidelity and is robust with…
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…
Despite their outstanding performance in a broad spectrum of real-world tasks, deep artificial neural networks are sensitive to input noises, particularly adversarial perturbations. On the contrary, human and animal brains are much less…
Single-shot read-out of individual qubits is typically the slowest process among the elementary single- and two-qubit operations required for quantum information processing. Here, we use resonance fluorescence from a single-electron charged…
Charge noise is one of the main sources of environmental decoherence for spin qubits in silicon, presenting a major obstacle in the path towards highly scalable and reproducible qubit fabrication. Here we demonstrate in-depth…
In recent years, deep neural networks (DNNs) have gained remarkable achievement in computer vision tasks, and the success of DNNs often depends greatly on the richness of data. However, the acquisition process of data and high-quality…
The detection of nuclear spins using individual electron spins has enabled new opportunities in quantum sensing and quantum information processing. Proof-of-principle experiments have demonstrated atomic-scale imaging of nuclear-spin…
Noisy labels are ubiquitous in real-world datasets, which poses a challenge for robustly training deep neural networks (DNNs) as DNNs usually have the high capacity to memorize the noisy labels. In this paper, we find that the test accuracy…