Related papers: Identifying single electron charge sensor events u…
We demonstrate dispersive readout of individual charge states in a gate-defined few-electron quantum dot in bilayer graphene. We employ a radio frequency reflectometry circuit, where an LC resonator with a resonance frequency close to 280…
We consider a model of a detector of ballistic electrons at the edge of a two-dimensional electron gas in the integer quantum Hall regime. The electron is detected by capacitive coupling to a gate which is also coupled to a passive RC…
Detection of moving charge in free space is presented in the framework of single electron CMOS devices. It opens the perspective for construction of new type detectors for beam diagnostic in accelerators or for the detection of solar wind.…
Depleted p-channel field effect transistor detectors with repetitive-non-destructive readout (RNDR-DEPFETs) achieve a deep sub-electron noise by averaging several independent measurements of one single event. During the repetitive readout…
The research is aimed to address issues of analysis and mitigation of high repetition rate effects in Dielectric Wakefield Accelerators, and more specifically, to study charging rate and charge distribution in a thin walled dielectric…
Charge-coupled devices (CCDs) are a leading technology in direct dark matter searches because of their eV-scale energy threshold and high spatial resolution. The sensitivity of future CCD experiments could be enhanced by distinguishing…
A method is presented which allows to obtain the position-dependent electric field and charge density by fits to velocity profiles from edge-TCT data from silicon strip-detectors. The validity and the limitations of the method are…
Single-shot measurement of the charge arrangement and spin state of a double quantum dot are reported, with measurement times down to ~ 100 ns. Sensing uses radio-frequency reflectometry of a proximal quantum dot in the Coulomb blockade…
We report measurements on a graphene quantum dot with an integrated graphene charge detector. The quantum dot device consists of a graphene island (diameter approx. 200 nm) connected to source and drain contacts via two narrow graphene…
Single charge detection with nanoscale spatial resolution in ambient conditions is a current frontier in metrology that has diverse interdisciplinary applications. Here, such single charge detection is demonstrated using two…
Charge sensing in quantum-dot structures is studied by an exactly solvable reduced model and numerical density-matrix renormalization group methods. Charge sensing is characterized by the repeated cycling of the occupation of…
Experiments over the past years have demonstrated that it is possible to bring nanomechanical resonators and superconducting qubits close to the quantum regime and to measure their properties with an accuracy close to the Heisenberg…
Detecting single atoms (qubits) is a key requirement for implementing quantum information processing on an atom chip. The detector should ideally be integrated on the chip. Here we present and compare different methods capable of detecting…
High-fidelity detection of charge transitions in quantum dots (QDs) is a key ingredient in solid state quantum computation. We demonstrate high-bandwidth radio-frequency charge detection in bilayer graphene quantum dots (QDs) using a…
Phonon-mediated cryogenic calorimeters find application in rare event searches due to their intrinsically low energy threshold. Achieving the best sensitivity for this kind of detectors is crucial for signal identification, leading to…
Detecting edges is a fundamental problem in computer vision with many applications, some involving very noisy images. While most edge detection methods are fast, they perform well only on relatively clean images. Indeed, edges in such…
Understanding and suppressing sources of decoherence is a leading challenge in building practical quantum computers. In superconducting qubits, low frequency charge noise is a well-known decoherence mechanism that is effectively suppressed…
Sound event detection is a challenging task, especially for scenes with multiple simultaneous events. While event classification methods tend to be fairly accurate, event localization presents additional challenges, especially when large…
Anomaly detection is widely used in a broad range of domains from cybersecurity to manufacturing, finance, and so on. Deep learning based anomaly detection has recently drawn much attention because of its superior capability of recognizing…
This paper presents fault detection and classification using Wavelet and ANN based methods in a DFIG-based series compensated system. The state-of-the art methods include Wavelet transform, Fourier transform, and Wavelet-neuro fuzzy…