Related papers: The Triggerless Data Acquisition System of the XEN…
High-efficiency single-photon detection in the microwave domain is a key enabling technology for quantum sensing, communication, and information processing. However, the extremely low energy of microwave photons (~{\mu}eV) presents a…
We have developed an atom trap trace analysis (ATTA) system to measure Kr in Xe at the part per trillion (ppt) level, a prerequisite for the sensitivity achievable with liquid xenon dark matter detectors beyond the current generation. Since…
Deep Q-Network (DQN) marked a major milestone for reinforcement learning, demonstrating for the first time that human-level control policies could be learned directly from raw visual inputs via reward maximization. Even years after its…
The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino oscillation experiment aiming to measure the oscillation parameters with an unprecedented precision that will allow determining the CP violation phase in the…
As liquid xenon TPCs increase in target mass while pursuing the direct detection of WIMP dark matter, the technical challenges arising due to their size call for new solutions and open the discussion on alternative detector concepts.…
Quantization is commonly used in Deep Neural Networks (DNNs) to reduce the storage and computational complexity by decreasing the arithmetical precision of activations and weights, a.k.a. tensors. Efficient hardware architectures employ…
Recently, data-driven approaches motivated by modern deep learning have been applied to optical communications in place of traditional model-based counterparts. The application of deep neural networks (DNN) allows flexible statistical…
ProtoDUNE-DP is a 6x6x6 m3 liquid argon time-projection-chamber operated at the CERN Neutrino Platform in 2019-2020 as a prototype of the Dual Phase concept for the DUNE Far Detector. The Photon Detection System (PDS) is based on 36 8-inch…
Quantum systems subject to random unitary evolution and measurements at random points in spacetime exhibit entanglement phase transitions which depend on the frequency of these measurements. Past work has experimentally observed…
We develop a novel approach for a Time Projection Chamber (TPC) concept suitable for deployment in kilotonne scale detectors, with a charge-readout system free from reconstruction ambiguities, and a robust TPC design that reduces…
In the past decade, dual-phase xenon time projection chambers (Xe-TPCs) have emerged as some of the most powerful detectors in the fields of astroparticle physics and rare-event searches. Developed primarily towards the direct detection of…
Designing parameterized quantum circuits (PQCs) that are expressive, trainable, and robust to hardware noise is a central challenge for quantum machine learning (QML) on noisy intermediate-scale quantum (NISQ) devices. We present a…
A data acquisition (DAQ) system is described which will be used for the next generation of prototype calorimeters using particle flow algorithms for the International Linear Collider (ILC). The design is sufficiently generic and scalable…
A new data acquisition system for the high resolution magnetic spectrometer Lintott at the superconducting Darmstadt electron linear accelerator S-DALINAC was developed. It allows inclusive and coincidence electron scattering experiments…
State of the art detector readout electronics require high-throughput data acquisition (DAQ) systems. In many applications, e. g. for medical imaging, the front-end electronics are set up as separate modules in a distributed DAQ. A…
This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T was mapped…
This paper introduces a deep learning approach to dynamic spectrum access, leveraging the synergy of multi-modal image and spectrum data for the identification of potential transmitters. We consider an edge device equipped with a camera…
Novel electronic devices can often be operated in a plethora of ways, which makes testing circuits comprised of them difficult. Often, no single tool can simultaneously analyze the operating margins, maximum speed, and failure modes of a…
Diffusion transformers have demonstrated remarkable generation quality, albeit requiring longer training iterations and numerous inference steps. In each denoising step, diffusion transformers encode the noisy inputs to extract the…
Background: The established GADGET detection system, designed for measuring weak, low-energy $\beta$-delayed proton decays, features a gaseous Proton Detector with MICROMEGAS readout for calorimetric particle detection, surrounded by a…