Related papers: The Triggerless Data Acquisition System of the XEN…
The QuarkNet DAQ card for school-network cosmic ray detectors provides a low-cost alternative to using standard particle and nuclear physics fast pulse electronics modules. Individual detector stations, each consisting of 4 scintillation…
Accurate and low-latency qubit state measurement is critical for trapped-ion quantum computing. While deep neural networks (DNNs) have been integrated to enhance detection fidelity, their latency performance on specific hardware platforms…
In this study, we present a low cost and commercially available data acquisition system (DAQ) for an ordinary low alpha proportional counter. By employing this DAQ system and aid of a simple physical model, we can easily rule out the common…
Time series anomaly detection is critical for maintaining the reliability of mission-critical systems. While Transformer-based models like PatchTST have shown remarkable performance, their $\mathcal{O}(L^2)$ computational complexity…
The XENON1T experiment at the Laboratori Nazionali del Gran Sasso (LNGS) is the first WIMP dark matter detector operating with a liquid xenon target mass above the ton-scale. Out of its 3.2t liquid xenon inventory, 2.0t constitute the…
We present tensor networks for feature extraction and refinement of classifier performance. These networks can be initialised deterministically and have the potential for implementation on near-term intermediate-scale quantum (NISQ)…
We give an overview of the main features of the CMS trigger and data acquisition (DAQ) system. Then, we illustrate the strategies and trigger configurations (trigger tables) developed for the detector calibration and physics program of the…
In this contribution we describe the design of the Data AcQuisition (DAQ) and online analysis software of the MAGIC telescopes after the 2012 upgrade. Although the final stereo trigger requires coincidence between the two telescopes, the…
Data logging at an upgraded KEKB accelerator or the J-PARC facility, currently under commission, requires a high density data acquisition platform with integrated data reduction CPUs. To follow market trends, we have developed a DAQ…
High pressure gas detectors offer advantages for the detection of rare events, where background reduction is crucial. For the neutrinoless double beta decay of 136Xe a high pressure xenon gas Time Projection Chamber (TPC) combines a good…
The XENON1T dark matter experiment aims to detect Weakly Interacting Massive Particles (WIMPs) through low-energy interactions with xenon atoms. To detect such a rare event necessitates the use of radiopure materials to minimize the number…
A new prototype wireless data acquisition system has been developed with the intended application to read-out instrumentation systems having a large number of channels. In addition such system could be deployed in smaller detectors…
Present state of the art applications in the area of high energy physics experiments (HEP), radar communication, satellite communication and bio medical instrumentation require fault resilient data acquisition (DAQ) system with the data…
The FASER experiment is a new small and inexpensive experiment that is placed 480 meters downstream of the ATLAS experiment at the CERN LHC. FASER is designed to capture decays of new long-lived particles, produced outside of the ATLAS…
Monolithically integrated, antenna-coupled field-effect transistors (TeraFETs) are rapid and sensitive detectors for the terahertz range (0.3-10~THz) that can operate at room temperature. We conducted experimental characterizations of a…
Quantum cloud platforms have scaled hardware capacity but not the abstraction exposed to users: small programs still monopolise entire processors, and existing Quantum Virtual Machine (QVM) designs often rely on fixed, topology-specific…
BiDAQ is a custom filtering and data acquisition system designed for next-gen bolometric experiments dedicated to the search of neutrinoless double beta decay. The system is composed of 12-channel analog-to-digital boards interfaced with…
New deep learning techniques present promising new analysis methods for Imaging Atmospheric Cherenkov Telescopes (IACTs) such as the upcoming Cherenkov Telescope Array (CTA). In particular, the use of Convolutional Neural Networks (CNNs)…
Model quantization is a widely used technique to compress and accelerate deep neural network (DNN) inference. Emergent DNN hardware accelerators begin to support mixed precision (1-8 bits) to further improve the computation efficiency,…
The complexity and scale of IT systems are increasing dramatically, posing many challenges to real-world anomaly detection. Deep learning anomaly detection has emerged, aiming at feature learning and anomaly scoring, which has gained…