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The recent experimental determinations of a large theta_13 angle have opened the way to a determination of the mass hierarchy and of the CP-violating phase. Experiments based on horn produced (anti-)neutrino conventional beams are presently…
A new detector is being developed at the National Superconducting Cyclotron Laboratory (NSCL) to measure low energy charged-particles from beta-delayed particle emission. These low energy particles are very important for nuclear…
The large-volume liquid-scintillator detector LENA (Low Energy Neutrino Astronomy) will provide high-grade background discrimination and enable the detection of diffuse supernova neutrinos (DSN) in an almost background-free energy window…
PAX (antiProtonic Atom X-ray spectroscopy) is a new experiment with the aim to test strong-field quantum electrodynamics (QED) effects by performing high-precision x-ray spectroscopy of antiprotonic atoms. By utilizing advanced…
A future large-volume liquid scintillator detector such as the proposed 50 kton LENA (Low Energy Neutrino Astronomy) detector would provide a high-statistics measurement of terrestrial antineutrinos originating from $\beta$-decays of the…
The ASACUSA (Atomic Spectroscopy And Collisions Using Slow Antiprotons) collaboration at the Antiproton Decelerator at CERN aims to measure the ground state hyperfine structure of antihydrogen. A Rabi-like spectrometer line has been built…
Deep neural network (DNN) models have shown remarkable success in many real-world scenarios, such as object detection and classification. Unfortunately, these models are not yet widely adopted in health monitoring due to exceptionally high…
In this paper we describe the design, construction, and operation of a first large area double-phase liquid argon Large Electron Multiplier Time Projection Chamber (LAr LEM-TPC). The detector has a maximum drift length of 60 cm and the…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
The ATLAS detector at the LHC is equipped with dedicated systems designed for the detection of forward protons produced in diffractive and photon-induced processes. These detectors significantly extend the ATLAS physics reach. Recent…
In June 2012, an Expression of Interest for a long-baseline experiment (LBNO) has been submitted to the CERN SPSC. LBNO considers three types of neutrino detector technologies: a double-phase liquid argon (LAr) TPC and a magnetised iron…
PANDA, the detector to study AntiProton ANnihilations at DArmstadt, will be installed at the future international Facility for Anti-proton and Ion Research (FAIR) in Darmstadt, Germany. The PANDA physics program is oriented towards the…
In coherent optical orthogonal frequency-division multiplexing (CO-OFDM) fiber communications, a novel end-to-end learning framework to mitigate Laser Phase Noise (LPN) impairments is proposed in this paper. Inspired by Autoencoder (AE)…
We constructed and operated a double phase (liquid-vapour) pure argon Large Electron Multiplier Time Projection Chamber (LAr LEM-TPC) with a sensitive area of 10x10 cm$^2$ and up to 30 cm of drift length. The LEM is a macroscopic hole…
The tracking system of the CMS experiment, currently under construction at the Large Hadron Collider (LHC) at CERN (Geneva, Switzerland), will include a silicon pixel detector providing three spacial measurements in its final configuration…
A system for online measurement of the transverse beam emittance was developed. It is named $^{4}$PrOB$\varepsilon$aM (4-Profiler Online Beam Emittance Measurement) and was conceived to measure the emittance in a fast and efficient way…
Precision measurements of the beam pattern response are needed to predict the response of a radio telescope. Mapping the beam of a low frequency radio array presents a unique challenge and science cases such as the observation of the 21\,cm…
Deploying deep neural networks~(DNNs) on edge devices provides efficient and effective solutions for the real-world tasks. Edge devices have been used for collecting a large volume of data efficiently in different domains. DNNs have been an…
Improving the efficiency of edge detection in embedded applications, such as UAV control, is critical for reducing system cost and power dissipation. Field programmable gate arrays (FPGA) are a good platform for making improvements because…
We report the development of deep learning coherent electron diffractive imaging at sub-angstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying…