Related papers: Efficient Antihydrogen Detection in Antimatter Phy…
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure $CP$-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional…
The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electrons and photons. It also provides a crucial input for…
Low energy antideuteron detection presents a unique channel for indirect detection, targeting dark matter that annihilates into hadrons in a relatively background-free way. Since the idea was first proposed, many WIMP-type models have…
Simplified models of the dark matter (co)annihilation mechanism predict striking new collider signatures untested by current searches. These models, which were codified in the coannihilation codex, provide the basis for a dark matter (DM)…
As the development of atom scale devices transitions from novel, proof-of-concept demonstrations to state-of-the-art commercial applications, automated assembly of such devices must be implemented. Here we present an automation method for…
Novelty detection is the machine learning task to recognize data, which belong to an unknown pattern. Complementary to supervised learning, it allows to analyze data model-independently. We demonstrate the potential role of novelty…
Antiprotonic helium, a neutral exotic three-body system consisting of a helium nucleus, an electron and an antiproton, is being studied at the Antiproton Decelerator of CERN by the ASAUCSA collaboration. Using laser spectroscopy of the…
Space-based X-ray detectors are subject to significant fluxes of charged particles in orbit, notably energetic cosmic ray protons, contributing a significant background. We develop novel machine learning algorithms to detect charged…
Gravitational wave astronomy is a vibrant field that leverages both classic and modern data processing techniques for the understanding of the universe. Various approaches have been proposed for improving the efficiency of the detection…
The functionality of electronic circuits can be seriously impaired by the occurrence of dynamic hardware faults. Particularly, for digital ultra low-power systems, a reduced safety margin can increase the probability of dynamic failures.…
Automatic hardhat wearing detection can strengthen the safety management in construction sites, which is still challenging due to complicated video surveillance scenes. To deal with the poor generalization of previous deep learning based…
Efficient and accurate object detection is an important topic in the development of computer vision systems. With the advent of deep learning techniques, the accuracy of object detection has increased significantly. The project aims to…
To world-wide notice, in 2002 the ATHENA collaboration at CERN (in Geneva, Switzerland) announced the creation of order 100,000 low energy antihydrogen atoms. Thus, the concept of using condensed antihydrogen as a low-weight, powerful fuel…
The Antiproton Decelerator of CERN began operation in 1999 to serve experiments for studies of CPT invariance by precision laser and microwave spectroscopy of antihydrogen ($\bar{\rm H}$) and antiprotonic helium ($\bar{p}{\rm He}^+$). The…
The ATLAS Inner Detector is responsible for particle tracking in ATLAS experiment at CERN Large Hadron Collider (LHC) and comprises silicon and gas based detectors. The combination of both silicon and gas based detectors provides high…
Recent years have seen increased theoretical and experimental effort towards the first-ever detection of cosmic-ray antideuterons, in particular as an indirect signature of dark matter annihilation or decay. In contrast to indirect dark…
This paper describes the algorithms for the reconstruction and identification of electrons in the central region of the ATLAS detector at the Large Hadron Collider (LHC). These algorithms were used for all ATLAS results with electrons in…
In light of recent experimental proposals to measure the free fall acceleration of antihydrogen in the earth's gravitational field, we investigate the bounds that existing experiments place on any asymmetry between the free fall of matter…
Anomaly detection methods used in a recent search for new phenomena by CMS at the CERN LHC are presented. The methods use machine learning to detect anomalous jets produced in the decay of new massive particles. The effectiveness of these…
In this article, we use artificial intelligence algorithms to show how to enhance the resolution of the elementary particle track fitting in inhomogeneous dense detectors, such as plastic scintillators. We use deep learning to replace more…