Related papers: Machine Learning for Imaging Cherenkov Detectors
Recent advances in engineered material technologies (e.g., photonic crystals, metamaterials, plasmonics, etc) provide valuable tools to control Cherenkov radiation. In all these approaches, however, the designed materials interact only with…
This paper presents a review of the recent Machine Learning activities carried out on beam measurements performed at the CERN Large Hadron Collider. This paper has been accepted for publication in IEEE Instrumentation and Measurement…
We present a perspective on molecular machine learning (ML) in the field of chemical process engineering. Recently, molecular ML has demonstrated great potential in (i) providing highly accurate predictions for properties of pure components…
Water Cherenkov detectors offer a robust and economical solution for real-time radiation monitoring by detecting Cherenkov light from charged particles moving faster than light in water. This work presents a novel two-stage classification…
Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many different approaches for many different IR problems. The amount of…
Advances in the technologies associated with position sensitive gaseous detectors especially featuring CsI as reflective photoconverters will be reviewed. These photodetectors represent the most effective solution for what concerns cost and…
Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…
This chapter reviews the application of Artificial Intelligence (AI) techniques to the study of galaxy clusters, covering both theoretical developments and their use as tools to infer cluster properties from a variety of observational…
Most of the computing resources pledged to the LHCb experiment at CERN are necessary to the production of simulated samples used to predict resolution functions on the reconstructed quantities and the reconstruction and selection…
Reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors. Artificial intelligence (AI) has made significant contributions to reactor physics,…
We have developed particle detectors based on fused silica (quartz) Cherenkov radiators read out with micro-channel plate photomultipliers (MCP-PMTs) or silicon photomultipliers (SiPMs) for high precision timing (Sigma(t) about 10-15 ps).…
Artificial Intelligence (AI), especially AI agents, is increasingly being applied to chemistry, healthcare, and manufacturing to enhance productivity. In this review, we discuss the progress of AI and agentic AI in areas related to, and…
Machine learning (ML) has emerged into formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In the recent years, it is safe to…
Recent developments in photo-detectors and photo-detector systems are reviewed. The main emphasis is made on Silicon Photo-Multipliers (SiPM) - novel and very attractive photo-detectors. Their main features are described. Properties of…
The LHCb detector will be upgraded to make more efficient use of the available luminosity at the LHC in Run III and extend its potential for discovery. The Ring Imaging Cherenkov detectors are key components of the LHCb detector for…
Nuclear reactors produce a high flux of MeV-scale antineutrinos that can be observed through inverse beta-decay (IBD) interactions in particle detectors. Reliable detection of reactor IBD signals depends on suppression of backgrounds, both…
Progress in nuclear physics is driven by the experimental observation that requires state of the art detectors to measure various kinematic properties, such as energy, momentum, position etc. of the particles produced in a nuclear reaction.…
In nuclear, particle and astroparticle physics experiments, calorimeters are used to measure the properties of particles with kinetic energies that range from a fraction of 1 eV to 10^20 eV or more. These properties are not necessarily…
The CLEO detector has been upgraded to include a state of the art particle identification system, based on the Ring Imaging Cherenkov Detector (RICH) technology, in order to take data at the upgraded CESR electron positron collider. The…
Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based…