相关论文: Track identification and reconstruction in fast ne…

One of our two methods for fast-neutron imaging with spectrometric capability is presented here. It is a neutron-counting technique based on a hydrogenous neutron converter coupled to Gaseous Electron Multipliers (GEM). The principles of…

Many current and future nuclear physics (NP) experiments across the United States have and are implementing micro-pattern gas detectors (MPGDs) to be used for tracking and PID purposes. MPGDs are capable of operating in high rate…

Fast neutron detection is often based on the neutron-proton elastic scattering reaction: the ionization caused by recoil protons in a hydrogenous material constitutes the basic information for the design and development of a class of…

Gaseous detectors are fundamental components of all present and planned high energy physics experiments. Over the past decade two representatives (GEM, Micromegas) of the Micro-Pattern Gas Detector (MPGD) concept have become increasingly…

Fast 4$\pi$ solid angle particle track recognition has been a challenge in particle physics for a long time, especially in using nuclear emulsion detectors. The recent advances in computing technology opened the way for its realization. A…

The fast timing MPGD is a micro-pattern gaseous detector conceived for achieving sub-nanosecond time resolution while maintaining the ability to instrument large areas in high-rate environments; applications of such technology are…

We present track reconstruction algorithms based on deep learning, tailored to overcome specific central challenges in the field of hadron physics. Two approaches are used: (i) deep learning (DL) model known as fully-connected neural…

We propose an algorithm, deployable on a highly-parallelized graph computing architecture, to perform rapid reconstruction of charged-particle trajectories in the high energy collisions at the Large Hadron Collider and future colliders. We…

In-time particle trajectory reconstruction in the Large Hadron Collider is challenging due to the high collision rate and numerous particle hits. Using GNN (Graph Neural Network) on FPGA has enabled superior accuracy with flexible…

A centenary after the invention of the basic principle of gas amplification, gaseous detectors - are still the first choice whenever the large area coverage with low material budget is required. Advances in photo-lithography and…

Compared to Multi Wires Proportional Chambers (MWPC), Micro-Pattern Gas Detectors (MPGD) used in HEP to detect MIPs offer better spatial resolution, counting rate capability, and radiation hardness; their fabrication is also more…

The detection of low energy neutrinos ($<$ few tens of MeV) via coherent nuclear scattering remains a holy grail of sorts in neutrino physics. This uncontroversial mode of interaction is expected to profit from a sizeable increase in cross…

We propose a novel fast track finding system capable of reconstructing four dimensional particle trajectories in real time using precise space and time information of the hits. Recent developments in silicon pixel detectors achieved 150 ps…

In this study, we have developed a new sub-MeV neutron detector that has a high position resolution, energy resolution, directional sensitivity, and low background. The detector is based on a super-fine-grained nuclear emulsion, called the…

Micro-pattern gaseous detectors (MPGDs) are a class of technologies that enable the full three-dimensional spatial reconstruction of ionisation tracks from nuclear and electron recoils in gas. Anticipating near-future 30 m$^3$-scale time…

The Time Projection method is an ideal candidate to track low energy release particles. Large volumes can be readout by means of a moderate number of channels providing a complete 3D reconstruction of the charged tracks within the sensitive…

Neutron detectors are an essential tool for the development of many research fields, as nuclear, particle and astroparticle physics as well as radiotherapy and radiation safety. Since neutrons cannot directly ionize, their detection is only…

High-energy physics experiments require fast and efficient methods for reconstructing the tracks of charged particles. The commonly used algorithms are sequential, and the required CPU power increases rapidly with the number of tracks.…

The aim of this document is to summarise the discussion and the contributions from the 2nd Academia-Industry Matching Event on Detecting Neutrons with MPGDs which took place at CERN on the 16th and the 17th of March 2015. These events…

A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. The model is based on recurrent neural network, which can be trained…