Related papers: ML for the hKLM at the 2nd Detector
The scintillating properties of active materials used in high energy and particle physics experiments play an important role regarding the performances of both calorimeters and experiments. Two scintillator materials, a scintillating glass…
We propose a novel method for identification of a linear pattern of pixels on a two-dimensional grid. Following principles employed by the visual cortex, we employ orientation selective neurons in a neural network which performs this task.…
The original dual-readout calorimeter prototype (DREAM), constructed two decades ago, has proven instrumental in advancing our understanding of calorimetry. It has facilitated a multitude of breakthroughs by leveraging signals from…
Due to the environmental impacts caused by the construction industry, repurposing existing buildings and making them more energy-efficient has become a high-priority issue. However, a legitimate concern of land developers is associated with…
Transformer based models, especially large language models (LLMs) dominate the field of NLP with their mass adoption in tasks such as text generation, summarization and fake news detection. These models offer ease of deployment and…
We present the development and evaluation of a real-time Graph Neural Network-based trigger for the electromagnetic calorimeter of the Belle II experiment at the SuperKEKB collider. The algorithm processes calorimeter trigger cells as graph…
The precise simulation of particle transport through detectors remains a key element for the successful interpretation of high energy physics results. However, Monte Carlo based simulation is extremely demanding in terms of computing…
Glass RPC detectors are an attractive candidate for the active part of a highly granular digital hadron calorimeter (DHCAL) at the ILC. A numerical study, based on the GEANT3 simulation package, of the performance of such a calorimeter is…
State estimation is highly critical for accurately observing the dynamic behavior of the power grids and minimizing risks from cyber threats. However, existing state estimation methods encounter challenges in accurately capturing power…
A prototype module for an International Linear Collider (ILC) detector was built, installed, and tested between 2006 and 2009 at CERN and Fermilab as part of the CALICE test beam program, in order to study the possibilities of extending…
This paper presents studies on application of convolutional neural network (CNN) to GEANT4 optical simulation data generated with a scintillator detector subdivided into 1 cubic cm, which is designed for the long-baseline neutrino…
Graph neural networks (GNNs) have drawn more and more attention from material scientists and demonstrated a high capacity to establish connections between the structure and properties. However, with only unrelaxed structures provided as…
The analog hadron calorimeter for the International Linear Collider (ILC) of the CALICE collaboration utilized novel silicon detectors, the Sillicon Photomultipliers (SiPMs), for the detection of scintillation light coming from very small…
Hadronic calorimeters with dual readout measure both scintillation and Cherenkov lights produced in their active media. They offer improvements in energy resolution and, therefore, have become increasingly interesting due to the need for…
The HGND (High Granular Neutron Detector) is developed for the BM@N (Baryonic Matter at Nuclotron) experiment on the extracted beam of the Nuclotron at JINR, Dubna. The HGND will be used to measure the azimuthal flow of neutrons produced…
A highly granular electromagnetic calorimeter with scintillator strip readout is being developed for future lepton collider experiments. A prototype of 21.5 $X_0$ depth and $180 \times 180 $mm$^2$ transverse dimensions was constructed,…
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high energy particle physics. In particular, particle tracking data is…
Scintillators have long been known as radiation detectors and are still used in various applications. Recently, scintillators containing $^6$Li have been developed as neutron detectors and have attracted attention. $^6$Li absorbs thermal…
In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a…
Real-time particle transverse momentum ($p_T$) estimation in high-energy physics demands algorithms that are both efficient and accurate under strict hardware constraints. Static machine learning models degrade under high pileup and lack…