Related papers: ML for the hKLM at the 2nd Detector
In this research, we developed a graph-based framework to represent various aspects of optimal thermal management system design, with the aim of rapidly and efficiently identifying optimal design candidates. Initially, the graph-based…
This study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN)…
The successful realization of the EIC scientific program requires the design and construction of high-performance particle detectors. Recent developments in the field of scientific computing and increased availability of high performance…
The successful integration of machine learning models into decision support tools for grid operation hinges on effectively capturing the topological changes in daily operations. Frequent grid reconfigurations and N-k security analyses have…
Materials discovery, especially for applications that require extreme operating conditions, requires extensive testing that naturally limits the ability to inquire the wealth of possible compositions. Machine Learning (ML) has nowadays a…
We present a measurement of scintillation efficiency for a few tens of keV nuclear recoils (NR) with a liquid argon time projection chamber under electric fields ranging from $0$ to $3\ {\rm kV/cm}$. The calibration data are taken with…
Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations when the underlying lattices can be represented as small…
Liquid argon is being employed as a detector medium in neutrino physics and Dark Matter searches. A recent push to expand the applications of scintillation light in Liquid Argon Time Projection Chamber neutrino detectors has necessitated…
In this work, we present results for discrimination of neutron and $\gamma$ events using a plastic scintillator detector with pulse shape discrimination capabilities. Machine learning (ML) algorithms are used to improve the discriminatory…
The basic prototype of a tile hadron calorimeter (HCAL) for the International Linear Collider (ILC) has been realised and extensively tested. A major aspect of the proposed concept is the improvement of the jet energy resolution by…
Recent progress in Graph Neural Networks (GNNs) has greatly enhanced the ability to model complex molecular structures for predicting properties. Nevertheless, molecular data encompasses more than just graph structures, including textual…
The measurement of energy is a fundamental tool used, for example, in exploring the early universe, characterizing particle decay processes, as well as in quantum technology and computing. Some of the most sensitive energy detectors are…
We exposed a prototype of the lead-scintillating fiber KLOE calorimeter to neutron beam of 21, 46 and 174 MeV at The Svedberg Laboratory, Uppsala, to study its neutron detection efficiency. This has been found larger than what expected…
Antiferromagnetic materials are exciting quantum materials with rich physics and great potential for applications. It is highly demanded of the accurate and efficient theoretical method for determining the critical transition temperatures,…
This paper introduces a novel approach to sea ice modeling using Graph Neural Networks (GNNs), utilizing the natural graph structure of sea ice, where nodes represent individual ice pieces, and edges model the physical interactions,…
Molecular dynamics simulations offer detailed insights into atomic motions but face timescale limitations. Enhanced sampling methods have addressed these challenges but even with machine learning, they often rely on pre-selected…
A high-energy e+e- collider, such as the ILC or CLIC, is arguably the best option to complement and extend the LHC physics programme. A lepton collider will allow for exploration of Standard Model Physics, such as precise measurements of…
A compact and fast electromagnetic calorimeter prototype was designed, built, and tested in preparation for a next-generation, high-rate muon g-2 experiment. It uses a simple assembly procedure: alternating layers of 0.5-mm-thick tungsten…
In this paper we present a method of scintillation detector energy calibration using the gamma-rays. The technique is based on the Compton scattering of gamma-rays in a scintillation detector and subsequent photoelectric absorption of the…
A new method for measuring the electron temperature of the plasma in GOL-NB facility is proposed. The proposed method is based on measuring the ratio of intensities of spectral lines emitted by fast atoms injected into the plasma. The beams…