Search Results (46)

A number of phenomena were observed in experiments on the study of cosmic rays at mountain altitudes and in the stratosphere at ultra-high energies; in particular, the coplanarity of the most energetic particles and local subcascades in the so-called families of γ-rays and hadrons in the cores of extensive air showers at E₀ ≳ 2·10¹⁵ eV (√s ≳ 2 TeV). These effects are not described by theoretical models. To explain this phenomenon, it may be necessary to introduce a new process of generating the most energetic particles in the interactions of hadrons with the nuclei of atmospheric atoms. A new experimental array of cosmic ray detectors, including the ADRON-55 ionization calorimeter, has been created to study processes in EAS cores at ultra-high energies. The possibility of using it to study the coplanarity effect is being considered. Full article

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects. Full article

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 homogeneous lead tungstate calorimeter with high transverse and longitudinal segmentation, we investigated the discrimination of protons, positive pions, and positive kaons at 100 GeV. The analysis focuses on the impact of calorimeter granularity by progressively merging detector cells and extracting features like energy deposition patterns and timing information. Two machine learning approaches, XGBoost and fully connected deep neural networks, were employed to assess the classification performance across particle pairs. The results indicate that fine segmentation improves particle discrimination, with higher granularity yielding more detailed characterization of energy showers. Additionally, the results highlight the importance of shower radius, energy fractions, and timing variables in distinguishing particle types. The XGBoost model demonstrated computational efficiency and interpretability advantages over deep learning for tabular data structures, while achieving similar classification performance. This motivates further work required to combine high- and low-level feature analysis, e.g., using convolutional and graph-based neural networks, and extending the study to a broader range of particle energies and types. Full article

We simulate hadrons impinging on a homogeneous lead tungstate (${\mathrm{PbWO}}_4$) calorimeter using GEANT4 software to investigate how the resulting light yield and its temporal structure, as detected by an array of light-sensitive sensors, can be processed by a neuromorphic computing system. Our model encodes temporal photon distributions as spike trains and employs a fully connected spiking neural network to estimate the total deposited energy, as well as the position and spatial distribution of the light emissions within the sensitive material. The extracted primitives offer valuable topological information about the shower development in the material, achieved without requiring a segmentation of the active medium. A potential nanophotonic implementation using III-V semiconductor nanowires is discussed. It can be both fast and energy efficient. Full article

Calorimetry at the High Luminosity LHC (HL-LHC) faces many challenges, particularly in the forward direction, such as radiation tolerance and large in-time event pileup. To meet these challenges, the CMS Collaboration is preparing to replace its current endcap calorimeters from the HL-LHC era with a high-granularity calorimeter (HGCAL), featuring an unprecedented transverse and longitudinal segmentation, for both the electromagnetic and hadronic compartments, with 5D information (space–time–energy) read out. The proposed design uses silicon sensors for the electromagnetic section (with fluences above ${10}^{16} {\mathrm{n}}_{eq}{\mathrm{/cm}}^2$) and high-irradiation regions (with fluences above ${10}^{14} {\mathrm{n}}_{eq}{\mathrm{/cm}}^2$) of the hadronic section, while in the low-irradiation regions of the hadronic section, plastic scintillator tiles equipped with on-tile silicon photomultipliers (SiPMs) are used. Full HGCAL will have approximately 6 million silicon sensor channels and about 280 thousand channels of scintillator tiles. This will allow for particle-flow-type calorimetry, where the fine structure of showers can be measured and used to enhance particle identification, energy resolution and pileup rejection. In this overview we present the ideas behind HGCAL, the current status of the project, results of the beam tests and the challenges that lie ahead. Full article

The general-purpose Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN is used to study the production of new particles in proton–proton collisions at an LHC center of mass energy of 13.6 TeV. The detector includes a magnet based on a 6 m diameter superconducting solenoid coil operating at a current of 18.164 kA. This current creates a central magnetic flux density of 3.8 T that allows for the high-precision measurement of the momenta of the produced charged particles using tracking and muon subdetectors. The CMS magnet contains a 10,000 ton flux-return yoke of dodecagonal shape made from the assembly of construction steel blocks distributed in several layers. These steel blocks are magnetized with the solenoid returned magnetic flux and wrap the muons escaping the hadronic calorimeters of total absorption. To reconstruct the muon trajectories, and thus to measure the muon momenta, the drift tube and cathode strip chambers are located between the layers of the steel blocks. To describe the distribution of the magnetic flux in the magnet yoke layers, a three-dimensional computer model of the CMS magnet is used. To validate the calculations, special measurements are performed, with the flux loops wound in 22 cross-sections of the flux-return yoke blocks. The measured voltages induced in the flux loops during the CMS magnet ramp-ups and -downs, as well as during the superconducting coil fast discharges, are integrated over time to obtain the initial magnetic flux densities in the flux loop cross-sections. The measurements obtained during the seven standard ramp-downs of the magnet were analyzed in 2018. From that time, three fast discharges occurred during the standard ramp-downs of the magnet. This allows us to single out the contributions of the eddy currents, induced in steel, to the flux loop voltages registered during the fast discharges of the coil. Accounting for these contributions to the flux loop measurements during intentionally triggered fast discharges in 2006 allows us to perform the validation of the CMS magnet computer model with better precision. The technique for the flux loop measurements and the obtained results are presented and discussed. The method for measuring magnetic flux density in steel blocks described in this study is innovative. The experience of 3D modeling and measuring the magnetic field in steel blocks of the magnet yoke, as part of a muon detector system, has good prospects for use in the construction and operation of particle detectors for the Future Circular Electron–Positron Collider and the Circular Electron–Positron Collider. Full article

A comprehensive multi-jet physics program is anticipated for experiments at future colliders. Key physics processes necessitate detectors that can distinguish signals from W and Z bosons and the Higgs boson. Typical examples include channels with $W^{+}{W}^{-}$ or $Z^o{Z}^o$ pairs and processes involving new physics in those cases where neutral particles must be disentangled from charged ones due to the presence of W or Z bosons in their final states. Such a physics program demands calorimetric energy resolution at or beyond the limits of traditional calorimetric techniques. Multiple-readout calorimetry, which aims to reduce fluctuations in energy measurements of hadronic showers, is a promising approach. The first part of this article reviews dual- and triple-readout calorimetry within a mathematical framework describing the underlying compensating mechanism. The second part proposes a potential implementation using an integrally active and total absorption detector. This model serves as the basis for several Monte Carlo studies, illustrating how the response of a multiple-readout calorimeter depends on construction parameters. Among the layouts considered, one configuration operating in triple-readout mode shows the potential to achieve an energy resolution approaching $20\%/\sqrt{E}$. Full article

To study EAS cores (beams of most energetic particles near the shower axis) at E₀ ≳ 10¹⁵ eV (√s ≳ 2 TeV), which carry the most valuable information about the types of primary particles and the characteristics of their interactions in the atmosphere, a new set of detectors has been developed, including a high-altitude ionization calorimeter “ADRON-55”, located at a high-altitude scientific station on the Tien Shan. The first results of modeling the development of EAS from primary protons, main groups of nuclei and hypothetical strangelets at various energies, related to measurements with the “ADRON-55” calorimeter, are presented. Full article

Calorimetric experiments in space of the current and of the next generation measure cosmic rays directly above TeV on satellites in low Earth orbit. A common issue of these detectors is the determination of the absolute energy scale for hadronic showers above TeV. In this work, we propose the use of the Moon–Earth spectrometer technique for the calibration of calorimeters in space. In brief, the presence of the Moon creates a detectable lack of particles in the detected cosmic ray arrival directions. The position of this depletion has an offset with respect to the Moon center due to the deflection effect of the geomagnetic field on the cosmic rays that depends on the energy and the charge of the particle. The developed simulation will explore if, with enough statistics, angular, and energy resolutions, this effect can be exploited for the energy scale calibration of calorimeters on satellites in orbit in Earth’s proximity. Full article

In high-altitude experiments to study the central cores of EAS at E₀ ≳ 10¹⁶ eV (√s ≳ 5 TeV) using X-ray emulsion chambers and ionization calorimeters, phenomena such as the coplanarity of the arrival of the most energetic particles in super families of γ-rays and hadrons and a so-called Tien Shan effect (too slow absorption of cascades initiated by high-energy hadrons in the calorimeter) were observed. These effects could not be reproduced within the framework of theoretical models of the 80s and 90s. The coplanarity is explained via a process of coplanar generation of the most energetic secondary particles in interactions of super high-energy hadrons with nuclei of air atoms. Perhaps the Tien Shan effect could be explained using a high cross section for the generation of fragmentation-region charmed hadrons. To study these phenomena, a new set of detectors has been developed, including the world’s highest high-mountain ionization calorimeter, “Hadron-55”. This paper presents the initial experimental results. Full article

The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality monitoring (DQM) system to promptly spot and diagnose particle data acquisition problems to avoid data quality loss. In this study, we present a semi-supervised spatio-temporal anomaly detection (AD) monitoring system for the physics particle reading channels of the Hadron Calorimeter (HCAL) of the CMS using three-dimensional digi-occupancy map data of the DQM. We propose the GraphSTAD system, which employs convolutional and graph neural networks to learn local spatial characteristics induced by particles traversing the detector and the global behavior owing to shared backend circuit connections and housing boxes of the channels, respectively. Recurrent neural networks capture the temporal evolution of the extracted spatial features. We validate the accuracy of the proposed AD system in capturing diverse channel fault types using the LHC collision data sets. The GraphSTAD system achieves production-level accuracy and is being integrated into the CMS core production system for real-time monitoring of the HCAL. We provide a quantitative performance comparison with alternative benchmark models to demonstrate the promising leverage of the presented system. Full article

The upgrade of the A Toroidal LHC ApparatuS (ATLAS) hadronic Tile Calorimeter (TileCal) Low-Voltage Power Supply (LVPS) forms a part of the Phase-II Upgrade preparations undertaken by the ATLAS experiment for the data taking during the High-Luminosity Large Hadron Collider era. This paper serves to provide a detailed overview of the development of a Burn-in test station for an upgraded LVPS component known as a Brick. The production, quality assurance testing, and all associated apparatus are being jointly undertaken by the University of the Witwatersrand (Wits) and the University of Texas at Arlington (UTA). These Bricks are radiation-hard transformer-coupled buck converters that function to step-down bulk 200 VDC power to the 10 VDC required by the on-detector electronics. To ensure the high reliability of the Bricks, once installed within the TileCal, a Burn-in test station has been designed and built. The Burn-in station functions to implement a Burn-in procedure on eight Bricks simultaneously. This procedure subjects the Bricks to sub-optimal operating conditions, which function to accelerate their ageing, as well as to stimulate failure mechanisms. This results in elements of the Brick that would fail prematurely within the TileCal failing within the Burn-in station or experience performance degradation that can be detected by follow-up testing effectively screening out the non-performative sub-population. The Burn-in station is of fully custom design in both its hardware and software. The development of the test station will be explored in detail; the preliminary Burn-in procedure to be employed will be provided; the preliminary and final commissioning of the test station will be presented. The paper will culminate in the presentation and discussion of the Burn-in of a V8.4.2 Brick and the future outlook of the project. Full article

The general-purpose Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) at CERN incorporates a hadronic calorimeter to register the energies of the charged and neutral hadrons produced in proton–proton collisions at the LHC at a center-of-mass energy of 13.6 TeV. This calorimeter is located inside a superconducting solenoid that is 6 m in diameter and 12.5 m in length, generating a central magnetic flux density of 3.8 T. For operating optimally in the high pileup and high radiation environment of the High-Luminosity LHC, the existing CMS endcap calorimeters will be replaced with a new high granularity calorimeter (HGCal) with an electromagnetic section and a hadronic section in each of the two endcaps. The hadronic section of the HGCal will include 44 stainless-steel absorber plates with a relative permeability value well below 1.05. The volume occupied by 22 plates in each endcap is about 21 m³. The calculation of the axial electromagnetic forces acting on the absorber plates is a crucial element in designing the mechanical construction of the device. With a three-dimensional computer model of the CMS magnet, the axial forces on each absorber plate were calculated, and the dependence of forces on the central magnetic flux density value is presented. The method of calculation and the obtained results are discussed. Full article

SND@LHC is designed to perform measurements with neutrinos produced at the LHC in the pseudo-rapidity range of $7.2<\eta <8.4$. The experiment is located 480 m downstream of the ATLAS interaction point in the TI18 tunnel. The detector is a hybrid system composed of an 830 kg target made from 1 mm thick tungsten plates interleaved with nuclear emulsion films, electronic trackers also acting as an electromagnetic calorimeter, a hadronic calorimeter and a muon identification system. The detector is able to distinguish three neutrino flavours using the emulsion detector which can identify primary electrons and taus in charged current neutrino interactions. This capability allows probing heavy flavour forward production at the LHC, which even LHCb cannot access. The LHC CM energy corresponds to the ${10}^{17}$ eV astronomical energy region, which is of interest for future detectors. The SND@LHC’s capabilities and current status are reported in this document. Full article

In this review, we discuss and extend the study of the inclusive production of vector quarkonia, $J/\psi$ and $\mathrm{{\rm Y}}$, emitted with large transverse momenta and rapidities at the LHC. We adopt the novel ZCW19${}^{+}$ determination of fragmentation functions to depict the quarkonium production mechanism at the next-to-leading level of perturbative QCD. This approach is based on the nonrelativistic QCD formalism well adapted to describe the formation of a quarkonium state from the collinear fragmentation of a gluon or a constituent heavy quark at the lowest energy scale. We rely upon the $\mathrm{NLL}/{\mathrm{NLO}}^{+}$ hybrid high-energy and collinear factorization for differential cross-sections, where the collinear formalism is enhanced by the BFKL resummation of next-to-leading energy logarithms arising in the t-channel. We employ the method to analyze the behavior of the rapidity distributions for double-inclusive vector quarkonium and inclusive vector quarkonium plus jet emissions. We discover that the natural stability of the high-energy series, previously seen in observables sensitive to the emission of hadrons with heavy flavor detected in the rapidity acceptance of LHC barrel calorimeters, becomes even more manifest when these particles are tagged in forward regions covered by endcaps. Our findings present the important message that vector quarkonia at the LHC via hybrid factorization offer a unique chance to perform precision studies of high-energy QCD, as well as an intriguing opportunity to shed light on the quarkonium production puzzle. Full article