Electromagnetic Showers Research Articles

Mean arrival time distributions of extensive air showers at ultrahigh energies

This paper investigates extensive air showers by estimating the muon and electron mean arrival time distributions at ultrahigh energies for various cosmic-ray particles. The Monte Carlo package AIRES (version 19.04.00) was used to perform simulations at energies of 1019 and 1020 eV. The influence of primary particles (p, 56Fe, and 16O), energies, and zenith angles (0°, 10°, and 20°) on the mean arrival time of muonic and electromagnetic shower disks created in an extensive air shower was examined. Parameterized mean arrival time distributions were calculated for secondary particles e-, e+, and μ, created by proton, iron, and oxygen nuclei at energy 1019 eV in a vertical shower. A polynomial function for these primaries in vertical showers was established using the results of this simulation. The results were compared with the KASCADE-Grande experiment and Sciutto's simulations at energy 1020 eV and θ = 0. In this work the construction of a database that can be used to compute the arrival time of elementary particles is crucial in ultra-high energy ranges through an analytic description between the time structure and the distance distribution.

Multiplicity of electron- and photon-seeded electromagnetic showers at multipetawatt laser facilities

Multiplicity of electron- and photon-seeded electromagnetic showers at multipetawatt laser facilities

Particle identification in high-granularity 3D calorimeters for space-borne applications

High granularity 3D calorimeters offer the potential to precisely reconstruct the 3D topology of electromagnetic and hadronic showers originating from isotropic sources. This distinctive capability creates the opportunity for applying reconstruction and analysis methods that could yield additional information compared to those based on the traditional layer-by-layer energy deposit analysis common in particle and astroparticle physics experiments utilizing calorimeters with layer segmentation. In this study, we present a strategy for analyzing the energy deposit in a crystal array calorimeter, utilizing the 3D parametrization of both longitudinal and transversal shapes of showers to implement likelihood tests on single events. While this analysis was developed using the High Energy cosmic Radiation Detector (HERD) calorimeter as a case study, its applicability may extend to any high granularity, homogeneous, isotropic calorimeter employed in particle physics experiments.

PICOSEC-Micromegas Detector, an innovative solution for Lepton Time Tagging

The PICOSEC-Micromegas (PICOSEC-MM) detector is a novel gaseous detector designed for precise timing resolution in experimental measurements. It eliminates time jitter from charged particles in ionization gaps by using extreme UV Cherenkov light emitted in a crystal, detected by a Micromegas photodetector with an appropriate photocathode. The first single-channel prototype tested in 150 GeV/c muon beams achieved a timing resolution below 25 ps, a significant improvement compared to standard Micropattern Gaseous Detectors (MPGDs). This work explores the specifications for applying these detectors in monitored neutrino beams for the ENUBET Project. Key aspects include exploring resistive technologies, resilient photocathodes, and scalable electronics. New 7-pad resistive detectors are designed to handle the particle flux. In this paper, two potential scenarios are briefly considered: tagging electromagnetic showers with a timing resolution below 30ps in an electromagnetic calorimeter as well as individual particles (mainly muons) with about 20ps respectively.

Novel search for light dark photon in the forward experiments at the LHC

We propose a novel approach for discovering a light dark photon in the forward experiments at the LHC, including the SND@LHC and the FASER experiments. Assuming the dark photon is lighter than twice the electron mass and feebly interacts with ordinary matter, it is long-lived enough to pass through 100 m of rock in front of the forward experiments and also through the detector targets. However, some portion of them could be converted into an electron-positron pair inside the detector through their interaction with the detector target, leaving an isolated electromagnetic shower as a clear new physics signature of the dark photon. With copiously produced dark photons from neutral pion decays in the forward region of the LHC, we expect to observe sizable events inside the detector. Our estimation shows that more than 10 signal events of the dark photon could be observed in the range of kinetic mixing parameter, 6.2×10-5≲ϵ≲2×10-1 and 3×10-5≲ϵ≲2×10-1 for dark photon mass mA′≲ 1 MeV with integrated luminosities of 150 fb-1 and 3 ab-1, respectively.

Simulation of a capillary tube, fibre dual-readout calorimeter in DD4hep

Over the past years the dual-readout method for calorimetry, which exploits complementary information from Scintillation and Cherenkov channels, has emerged as candidate to fulfil the requirements for precision physics at future circular lepton colliders. While the dual-readout approach has been tested experimentally quite extensively, this type of calorimeter has never been used in an experiment at a collider. In recent years dedicated studies in simulation have investigated various detector geometries based on a fibre dual-readout calorimeter. One variation of the geometry, relying on capillary tubes, promises easy assembly with excellent geometrical accuracy at a moderate cost. In these proceedings, we present the status and latest results from a full 4π detector geometry simulation in DD4hep. The simulation is used to estimate the performance of a dual-readout calorimeter for single electromagnetic and hadronic particles. The results for the dual-readout technique show an improvement in energy resolution for both electromagnetic and hadronic showers, with respect to single channel measurements.

Particle identification capability of a homogeneous calorimeter composed of oriented crystals

Recent studies have shown that the electromagnetic shower induced by a high-energy electron, positron or photon incident along the axis of an oriented crystal develops in a space more compact than the ordinary. On the other hand, the properties of the hadronic interactions are not affected by the lattice structure. This means that, inside an oriented crystal, the natural difference between the hadronic and the electromagnetic shower profile is strongly accentuated. Thus, a calorimeter composed of oriented crystals could be intrinsically capable of identifying more accurately the nature of the incident particles, with respect to a detector composed only of non-aligned crystals. Since no oriented calorimeter has ever been developed, this possibility remains largely unexplored and can be investigated only by means of numerical simulations. In this work, we report the first quantitative evaluation of the particle identification capability of such a calorimeter, focusing on the case of neutron-gamma discrimination. We demonstrate through Geant4 simulations that the use of oriented crystals significantly improves the performance of a Random Forest classifier trained on the detector data. This work is a proof that oriented calorimeters could be a viable option for all the environments where particle identification must be performed with a very high accuracy, such as future high-intensity particle physics experiments and satellite-based γ-ray telescopes.

Anomaly detection with flow-based fast calorimeter simulators

Recently, several normalizing flow-based deep generative models have been proposed to accelerate the simulation of calorimeter showers. Using alolow as an example, we show that these models can simultaneously perform unsupervised anomaly detection with no additional training cost. As a demonstration, we consider electromagnetic showers initiated by one (background) or multiple (signal) photons. The alolow model is designed to generate single-photon showers, but it also provides access to the shower likelihood. We use this likelihood as an anomaly score and study the showers tagged as being unlikely. As expected, the tagger struggles when the signal photons are nearly collinear but is otherwise effective. This approach is complementary to a supervised classifier trained on only specific signal models using the same low-level calorimeter inputs. While the supervised classifier is also highly effective at unseen signal models, the unsupervised method is more sensitive in certain regions, and, thus, we expect that the ultimate performance will require a combination of these approaches. Published by the American Physical Society 2024

Study of time resolution measurements and prospects for energy resolution of an ultra-compact sampling calorimeter (RADiCAL) module at EM shower maximum over the energy range 25 GeV 150 GeV

The RADiCAL Collaboration is conducting R&D on high performance electromagnetic (EM) calorimetry to address the challenges expected in future collider experiments under conditions of high luminosity and/or high irradiation (FCC-ee, FCC-hh, fixed target and forward physics environments). Under development is a sampling calorimeter approach, known as RADiCAL modules, based on scintillation, wavelength-shifting (WLS) technologies and photosensor, including SiPM or SiPM-like technology. The modules discussed herein consist of alternating layers of very dense tungsten (W) absorber and scintillating crystal Lutetium Yttrium Orthosilicate LYSO(Ce) plates, assembled to a depth of 25 X0. The scintillation signals produced by the EM showers in the region of EM shower maximum (shower max) are transmitted to SiPM located at the upstream/downstream ends of the modules via quartz capillaries which penetrate the full length of the module. The capillaries contain DSB1 organic plastic WLS filaments positioned within the region of shower max, where the shower energy deposition is greatest, then fused with quartz rod elsewhere. The wavelength shifted light from this spatially-localized shower max region is then propagated to the photosensors. This paper presents the results of an initial measurement of the time resolution of a RADiCAL module over the energy range 25 GeV ≤ E ≤ 150 GeV using the H2 electron beam at CERN. The data indicate an energy dependence of the time resolution that follows the functional form: σt=a/E⊕b, where a = 256 GeV ps and b = 17.5 ps. The time resolution measured at the highest electron beam energy for which data was currently recorded (150 GeV) was found to be σt = 27 ps.

Search for long-lived heavy neutral leptons decaying in the CMS muon detectors in proton-proton collisions at s=13 TeV

A search for heavy neutral leptons (HNLs) decaying in the CMS muon system is presented. A data sample is used corresponding to an integrated luminosity of 138 fb−1 of proton-proton collisions at s=13 TeV, recorded at the CERN LHC in 2016–2018. Decay products of long-lived HNLs could interact with the shielding materials in the CMS muon system and create hadronic and electromagnetic showers detected in the muon chambers. This distinctive signature provides a unique handle to search for HNLs with masses below 4 GeV and proper decay lengths of the order of meters. The signature is sensitive to HNL couplings to all three generations of leptons. Candidate events are required to contain a prompt electron or muon originating from a vertex on the beam axis and a displaced shower in the muon chambers. No significant deviations from the standard model background expectation are observed. In the electron (muon) channel, the most stringent limits to date are set for HNLs in the mass range of 2.1–3.0 (1.9–3.3) GeV, reaching mixing matrix element squared values as low as 8.6(4.6)×10−6. © 2024 CERN, for the CMS Collaboration 2024 CERN

Updated Big Bang nucleosynthesis bounds on long-lived particles from dark sectors

As electromagnetic showers may alter the abundance of Helium, Lithium, and Deuterium, we can place severe constraints on the lifetime and amount of electromagnetic energy injected by long-lived particles. Considering up-to-date measurements of the light element abundances that point to Yp=0.245±0.003, (D/H)=(2.527±0.03)×10−5, and the baryon-to-photon ratio obtained from the Cosmic Microwave Background data, η=6.104×10−10, we derive upper limits on the fraction of electromagnetic energy produced by long-lived particles. Our findings apply to decaying dark matter models, long-lived gravitinos, and other non-thermal processes that occurred in the early universe between 102−1010 seconds.

Performance of the electromagnetic and hadronic prototype segments of the ALICE Forward Calorimeter

We present the performance of a full-length prototype of the ALICE Forward Calorimeter (FoCal). The detector is composed of a silicon-tungsten electromagnetic sampling calorimeter with longitudinal and transverse segmentation (FoCal-E) of about 20X 0 and a hadronic copper-scintillating-fiber calorimeter (FoCal-H) of about 5λ int. The data were taken in various test beam campaigns between 2021 and 2023 at the CERN PS and SPS beam lines with hadron beams up to energies of 350 GeV, and electron beams up to 300 GeV. Regarding FoCal-E, we report a comprehensive analysis of its response to minimum ionizing particles across all pad layers, employing various operational modes including different pre-amplifier and bias voltage settings. The longitudinal shower profile of electromagnetic showers is measured with a layer-wise segmentation of 1X 0. As a projection to the performance of the final detector in electromagnetic showers, we demonstrate linearity in the full energy range, and show that the energy resolution fulfills the requirements for the physics needs. Additionally, the performance to separate two-showers events was studied by quantifying the transverse shower width. Regarding FoCal-H, we report a detailed analysis of the response to hadron beams between 60 and 350 GeV. The results are compared to simulations obtained with a Geant4 model of the test beam setup, which in particular for FoCal-E are in good agreement with the data. The energy resolution of FoCal-E was found to be lower than 3% at energies larger than 100 GeV. The response of FoCal-H to hadron beams was found to be linear, albeit with a significant intercept that is about factor 2 larger than in simulations. Its resolution, which is non-Gaussian and generally larger than in simulations, was quantified using the FWHM, and decreases from about 16% at 100 GeV to about 11% at 350 GeV. The discrepancy to simulations, which is particularly evident at low hadron energies, needs to be further investigated.

Reconstruction of electromagnetic showers in calorimeters using Deep Learning

The precise reconstruction of properties of photons and electrons in modern high energy physics detectors, such as the CMS or ATLAS experiments, plays a crucial role in numerous physics results. Conventional geometrical algorithms are used to reconstruct the energy and position of these particles from the showers they induce in the electromagnetic calorimeter. Despite their accuracy and efficiency, these methods still suffer from several limitations, such as low-energy background and limited capacity to reconstruct close-by particles. This paper introduces an innovative machine-learning technique to measure the energy and position of photons and electrons based on convolutional and graph neural networks, taking the geometry of the CMS electromagnetic calorimeter as an example. The developed network demonstrates a significant improvement in resolution both for photon energy and position predictions compared to the algorithm used in CMS. Notably, one of the main advantages of this new approach is its ability to better distinguish between multiple close-by electromagnetic showers.

Reconstruction of 400 GeV/c proton interactions with the SHiP-charm project

The SHiP-charm project was proposed to measure the associated charm production induced by 400 GeV/c protons in a thick target, including the contribution from cascade production. An optimisation run was performed in July 2018 at CERN SPS using a hybrid setup. The high resolution of nuclear emulsions acting as vertex detector was complemented by electronic detectors for kinematic measurements and muon identification. Here we present first results on the analysis of nuclear emulsions exposed in the 2018 run, which prove the capability of reconstructing proton interaction vertices in a harsh environment, where the signal is largely dominated by secondary particles produced in hadronic and electromagnetic showers within the lead target.

First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE.

We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41} cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.

On the transition radiation interpretation of anomalous ANITA events

The Antarctic Impulsive Transient Antenna (ANITA) detector has observed several radio pulses coming from the surface of the ice cap at the South Pole. These pulses were attributed to upward-going atmospheric particle showers instead of the downward-going showers induced by cosmic rays that exhibit a characteristic polarity inversion of the radio signal due to reflection in the ice. Coherent transition radiation from cosmic-ray showers developing in the atmosphere and intercepting the ice surface has been suggested as a possible and alternative explanation of these so-called “anomalous” events. To test this interpretation, we have developed an extension of ZHS, a program to calculate coherent pulses from electromagnetic showers, to deal with showers that transit a planar interface between two homogeneous and dielectric media, including transition radiation. By considering different geometries, it is found that all pulses from air showers intercepting the ice surface and detected at the height of ANITA, display the same polarity as pulses emitted by ultra-high-energy cosmic-ray showers that fully develop in the atmosphere and are reflected on the ice. We find that transition radiation is disfavored as a possible explanation of the anomalous ANITA events.

Study of residual artificial neural network for particle identification in the CEPC high-granularity calorimeter prototype

Particle Identification (PID) plays a central role in associating the energy depositions in calorimeter cells with the type of primary particle in a particle flow oriented detector system. In this paper, we propose novel PID methods based on the Residual Network (ResNet) architecture which enable the training of very deep networks, bypass the need to reconstruct feature variables, and ensure the generalization ability among various geometries of detectors, to classify electromagnetic showers and hadronic showers. Using Geant4 simulation samples with energy ranging from 5 GeV to 120 GeV, the efficacy of Residual Connections is validated and the performance of our model is compared with Boosted Decision Trees (BDT) and other pioneering Artificial Neural Network (ANN) approaches. In shower classification, we observe an improvement in background rejection over a wide range of high signal efficiency (> 95%). These findings highlight the prospects of ANN with Residual Blocks for imaging detectors in the PID task of particle physics experiments.

The Excess-Path-Length Distribution of Electrons in Electromagnetic Cascade Showers

Abstract The excess-path-length distribution of cascade-shower particles due to the multiple Coulomb scattering of shower electrons is investigated analytically. A diffusion equation for the distribution under the Landau approximation is proposed and solved under the conditions of neglecting and including the ionization loss. Contributions of the Rutherford single scattering on the distribution are also investigated and found to dominate in very large excess regions of path length. The excess-path-length distribution of shower electrons is observed as an arrival-time distribution at a given thickness of traverse. The present results will be valuable for qualitative and quantitative analyses of cascade showers observed by the arrival-time distribution.

Deep Generative Models for Fast Photon Shower Simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Towards Real-Time Machine Learning-Based Signal/Background Selection in the CMS Detector Using Quantized Neural Networks and Input Data Reduction

The Large Hadron Collider (LHC) is being prepared for an extensive upgrade to boost its particle discovery potential. The new phase, High Luminosity LHC, will operate at a factor-of-five-increased luminosity (the number proportional to the rate of collisions). Consequently, such an increase in luminosity will result in enormous quantities of generated data that cannot be transmitted or stored with the currently available resources and time. However, the vast majority of the generated data consist of uninteresting data or pile-up data containing few interesting events or electromagnetic showers. High-Luminosity LHC detectors, including the Compact Muon Solenoid (CMS), will thus have to rely on innovative approaches like the proposed one to select interesting collision data. In charge of data reduction/selection at the early stages of data streaming is a level 1 trigger (L1T), a real-time event selection system. The final step of the L1T is a global trigger, which uses sub-system algorithms to make a final decision about signal acceptance/rejection within a decision time of around 12 microseconds. For one of these sub-system L1T algorithms, we propose using quantized neural network models deployed in targeted L1T devices, namely, field-programmable gate arrays (FPGA), as a classifier between electromagnetic and pile-up/quantum chromodynamics showers. The developed quantized neural network operates in an end-to-end manner using raw detector data to speed up the classification process. The proposed data reduction methods further decrease model size while retaining accuracy. The proposed approach was tested with simulated data (since the detector is still in the production stage) and took less than 1 microsecond, achieving real-time signal–background classification with a classification accuracy of 97.37% for 2-bit-only quantization and 97.44% for quantization augmented with the data reduction approach (compared to 98.61% for the full-precision, standard network).