Particles

11 pages, 14103 KiB

Open AccessArticle

Production Optimization of Exotic Hypernuclei via Heavy-Ion Beams at GSI-FAIR

by Samuel Escrig and Christophe Rappold

Particles 2025, 8(2), 54; https://doi.org/10.3390/particles8020054 (registering DOI) - 1 May 2025

Building on the successful demonstration of hypernuclear spectroscopy using heavy-ion beams, the HypHI Collaboration is shifting its focus to investigating proton- and neutron-rich hypernuclei. A crucial component of this research is the implementation of a fragment separator, which facilitates the production and separation [...] Read more.

Building on the successful demonstration of hypernuclear spectroscopy using heavy-ion beams, the HypHI Collaboration is shifting its focus to investigating proton- and neutron-rich hypernuclei. A crucial component of this research is the implementation of a fragment separator, which facilitates the production and separation of rare isotope beams and is vital for accessing hypernuclei far from the stability line. High-precision spectroscopy of these exotic hypernuclei is planned to be conducted at GSI first, which will be followed by experiments at the FAIR facility utilizing the FRS and Super-FRS fragment separators. A thorough systematic investigation paired with an optimization analysis was employed to establish the most favorable experimental setup for producing high-isospin hypernuclei. Theoretical models describing heavy-ion-induced reactions and hypernuclear synthesis guided this process, which was complemented by Monte Carlo simulations to obtain experimental efficiencies for the production and transmission of the exotic secondary beams. The outlined methodology offers insights into the anticipated yields of

{}_{Λ}^{6}{He}

,

{}_{Λ}^{9}C

, and a range of both proton- and neutron-rich hypernuclei. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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20 pages, 1548 KiB

Open AccessArticle

Optimisation of Muon Tomography Scanners for Border Control Using TomOpt

by Zahraa Zaher, Samuel Alvarez, Tommaso Dorigo, Andrea Giammanco, Maxime Lagrange, Giles C. Strong, Pietro Vischia and Haitham Zaraket

Particles 2025, 8(2), 53; https://doi.org/10.3390/particles8020053 (registering DOI) - 1 May 2025

Abstract

The TomOpt software package is designed to optimise the geometric configuration and the specifications of detectors intended for muon scattering tomography, an imaging technique exploiting cosmic-ray muons. The software employs an end-to-end differentiable pipeline that models the interactions of muons with detectors and [...] Read more.

The TomOpt software package is designed to optimise the geometric configuration and the specifications of detectors intended for muon scattering tomography, an imaging technique exploiting cosmic-ray muons. The software employs an end-to-end differentiable pipeline that models the interactions of muons with detectors and scanned volumes, infers properties of the scanned materials, and performs an optimisation cycle minimising a user-defined loss function. This article presents the implementation of a case study related to cargo scanning applications in the context of homeland security. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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16 pages, 1496 KiB

Open AccessArticle

Neuromorphic Readout for Hadron Calorimeters

by Enrico Lupi, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Abhijit Das, Andrea De Vita, Tommaso Dorigo, Nicolas Ralph Gauger, Ralf Keidel, Jan Kieseler, Anders Mikkelsen, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Kylian Schmidt, Pietro Vischia and Joseph Willmore

Particles 2025, 8(2), 52; https://doi.org/10.3390/particles8020052 (registering DOI) - 1 May 2025

Abstract

We simulate hadrons impinging on a homogeneous lead tungstate (

{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 [...] Read more.

We simulate hadrons impinging on a homogeneous lead tungstate (

{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

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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19 pages, 6110 KiB

Open AccessArticle

Localized Multilayer Shielding of an Electron Beam Irradiation Station for FLASH Radiotherapy Experiments

by Kanlayaporn Kongmali, Pittaya Apiwattanakul, Phanthip Jaikeaw and Sakhorn Rimjaem

Particles 2025, 8(2), 51; https://doi.org/10.3390/particles8020051 (registering DOI) - 1 May 2025

Abstract

FLASH radiotherapy (FLASH-RT) is a cancer treatment delivering high-dose radiation within microseconds, reducing side-effects on healthy tissues. Implementing this technology at the PBP-CMU Electron Linac Laboratory poses challenges in ensuring radiation safety within a partially underground hall with thin walls and ceiling structures. [...] Read more.

FLASH radiotherapy (FLASH-RT) is a cancer treatment delivering high-dose radiation within microseconds, reducing side-effects on healthy tissues. Implementing this technology at the PBP-CMU Electron Linac Laboratory poses challenges in ensuring radiation safety within a partially underground hall with thin walls and ceiling structures. This study develops a localized shielding design for electron beams (6–25 MeV) using the GEANT4 release 11.2.2 Monte Carlo simulation toolkit. A multilayer system of lead, iron, polyethylene, and concrete effectively attenuates X-rays, gamma-rays, and neutrons, achieving dose levels below 1 mSv/year for public areas and within 20 mSv/year for controlled areas, meeting international standards. The B-factor analysis highlights efficient low-energy gamma attenuation and thicker shielding requirements for high-energy rays. The design minimizes radiation leakage, ensuring safe operation for FLASH-RT while safeguarding personnel and the environment. Future work includes constructing and validating the system, with methodologies applicable to other electron beam facilities. Full article

(This article belongs to the Special Issue Generation and Application of High-Power Radiation Sources 2025)

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10 pages, 4218 KiB

Open AccessArticle

Front-End Prototype ASIC with Low-Gain Avalanche Detector Sensors for the ATLAS High Granularity Timing Detector

by Salah El Dine Hammoud

Particles 2025, 8(2), 50; https://doi.org/10.3390/particles8020050 (registering DOI) - 1 May 2025

Abstract

Timing measurements are critical for the detectors at the future HL-LHC, to resolve reconstruction ambiguity when the number of simultaneous interactions reaches up to 200 per bunch crossing. The ATLAS collaboration therefore builds a new High-Granularity Timing detector for the forward region. A [...] Read more.

Timing measurements are critical for the detectors at the future HL-LHC, to resolve reconstruction ambiguity when the number of simultaneous interactions reaches up to 200 per bunch crossing. The ATLAS collaboration therefore builds a new High-Granularity Timing detector for the forward region. A customized ASIC, called ALTIROC, has been developed, to read out fast signals from low-gain avalanche detectors (LGADs), which has 50 ps time-resolution for signals from minimum-ionizing particles. To meet these requirements, a custom-designed pre-amplifier, a discriminator, and TDC circuits with minimal jitter have been implemented in a series of prototype ASICs. The latest version, ALTIROC3, is designed to contain full functionality. Hybrid assemblies with ALTIROC3 ASICs and LGAD sensors have been characterized with charged-particle beams at CERN-SPS and with laser-light injection. The time-jitter contributions of the sensor, pre-amplifier, discriminator, TDC, and digital readout are evaluated. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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9 pages, 2062 KiB

Open AccessArticle

Versal Adaptive Compute Acceleration Platform Processing for ATLAS-TileCal Signal Reconstruction

by Francisco Hervás Álvarez, Alberto Valero Biot, Luca Fiorini, Héctor Gutiérrez Arance, Fernando Carrió, Sonakshi Ahuja and Francesco Curcio

Particles 2025, 8(2), 49; https://doi.org/10.3390/particles8020049 (registering DOI) - 1 May 2025

Abstract

Particle detectors at accelerators generate large amounts of data, requiring analysis to derive insights. Collisions lead to signal pile-up, where multiple particles produce signals in the same detector sensors, complicating individual signal identification. This contribution describes the implementation of a deep-learning algorithm on [...] Read more.

Particle detectors at accelerators generate large amounts of data, requiring analysis to derive insights. Collisions lead to signal pile-up, where multiple particles produce signals in the same detector sensors, complicating individual signal identification. This contribution describes the implementation of a deep-learning algorithm on a Versal Adaptive Compute Acceleration Platform (ACAP) device for improved processing via parallelization and concurrency. Connected to a host computer via Peripheral Component Interconnect express (PCIe), this system aims for enhanced speed and energy efficiency over Central Processing Units (CPUs) and Graphics Processing Units (GPUs). In the contribution, we will describe in detail the data processing and the hardware, firmware and software components of the system. The contribution presents the implementation of the deep-learning algorithm on a Versal ACAP device, as well as the system for transferring data in an efficient way. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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11 pages, 837 KiB

Open AccessArticle

Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors

by Kalina Dimitrova, Venelin Kozhuharov and Peicho Petkov

Particles 2025, 8(2), 48; https://doi.org/10.3390/particles8020048 - 23 Apr 2025

Viewed by 148

Abstract

Machine learning methods are being introduced at all stages of data reconstruction and analysis in various high-energy physics experiments. We present the development and application of convolutional neural networks with modified autoencoder architecture for the reconstruction of the pulse arrival time and amplitude [...] Read more.

Machine learning methods are being introduced at all stages of data reconstruction and analysis in various high-energy physics experiments. We present the development and application of convolutional neural networks with modified autoencoder architecture for the reconstruction of the pulse arrival time and amplitude in individual scintillating crystals in electromagnetic calorimeters and other detectors. The network performance is discussed as well as the application of xAI methods for further investigation of the algorithm and improvement of the output accuracy. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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16 pages, 820 KiB

Open AccessArticle

End-to-End Detector Optimization with Diffusion Models: A Case Study in Sampling Calorimeters

by Kylian Schmidt, Krishna Nikhil Kota, Jan Kieseler, Andrea De Vita, Markus Klute, Abhishek, Max Aehle, Muhammad Awais, Alessandro Breccia, Riccardo Carroccio, Long Chen, Tommaso Dorigo, Nicolas R. Gauger, Enrico Lupi, Federico Nardi, Xuan Tung Nguyen, Fredrik Sandin, Joseph Willmore and Pietro Vischia

Particles 2025, 8(2), 47; https://doi.org/10.3390/particles8020047 - 23 Apr 2025

Viewed by 227

Abstract

Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce the end-to-end. AI Detector Optimization framework [...] Read more.

Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce the end-to-end. AI Detector Optimization framework (AIDO), which leverages a diffusion model as a surrogate for the full simulation and reconstruction chain, enabling gradient-based design exploration in both continuous and discrete parameter spaces. Although this framework is applicable to a broad range of detectors, we illustrate its power using the specific example of a sampling calorimeter, focusing on charged pions and photons as representative incident particles. Our results demonstrate that the diffusion model effectively captures critical performance metrics for calorimeter design, guiding the automatic search for a layer arrangement and material composition that align with known calorimeter principles. The success of this proof-of-concept study provides a foundation for the future applications of end-to-end optimization to more complex detector systems, offering a promising path toward systematically exploring the vast design space in next-generation experiments. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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26 pages, 2940 KiB

Open AccessReview

Cosmic Ray Muon Navigation for Subsurface Environments: Technologies and Challenges

by Dongqing Zhao, Pengfei Li and Linyang Li

Particles 2025, 8(2), 46; https://doi.org/10.3390/particles8020046 - 22 Apr 2025

Viewed by 161

Abstract

The global navigation satellite system (GNSS), using electromagnetic signals, enables continuous positioning throughout the entire surface of the Earth. However, underwater and underground environments significantly restrict the propagation of electromagnetic waves. The sole approach to aid positioning is the utilization of sound signals. [...] Read more.

The global navigation satellite system (GNSS), using electromagnetic signals, enables continuous positioning throughout the entire surface of the Earth. However, underwater and underground environments significantly restrict the propagation of electromagnetic waves. The sole approach to aid positioning is the utilization of sound signals. Signal blockage in underground and indoor environments demands the accurate location of anchor points for local positioning, which requires previous deployment. Unlike radio waves, the cosmic ray muons are highly reliable natural signal sources for positioning, remaining immune to spoofing and interference. Starting from the standpoint of navigation and positioning, this paper briefly introduces the physical properties of cosmic ray muons and outlines the measurements and positioning principles of muon navigation, including trilateral localization based on the time of flight (TOF) and angular localization based on the angle of arrival (AOA). It subsequently presents the pertinent studies conducted and analyzes the findings. Finally, the challenges of muon navigation are explored from three perspectives: positioning signals, positioning models, and application scenarios. This will offer some new ideas for the domain of localization for further research on muon positioning. Full article

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10 pages, 5511 KiB

Open AccessReview

Multimessenger Studies with the Pierre Auger Observatory

by Jon Paul Lundquist and the Pierre Auger Collaboration

Particles 2025, 8(2), 45; https://doi.org/10.3390/particles8020045 - 22 Apr 2025

Viewed by 120

Abstract

The Pierre Auger Observatory, the world’s largest ultra-high-energy (UHE) cosmic ray (CR) detector, plays a crucial role in multi-messenger astroparticle physics with its high sensitivity to UHE photons and neutrinos. Recent Auger Observatory studies have set stringent limits on the diffuse and point-like [...] Read more.

The Pierre Auger Observatory, the world’s largest ultra-high-energy (UHE) cosmic ray (CR) detector, plays a crucial role in multi-messenger astroparticle physics with its high sensitivity to UHE photons and neutrinos. Recent Auger Observatory studies have set stringent limits on the diffuse and point-like fluxes of these particles, enhancing constraints on dark-matter models and UHECR sources. Although no temporal coincidences of neutrinos or photons with LIGO/Virgo gravitational wave events have been observed, competitive limits on the energy radiated in these particles have been established, particularly from the GW170817 binary neutron star merger. Additionally, correlations between the arrival directions of UHECRs and high-energy neutrinos have been explored using data from the IceCube Neutrino Observatory, ANTARES, and the Auger Observatory, providing additional neutrino flux constraints. Efforts to correlate UHE neutron fluxes with gamma-ray sources within our galaxy continue, although no significant excesses have been found. These collaborative and multi-faceted efforts underscore the pivotal role of the Auger Observatory in advancing multi-messenger astrophysics and probing the most extreme environments of the Universe. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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9 pages, 340 KiB

Open AccessArticle

A Systematic Approach to Studying Quark Energy Loss in Nuclei Using Positive Pions

by Nicolás Zambra-Gómez, William K. Brooks and Nicolás Viaux

Particles 2025, 8(2), 44; https://doi.org/10.3390/particles8020044 - 15 Apr 2025

Viewed by 148

Abstract

Our objective is to test the published models of partonic energy loss, particularly those describing the energy loss mechanisms of quarks traversing nuclear matter, within the framework of semi-inclusive deep inelastic scattering. Our methodological approach focuses on quantifying the quark energy loss in [...] Read more.

Our objective is to test the published models of partonic energy loss, particularly those describing the energy loss mechanisms of quarks traversing nuclear matter, within the framework of semi-inclusive deep inelastic scattering. Our methodological approach focuses on quantifying the quark energy loss in cold matter by analyzing the positive pions (

π^{+}

) produced in various nuclear targets, including deuterium, carbon, iron and lead, while our first approach only includes deuterium and carbon. Before normalizing the pions’ energy distribution to unity to perform a shape analysis, acceptance corrections were performed to account for the detector’s efficiency and ensure accurate comparisons of the spectra. By normalizing the energy spectra of

π^{+}

produced from these distinct targets and based on the Baier–Dokshitzer–Mueller–Peigné–Schiff theory, which posits that quark energy loss depends only on nuclear size, it is assumed that the energy distributions of the targets will exhibit similar behavior. For this normalization, an energy shift between these distributions, corresponding to the quark energy loss, is identified. To ensure accuracy, statistical techniques such as the Kolmogorov–Smirnov test are used. The data used to test and explore the analysis technique and method were from the CLAS6 EG2 dataset collected using Jefferson Lab’s CLAS detector. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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20 pages, 2061 KiB

Open AccessArticle

Scattering-Based Machine Learning Algorithms for Momentum Estimation in Muon Tomography

by Florian Bury and Maxime Lagrange

Particles 2025, 8(2), 43; https://doi.org/10.3390/particles8020043 - 14 Apr 2025

Viewed by 276

Abstract

Muon tomography leverages the small, continuous flux of cosmic rays produced in the upper atmosphere to measure the density of unknown volumes. The multiple Coulomb scattering that muons undergo when passing through the material can either be leveraged or represent a measurement nuisance. [...] Read more.

Muon tomography leverages the small, continuous flux of cosmic rays produced in the upper atmosphere to measure the density of unknown volumes. The multiple Coulomb scattering that muons undergo when passing through the material can either be leveraged or represent a measurement nuisance. In either case, the scattering dependence on muon momentum is a significant source of imprecision. This can be alleviated by including dedicated momentum measurement devices in the experiment, which have a potential cost and can interfere with measurement. An alternative consists of leveraging information on scattering withstood through a known medium. We present a comprehensive study of diverse machine-learning algorithms for this regression task, from classical feature engineering with a fully connected network to more advanced architectures such as recurrent and graph neural networks and transformers. Several real-life requirements are considered, such as the inclusion of hit reconstruction efficiency and resolution and the need for a momentum resolution prediction that can improve reconstruction methods. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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10 pages, 392 KiB

Open AccessArticle

Calculation of α Decay Half-Lives for Tl, Bi, and At Isotopes

by Myeong-Hwan Mun, Kyoungsu Heo and Myung-Ki Cheoun

Particles 2025, 8(2), 42; https://doi.org/10.3390/particles8020042 - 11 Apr 2025

Viewed by 147

Abstract

We investigated the reaction Q-value (

Q_{α}

) for the

α

decay of Tl, Bi, and At isotopes using the deformed relativistic Hartree–Bogoliubov theory in continuum (DRHBc) with the covariant density functional PC-PK1. The

α

decay half-lives of Tl, Bi, and At [...] Read more.

We investigated the reaction Q-value (

Q_{α}

) for the

α

decay of Tl, Bi, and At isotopes using the deformed relativistic Hartree–Bogoliubov theory in continuum (DRHBc) with the covariant density functional PC-PK1. The

α

decay half-lives of Tl, Bi, and At isotopes are evaluated using various empirical formulas, based on both experimental

Q_{α}

and those obtained from DRHBc calculations. The calculated

Q_{α}

and

α

decay half-lives are compared with experimental data. On the basis of these results, we also predicted the

α

decay half-lives of isotopes for which experimental data are unavailable. Full article

(This article belongs to the Special Issue Selected Papers from the “7th Workshop on the Nuclear Mass Table with DRHBc Theory”)

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6 pages, 1393 KiB

Open AccessArticle

Results from Cryo-PoF Project: Power over Fiber at Cryogenic Temperature for Fundamental and Applied Physics

by Andrea Falcone, Alessandro Andreani, Claudia Brizzolari, Esteban Javier Cristaldo Morales, Maritza Juliette Delgado Gonzales, Claudio Gotti, Massimo Lazzaroni, Luca Meazza, Gianluigi Pessina, Francesco Terranova, Marta Torti and Valeria Trabattoni

Particles 2025, 8(2), 41; https://doi.org/10.3390/particles8020041 - 8 Apr 2025

Viewed by 152

Abstract

The Cryo-PoF project is an R&D project funded by the Italian Insitute for Nuclear Research (INFN) in Milano-Bicocca (Italy). The technology at the basis of the project is Power over Fiber (PoF). By sending laser light through an optical fiber, this technology delivers [...] Read more.

The Cryo-PoF project is an R&D project funded by the Italian Insitute for Nuclear Research (INFN) in Milano-Bicocca (Italy). The technology at the basis of the project is Power over Fiber (PoF). By sending laser light through an optical fiber, this technology delivers electrical power to a photovoltaic power converter, in order to power sensors or electrical devices. Among the several advantages this solution can provide, we can underline the spark-free operation when electric fields are present, the removal of noise induced by power lines, the absence of interference with electromagnetic fields, and robustness in hostile environments. R&D for the application of PoF in cryogenic environments started at Fermilab in 2020; for the DUNE Vertical Drift detector, it was needed to operate the Photon Detector System on a high-voltage cathode surface. Cryo-PoF, starting from this project, developed a single-laser input line system to power, at cryogenic temperatures, both an electronic amplifier and Photon Detection devices, tuning their bias by means of the input laser power, without adding ancillary fibers. The results obtained in Milano-Bicocca will be discussed, presenting the tests performed using power photosensors at liquid nitrogen temperature. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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25 pages, 1460 KiB

Open AccessArticle

Unsupervised Particle Tracking with Neuromorphic Computing

by Emanuele Coradin, Fabio Cufino, Muhammad Awais, Tommaso Dorigo, Enrico Lupi, Eleonora Porcu, Jinu Raj, Fredrik Sandin and Mia Tosi

Particles 2025, 8(2), 40; https://doi.org/10.3390/particles8020040 - 7 Apr 2025

Viewed by 331

Abstract

We study the application of a neural network architecture for identifying charged particle trajectories via unsupervised learning of delays and synaptic weights using a spike-time-dependent plasticity rule. In the considered model, the neurons receive time-encoded information on the position of particle hits in [...] Read more.

We study the application of a neural network architecture for identifying charged particle trajectories via unsupervised learning of delays and synaptic weights using a spike-time-dependent plasticity rule. In the considered model, the neurons receive time-encoded information on the position of particle hits in a tracking detector for a particle collider, modeled according to the geometry of the Compact Muon Solenoid Phase-2 detector. We show how a spiking neural network is capable of successfully identifying in a completely unsupervised way the signal left by charged particles in the presence of conspicuous noise from accidental or combinatorial hits, opening the way to applications of neuromorphic computing to particle tracking. The presented results motivate further studies investigating neuromorphic computing as a potential solution for real-time, low-power particle tracking in future high-energy physics experiments. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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9 pages, 3124 KiB

Open AccessArticle

Information Field Theory for Two Applications in Astroparticle Physics

by Martin Erdmann, Frederik Krieger, Alex Reuzki, Josina Schulte, Michael Smolka and Maximilian Straub

Particles 2025, 8(2), 39; https://doi.org/10.3390/particles8020039 - 7 Apr 2025

Viewed by 229

Abstract

Information field theory (IFT) provides a powerful framework for reconstructing continuous fields from noisy and sparse data. Based on Bayesian statistics, IFT allows for the approximation of posterior distributions over field-like parameter spaces in high-dimensional problems. In this contribution, we discuss two applications [...] Read more.

Information field theory (IFT) provides a powerful framework for reconstructing continuous fields from noisy and sparse data. Based on Bayesian statistics, IFT allows for the approximation of posterior distributions over field-like parameter spaces in high-dimensional problems. In this contribution, we discuss two applications of IFT in the context of astroparticle physics. First, we present its intended use for the calibration of the newly installed radio detector upgrade of the Pierre Auger Observatory. Second, we demonstrate its application to infer the initial directions of ultra-high-energy cosmic rays before their deflection in the Galactic magnetic field using a simplified model. Full article

(This article belongs to the Special Issue Selected Papers from the 4th MODE Workshop on Differentiable Programming for Experiment Design)

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14 pages, 962 KiB

Open AccessArticle

Probing QGP-like Dynamics via Multi-Strange Hadron Production in High-Multiplicity pp Collisions

by Haifa I. Alrebdi, Muhammad Ajaz, Muhammad Waqas, Maryam Waqar and Taoufik Saidani

Particles 2025, 8(2), 38; https://doi.org/10.3390/particles8020038 - 4 Apr 2025

Viewed by 234

Abstract

This study employs Monte Carlo (MC) models and thermal-statistical analysis to investigate the production mechanisms of strange (

K_{S}^{0}

,

Λ

) and multi-strange (

Ξ

,

Ω

) hadrons in high-multiplicity proton–proton collisions. Through systematic comparisons with experimental data, we [...] Read more.

This study employs Monte Carlo (MC) models and thermal-statistical analysis to investigate the production mechanisms of strange (

K_{S}^{0}

,

Λ

) and multi-strange (

Ξ

,

Ω

) hadrons in high-multiplicity proton–proton collisions. Through systematic comparisons with experimental data, we evaluate the predictive power of EPOS, PYTHIA8, QGSJETII04, and Sibyll2.3d. EPOS, with its hydrodynamic evolution, successfully reproduces low-

p_{T}

K_{S}^{0}

and

Λ

yields in high-multiplicity classes (MC1–MC3), mirroring quark-gluon plasma (QGP) thermalization effects. PYTHIA8’s rope hadronization partially mitigates mid-

p_{T}

multi-strange baryon suppression but underestimates

Ξ

and

Ω

yields due to the absence of explicit medium dynamics. QGSJETII04, tailored for cosmic-ray showers, overpredicts soft

K_{S}^{0}

yields from excessive soft Pomeron contributions and lacks multi-strange hadron predictions due to enforced decays. Sibyll2.3d’s forward-phase bias limits its accuracy at midrapidity. No model fully captures

Ξ

and

Ω

production, though EPOS remains the closest. Complementary Tsallis distribution analysis reveals a distinct mass-dependent hierarchy in the extracted effective temperature (

T_{eff}

) and non-extensivity parameter (q). As multiplicity decreases,

T_{eff}

rises while q declines—a trend amplified for heavier particles. This suggests faster equilibration of heavier particles compared to lighter species. The interplay of these findings underscores the necessity of incorporating QGP-like medium effects and refined strangeness enhancement mechanisms in MC models to describe small-system collectivity. Full article

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8 pages, 1295 KiB

Open AccessArticle

Bubble Structure in Isotopes of Lu to Hg

by Changhoon Song, Yongbeom Choi, Youngman Kim and Chang-Hwan Lee

Particles 2025, 8(2), 37; https://doi.org/10.3390/particles8020037 - 2 Apr 2025

Viewed by 201

Abstract

Bubble nuclei, characterized by a depletion in nucleon density at the nuclear center, are investigated within the atomic number range

71 \leq Z \leq 80

using the Deformed Relativistic Hartree–Bogoliubov theory in continuum. This study extends previous investigations, which were limited to even–even [...] Read more.

Bubble nuclei, characterized by a depletion in nucleon density at the nuclear center, are investigated within the atomic number range

71 \leq Z \leq 80

using the Deformed Relativistic Hartree–Bogoliubov theory in continuum. This study extends previous investigations, which were limited to even–even isotopes, by incorporating even–odd, odd–even, and odd–odd nuclei within this range. The extension is achieved by introducing the blocking effect into the point-coupling approach to ensure self-consistency. Following previous studies, we define a nucleus as a bubble candidate if the bubble parameter exceeds

B_{p}^{★} = 20 %

, and identify five bubble nuclei in both even-Z and odd-Z nuclei groups, based on the highest

B_{p}^{★}

values. The formation of bubble structures is confirmed through an analysis of proton single-particle energy levels of the most centrally depleted nuclei across four categories: even–odd, even–even, odd–even, and odd–odd. Full article

(This article belongs to the Special Issue Selected Papers from the “7th Workshop on the Nuclear Mass Table with DRHBc Theory”)

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13 pages, 6249 KiB

Open AccessArticle

The High-Granularity Timing Detector for ATLAS at HL-LHC

by Joaquim Pinol

Particles 2025, 8(2), 36; https://doi.org/10.3390/particles8020036 - 1 Apr 2025

Viewed by 149

Abstract

The increased particle flux expected at the HL-LHC poses a serious challenge for the ATLAS detector performance, especially in the forward region. The High-Granularity Timing Detector (HGTD), featuring novel Low-Gain Avalanche Detector silicon technology, will provide pile-up mitigation and luminosity measurement capabilities, and [...] Read more.

The increased particle flux expected at the HL-LHC poses a serious challenge for the ATLAS detector performance, especially in the forward region. The High-Granularity Timing Detector (HGTD), featuring novel Low-Gain Avalanche Detector silicon technology, will provide pile-up mitigation and luminosity measurement capabilities, and augment the new all-silicon Inner Tracker in the pseudo-rapidity range from 2.4 to 4.0. Two double-sided layers will provide a timing resolution better than 50 ps/track for MIPs throughout the HL-LHC running period, and provide a new timing-based handle to assign particles to the correct vertex. The LGAD technology provides suitable gain to reach the required signal-to-noise ratio, and a granularity of 1.3 × 1.3 mm² (with 3.6 M channels in total). This paper presents the current status of the HGTD project with emphasis on the sensor development and module results. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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11 pages, 323 KiB

Open AccessArticle

HYDrodynamics with JETs (HYDJET++): Latest Developments and Results

by Garnik Ambaryan, Larissa Bravina, Alexey Chernyshov, Gyulnara Eyyubova, Vladimir Korotkikh, Igor Lokhtin, Sergei Petrushanko, Alexandr Snigirev and Evgeny Zabrodin

Particles 2025, 8(2), 35; https://doi.org/10.3390/particles8020035 - 1 Apr 2025

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Abstract

Analysis of the (i) charge balance function and (ii) fluctuations of the net electric charge of hadrons in

P b

+

P b

collisions at center-of-mass energy 2.76 TeV per nucleon pair was performed within a two-component hydjet++ model. It is shown that [...] Read more.

Analysis of the (i) charge balance function and (ii) fluctuations of the net electric charge of hadrons in

P b

+

P b

collisions at center-of-mass energy 2.76 TeV per nucleon pair was performed within a two-component hydjet++ model. It is shown that neither the widths of the balance function nor the strongly intensive quantities, D and Σ, used to describe the net-charge fluctuations, can be reproduced within the model based on a grand canonical ensemble approach for generating multiparticle production. To solve this problem, it is necessary to take into account exact charge conservation in an event-by-event basis. The corresponding procedure was developed and implemented in the modified hydjet++ model. It provides a fair description of the experimental data. Full article

(This article belongs to the Special Issue Selected Papers from the 13th International Conference on New Frontiers in Physics (ICNFP 2024))

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Particles, Volume 8, Issue 2 (June 2025) – 20 articles

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