Particle Detectors Research Articles

The PMT Acquisition and Trigger Generation System of the HEPD-02 Calorimeter for the CSES-02 Satellite

This contribution describes the acquisition and trigger system for the HEPD-02 calorimeter that will be used onboard the CSES-02 satellite for the CSES/Limadou mission. This mission arises from the collaboration between the Chinese Space Agency (CNSA) and the Italian Space Agency (ASI) and plans the realization of a constellation of satellites which will monitor ionospheric parameters supposed to be related to earthquakes. It will also monitor the solar activity and the interaction with the magnetosphere and will study the cosmic rays in low energy ranges, extending data from PAMELA and AMS. The CSES-02 satellite will be equipped with various instruments, including the High-Energy Particle Detector (HEPD-02), which was designed to measure the energy of particles coming from Van Allen belts. Signals from the HEPD-02 are acquired and digitized by an electronic board that also produces the trigger for the experiment. A new generation ASIC (CITIROC) for the amplification, shaping and memorization of signals from PMTs will be used on this board. The new ASIC allows the use of the peak detector feature, optimizing the acquisition of signals with different temporal characteristics. Along with this, new algorithms for trigger generation have been developed, providing trigger pre-scaling, concurrent trigger masks and Gamma Ray Burst detection. Using pre-scaled concurrent triggers will allow the study of very sensitive regions of a satellite’s orbit such as the South Atlantic Anomaly and polar regions and to detect rare events such as GRBs while still monitoring particle bursts. In this contribution, the progress status of this work will be presented along with the measurements and tests made to finalize the flight model of the board.

Conditions for Energetic Electrons and Gamma Rays in Thunderstorm Ground Enhancements

AbstractThe role of free passage distance (FPD: the distance between the avalanche region and surface detectors) in influencing the relative numbers of energetic electrons and gamma rays in Thunderstorm Ground Enhancements (TGEs) is reconsidered and focuses on the contrast between long (>100 m) versus short (<100 m) FPDs, respectively. Estimates of FPD are based on information from published balloon soundings of the electric field, from published profiles of radar reflectivity in TGEs, and from analyses of Japan winter storms. All these data sources support typical values of FPD >100 m. Neither the shortcomings of present particle detectors in distinguishing electrons from gamma rays, nor the dominance of gamma rays over electrons, are sufficient evidence to deny the robust presence of Compton electrons at FDP values greater than 100 m that have also been shown in earlier simulations as well as the present Comment. Problems with having sustained electric fields of breakeven magnitude within 100 m of the Earth's surface (in relatively rare TGEs) are identified. The resolution of these problems, and the prominent nocturnal presence of these rare events, may possibly be explained by the descent of a strong field region in a collapsing storm, and by a low cloud base that intercepts and immobilizes fast corona ions, thereby preserving the intense electric field.

Towards Neural Charged Particle Tracking in Digital Tracking Calorimeters with Reinforcement Learning.

We propose a novel technique for reconstructing charged particles in digital tracking calorimeters using reinforcement learning aiming to benefit from the rapid progress and success of neural network architectures without the dependency on simulated or manually-labeled data. Here we optimize by trial-and-error a behavior policy acting as an approximation to the full combinatorial optimization problem, maximizing the physical plausibility of sampled trajectories. In modern processing pipelines used in high energy physics and related applications, tracking plays an essential role allowing to identify and follow charged particle trajectories traversing particle detectors. Due to the high multiplicity of charged particles and their physical interactions, randomly deflecting the particles, the reconstruction is a challenging undertaking, requiring fast, accurate and robust algorithms. Our approach works on graph-structured data, capturing track hypotheses through edge connections between particles in the detector layers. We demonstrate in a comprehensive study on simulated data for a particle detector used for proton computed tomography, the high potential as well as the competitiveness of our approach compared to a heuristic search algorithm and a model trained on ground truth. Finally, we point out limitations of our approach, guiding towards a robust foundation for further development of reinforcement learning based tracking.

Differentiable Earth mover’s distance for data compression at the high-luminosity LHC

The Earth mover’s distance (EMD) is a useful metric for image recognition and classification, but its usual implementations are not differentiable or too slow to be used as a loss function for training other algorithms via gradient descent. In this paper, we train a convolutional neural network (CNN) to learn a differentiable, fast approximation of the EMD and demonstrate that it can be used as a substitute for computing-intensive EMD implementations. We apply this differentiable approximation in the training of an autoencoder-inspired neural network (encoder NN) for data compression at the high-luminosity LHC at CERN The goal of this encoder NN is to compress the data while preserving the information related to the distribution of energy deposits in particle detectors. We demonstrate that the performance of our encoder NN trained using the differentiable EMD CNN surpasses that of training with loss functions based on mean squared error.

DeepHCC: Deep learning model for real-time count rate determination of particles in homemade cloud chamber

Cosmic ray (CR) particles are high-energy particles originating from outer space that often reach the ground as alpha and proton particles, which can be studied using particle detectors. While investigating CR particles is a complex process, cloud chambers offer a simple means of detection. However, they cannot measure count rates directly. To overcome this limitation, we developed a deep learning model for real-time count rate determination of particles in a homemade cloud chamber (DeepHCC), implementing YOLOv5 pre-trained weights to use with our homemade cloud chamber. We trained DeepHCC using a total of 2,435 images from our homemade cloud chamber and other cloud chambers and found that YOLOv5m was the most suitable model for our task due to its fast and accurate detection capabilities. DeepHCC performed well in fundamental evaluations, with an overall area under the precision-recall curve of 0.8886 and an F1 score of 0.8624 while operating at 61 frames per second. We also experimented on count rate determination compared to human performance, which yielded an overall accuracy of 80.15%. Overall, DeepHCC could be used with our homemade cloud chambers to create particle detector kits with comparable performance. However, our model could not detect muons and accurately identify electrons due to an imbalanced dataset used in the training process. These reveal opportunities for future research to explore other techniques to address this problem. We also plan to compare our results with other detectors to verify reliability. The results demonstrate that our work could also be an innovative prototype for an engaging educational physics instrument.

Self-protected high-temperature superconducting demonstrator magnet for particle detectors

A high temperature superconducting (HTS) demonstration coil has been developed in the frame of the Experimental Physics department Research and Development program at CERN The magnet extends the recent experimental demonstration of aluminium-stabilised HTS conductors and supports the development of future large scale detector magnets. The HTS magnet has five turns and an open bore diameter of 230 mm. Up to 30 K, the coil was measured to be fully superconducting across four central turns at 4.4 kA, the maximum available current of existing power supply. The central magnetic field is 0.113 T, the peak field on the conductor is 1.2 T and the coil has a stored magnetic energy of 0.1 kJ. A 3D-printed aluminium alloy (Al10SiMg) cylinder acts both as a stabiliser and a mechanical support for the superconductor. The resistivity of Al10SiMg was measured at cryogenic temperatures, and has a residual resistivity ratio of approximately 2.5. The ability to solder ReBCO tapes (a stack of four REBCO tapes, 4 mm wide, Fujikura) to Al10SiMg stabiliser, electroplated with copper and tin, forming a coil, is demonstrated using tin-lead solder at 188 ∘C. The HTS magnet was proven to be stable when superconductivity was broken locally using a thin-film heater. Despite voids in the solder joint between HTS and stabiliser, no degradation of the magnet’s performance was observed after 12 thermal cycles and locally quenching the magnet. A numerical model of the transient behaviour of solenoid with partially shorted turns is developed and validated against measurements. Our work experimentally and numerically validates that using an aluminium alloy as a stabiliser for HTS tapes can result in a stable, lightweight and transparent magnet.

Pattern recognition and signal parameters extraction using machine learning methods

Machine learning methods can be used for signal processing in different cases of physics research. A convolutional neural network was developed for the task of pulse counting in particle detectors for high energy physics. For the extraction of signal parameters was used a network with convolutional autoencoder architecture and a subsequent result reconstruction algorithm was developed and applied. A convolutional neural network was also developed for seismic studies with the task of identifying different events in seismograms. All of the algorithms with their architecture, input and output are presented and discussed.

Relativistic electron beams accelerated by an interplanetary shock

Context. Collisionless shock waves have long been considered to be among the most prolific particle accelerators in the universe. Shocks alter the plasma they propagate through, and often exhibit complex evolution across multiple scales. Interplanetary (IP) traveling shocks have been recorded in situ for over half a century and act as a natural laboratory for experimentally verifying various aspects of large-scale collisionless shocks. A fundamentally interesting problem in both heliophysics and astrophysics is the acceleration of electrons to relativistic energies (> 300 keV) by traveling shocks. Aims. The reason for an incomplete understanding of electron acceleration at IP shocks is due to scale-related challenges and a lack of instrumental capabilities. This Letter presents the first observations of field-aligned beams of relativistic electrons upstream of an IP shock, observed thanks to the instrumental capabilities of Solar Orbiter. This study presents the characteristics of the electron beams close to the source and contributes to the understanding of their acceleration mechanism. Methods. On 25 July 2022, Solar Orbiter encountered an IP shock at 0.98 AU. The shock was associated with an energetic storm particle event, which also featured upstream field-aligned relativistic electron beams observed 14 min prior to the actual shock crossing. The distance of the beam’s origin was investigated using a velocity dispersion analysis (VDA). Peak-intensity energy spectra were anaylzed and compared with those obtained from a semi-analytical fast-Fermi acceleration model. Results. By leveraging Solar Orbiter’s high temporal resolution Energetic Particle Detector (EPD), we successfully showcase an IP shock’s ability to accelerate relativistic electron beams. Our proposed acceleration mechanism offers an explanation for the observed electron beam and its characteristics, while we also explore the potential contributions of more complex mechanisms.

Reliability evaluation of the CAEN DT5202 for high-rate data acquisition

Multichannel readout systems play an important role in contemporary physics experiments. Apart from custom-designed highly specialized electronics, several commercial solutions exist on the market. The CAEN DT5202 readout module, comprised of two Citiroc 1A ASICs for a total of 64 channels, was chosen as a typical example. Its performance was studied in specific use cases in a laboratory test environment. The preliminary results of the tests and the evaluation of the hardware module for its applicability in particle detector readout systems are presented. In addition, the control software shipped together with the module has also been studied and its current limitations are discussed.

Three topologies of deep neural networks for pulse height extraction

Pulse shaping is a common technique for optimizing signal-to-noise ratio (SNR) in particle detectors. Although analog or digital linear shapers are typically used for this purpose, there are nonlinear approaches, such as neural networks (NN), which have demonstrated their potential to outperform linear ones. Their nonlinear nature makes it possible to optimize the SNR of incoming pulses and extract diverse information, such as particle type and energy, with extremely short shaping time to avoid crowding. This paper shows three different NNs for shaping pulses: (a) convolutional NN (CNN); (b) recurrent NN (RNN); (c) self-attenuating NN. These NNs shape the pulses and return them unfolded avoiding stacking, and even estimate the height of the pulses when there has been saturation in the preamplifier. In this work we show the architectures of the NNs and their results using CR–RC pulses with Brownian and white noise, but they could be extrapolated to any shape and type of noise. The results obtained show that when the noise level is low and the frequency is low, all the topologies presented are a valid solution, but with white noise and high pulse arrival frequency, CNN is a better solution than the others. In the case of Brownian noise, the three topologies presented give similar results.

Guided Search to Self‐Healing in Semiconductors

AbstractSelf‐healing (SH) of (opto)electronic material damage can have a huge impact on resource sustainability. The rising interest in halide perovskite (HaP) compounds over the past decade is due to their excellent semiconducting properties for crystals and films, even if made by low‐temperature solution‐based processing. Direct proof of self‐healing in Pb‐based HaPs is demonstrated through photoluminescence recovery from photodamage, fracture healing and their use as high‐energy radiation and particle detectors. Here, the question of how to find additional semiconducting materials exhibiting SH, in particular lead‐free ones is addressed. Applying a data‐mining approach to identify semiconductors with favorable mechanical and thermal properties, for which Pb HaPs are clear outliers, it is found that the Cs2AuIAuIIIX6, (X = I, Br, Cl) family, which is synthesized and tested for SH. This is the first demonstration of self‐healing of Pb‐free inorganic HaP thin films, by photoluminescence recovery.

Accelerated paths and Unruh effect: finite time detector response in (anti) de Sitter spacetime and Huygen’s principle

We study the finite time response of an Unruh–DeWitt particle detector described by a qubit (two-level system) moving with uniform constant acceleration in maximally symmetric spacetimes. The D dimensional massless fermionic response function in de Sitter (dS) background is found to be identical to that of a detector linearly coupled to a massless scalar field in 2D dimensional dS background. Furthermore, we visit the status of Huygen’s principle in the Unruh radiation observed by the detector.

Correlation harvesting between particle detectors in uniform motion

Correlation harvesting between particle detectors in uniform motion

The synchronous detection technique for the accurate monitoring of high-energy pulsed X-rays

At high energy, the smaller inelastic nucleon-Carbon cross-section implies that diamond has a radiation hardness an order of magnitude higher than that of silicon. The production of high-quality diamond crystals and films grown using the chemical vapor deposition technique opened the way for the use of synthetic diamonds in the fabrication of detectors for charged particles and high-energy photons. More recently, laser-processing technology for the fabrication of three-dimensional contacts in diamond has been proposed to produce highly efficient detectors, even with ultra-low active volumes. However, buried-contact structures made with laser treatments unavoidably induce structural defects in the volume surrounding the buried columns, thus affecting the detector response due to trap-related charge transport mechanisms. When pulsed radiation is concerned, experimental results reported in this work demonstrate that synchronous signal conditioning can strongly mitigate the trap-mediated contribution, thereby improving the performance of the overall detection system. Significantly, these results pave the way for the application of diamond samples with three-dimensional buried-contacts in the development of detectors for accurate dosimetry.

A Compact Particle Detector for Space-Based Applications: Development of a Low-Energy Module (LEM) for the NUSES Space Mission

NUSES is a planned space mission aiming to test new observational and technological approaches related to the study of relatively low-energy cosmic rays, gamma rays, and high-energy astrophysical neutrinos. Two scientific payloads will be hosted onboard the NUSES space mission: Terzina and Zirè. Terzina will be an optical telescope readout by SiPM arrays, for the detection and study of Cerenkov light emitted by Extensive Air Showers generated by high-energy cosmic rays and neutrinos in the atmosphere. Zirè will focus on the detection of protons and electrons up to a few hundred MeV and to 0.1–10 MeV photons and will include the Low Energy Module (LEM). The LEM will be a particle spectrometer devoted to the observation of fluxes of relatively low-energy electrons in the 0.1–7-MeV range and protons in the 3–50 MeV range along the Low Earth Orbit (LEO) followed by the hosting platform. The detection of Particle Bursts (PBs) in this Physics channel of interest could give new insight into the understanding of complex phenomena such as eventual correlations between seismic events or volcanic activity with the collective motion of particles in the plasma populating van Allen belts. With its compact sizes and limited acceptance, the LEM will allow the exploration of hostile environments such as the South Atlantic Anomaly (SAA) and the inner Van Allen Belt, in which the anticipated electron fluxes are on the order of 106 to 107 electrons per square centimeter per steradian per second. Concerning the vast literature of space-based particle spectrometers, the innovative aspect of the LEM resides in its compactness, within 10 × 10 × 10 cm3, and in its “active collimation” approach dealing with the problem of multiple scattering at these very relatively low energies. In this work, the geometry of the detector, its detection concept, its operation modes, and the hardware adopted will be presented. Some preliminary results from the Monte Carlo simulation (Geant4) will be shown.

Quantum Otto engine driven by quantum fields

We consider a quantum Otto engine using an Unruh-DeWitt particle detector model which interacts with a quantum scalar field in curved spacetime. We express a generic condition for extracting positive work in terms of the effective temperature of the detector. This condition reduces to the well-known positive work condition in the literature under the circumstances where the detector reaches thermal equilibrium with the field. We then evaluate the amount of work extracted by the detector in two scenarios: an inertial detector in a thermal bath and a circulating detector in the Minkowski vacuum, which is inspired by the Unruh quantum Otto engine.

The Resistive Cylindrical Chamber

A new generation of gaseous particle detectors named Resistive Cylindrical Chamber (RCC) (Cardarelli, 2021; Rocchi, 2022) [1,2] has been developed to overcome the limitations of Resistive Plate Chambers (Santonico and Cardarelli, 1981) [3] and broaden their application range. The principle behind this new technology consists in the transition from a planar to a cylindrical geometry while maintaining an almost planar electric field. The cylindrical structure of the electrodes allows to reach the following goals: increase the gas pressure to improve the intrinsic efficiency of the detector even for thin gas gaps or light gas mixtures; design the detector in order to produce an electric field gradient possibly useful to contain the development of the avalanche discharge. These features could lead to design detectors of simple mechanical realization with time resolution comparable with that of MRPCs maintaining a high efficiency of detection on a single thin gas-gap. The device pressurization could also allows to use new gases in view of the transition to eco-friendly gas.

Study of a metal-halide perovskite CsPbBr3 thin film deposited on a 10B layer for neutron detection

Metal halide perovskite materials have received significant attention in recent years due to their promising properties and potential applications, particularly their use as scintillator detectors, which is rapidly emerging due to their promising advantages as detectors, such as low costs, fast response, high quantum yield, strong absorption, scalability, flexibility, and emission wavelength tunability. Given the effectiveness of perovskites as α particle detectors and the potential of 10B as a neutron converter, in this paper a 10B converting layer was coupled with an all-inorganic lead halide perovskite (CsPbBr3) layer aiming to create a thermal neutron detector. Specifically, a 1 µm thin film of 10B and a 1 µm thin layer of CsPbBr3 were deposited on a suitable substrate using a laser ablation process. The fabricated detector was subjected to a comprehensive characterization, including structural, morphological, and detection properties. As output, the films exhibit macroscopically uniform behavior and good adhesion to the substrate. In terms of thermal neutron efficiency, an efficiency of (7.9 ± 0.3)% was determined with respect to a commercial detector (EJ-426), which corresponds to an intrinsic efficiency of (2.5 ± 0.1)%. Also, Monte Carlo simulations were conducted, and the optimum value of the 10B layer thickness was found to be 2.5 µm.

Energetic Electrons Near Europa From Juno JEDI Data

AbstractOptical remote sensing observations have suggested that the top layer of Europa's icy surface is heavily affected by external weathering agents. To model and understand these effects, it is necessary to characterize the environment as fully as possible. In this paper, we focus on one agent in the environment (energetic electrons). We show Juno electron data from its 2022 Europa flyby and other time periods. While the Juno sensor used here (Jupiter Energetic Particle Detector Instrument) was not designed to obtain high quality electron data in an intense radiation environment, it is possible to extract information such as how Europa blocks energetic particles from accessing some of the surrounding space. The decrease in charged particle flux in Europa's wake provides an upper limit on the precipitation fluxes of the same particles. We also report that electron pitch angle distributions near Europa for the single energy channel considered here are time variable and not isotropic.

Broadband infinite-Q plasmons enable intense Smith–Purcell radiation

With the rapid development of nanophotonics for enhancing free-electron radiation, bound states in the continuum (BICs) have emerged as a promising approach for emitting intense Smith–Purcell radiation (SPR) with enhanced intensity. However, current BIC-based methods are limited to single-frequency operation, thereby restricting their applications requiring spectral and angular tunability, such as particle detectors and light sources. To overcome this limitation, this work proposes an approach for constructing plasmonic BICs over a broad spectral range in symmetry-broken systems. By leveraging the high-Q resonances near the BICs, we achieve intense SPR with broadband tunability, potentially improving the radiation intensity by six orders compared to traditional methods. Experimentally, we validate the construction of BIC using plasmonic antennas and achieve broadband demonstration. Our proposed concept can be extended to other plasmonic or guided-wave systems, paving the way toward compact and efficient free-electron sources in hard-to-reach frequency regimes.