High Energy Physics Experiments Research Articles

Pressure resistance characterisation of vascular networks embedded in carbon composites for high energy physics applications

In state-of-the-art tracking detectors, lightweight carbon composite structures support the pixel or micro-strip sensors and provide the main thermal path between the silicon and a network of metallic or plastic pipes containing a cooling fluid. Despite the good results obtained with this design approach, the challenges associated with future high energy physics (HEP) experiments demand even lighter and more efficient technologies. In this regard, replacing the existing piping with a network of channels directly embedded in the composite laminates represents a promising solution to improve the thermal coupling, which also offers additional gains in terms of mass and thermo-elastic stability.While some research has been devoted to assessing the mechanical and thermal performance of such laminates, limited information about their resistance to internal pressure is currently available in the literature. This lack of data constitutes an important obstacle for the use of vascular networks in future HEP applications, which the present paper aims to address.Experimental methods were used to investigate the pressure resistance of channels embedded in carbon composite laminates. Modified poly (lactic) acid (PLA) preforms were embedded in carbon-fibre epoxy laminates. A post-cure vaporization technique removed the PLA, thus producing plates with longitudinal channels. Destructive tests were conducted to determine the burst pressure of the plates depending on the lay-up and the cross-section geometry of the channels. Both circular and oblong channels were evaluated, and various reinforcement techniques were explored to enhance the pressure resistance of the laminates. Micro-graphic examinations and X-ray micro-computed tomography were employed to gain a better understanding of the microstructure and the failure mechanisms of the plates.Plates with circular channels measuring 1.75 mm in diameter, embedded in [0/90/0]S laminates and reinforced with 2 mm lay length fuzzy carbon fibre over-braids, achieved burst pressures exceeding 45 MPa. This result, which is approximately an order of magnitude greater than that obtained for the equivalent non-reinforced laminates, demonstrates the enormous potential of this technology for future particle detectors.

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.

All-optical source size and emittance measurements of laser-accelerated electron beams

Novel schemes for generating ultralow emittance electron beams have been developed in past years and promise compact particle sources with excellent beam quality suitable for future high-energy physics experiments and free-electron lasers. Recent theoretical work has proposed a laser-based method capable of resolving emittances in the sub 0.1 mm mrad regime by modulating the electron phase space ponderomotively. Here we present the first experimental demonstration of this scheme using a laser wakefield accelerator. The observed emittance and source size are consistent with published values. We also show calculations demonstrating that tight bounds on the upper limit for emittance and source size can be derived from the “laser-grating” method even in the presence of low signal to noise and uncertainty in laser-grating parameters. Published by the American Physical Society 2024

Distilling particle knowledge for fast reconstruction at high-energy physics experiments

Knowledge distillation is a form of model compression that allows artificial neural networks of different sizes to learn from one another. Its main application is the compactification of large deep neural networks to free up computational resources, in particular on edge devices. In this article, we consider proton-proton collisions at the High-Luminosity Large Hadron Collider (HL-LHC) and demonstrate a successful knowledge transfer from an event-level graph neural network (GNN) to a particle-level small deep neural network (DNN). Our algorithm, DistillNet, is a DNN that is trained to learn about the provenance of particles, as provided by the soft labels that are the GNN outputs, to predict whether or not a particle originates from the primary interaction vertex. The results indicate that for this problem, which is one of the main challenges at the HL-LHC, there is minimal loss during the transfer of knowledge to the small student network, while improving significantly the computational resource needs compared to the teacher. This is demonstrated for the distilled student network on a CPU, as well as for a quantized and pruned student network deployed on an field programmable gate array. Our study proves that knowledge transfer between networks of different complexity can be used for fast artificial intelligence (AI) in high-energy physics that improves the expressiveness of observables over non-AI-based reconstruction algorithms. Such an approach can become essential at the HL-LHC experiments, e.g. to comply with the resource budget of their trigger stages.

A new cold cooling system using krypton for the future upgrade of the LHC after the long shutdown 4 (LS4)

Future silicon detectors for High Energy Physics Experiments will require operation at lower temperatures to cope with radiation damage of the sensors and consequent increase of the dark current, beyond the limit of the current CO2 evaporative cooling system. This, together with many other requirements such as mass minimization and high radiation hardness, pushes the need of a new advanced cooling technology. The new coolant shall be able to approach ultra-low temperatures below −60 °C, withstand high radiation levels while having cooling lines diameters comparable to the currently achieved with the CO2 technology. Among different natural working fluids, krypton appears as a promising coolant for the thermal management of future detectors in high-irradiated environments. The thermodynamic properties of krypton do not allow the use of a pumped loop cycle but rather impose a need of a novel cooling technology. A new ejector-supported krypton cycle is presented, highlighting the cycle dynamics involved due to the different temperature levels normally encountered during the detector lifetime.

Excitation signal optimization for minimizing fluctuations in knock out slow extraction

The synchrotron is a circular particle accelerator used for high energy physics experiments, material and life science, as well as hadron cancer therapy. After acceleration to the desired energies, particle beams are commonly extracted from the synchrotron using the method of resonant slow extraction. The goal is to deliver a steady particle flux—referred to as spill—to experiments and treatment facilities over the course of seconds while slowly emptying the storage ring. Any uncontrolled intensity fluctuations in the spill are detrimental to the efficiency of beam usage, as they lead to detector pileups or detector interlocks, hindering experiments and cancer treatment. Among the most widely used extraction scheme in medical facilities is the Radio Frequency Knock Out (RF-KO) driven resonant slow extraction, where the stored beam is transversely excited with a radio frequency (RF) field and the spill intensity is controlled by the excitation signal strength. This article presents particle dynamics simulations of the RF-KO system with the focus on finding effective mechanism for minimizing the intensity fluctuations while maintaining a good extraction efficiency and other advantages of KO extraction. An improved beam excitation signal which optimizes these main objectives is found, and is rigorously compared experimentally with other commonly applied techniques.

Interpretable deep learning models for the inference and classification of LHC data

The Shower Deconstruction methodology is pivotal in distinguishing signal and background jets, leveraging the detailed information from perturbative parton showers. Rooted in the Neyman-Pearson lemma, this method is theoretically designed to differentiate between signal and background processes optimally in high-energy physics experiments. A key challenge, however, arises from the combinatorial growth associated with increasing jet constituents, which hampers its computational feasibility. We address this by demonstrating that the likelihood derived from comparing the most probable signal and background shower histories is equally effective for discrimination as the conventional approach of summing over all potential histories in top quark versus Quantum Chromodynamics (QCD) scenarios. We propose a novel approach by conceptualising the identification of the most probable shower history as a Markov Decision Process (MDP). Utilising a sophisticated modular point-transformer architecture, our method efficiently learns the optimal policy for this task. The developed neural agent excels in constructing the most likely shower history and demonstrates robust generalisation capabilities on unencountered test data. Remarkably, our approach mitigates the complexity inherent in the inference process, achieving a linear scaling relationship with the number of jet constituents. This offers a computationally viable and theoretically sound method for signal-background differentiation, paving the way for more effective data analysis in particle physics.

Correlation between charge and current gain in LGADs treated with IR lasers

This study investigates the correlation between the gain, defined as the increase of measured charge generated from the absorption of incident radiation, and the gain measured as the increase of sensor leakage current in Low Gain Avalanche Detectors (LGAD) before and after neutron irradiations. LGADs exhibit high signal-to-noise ratios for minimum ionizing particles and will be used in high-energy physics experiments, mainly related to timing applications. Transient Current Technique (TCT) measurements were conducted with LGADs and PIN diodes. The electric field screening effect, caused by free and trapped carriers, is identified as the main reason for the differences measured in gain determined from the increase in leakage current and collected charge. These effects are more significant in irradiated LGAD sensors. The experimental results confirm expectations, demonstrating a growing spread between the two measured gains with fluence. The study enables the prediction of charge gain from the leakage current measurements, which are easier to conduct.

A new track finding algorithm based on a multi-dimensional extension of the Hough Transform

We introduce a new pattern recognition algorithm for track finding in High Energy Physics Experiments based on an extension of the Hough Transform to multiple dimensions. A remarkable property of this algorithm is that the execution time is simply proportional to the total number of the hits to be processed, making it particularly attractive for high occupancy situations. The algorithm needs to be trained using a sufficiently large set of simulated tracks. The same track finding algorithm can be used for very different detector geometries and only the set of simulated tracks used for training needs to be changed. The particular structure of the algorithm also lends itself naturally to parallel hardware implementations which, combined with its intrinsic flexibility, should provide a most powerful tool for triggering at future colliders.

Investigation of the stability in the performance of triple GEM detectors for High Energy Physics experiments

Gas Electron Multiplier (GEM) is one of the mostly used technologies in the High Energy Physics (HEP) experiments. GEMs are widely used as tracking devices due to their high-rate handling capability and good position resolution.An initiative is taken to study the stability in performance of the GEM chamber prototypes in the laboratory using external radiation for Argon/CO2 gas mixture in 70/30 volume ratio. The effect of ambient parameters on the gain and energy resolution are studied. Very recently some behavioural changes in the performance of a single-mask GEM chamber is observed. The details of the experimental setup, methodology and results are reported here.

Overview of the production and qualification tests of the lpGBT

The Low-Power Gigabit Transceiver (lpGBT) is a radiation-tolerant ASIC used in high-energy physics experiments for multipurpose high-speed bidirectional serial links. Around 200,000 chips have been tested with a production test system capable of exercising the majority of the ASIC functionality to ensure its correct operation.Furthermore, specific individual qualification tests were carried out beyond the production tester limits, including radiation, multi-drop bus topology, inter-chip communication through different types of electrical links and characterization of jitter and stability of the recovered clocks.In this article, an overview of the production and qualification tests is given together with their results demonstrating the robustness and flexibility of the lpGBT.

Breakdown performance of guard ring designs for pixel detectors in 150 nm CMOS technology

Silicon pixel sensors manufactured using commercial CMOS processes are promising instruments for high-energy particle physics experiments due to their high yield and proven radiation hardness. As one of the essential factors for the operation of detectors, the breakdown performance of pixel sensors constitutes the upper limit of the operating voltage. Six types of passive CMOS test structures were fabricated on high-resistivity wafers. Each of them features a combination of different inter-pixel designs and sets of floating guard rings, which differ from each other in the geometrical layout, implantation type, and overhang structure. A comparative study based on leakage current measurements in the sensor substrate of unirradiated samples was carried out to identify correlations between guard ring designs and breakdown voltages. TCAD simulations using the design parameters of the test structures were performed to discuss the observations and, together with the measurements, ultimately provide design features targeting higher breakdown voltages.

Radiation hardness of MALTA2 monolithic CMOS imaging sensors on Czochralski substrates

MALTA2 is the latest full-scale prototype of the MALTA family of Depleted Monolithic Active Pixel Sensors (DMAPS) produced in Tower Semiconductor 180 nm CMOS sensor imaging technology. In order to comply with the requirements of high energy physics (HEP) experiments, various process modifications and front-end changes have been implemented to achieve low power consumption, reduce random telegraph signal (RTS) noise, and optimise the charge collection geometry. Compared to its predecessors, MALTA2 targets the use of a high-resistivity, thick Czochralski (Cz) substrates in order to demonstrate radiation hardness in terms of detection efficiency and timing resolution up to 3 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes $$\\end{document} 1015\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{15}$$\\end{document} 1 MeV neq/cm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathrm {n_{eq}/{cm}^2}$$\\end{document} with backside metallisation to achieve good propagation of the bias voltage. This manuscript shows the results that were obtained with non-irradiated and irradiated MALTA2 samples on Cz substrates from the CERN SPS test beam campaign from 2021 to 2023 using the MALTA telescope.

Compact silicon photonic Mach-Zehnder modulators for high-energy physics

The characterization of compact non-traveling-wave Mach-Zehnder modulators for optical readout in high-energy physics experiments is reported to provide power-efficient alternatives to conventional traveling-wave devices and a more resilient operation compared to ring modulators. Electro-optical small-signal and large-signal measurements showcase the performances of custom NTW-MZMs designed and fabricated in iSiPP50G IMEC's technology in the framework of INFN's FALAPHEL project. Bit-error-rate results demonstrate their potential suitability for optical links up to 25 Gb/s when equipped with either conventional deep-etched or radiation-hardened shallow-etched free-carrier-based phase shifters.

Dual use driver for high speed links transmitters in the future high energy physics experiments

The paper presents the Dual Use Driver (DUDE) for high speed links, a circuit designed for the Demonstrator ASIC for Radiation-Tolerant Transmitter in 28 nm CMOS (DART28) developed under the EP-R&D programme on technologies for future high energy physics experiments. The driver operates at 25.6 Gbps and it allows driving both 100 Ω transmission lines and optical Ring Modulators (RMs) integrated in a photonics integrated circuit (PIC). The driver includes configurable pre-emphasis. The device will allow to demonstrate the feasibility of wavelength division multiplexing (WDM) optical links operating with bandwidths in excess of 100 Gbps per fiber that are capable of sustaining total ionizing radiation doses up to 10 MGy.

ParticleNet and its application on CEPC jet flavor tagging

Quarks (except top quarks) and gluons produced in collider experiments hadronize and fragment into sprays of stable particles, called jets. Identification of quark flavor is desired for collider experiments in high-energy physics, relying on flavor tagging algorithms. In this study, using a full simulation of the Circular Electron Positron Collider (CEPC), we investigate the flavor tagging performance of two different algorithms: ParticleNet, based on a Graph Neural Network, and LCFIPlus, based on the Gradient Booted Decision Tree. Compared to LCFIPlus, ParticleNet significantly enhances flavor tagging performance, resulting in a significant improvement in benchmark measurement accuracy, i.e., a 36% improvement for σ(ZH)·Br(Z→νν¯,H→cc¯)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma (ZH)\\cdot Br(Z\\rightarrow \ u \\bar{\ u }, H\\rightarrow c\\bar{c})$$\\end{document} measurement and a 75% improvement for |Vcb|\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$|V_{cb}|$$\\end{document} measurement via W boson decay, respectively, when the CEPC operates as a Higgs factory at the center-of-mass energy of 240 GeV and collects an integrated luminosity of 5.6 ab-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document}. We compare the performance of ParticleNet and LCFIPlus at different vertex detector configurations, observing that the inner radius is the most sensitive parameter, followed by material budget and spatial resolution.

A monolithic active pixel sensor with node-based, data-driven, parallel readout for the high energy physics experiment vertex detector

We present the design of a prototype MAPS sensor MIC6_V1 based on a 55 nm Quad-well CMOS Image Sensor process for the CEPC vertex detector. A new node-based, data-driven, parallel readout architecture is implemented to achieve high spatial resolution, fast readout, and low power consumption. The size of MIC6_V1 is 2.8 mm × 2.8 mm, which contains a pixel matrix of 64 rows by 64 columns, and the pixel size is 23.6 μ m × 20 μ m. The integration time is 5 μs, and the hit arrival time measurement accuracy is 10 ns.

Machine Learning based Reconstruction for the MUonE Experiment

As currently operating high energy physics experiments produce a huge amount of data, new methods of fast and efficient event reconstruction are necessary to handle the immense load. Storing the unprocessed data is not feasible, forcing experiments to process the data online employing the algorithms of quality provided for the offline analysis, but within strict time constraints. In the MUonE experiment the machine learning based event reconstruction techniques are being implemented and tested in order to provide efficient online reduction of data and to maximize the statistical power of the final physics measurement.

Detector development for particle physics

In high-energy physics experiments, tracking and vertexing is nowadays mostly done using semiconductor detectors. Among the employed detectors are hybrid pixel sensors, passive sensors and recently also depleted monolithic active pixel sensors (DMAPS), which integrate the particle sensor with front-end electronics. Currently, the dominant material for the production of such sensors is silicon. However, the use of silicon carbide is currently being investigated. In this work we report on our progress on the development of silicon-based DMAPS. Further, we present two approaches for reading out passive silicon carbide detectors at particle rates from the kHz to the GHz range.

The k4Clue package: Empowering future collider experiments with the CLUE algorithm

High granularity calorimeters have become increasingly crucial in modern particle physics experiments, and their importance is set to grow even further in the future. The CLUstering of Energy (CLUE) algorithm has shown excellent performance in clustering calorimeter hits in the High Granularity Calorimeter (HGCAL) developed for the Phase-2 upgrade of the CMS experiment. In this paper, the suitability of the CLUE algorithm for future collider experiments has been investigated and its capabilities tested outside the HGCAL reconstruction software. To this end, a new package, k4Clue, was developed which is now fully integrated into the Gaudi software framework and supports the EDM4hep data format for inputs and outputs. The performance of CLUE was demonstrated in three detectors for future colliders: CLICdet for the CLIC accelerator, CLD for the FCC-ee collider and a second calorimeter based on Noble Liquid technology also proposed for FCC-ee. Excellent reconstruction performance was observed for single photon events, even in the presence of noise, and the results are compatible with the performance of the algorithms used currently as the baseline for shower reconstruction in future e+e−-colliders. Moreover, CLUE demonstrates impressive timing capabilities, outperforming the current baseline algorithms and this advantage remains consistent regardless of the number of input hits. This work highlights the adaptability and versatility of the CLUE algorithm for a wide range of experiments and detectors and the algorithm’s potential for future high-energy physics experiments beyond CMS.