Search Results (153)

In scenarios involving radiation such as decommissioning of nuclear disasters and operating nuclear power plants, it is necessary to perform tasks including maintenance, demolition, and inspection using robots in order to protect human workers from harm. LIDAR (LIght Detection And Ranging) sensors are used for many demanding real-time tasks in robotics such as obstacle avoidance, localisation, mapping, and navigation. Standard silicon-based electronics including LIDAR fail quickly in gamma radiation, however, high-radiation areas have a critical need for robotic maintenance to keep people safe. Sensors need to be developed, which can cope with this environment. A prototype including most required transmitter and receiver circuits is designed utilising components expected to provide up to (1 MGy) gamma radiation tolerance. Initial results testing the concepts of the laser transmission and detection in a lab environment shows reliable signal detection. Performance tests utilising multiple receivers show a linear relationship between receiver separation and measured time difference, allowing for the possibility of calibration of a sensor using the time difference between pulses. Future work (such as radiation testing trials) is discussed and defined. These results contribute to de-risking the feasibility of long-term deployment of LIDAR systems utilising these approaches into environments with high gamma dose rates, such as nuclear fission decommissioning, big science facilities such as the Large Hadron Collider, and remote maintenance systems used in future nuclear fusion power plants such as STEP and EU-DEMO. Full article

The deployment of robotic systems in hazardous and magnetically intense environments requires careful assessment of their performance under external disturbances. In particular, electromagnetic motors used for actuation may interact with strong magnetic fields, potentially impairing their functionality. This study investigates the behaviour of miniature brushed coreless Direct Current (DC) motors for small Unmanned Aerial Vehicle (UAV) applications in magnetically harsh environments, such as underground accelerator facilities like the Large Hadron Collider (LHC) at CERN. Experimental tests were conducted measuring four main physical quantities: the torque components acting along the axes orthogonal to the shaft, the torque about the shaft axis, variations in angular speed, and electrical current consumption. The results showed that the motors were able to operate under external magnetic field intensities up to 0.4 T, although measurable torques acted on the internal permanent magnet and on the ferromagnetic housing material. Some discrepancies and speed fluctuations were observed during operation and were attributed to mobility of the internal permanent magnet. Overall, the findings demonstrate that the tested miniature motors exhibit resilience in high magnetic fields but suffer from manufacturing variability, suggesting that higher-quality motors with more consistent characteristics would be preferable for reliable robotic operation in harsh environments. Full article

Gluons within the proton may accumulate near a critical momentum due to nonlinear QCD effects, leading to a gluon condensation. Surprisingly, the pion distribution predicted by this gluon distribution could answer two puzzles in astronomy and high-energy physics. During ultra-high-energy cosmic ray collisions, gluon condensation may abruptly produce a large number of low-momentum pions, whose electromagnetic decays have the typical broken power law. On the other hand, the Large Hadron Collider (LHC) shows weak but recognizable signs of gluon condensation, which had been mistaken for BEC pions. Symmetry is one of the fundamental laws in natural phenomena. Conservation of energy stems from time symmetry, which is one of the most central principles in nature. In this study, we reveal that the connection between the above two apparently unrelated phenomena can be fundamentally explained from the fundamental principle of conservation of energy, highlighting the deep connection and unifying role symmetry plays in physical processes. Full article

Fourier transform-based frequency sweeping interferometry (FT-FSI) is an interferometric technique that enables absolute distance measurement by detecting the beat frequencies from the interference of reflected signals. This method allows robust, simultaneous distance measurements to multiple targets and is largely immune to variations in the reflected optical signal intensity. As a result, FT-FSI maintains accuracy even when measuring reflectors with low reflectance. FT-FSI has recently been integrated into the full remote alignment system (FRAS) developed for the High-Luminosity Large Hadron Collider (HL-LHC) project at CERN. Designed to operate in harsh environments with electromagnetic interference, ionizing radiation and cryogenic temperatures, FRAS employs FT-FSI for the precise monitoring of the alignment of accelerator components. The system includes specialized interferometers and a range of sensors, including inclinometers, distance sensors, and leveling sensors. This paper presents a comprehensive review of the challenges associated with remote measurement and monitoring systems in harsh environments such as those of particle accelerators. It details the development and validation of the FT-FSI-based measurement system, emphasizing its critical role in enabling micrometric alignment accuracy. The developments and results presented in this work can be readily translated to other demanding metrology applications in harsh environments. Full article

The Standard Model (SM) fails to explain many problems (neutrino masses, dark matter, and matter–antimatter asymmetry, among others) that may be resolved with new particles beyond the SM. No observation of such new particles may be explained either by their exceptionally high mass or by considerably small coupling to SM particles. The latter case implies relatively long lifetimes. Such long-lived particles (LLPs) then to have signatures different from those of SM particles. Searches in the “central region” are covered by the LHC general purpose experiments. The forward small angle region far from the interaction point (IP) is unexplored. Such particles are expected to have the energy as large as E = $\mathcal{O}$(1 TeV) and Lorentz time dilation factor $\gamma =E/m\approx {10}^2$–${10}^3$ (with m the particle mass) hence long enough decay distances. A new class of specialized LHC detectors dedicated to LLP searches has been proposed for the forward regions. Among these experiments, FASER is already operational, and FACET is under consideration at a location 100 m from the LHC IP5 (the CMS detector intersection). However, some features of FACET require a specially enlarged beam pipe, which cannot be implemented for LHC Run 4. In this study, we explore a simplified version of the proposed detector PREFACE compatible with the standard LHC beam pipe in the HL-LHC Run 4. Realistic Geant4 simulations are performed and the background is evaluated. An initial analysis of the physics potential with the PREFACE geometry indicates that several significant channels could be accessible with sensitivities comparable to FACET and other LLP searches. Full article

In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of $3\times {10}^{16}$ 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach. Full article

The dynamic aperture is an essential concept in circular particle accelerators, providing the extent of the phase space region where particle motion remains stable over multiple turns. The accurate prediction of the dynamic aperture is key to optimising performance in accelerators such as the CERN Large Hadron Collider and is crucial for designing future accelerators like the CERN Future Circular Hadron Collider. Traditional methods for computing the dynamic aperture are computationally demanding and involve extensive numerical simulations with numerous initial phase space conditions. In our recent work, we have devised surrogate models to predict the dynamic aperture boundary both efficiently and accurately. These models have been further refined by incorporating them into a novel active learning framework. This framework enhances performance through continual retraining and intelligent data generation based on informed sampling driven by error estimation. A critical attribute of this framework is the precise estimation of uncertainty in dynamic aperture predictions. In this study, we investigate various machine learning techniques for uncertainty estimation, including Monte Carlo dropout, bootstrap methods, and aleatory uncertainty quantification. We evaluated these approaches to determine the most effective method for reliable uncertainty estimation in dynamic aperture predictions using machine learning techniques. Full article

In this paper, we analyze the application of an analytical gluon distribution based on double-asymptotic scaling to the photoproduction of vector mesons in coherent $pp$, $pA$, and $AA$ collisions at LHC energies, using the color dipole formalism. Predictions for the rapidity distribution are presented for ${\rho }^0$, $J/\psi$, $\psi \left(2S\right)$, and $\mathrm{{\rm Y}}\left(1S\right)$ mesons photoproduction. An analysis of the uncertainties associated with different implementations of the dipole–proton amplitude is performed. The vector meson photoproduction accompanied by electromagnetic dissociation is also analyzed. Full article

The ALICE (A Large Ion Collider Experiment) detector at the Large Hadron Collider (LHC), operated by the European Organization for Nuclear Research (CERN), is dedicated to heavy-ion collisions. Within ALICE, the application logs of the online computing systems are consolidated through a logging system known as Infologger, which integrates data from various sources. To identify potential anomalies, shifters in the control room manually review logs for anomalies, which require significant expertise and pose challenges due to the frequent onboarding of new personnel. To address this issue, we propose a real-time semi-supervised log anomaly detection framework designed to automatically detect anomalies in ALICE operations. The framework leverages BERTopic, a topic modeling technique, to provide real-time insights for incoming log messages for shifters. This includes an analytical dashboard that represents the anomaly status in log messages, facilitating informative monitoring for shifters. Through evaluation, including Infologger and BGL (BlueGene/L supercomputer), we analyze the effects of word embeddings, clustering algorithms, and HDBSCAN hyperparameters on model performance. The result demonstrates that the BERTopic can enhance the log anomaly detection process over traditional topic models, achieving remarkable performance metrics and attaining F1-scores of 0.957 and 0.958 for the InfoLogger and BGL datasets, respectively, even without the preprocessing technique. Full article

A web-based tool called ADFilter (short for Anomaly Detection Filter) was developed to process collision events using autoencoders based on a deep unsupervised neural network. The autoencoders are trained on a small fraction of either collision data or Standard Model (SM) Monte Carlo simulations. The tool calculates loss distributions for input events, helping to determine the degree to which the events can be considered anomalous with respect to the SM events used for training. Therefore, it can be used for new physics searches in collider experiments. Real-life examples are provided to demonstrate how the tool can be used to reinterpret existing results from the Large Hadron Collider (LHC), with the goal of significantly improving exclusion limits. This tool is expected to mitigate the “reproducibility crisis” associated with various machine learning techniques, as it can incorporate machine learning approaches from third-party publications, making them accessible to the general public. Full article

Searches for new particles beyond the Standard Model (SM) are an important task for the Large Hadron Collider (LHC). In this paper, we investigate the properties of the heavy non-SM Higgs bosons in the $\mu$-term extended Next-to-Minimal Supersymmetric Standard Model ($\mu$NMSSM). We scan the parameter space of the $\mu$NMSSM considering the basic constraints from Higgs data, dark matter (DM) relic density, and LHC searches for sparticles. And we also consider the constraints from the LZ2022 experiment and the muon anomaly constraint at the 2$\sigma$ level. We find that the LZ2022 experiment has a strict constraint on the parameter space of the $\mu$NMSSM, and the limits from the DM-nucleon spin-independent (SI) and spin-dependent (SD) cross-sections are complementary. Then, we discuss the exotic decay modes of heavy Higgs bosons decaying into SM-like Higgs bosons. We find that for doublet-dominated Higgs $h_3$ and $A_2$, the main exotic decay channels are $h_3\to Z{A}_1$, $h_3\to h_1{h}_2$, $A_2\to A_1{h}_1$, and $A_2\to Z{h}_2$, and the branching ratio can reach to about 23%, 10%, 35%, and 10% respectively. Full article

Investigating the production of Higgs boson pairs (HH) at the LHC provides critical insights into the self-interaction properties of the Higgs boson, representing an essential verification of the Standard Model and contributing to our understanding of the Higgs boson properties. This work highlights the latest findings from the CMS collaboration on HH production measurements. These searches include different final states and integrate data collected by the CMS experiment at a center-of-mass energy of 13 TeV. Full article

The possibility to search for long-lived axion-like particles (ALPs) decaying into photons is investigated in ultraperipheral PbPb collisions at the Large Hadron Collider (LHC). We propose a search strategy for low-mass ALPs using the LHCb and ALICE experiments. The ALP identification is performed by requiring the decay vertex be reconstructed outside the region where a primary vertex is expected, which strongly suppress the contribution associated with the decay of light mesons. We also use the fact that a fraction of the photons convert into electron–positron pairs, allowing the reconstruction of the particle decay position. We present the predictions for the pseudorapidity and transverse momentum distributions of the ALPs and photons. Moreover, predictions for the fiducial cross-sections, derived considering the characteristics of the ALICE and LHCb detectors, are presented for different values of the ALP mass and the ALP—photon coupling. Full article

Multiphase DC/DC power converter architectures have recently been investigated for powering the superconducting electromagnets in the High-Luminosity (HL) upgrade of the Large Hadron Collider (LHC) at CERN, targeting high-performance figures and reliability. In terms of control, a master–slave voltage/current regulation configuration was previously proposed by the authors as an alternative to other well-known cascaded options. In this work, fault-tolerant features (i.e., diagnosis and reconfiguration under open-circuit switch faults) are incorporated into the aforementioned proposal. These features are highly desirable, as physics experiments—which can last for several hours—should not be interrupted in the event of a recoverable fault in the powering system. Simulation and experimental results are provided, demonstrating the correctness of the proposed fault-tolerant scheme. Full article

We propose a novel approach to real-time anomaly detection at the Large Hadron Collider, aimed at enhancing the discovery potential for new fundamental phenomena in particle physics. Our method leverages the Latent Outlier Exposure technique and is evaluated using three distinct anomaly detection models. Among these is a novel adaptation of the variational autoencoder’s reparameterisation trick, specifically optimised for anomaly detection. The models are validated on simulated datasets representing collider processes from the Standard Model and hypothetical Beyond the Standard Model scenarios. The results demonstrate significant advantages, particularly in addressing the formidable challenge of developing a signal-agnostic, hardware-level anomaly detection trigger for experiments at the Large Hadron Collider. Full article