Particle Physics Detectors Research Articles

Deep probabilistic direction prediction in 3D with applications to directional dark matter detectors

We present the first method to probabilistically predict 3D direction in a deep neural network model. The probabilistic predictions are modeled as a heteroscedastic von Mises-Fisher distribution on the sphere S2 , giving a simple way to quantify aleatoric uncertainty. This approach generalizes the cosine distance loss which is a special case of our loss function when the uncertainty is assumed to be uniform across samples. We develop approximations required to make the likelihood function and gradient calculations stable. The method is applied to the task of predicting the 3D directions of electrons, the most complex signal in a class of experimental particle physics detectors designed to demonstrate the particle nature of dark matter and study solar neutrinos. Using simulated Monte Carlo data, the initial direction of recoiling electrons is inferred from their tortuous trajectories, as captured by the 3D detectors. For 40 keV electrons in a 70% He 30% CO2 gas mixture at STP, the new approach achieves a mean cosine distance of 0.104 (26∘) compared to 0.556 (64∘) achieved by a non-machine learning algorithm. We show that the model is well-calibrated and accuracy can be increased further by removing samples with high predicted uncertainty. This advancement in probabilistic 3D directional learning could increase the sensitivity of directional dark matter detectors.

Application of Particle Physics Detector in Medical Science

Application of Particle Physics Detector in Medical Science

New vertex reconstruction algorithm for measuring gamma-rays with the AMS tracker

Gamma-ray polarization is one of the most promising tools to probe the universe at extreme conditions and search for new physics. The Alpha Magnetic Spectrometer (AMS) is a precision particle physics detector on the International Space Station. With its high accuracy thin silicon strip detectors and permanent magnet, AMS is unique to study the polarization of high energy gamma-rays. The detection of gamma-rays above a few hundreds of MeV typically utilize the electron–positron pair production process, and the key step is to reconstruct the vertex where gamma-ray converts into the electron–positron pair. We present a new vertex reconstruction algorithm that is based on an extended cellular automaton to determine the direction and energy information of gamma-rays from the electron and positron trajectories in the AMS tracker. The vertex reconstruction efficiency is significantly improved with the presented algorithm over the entire energy range above 100 MeV and reaches >90% above 1 GeV. The fake rate is drastically reduced over the entire energy range and is reduced from ∼10% to ∼3% at 200 MeV. The presented algorithm will thus provide the basis for measuring gamma-ray polarization with AMS.

High Temperature Superconductor Detector Magnets for Future Particle Physics Experiments

Particle physics experiments make use of magnetic fields up to 4T to bend electrically charged particles such that their charge and momentum can be determined. The particle energy measurement requires a low amount of material, or ma-terial that is highly transparent to particles inside the calorimeter volume. The conflict between the small volume of space reserved for a magnet and having a field of several teslas inside the detector is often resolved by using superconducting magnets. Up to now, large particle physics detector magnets have been constructed with low temperature superconductors, but there are clear benefits from using high temperature superconductors in future particle physics detector designs, such as allowing for an elevated operating temperature and the reduced amount of superconductor needed. In addition to the HTS material itself, additional material is needed to support the Lorentz forces, and to temporarily carry the current in case of a quench since these magnets are always one-of-a-kind and they need to operate reliably and without damage in case of a failure scenario. The stabilizer has to be a low-density material for high particle transparency, such as aluminium. Since the density of the superconductor is a factor of 4 higher than the density of aluminium, a reduction of superconducting material also means an improvement of the particle transparency: the density of a material is directly related to its particle transparency. This paper presents a conceptual design for high temperature superconducting detector magnets and a study of the type of aluminium stabilizer used.

Successful cooling of a pixel tracker using gaseous helium: Studies with a mock-up and a detector prototype

We report the successful operation of a functional pixel detector with gaseous helium cooling. Using an accurate mock-up beforehand, the cooling was validated. We use a miniature turbo compressor to propel the helium at 2g/s under ambient pressure conditions with gas temperatures above 0 °C. Our earlier results based on computational fluid dynamics simulations and a much simpler mock-up are confirmed. With this, we paved the path to cool pixel detectors in experimental particle physics at heat densities up to 400mW/cm2 using helium. This enables cooling of detectors with very low mass requirements, minimising the effects of multiple Coulomb scattering effectively. This technique requires sensors tolerant to be operated in a wide temperature range and a detector geometry to guide the helium flow adequately. The concept presented here is not limited to pixel detector applications and can be used to cool any surface with comparable heat-densities, only limited by shaping the helium gas flow.

Alignment of the Alpha Magnetic Spectrometer (AMS) in space

The Alpha Magnetic Spectrometer (AMS) is a precision particle physics detector operating at an altitude of sim 410 km aboard the International Space Station. The AMS silicon tracker, together with the permanent magnet, measures the rigidity (momentum/charge) of cosmic rays in the range from sim 0.5 GV to several TV. In order to have accurate rigidity measurements, the positions of more than 2000 tracker modules have to be determined at the micron level by an alignment procedure. The tracker was first aligned using the 400 GeV/c proton test beam at CERN and then re-aligned using cosmic-ray events after being launched into space. A unique method to align the permanent magnetic spectrometer for a space experiment is presented. The developed underlying mathematical algorithm is discussed in detail.

Reflectance and fluorescence characteristics of PTFE coated with TPB at visible, UV, and VUV as a function of thickness

Polytetrafluoroethylene (PTFE) is an excellent diffuse reflector widely used in light collection systems for particle physics experiments. In noble element systems, it is often coated with tetraphenyl butadiene (TPB) to allow detection of vacuum ultraviolet scintillation light. In this work this dependence is investigated for PTFE coated with TPB in air for light of wavelengths of 200 nm, 260 nm, and 450 nm. The results show that TPB-coated PTFE has a reflectance of approximately 92% for thicknesses ranging from 5 mm to 10 mm at 450 nm, with negligible variation as a function of thickness within this range. A cross-check of these results using an argon chamber supports the conclusion that the change in thickness from 5 mm to 10 mm does not affect significantly the light response at 128 nm. Our results indicate that pieces of TPB-coated PTFE thinner than the typical 10 mm can be used in particle physics detectors without compromising the light signal.

Sparse Convolutional Neural Networks for particle classification in ProtoDUNE-SP events

Deep Learning (DL) methods and Computer Vision are becoming important tools for event reconstruction in particle physics detectors. In this work, we report on the use of submanifold sparse convolutional neural networks (SparseNets) for the classification of track and shower hits from a DUNE prototype liquid-argon detector at CERN (ProtoDUNE-SP). By taking advantage of the three-dimensional nature of the problem we use a set of nine input features to classify sparse and locally dense hits associated to track or shower particles. The SparseNet has been trained on a test sample and shows promising results: efficiencies and purities greater than 90%. This has also been achieved with a considerable speedup and substantially less resource utilization with respect to other DL networks such as graph neural networks. This method offers great scalability advantages for future large neutrino detectors such as the planned DUNE experiment.

Verification of simulated ASIC functionality and radiation tolerance for the HL-LHC ATLAS ITk Strip Detector

The verification of ASICs through simulation is critical to ensure their successful operation in particle physics detectors and to minimize the number of long and expensive production cycles required. Three radiation-tolerant ASICs (HCC, AMAC, and ABC) will perform the front-end readout, monitoring, and control of the ITk Strip charged-particle tracker for the ATLAS detector at the HL-LHC. The Python-based cocotb verification framework is used to design sophisticated tests with contributions from ASIC verification non-experts and students. The verification program includes interactions between multiple ASICs, realistic data flows, operational stress tests, and a focus on mitigation of disruptive Single Event Effects due to radiation.

Evolution of detectors for particle physics

A patrimony of technical skills, observations, and knowledge of natural facts, acquired through ages, has been a powerful motor of human progress. Over the last century, scientific progress has become impressively fast, thanks to a closer interplay of research and technology. The field of particle physics has witnessed a spectacular evolution, with the construction of huge particle accelerators and colliders, associated with massive experimental apparatus, where engineers and physicists have been closely collaborating. The data from these experiments have brought new discoveries, and new questions as well. Few examples are given of ways in which conceptual advances, technological progress, and experimental ingenuity have conspired towards the solution of fundamental physics problems. New challenges in the future are outlined.

Probability Distributions for Track Fitting and the Advanced Lucky Model

Probability distributions for the center of gravity are fundamental tools for track fitting. The center of gravity is a widespread algorithm for position reconstruction in tracker detectors for particle physics. Its standard use is always accompanied by an easy guess (Gaussian) for the probability distribution of the positioning errors. This incorrect assumption degrades the results of the fit. The explicit error forms evident Cauchy–Agnesi tails that render the use of variance minimizations problematic. Therefore, it is important to report probability distributions for some combinations of random variables essential for track fitting: x=ξ/(ξ+μ), y=(ξ−μ)/[2(ξ+μ)], w=ξ/μ, x=θ(x3−x1)(−x3)/(x3+x2)+θ(x1−x3)x1/(x1+x2) and x=(x1−x3)/(x1+x2+x3). The first two are partial forms of the two strip center of gravity. The fourth is the complete two strip center of gravity, and the fifth is a partial form of the three strip center of gravity. For the complexity of the forth equation, only approximate expressions of the probability are allowed. Analytical expressions are calculated assuming ξ, μ, x1, x2 and x3 independent Gaussian random variables. The analytical form of the probability for the two strip center of gravity allows one to construct an approximate proof for the lucky model of our previous paper. This proof also suggests how to complete the lucky model by its absence of a scaling constant, relevant to combine different detector types. This advanced lucky model (the super-lucky model) can be directly used in trackers composed of non-identical detectors. The construction of the super-lucky model is very simple. Simulations with this upgraded tool also show resolution improvements for a combination of two types of very different detectors, near to the resolutions of the schematic model.

Thermal simulation of Alpha Magnetic Spectrometer in orbit

Alpha Magnetic Spectrometer (AMS) is a unique particle physics detector installed on the International Space Station (ISS). In this article, the numerical simulation model of AMS in orbit was established in Thermal Desktop. With the model, temperature variations of AMS surfaces under the ISS normal and special operating conditions were analyzed, the effects of ISS orbital parameters and ISS special operations on the temperatures of AMS were revealed, and the extreme thermal situations of AMS RAM and WAKE main radiators were obtained. As for the high temperature warnings occurred at Power distribution system (PDS) under the hottest situation, locking ISS starboard solar arrays vertically is effectively and suggested as the thermal control strategy.

Noble liquid calorimetry for a future FCC-ee experiment

Noble liquid calorimetry is a well proven technology that successfully operated in numerous particle physics detectors (D0, H1, NA48, NA62, ATLAS, …). Its excellent linearity, stability, uniformity and radiation hardness as well as very good energy and time resolution make it a strong candidate for future hadron and lepton colliders. Recently, a highly granular noble liquid sampling calorimeter was proposed for a possible FCC-hh experiment. It has been shown that, on top of its intrinsic excellent conventional calorimetry performance, this technology can be optimized in terms of granularity to allow for 4D imaging, machine learning and – in combination with the tracker measurements – particle-flow reconstruction. This paper discusses how such a detector can be adapted to an electron–positron collider (FCC-ee) experiment, shows that a signal over noise ratio above five can be reached while keeping the cross-talk at the percent level, presents a possible signal extraction scheme and reports on the first performance studies derived with the Key4hep full simulation framework.

Quantum Systems for Enhanced High Energy Particle Physics Detectors

Developments in quantum technologies in the last decades have led to a wide range of applications, but have also resulted in numerous novel approaches to explore the low energy particle physics parameter space. The potential for applications of quantum technologies to high energy particle physics endeavors has however not yet been investigated to the same extent. In this paper, we propose a number of areas where specific approaches built on quantum systems such as low-dimensional systems (quantum dots, 2D atomic layers) or manipulations of ensembles of quantum systems (single atom or polyatomic systems in detectors or on detector surfaces) might lead to improved high energy particle physics detectors, specifically in the areas of calorimetry, tracking or timing.

Evaluation of passive CMOS strip sensors

Silicon sensors will continue to be the central tracking elements for upcoming particle physics detectors. They will have to cover large areas and thus be a main cost driver. The silicon sensors currently used are available only from very few manufacturers, thus detector technologies and designs that can be realized through established commercial industrial production processes and are cost-effective are becoming increasingly relevant. The CMOS technology is one of the important candidates. Since typically CMOS foundries are equipped for producing much smaller sizes than the currently used wafer-scale strip sensors, several neighbouring reticles have to be connected via a stitching process to obtain large sensors. In this study, strip sensors were designed and developed with the passive p-CMOS 150 nm process including stitching of up to five reticles. After initial electrical characterizations the sensors were tested in the laboratory with a 90Sr source and infrared lasers. The key investigation was to evaluate the impact of stitching on the sensor performance. The results presented will demonstrate that the stitching does not show any negative effect on the sensor performance before and after irradiation, and the stitching process is successful.

The Use of the BIM Approach from the Conceptual Planning to the Construction Phase: The Case Study of the SHiP Experiment

The Search for Hidden Particles (SHiP) experiment is a new purpose fixed target facility proposed for the CERN Super Proton Synchrotron accelerator to search for long-lived exotic particles associated with Hidden Sectors and Dark Matter. This paper reports on the development of BIM integrated design for the SHiP experiment, applied initially to the Decay Volume, a >2000 m3 conical steel vessel under a vacuum hosting several large particle physics detector systems. A BIM methodology is used to address all the design phases of the Decay Volume of the SHiP experiment from the conceptual planning to the constructive drawings production. This proposed workflow is a basic plan to be repeated for each sub-component of the SHiP experiment in order to have a full and overall integration of the experiment. In particular, the Decay Volume’s geometrical and structural design and the simulation of its assembly process, both in factory and on site, are proposed. Moreover, the use of collaborative platforms to speed up the ideas exchange, as the basis of a highly multidisciplinary and complex project, is discussed. The complexity, multidisciplinary nature, and size of the SHiP project severely challenge design information management. The final plan to solve this issue is to have a BIM integrated design of each experiment sub-component, such as that demonstrated in this work for the Decay Volume, in order to have a full and multidisciplinary integration of the overall project.

A parametric approach for the identification of single-charged isotopes with AMS-02

Measurements of the isotopic composition of single-charged cosmic rays provide important insights in the propagation processes. However, the isotopic identification is challenging due to the one hundred times greater abundance of protons when compared to deuterons, the only stable isotope of hydrogen. Taking advantage of the precise measurements of the velocity and momentum in the Alpha Magnetic Spectrometer (AMS-02), a particle physics detector operating aboard the International Space Station since May 2011, we describe a parametric template fit method, which takes into account systematic uncertainties such as the fragmentation of particles inside AMS-02 and eventual differences between data and simulation through the use of nuisance parameters. With this method we are also able to assess the AMS-02 performance in terms of mass resolution, showing that it is able to separate the isotopes of hydrogen up to 10 GeV/n.

OuroborosBEM: a fast multi-GPU microscopic Monte Carlo simulation for gaseous detectors and charged particle dynamics

The design of gaseous detectors for accelerator, particle and nuclear physics requires simulations relying on multi-physics aspects. In fact, these simulations deal with the dynamics of a large number of charged particles interacting in a gaseous medium immersed in the electric field generated by a more or less complex assembly of electrodes and dielectric materials. We report here on a homemade software, called ouroborosbem, able to tackle the different features involved in such simulations. After solving the electrostatic problem for which a solver based on the boundary element method (BEM) has been implemented, particles are tracked and will microscopically interact with the gas medium. Dynamical effects have been included such as the electron-ion recombination process, the charging-up of the dielectric materials and other space charge effects that might alter the detector performances. These were made possible thanks to the nVidia CUDA language specifically optimised to run on Graphical Processor Units (GPUs) to minimize the computing times. Comparisons of the results obtained for parallel plate avalanche counters and GEM detectors to literature data on swarm parameters fully validate the performances of ouroborosbem. Moreover, we were able to precisely reproduce the measured gains of single and double GEM detectors as a function of the applied voltage.

Laboratory limits on the annihilation or decay of dark matter particles

Abstract Constraints on the indirect detection of dark matter are usually obtained from observations of astrophysical objects—the Galactic Center, dwarf galaxies, M31, etc. Here we propose instead to look for the annihilation or decay of dark matter particles taking place inside detectors searching directly for dark matter or in large neutrino experiments. We show that the data from XENON1T and Borexino set limits on the annihilation and decay rates of dark matter particles with masses in the keV to few MeV range. All relevant final states are considered: annihilation into γγ and e−e+ and decays into γγ, γν, and e−e+. The expected sensitivities in XENONnT, DARWIN, JUNO, and THEIA are also computed. Though weaker than current astrophysical bounds, the laboratory limits (and projections) obtained are free from the usual astrophysical uncertainties associated with J-factors and unknown backgrounds, and may thus offer a complementary probe of the dark matter properties. We point out that current and future (astro)particle physics detectors might also be used to set analogous limits for different decays and dark matter masses above a few MeV.

Calibration of the momentum scale of a particle physics detector using the Armenteros-Podolanski plot

A method for calibrating the momentum scale in a particle physics detector is described. The method relies on the determination of the masses of the final state particles in two-body decays of neutral particles, which can then be used to obtain corrections in the momentum scale. A modified version of the Armenteros-Podolanski plot and the KS 0 → π+ π- decay is used as a proof of principle for this method.A precision at the 10-6–10-8 level is achieved in simplified simulations.