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At least 73 records · Page 4

Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors

NOvA is a long-baseline neutrino oscillation experiment that detects neutrino particles from the NuMI beam at Fermilab. Before data from this experiment can be used in analyses, raw hits in the detector must be matched to their source particles, and the type of each particle must be identified. This task has commonly been done using a mix of traditional clustering approaches and convolutional neural networks (CNNs). Due to the construction of the detector, the data is presented as two sparse 2D images: an XZ and a YZ view of the detector, rather than a 3D representation. We propose a point set neural network that operates on the sparse matrices with an operation that mixes information from both views. Our model uses less than 10% of the memory required using previous methods while achieving a 96.8% AUC score, a higher score than obtained when both views are processed independently (85.4%).

Robles, Edgar E. [UC, Irvine (main)]↗

Development of High-QE GaN Photodectors for Liquid Noble Particle Detectors

Detection of the handful of photons generated when a dark matter particle interacts in a liquid Xenon detector requires a new type of photodetector with very high detection efficiency at ultraviolet wavelengths, very low radioactive backgrounds, and essentially no measureable readout noise (achieved with devices with high intrisic gain). Such devices would find wide applicability to not only high energy physics experiments, but to a number of commercial applications including, e.g., biomedical imaging of fluorescent tags. We developed photodetectors based on amorphous GaN thin film structures (photocathodes) grown by molecular beam epitaxy on quartz windows. We also developed approaches to integrate these photocathode device structures with vacuum electron multipliers. All materials and fabrication techniques were developed to minimize radioactive backgrounds in materials, so these detectors could be used for very low count rate experiments, such as the future liquid-Xenon dark matter detectors, and future liquid-Argon neutrino detectors. We demonstrated growth of very high quantum efficiency amorphous GaN cathodes grown on a number of different substrates (Stainless steel, p-Silicon) reaching detection efficiencies of 80% at 220nm. The key to this growth was to use nitrogen plasma-assistend MBEs and very low growth temperatures. We also discovered that thinner structures (e.g.,40nm a-GaN thin films) had the best performance. We successfully demonstrated techniques for the vacuum transfer of these photocathode structures to a novel chamber that used hydraulics and bellow to form a cold indium bond needed to integrate these cathodes into sealed-tube devices. A complete, stand-along, device could not be completed during this proposal period due to difficulties in growing structures on the thick quartz window. Subsequent work is aimed at addressing this difficulty, by growing a buffer layer on the quartz substrate.

07 ISOTOPE AND RADIATION SOURCES↗

Towards a high performance geometry library for particle-detector simulations

Thread-parallelization and single-instruction multiple data (SIMD) ”vectorisation” of software components in HEP computing has become a necessity to fully benefit from current and future computing hardware. In this context, the Geant-Vector/GPU simulation project aims to re-engineer current software for the simulation of the passage of particles through detectors in order to increase the overall event throughput. As one of the core modules in this area, the geometry library plays a central role and vectorising its algorithms will be one of the cornerstones towards achieving good CPU performance. Here, we report on the progress made in vectorising the shape primitives, as well as in applying new C++ template based optimizations of existing code available in the Geant4, ROOT or USolids geometry libraries. We will focus on a presentation of our software development approach that aims to provide optimized code for all use cases of the library (e.g., single particle and many-particle APIs) and to support different architectures (CPU and GPU) while keeping the code base small, manageable and maintainable. We report on a generic and templated C++ geometry library as a continuation of the AIDA USolids project. As a result, the experience gained with these developments will be beneficial to other parts of the simulation software, such as for the optimization of the physics library, and possibly to other parts of the experiment software stack, such as reconstruction and analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mission Operations and Data Analysis Phase of the SupraThermal through Energetic Particle detector (STEP) of the EPACT experiment on the Wind Spacecraft

Scientific studies of energetic particle populations observed by STEP are summarized. Science highlights cover: upstream He-3 events general upstream events, energy spectra of ions accelerated in impulsive and gradual solar events, impulsive solar particle events, and corotating interaction regions. Bibliographies of journal publications and papers presented at conferences are also provided.

Mason, G. M.↗

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring important upgrades to the Compact Muon Solenoid (CMS) to handle an increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.] (ORCID:0009000151↗

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring significant upgrades to the Compact Muon Solenoid (CMS) to handle the increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.; Fermilab] (ORCID:↗

LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens

A new type of position-sensitive detectors is gaining attention in the neutron community. They are scintillator based detectors that detect the scintillation light on an individual photon basis via an image intensifier and a fast image sensor. Their readout operates in event mode i.e. it produces information about individual neutron interactions, reconstructed from the sensor data, thus enabling to achieve superior spatial and temporal resolutions compared to regular detectors. Although the development of current detectors is focused on neutrons, the concept is also applicable to the detection of other particles such as high-energy photons. This document provides a description on how these detectors are built, how they operate, and what their characteristics are. An example of a detector implementation based on a Timepix3 chip is described to illustrate the detector concept. This includes a detailed description of the algorithm that reconstructs the neutron interactions from the sensor data, one of the core components that sets it apart from established scintillator-based imaging detectors. Energy-resolved epithermal neutron radiography was performed at the ISIS EMMA beamline with this detector, illustrating some of the fundamental differences in the data that can be produced with the new type of detector compared to more established types of scintillator based neutron detectors. The term LumaCam is proposed to refer to this new class of position-sensitive event-mode detectors.

47 OTHER INSTRUMENTATION↗

Wedge-and-strip anodes for centroid-finding position-sensitive photon and particle detectors

The paper examines geometries employing position-dependent charge partitioning to obtain a two-dimensional position signal from each detected photon or particle. Requiring three or four anode electrodes and signal paths, images have little distortion and resolution is not limited by thermal noise. An analysis of the geometrical image nonlinearity between event centroid location and the charge partition ratios is presented. In addition, fabrication and testing of two wedge-and-strip anode systems are discussed. Images obtained with EUV radiation and microchannel plates verify the predicted performance, with further resolution improvements achieved by adopting low noise signal circuitry. Also discussed are the designs of practical X-ray, EUV, and charged particle image systems.

Martin, C.↗

A Supra-Thermal Energetic Particle detector (STEP) for composition measurements in the range approximately 20 keV/nucleon to 1 MeV/nucleon

A detector system is described, employing a time-of-flight versus residual energy technique which allows measurement of particle composition (H-Fe), energy spectral and anisotropies in an energy range unaccessible with previously flown sensors. Applications of this method to measurements of the solar wind ion composition are discussed.

Mason, G. M.↗

A supra-thermal energetic particle detector /STEP/ for composition measurements in the range of about 20 keV/nucleon to 1 MeV/nucleon

A novel detector system is described, employing a time-of-flight versus residual energy technique which allows measurement of particle composition (H-Fe), energy spectra and anisotropies in an energy range unaccessible with previously flown sensors. Applications of this method to measurements of the solar wind ion composition are also discussed.

Mason, G. M.↗

The atmosphere as particle detector

The possibility of using an inflatable, gas-filled balloon as a TeV gamma-ray detector on the moon is considered. By taking an atmosphere of Xenon gas there, or by extracting it on the moon, a layman's detector design is presented. In spite of its shortcomings, the exercise illustrates several of the novel features offered by particle physics on the moon.

Stanev, Todor↗

FACET: a new long-lived particle detector in the very forward region of the CMS experiment

We describe a proposal to add a set of very forward detectors to the CMS experiment for the high-luminosity era of the Large Hadron Collider to search for beyond the standard model long-lived particles, such as dark photons, heavy neutral leptons, axion-like particles, and dark Higgs bosons. The proposed subsystem is called FACET for Forward-Aperture CMS ExTension, and will be sensitive to any particles that can penetrate at least 50 m of magnetized iron and decay in an 18 m long, 1 m diameter vacuum pipe. The decay products will be measured in detectors using identical technology to the planned CMS Phase-2 upgrade.

Particle and Resonance Production↗

An ultra-thin diamond membrane as a transmission particle detector and vacuum window for external microbeams

Several applications of external microbeam techniques demand a very accurate and controlled dose delivery. To satisfy these requirements when post-sample ion detection is not feasible, we constructed a transmission single-ion detector based on an ultra-thin diamond membrane. The negligible intrinsic noise provides an excellent signal-to-noise ratio and enables a hit-detection efficiency of close to 100%, even for energetic protons, while the small thickness of the membrane limits beam spreading. Moreover, because of the superb mechanical stiffness of diamond, this membrane can simultaneously serve as a vacuum window and allow the extraction of an ion microbeam into the atmosphere.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dead layer on silicon p-i-n diode charged-particle detectors

Abstract Semiconductor detectors in general have a dead layer at their surfaces that is either a result of natural or induced passivation, or is formed during the process of making a contact. Charged particles passing through this region produce ionization that is incompletely collected and recorded, which leads to departures from the ideal in both energy deposition and resolution. The silicon p-i-n diode used in the KATRIN neutrinomass experiment has such a dead layer. We have constructed a detailed Monte Carlo model for the passage of electrons from vacuum into a silicon detector, and compared the measured energy spectra to the predicted ones for a range of energies from 12 to 20 keV. The comparison provides experimental evidence that a substantial fraction of the ionization produced in the "dead" layer evidently escapes by discussion, with 46% being collected in the depletion zone and the balance being neutralized at the contact or by bulk recombination. The most elementary model of a thinner dead layer from which no charge is collected is strongly disfavored.

Dead layer↗

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗