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Instrumentation and Techniques in High Energy Physics

This book provides an introduction of some of the technology and techniques of modern particle physics. Each chapter is a deep dive into the relevant subject, which includes silicon pixel detectors, plastic scintillator in a high radiation environment, Cerenkov detectors, particle jet identification, noble gas neutrino detectors, and machine learning. The target audience is graduate students and more senior researchers who wish to learn a new technology or technique. The text pedagogical in nature and each chapter is a standalone treatment of a specific topic. The coverage focuses on state-of-the-art techniques, rather than describing the technology's history. Written by acknowledged experts in the subject matter, Instrumentation and Techniques in High Energy Physics, is an important addition to the library of any particle physicist.

Lincoln, Don↗

Integrated Data Analysis to Improve Te and Zeff Measurement on NSTX-U

The multi-energy soft x-ray (ME-SXR) camera is a new concept for a fusion plasma diagnostic based on a pixelated detector with adjustable photon cutoff thresholds. It is a single, compact, solid-state detector which combines spatial and spectral sensitivity and can be configured remotely at run time, making it ideal for a fusion environment. The detector can be configured for application to a wide range of physics problems including impurity transport, electron temperature profiles, and non-thermal effects. The detector has been installed on the Madison Symmetric Torus (MST) as part of a collaboration between Princeton Plasma Physics Laboratory and the University of Wisconsin–Madison to develop the technology and analysis techniques. A full diagnostic forward model of the ME-SXR diagnostic has been developed to enable analysis of the raw photon count data. This model incorporates the atomic physics underlying the plasma emission, diagnostic geometry, and detector response characteristics. Employing this model, a Bayesian analysis approach is used to extract electron temperature from the raw data. This analysis approach uses all available information, clearly quantifies prior information, and handles uncertainties transparently. The ME-SXR camera is being used to study the 3D (helical, stellarator-like) state that forms in the MST device. This helical core structure has improved energy confinement. The transition to the helical state is accompanied by a rise in electron temperature in the central part of the helical structure, but then this enhancement fluctuates. The characteristics of this fluctuation are being compared to a magneto-hydrodynamics model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

RD53 analog front-end processors for the ATLAS and CMS experiments at the High-Luminosity LHC

This work discusses the design and the main results relevant to the characterization of analog front-end processors in view of their operation in the pixel detector readout chips of ATLAS and CMS at the High-Luminosity LHC. The front-end channels presented in this paper are part of RD53A, a large scale demonstrator designed in a 65 nm CMOS technology by the RD53 collaboration.The collaboration is now developing the full-sized readout chips for the actual experiments. Some details on the improvements implemented in the analog front-ends are provided in the paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Algorithm to Calibrate and Correct the Response to Unpolarized Radiation of the X-Ray Polarimeter Onboard IXPE

The Gas Pixel Detector (GPD) is an X-ray polarimeter to fly onboard IXPE and other missions. To correctly measure the source polarization, the response of IXPE’s GPDs to unpolarized radiation has to be calibrated and corrected. In this paper, we describe the way such response is measured with laboratory sources and the algorithm to apply such correction to the observations of celestial sources. The latter allows to correct the response to polarization of single photons, therefore allowing great flexibility in all the subsequent analysis. Our correction approach is tested against both monochromatic and nonmonochromatic laboratory sources and with simulations, finding that it correctly retrieves the polarization up to the statistical limits of the planned IXPE observations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

System, apparatus, and method for determining elemental composition using 4D STEM

The present disclosure relates to transmission electron microscopy for evaluation of biological matter. According to an embodiment, the present disclosure further relates to an apparatus for determining the structure and/or elemental composition of a sample using 4D STEM, comprising a direct bombardment detector operating with global shutter readout, processing circuitry configured to acquire images of bright-field disks using either a contiguous array or non-contiguous array of detector pixel elements, correct distortions in the images, align each image of the images based on a centroid of the bright-field disk, calculate a radial profile of the images, normalize the radial profiles by a scaling factor, calculate the rotationally-averaged edge profile of the bright-field disk, and determine elemental composition within the specimen based on the characteristics of the edge profile of the bright-field disk corresponding to each specimen location.

Bammes, Benjamin↗

Interactive automated Bragg peak identification with 3D neutron scattering data

Neutron scattering experiments have undergone significant technological development through large area detectors with concurrent enhancements in neutron transport and electronic functionality. Data collected for neutron events include detector pixel location in 3D, time and associated metadata, such as, sample orientation, neutron wavelength, and environmental conditions. RadiaSoft and Oak Ridge National Laboratory personnel are considering single-crystal diffraction data from the TOPAZ instrument. We are leveraging a new method for rapid, interactive analysis of neutron data using NVIDIA’s IndeX 3D volumetric visualization framework. We have implemented machine learning techniques to automatically identify Bragg peaks and separate them from diffuse backgrounds and analyze the crystalline lattice parameters for further analysis. The implementation of automatic peak identification into IndeX allows scientists to visualize and analyze data in real-time. Our methods include a robust comparison with current analysis techniques which show improvement in a variety of aspects. These improvements will be incorporated into IndeX for visualization to allow scientists an interactive tool for crystal analysis.

Kilpatrick, Matthew↗

An Open-Source Framework for Rapid Validation of Scientific ASICs

Spacely is an open-source framework for the post-silicon validation of analog, digital, and mixed-signal ASICs (Application-Specific Integrated Circuits) which maximizes the reuse of hardware and software, reducing the time taken to achieve meaningful test results. Spacely specifically addresses the needs of small, flexible ASIC design teams commonly found in academia or research institutions which benefit most from sharing the overhead of test stand creation between many unique ASIC designs. Spacely is a set of software, firmware, and design practices. It targets two primary hardware platforms (NI-PXI and Caribou) as well as offering extensible support for bench instruments. Spacely provides a high-level Python interface to all test hardware for accessibility, while also giving more sophisticated teams the opportunity to integrate custom test firmware. The design principles of Spacely are presented, along with a demonstrative example of using Spacely to test a pixel detector readout ASIC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Monte Carlo N-Particle Transport Performance of Predicting Digital Radiographic IQI Inspection

The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.

digital X-ray radiography↗

Spatial calibration and synthetic diagnostic of a multi-energy hard x-ray camera at WEST tokamak

WEST (tungsten environment in steady-state tokamak) is starting operation for the first time with a water-cooled full tungsten divertor, enabling long pulse operation. Heating is provided by radiofrequency systems, including lower hybrid current drive (LHCD). In this context, a compact multi-energy hard x-ray camera has been installed for energy and space-resolved measurements of the electron temperature, the fast electron tail density produced by LHCD and runaway electrons, and the beam–target emission of tungsten at the target due to fast electron losses interacting with the divertor plates. The diagnostic is a pinhole camera based on a 2D pixel array detector (Pilatus 3 CdTe CMOS Hybrid-Pixel detector produced by DECTRIS). The novelty of this diagnostic technique is the detector’s capability of adjusting the threshold energy at pixel level. This innovation provides great flexibility in the energy configuration, allowing simultaneous space and energy-resolved x-ray measurements. This contribution details two important steps in the preparation of the diagnostic operation. First, the in-vessel spatial calibration that was carried out with a radioactive source. Second, the synthetic diagnostic is obtained by the suite of codes ALOHA/C3PO/LUKE/R5-X2, which simulates LH wave propagation and absorption, as well as the fast electron bremsstrahlung production.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Wide Dynamic Range, 10 kHz Framing Detector for 4D-STEM

Hybrid pixel array detectors (PADs) have expanded the fidelity, frame rate and dynamic range for diffractive imaging in electron microscopes. With their high detective quantum efficiencies (DQE), the noise performance limited is by counting statistics. Consequently, improving the precision and quality of high-speed images requires increasing the linear dynamic range and the maximum usable beam current. Here we describe a new prototype hybrid PAD, our next-generation electron microscope pixel array detector (NG-EMPAD) that expands both the framing speed and dynamic range of our earlier EMPAD design. Like the EMPAD, electrons are detected directly in a 500 μm thick silicon sensor bonded pixel-by-pixel to a custom signal processing integrated circuit (IC). Each pixel in the IC integrates charge carriers produced by the high-energy incident electrons. Here, in-pixel circuitry uses a combination of techniques to extend the dynamic range, including adaptive gain switching and the quantitative excess charge dumping similar to the EMPAD. In-pixel buffering of signals during readout allows acquiring a new image while reading out the previously collected image, yielding an image collection duty cycle of nearly 100%.

36 MATERIALS SCIENCE↗

Unsupervised Learning for Improved Gamma-Ray Spectrometry in Pixelated Cadmium Zinc Telluride (CZT) Detectors

Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pixel Array Germanium Detectors for Nuclear Physics (Final Technical Report)

The Department of Energy (DOE) Office of Nuclear Physics supports the development and maintenance of germanium gamma-ray detector arrays at national laboratories and universities. Germanium gamma-ray detectors provide state-of-the-art gamma-ray energy resolution, making them critical for gamma-ray and x-ray spectroscopy in Nuclear Physics. Furthermore, detector segmentation and charge-signal waveform processing enables 3-dimensional (3D) measurement of gamma-ray interaction locations needed for the highest-fidelity Nuclear Physics experiments. Attaining and maintaining excellent gamma-ray energy resolution depends largely on the naturally excellent charge-collection properties of germanium crystals. However, the optimal method for achieving the best practical 3D spatial resolution within the detector volume at high counting rates is less clear.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensor Co-design for $\textit{smartpixels}$

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trigger for a hadron collider. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (``cluster''). To design a viable detector for deployment at an experiment, the dependence of the NN as a function of the sensor geometry, external magnetic field, and irradiation must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector depth. An external magnetic field parallel to the sensor plane induces Lorentz drift of the electron-hole pairs produced by the charged particle, broadening the cluster and improving the network performance. The absence of the external field diminishes the background rejection compared to the baseline by $\mathcal{O}$(10%). Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by $\sim$ 30 - 60%, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.

Shekar, Danush [Illinois U., Chicago]↗

Super-Resolution Ptychography with Small Segmented Detectors

To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. Further, we demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe 2 /WSe 2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors.

2D materials↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Non-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010-2012) and Run 2 (2015-2018) of the Large Hadron Collider. The extracted fluence shows a much stronger |z|-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.

47 OTHER INSTRUMENTATION↗

Novel imaging technique for α-particles using a fast optical camera

A new imaging technique forα-particles using a fast optical camera focused on a thin scintillator is presented. Asα-particles interact in a thin layer of LYSO fast scintillator, they produce a localized flash of light. Furthermore, the light is collected with a lens to an intensified optical camera, Tpx3Cam, with single photon sensitivity and excellent spatial & temporal resolutions. The interactions of photons with the camera is reconstructed by means of a custom algorithm, capable of discriminating single photons using time and spatial information

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

First results from a multiplexed and massive instrument with sub-electron noise Skipper-CCDs

Here, we present a new instrument composed of a large number of sub-electron noise Skipper-CCDs operated with a two stage analog multiplexed readout scheme suitable for scaling to thousands of channels. New, thick, 1.35 Mpix sensors, from a new foundry, are glued into a Multi-Chip Module (MCM) printed circuit board on a ceramic substrate which has 16 sensors each. The instrument, that can hold up-to 16 MCMs, a total of 256 Skipper-CCD sensors (called a Super-Module with ≈ 130 grams of active mass and 346 Mpix), is part of the R&D effort of the OSCURA experiment which will have ≈ 94 super-modules. Experimental results with 10 MCMs and 160 Skipper-CCDs sensors are presented in this paper. This is already the largest ever built instrument with single electron sensitivity CCDs using nondestructive readout, both, in terms of active mass and number of channels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗