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  1. A 28 nm multiply-accumulate ASIC architecture for on-chip data compression in MHz frame rate X-ray and electron pixel detectors

    Modern X-ray detector systems urgently require compact, efficient, and fast data compression schemes to handle the transmission of big data from pixel arrays, enabling frame rates in the MHz regime. Here, in this work, a data compression ASIC that implements a streaming fixed-length lossy compression scheme is introduced and analyzed, proving the feasibility and benefits of on-chip compression. The compression scheme utilizes a vector matrix product logic, which performs a number of floating-point multiplications, additions, and accumulations. The logic is verified, synthesized, and shown to fit in the area resource available for the X-ray detector under study, which comprises 192more » × 168 pixels each of 12-bit width, and having a total area of 20 mm× 20 mm, about 2 mm× 20 mm of which are available for the digital logic. Several system architectures, precisions, and compression ratios ranging from 100 to 250 were analyzed to pave the way for on-chip fixed-length compression (e.g., principal component analysis, singular value decomposition) and data reduction (e.g., azimuthal integration) for X-ray and electron detectors.« less
  2. Skipper-in-CMOS: Nondestructive Readout With Subelectron Noise Performance for Pixel Detectors

    The Skipper-in-CMOS image sensor integrates the nondestructive readout capability of skipper charge coupled devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode (PPD) in a CMOS imaging process while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly parallel processing. The first results obtained from a $${15} \times {15}~\mu $$ m2 pixel cell of a Skipper-in-CMOS sensor fabricated in Tower Semiconductor’s commercial 180-nm CMOS image sensor process are presented. Measurements confirm the expected reduction of the readout noise with the number of samples down to deepmore » subelectron noise of $$0.15\text {e}^ - $$ , demonstrating the charge transfer operation from the PPD and the single photon counting operation when the sensor is exposed to light. This article also discusses new testing strategies employed for its operation and characterization.« less
  3. Supernova pointing capabilities of DUNE

    The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on Ar 40 and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from anmore » ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage.« less
  4. 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, efficientmore » 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.« less
  5. Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% formore » the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$$\pm 0.6$$% and 84.1$$\pm 0.6$$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.« less
  6. Highly-parallelized simulation of a pixelated LArTPC on a GPU

    The rapid development of general-purpose computing ongraphics processing units (GPGPU) is allowing the implementationof highly-parallelized Monte Carlo simulation chains for particlephysics experiments. This technique is particularly suitable forthe simulation of a pixelated charge readout for time projectionchambers, given the large number of channels that this technologyemploys. Here we present the first implementation of a fullmicrophysical simulator of a liquid argon time projectionchamber (LArTPC) equipped with light readout and pixelated chargereadout, developed for the DUNE Near Detector. The software isimplemented with an end-to-end set of GPU-optimizedalgorithms. The algorithms have been written in Python andtranslated into CUDA kernels using Numba, a just-in-timemore » compilerfor a subset of Python and NumPy instructions. The GPUimplementation achieves a speed up of four orders of magnitudecompared with the equivalent CPU version. The simulation of thecurrent induced on 10^3 pixels takes around 1 ms on the GPU,compared with approximately 10 s on the CPU. The results of thesimulation are compared against data from a pixel-readout LArTPCprototype.« less
  7. First Soft X-ray Quantum Efficiency Measurements on Microwave Annealed Thin-Entrance Window Sensors

    Free electron lasers, such as SLAC’s LCLS-II, will provide unique scientific imaging opportunities. In order to fully utilize these facilities, we need to develop detectors with shallow entrance windows that will enable detection of soft x-rays from 250eV-1.5KeV. In addition, there are other light sources such as the FERMI, EuXFEL, and FLASH XFELs, as well as numerous synchrotrons such as the ALS, where soft x-ray science would benefit from detectors with higher quantum efficiency in the 20 eV to 1.5KeV range.A new microwave annealing technology provides an efficient way to achieve shallow entrance windows in fully depleted high-resistivity silicon sensors.more » Previously, SRP and SIMS measurements were used to characterize the shallow dopant profile, and sensors with the new entrance window process were deployed successfully to measure an Fe-55 x-ray spectrum. For the first time, we present quantum efficiency measurement for soft x-rays. Furthermore, the resulting estimate of the entrance window is 20nm for an arsenic implanted entrance window and 55nm for a boron implanted entrance window.« less
  8. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

    Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagneticmore » cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.« less
  9. Thin-Entrance Window Process for Soft X-Ray Sensors

    New free electron lasers, such as SLAC’s LCLS-II, will provide unique scientific imaging opportunities. In order to fully utilize these facilities, we need to develop detectors with shallow entrance windows that will enable detection of soft x-rays from 250 eV to 1.5 KeV. Achieving adequately shallow entrance windows is challenging because the high temperature anneal needed to activate the dopant also drives the dopant profile deeper, growing the region that is insensitive to soft x-rays. A new microwave annealing technology provides an efficient way to achieve shallow entrance windows in fully depleted high-resistivity silicon sensors. The microwave anneal technique canmore » activate dopants at low substrate temperature, with minimal dopant diffusion, and can be used to fabricate both n-type and p-type entrance windows. SRP and SIMS measurements were used to verify dopant activation with negligible dopant diffusion. We then applied the microwave anneal process to a planar sensor wafer, using the new process to create the backside diode contact. Electrical test of the resulting sensors shows good reverse bias characteristics. The sensors have been bump-bonded to a read-out ASIC and used successfully to measure an Fe-55 x-ray spectrum. Process and device simulations were performed to characterize the quantum efficiency of the entrance window for soft x-rays. This technique is useful for other sensor applications requiring a shallow entrance window, including detectors for UV photons, low energy ions and low energy electrons.« less
  10. The ePix10k 2-megapixel hard X-ray detector at LCLS

    The ePix10ka2M (ePix10k) is a new large area detector specifically developed for X-ray free-electron laser (XFEL) applications. The hybrid pixel detector was developed at SLAC to provide a hard X-ray area detector with a high dynamic range, running at the 120 Hz repetition rate of the Linac Coherent Light Source (LCLS). The ePix10k consists of 16 modules, each with 352 × 384 pixels of 100 µm × 100 µm distributed on four ASICs, resulting in a 2.16 megapixel detector, with a 16.5 cm × 16.5 cm active area and ∼80% coverage. The high dynamic range is achieved with three distinct gain settings (low, medium, high)more » as well as two auto-ranging modes (high-to-low and medium-to-low). Here the three fixed gain modes are evaluated. The resulting dynamic range (from single photon counting to 10000 photons pixel −1 pulse −1 at 8 keV) makes it suitable for a large number of different XFEL experiments. The ePix10k replaces the large CSPAD in operation since 2011. The dimensions of the two detectors are similar, making the upgrade from CSPAD to ePix10k straightforward for most setups, with the ePix10k improving on experimental performance. The SLAC-developed ePix cameras all utilize a similar platform, are tailored to target different experimental conditions and are designed to provide an upgrade path for future high-repetition-rate XFELs. Here the first measurements on this new ePix10k detector are presented and the performance under typical XFEL conditions evaluated during an LCLS X-ray diffuse scattering experiment measuring the 9.5 keV X-ray photons scattered from a thin liquid jet.« less
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