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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Design, construction, and test of the Gas Pixel Detectors for the IXPE mission

Due to be launched in late 2021, the Imaging X-ray Polarimetry Explorer (IXPE) is a NASA Small Explorer mission designed to perform polarization measurements in the 2–8 keV band, complemented with imaging, spectroscopy and timing capabilities. At the heart of the focal plane is a set of three polarization-sensitive Gas Pixel Detectors (GPD), each based on a custom ASIC acting as a charge-collecting anode. In this paper we shall review the design, manufacturing, and test of the IXPE focal-plane detectors, with particular emphasis on the connection between the science drivers, the performance metrics and the operational aspects. We shall present a thorough characterization of the GPDs in terms of effective noise, trigger efficiency, dead time, uniformity of response, and spectral and polarimetric performance. In addition, we shall discuss in detail a number of instrumental effects that are relevant for high-level science analysis—particularly as far as the response to unpolarized radiation and the stability in time are concerned.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cosmic Ray Background Removal With Deep Neural Networks in SBND

In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons, and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, both as a source of event triggers and as the majority of the particle count in true neutrino-triggered events. In this work, we demonstrate a novel application of deep learning techniques to remove these background particles by applying deep learning on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program. We use this technique to identify, on a pixel-by-pixel level, whether recorded activity originated from cosmic particles or neutrino interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Light detection with power and signal transmission over fiber

The Deep Underground Neutrino Experiment is a next generation long baseline (1300 km) neutrino oscillation experiment. The neutrino beam measurements will be performed by a near detector and far detector. The far detector will consist of four modules, installed 1.5 km deep underground, based on Liquid Argon Time Projection Chamber (LArTPC) technology to detect particles. The Vertical Drift (VD) LArTPC is a recent technology proposed by the DUNE collaboration for the second FD module. In VD, light collection will be optimized by embedding photon detectors within the LArTPC cathode, which is biased at −300 kV. As a result, power must arrive to the Photon Detection System and signal must be transmitted via non-conductive material. The proposed solution is to use Power-over-Fiber and Signal-over-Fiber. An intense validation of the system is being performed by the collaboration at the CERN Neutrino Platform. The design of the system and the results of the validation collected over the first half of 2022 are presented here.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Characterization of Transition Edge Sensors for the Simons Observatory

The Simons Observatory is building both large (6 m) and small (0.5 m) aperture telescopes in the Atacama Desert in Chile to observe the cosmic microwave background CMB radiation with unprecedented sensitivity. Simons Observatory telescopes in total will use over 60,000 transition edge sensor (TES) detectors spanning center frequencies between 27 and 285 GHz and operating near 100 mK. TES devices have been fabricated for the Simons Observatory by NIST, Berkeley, and HYPRES/SeeQC corporation. Iterations of these devices have been tested cryogenically in order to inform the fabrication of further devices, which will culminate in the final TES designs to be deployed in the field. The detailed design specifications have been independently iterated at each fabrication facility for particular detector frequencies. We present test results for prototype devices, with emphasis on NIST high frequency detectors. A dilution refrigerator was used to achieve the required temperatures. Measurements were taken both with 4-lead resistance measurements and with a time-domain Superconducting Quantum Interference Device (SQUID) multiplexer system. The SQUID readout measurements include analysis of current versus voltage (IV) curves at various temperatures, square wave bias step measurements, and detector noise measurements. Lastly, normal resistance, superconducting critical temperature, saturation power, thermal and natural time constants, and thermal properties of the devices are extracted from these measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Magnetic-Field Diffusion Effects in Beam Position Monitors III: Application to DARHT-II Beam Data

Beam position monitors (BPMs) provide time-resolved measurements of the current and centroid position of high-current electron beams in linear induction accelerators (LIAs). One of the types of detectors used in BPMs is the B-dot loop, which generates a signal from the EMF due to the time varying magnetic flux through the loop. If some of the boundaries of the loop are composed of thick metal walls with finite conductivity, the resulting signal must be corrected for the magnetic field diffusion into the metal. The theoretically predicted flux due to diffusion is in remarkable agreement with experimental measurements. Although accurate BPM measurements of beam current require correction of magnetic field diffusion, accurate measurement of beam position requires no correction. In this note, we present experimental validation of current and position results from a prototype detector employing finite conductivity sensing areas, based on experiments on the DARHT-II LIA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a foreground that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about 5% of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about 10 times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a {\it foreground} that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about $5\%$ of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about $10$ times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Characterization of EJ-270 and Ce-doped LiCAF scintillators for the development of high-rate neutron reflectometer detectors

The Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory is anticipated to provide a neutron source with ∼20 times increase in peak brightness than the First Target Station. The neutron reflectometers currently in operation at the First Target Station need to be upgraded due to the increased neutron flux. A prototype neutron detector module based upon a pixelated scintillator array readout by silicon photomultipliers is being developed to address the high-rate challenge faced with future neutron reflectometer instruments at the Second Target Station. Two types of scintillator materials were considered for this detector development, i.e., 6 Li-loaded EJ-270 plastic scintillator and Ce-doped LiCAF single crystal. This paper reports the scintillator characterization results, including light yield, pulse shape discrimination performance, capability to detect thermal neutrons in a high γ-ray field, and γ-ray sensitivity. The number of photons produced per neutron capture by EJ-270 and LiCAF:Ce was measured to be 2176 ± 91 and 2651 ± 108, respectively. EJ-270 demonstrated a good capability to discriminate between neutrons and γ-rays by employing the commonly used charge comparison method (figure-of-merit: 1.13 ± 0.01 for an energy cut of 292–426 keVee) and a reasonable performance when using the time-over-threshold techniques; however, no discrimination was observed from LiCAF:Ce regardless of the pulse shape discrimination approaches utilized, making pulse height discrimination necessary for LiCAF:Ce to differentiate between neutrons and γ-rays. Both EJ-270 and LiCAF:Ce exhibited an acceptable capacity to detect thermal neutrons at high exposure rates up to approximately 584 mR/h. Furthermore, the γ-ray sensitivities measured with a 60 Co source at an exposure rate of around 1145 mR/h were determined to be (6.11 ± 0.87) × 10 −6 and (7.64 ± 1.08) × 10 −7 for EJ-270 and LiCAF:Ce, respectively.

EJ-270↗
DOE OSTI2021

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography *

Abstract Neutron computed tomography (NCT), a 3D non-destructive characterization technique, is carried out at nuclear reactor or spallation neutron source-based user facilities. Because neutrons are not severely attenuated by heavy elements and are sensitive to light elements like hydrogen, neutron radiography and computed tomography offer a complementary contrast to x-ray CT conducted at a synchrotron user facility. However, compared to synchrotron x-ray CT, the acquisition time for an NCT scan can be orders of magnitude higher due to lower source flux, low detector efficiency and the need to collect a large number of projection images for a high-quality reconstruction when using conventional algorithms. As a result of the long scan times for NCT, the number and type of experiments that can be conducted at a user facility is severely restricted. Recently, several deep convolutional neural network (DCNN) based algorithms have been introduced in the context of accelerating CT scans that can enable high quality reconstructions from sparse-view data. In this paper, we introduce DCNN algorithms to obtain high-quality reconstructions from sparse-view and low signal-to-noise ratio NCT data-sets thereby enabling accelerated scans. Our method is based on the supervised learning strategy of training a DCNN to map a low-quality reconstruction from sparse-view data to a higher quality reconstruction. Specifically, we evaluate the performance of two popular DCNN architectures—one based on using patches for training and the other on using the full images for training. We observe that both the DCNN architectures offer improvements in performance over classical multi-layer perceptron as well as conventional CT reconstruction algorithms. Our results illustrate that the DCNN can be a powerful tool to obtain high-quality NCT reconstructions from sparse-view data thereby enabling accelerated NCT scans for increasing user-facility throughput or enabling high-resolution time-resolved NCT scans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

DR-RINS: Digital real-time relative intensity noise suppressor for pump–probe spectroscopy and microscopy

Relative intensity noise (RIN) inherent in fiber lasers poses a serious obstacle to their use in pump–probe spectroscopy and imaging. RIN can be removed through an analog balanced detector, or, as we have previously shown, software adaptive noise cancellation (ANC) on digitized signals. One major drawback to software ANC is the added time required for digitizing and post-processing. In this article, we describe a design for ANC on a field-programmable gate array (FPGA), making use of high-level synthesis tools and fixed-point arithmetic to achieve real-time laser RIN suppression at 25 MHz sample rates. Unlike the software-ANC approach, the FPGA-ANC device can serve as a dedicated drop-in denoiser, placed between the detectors and a commercial lock-in amplifier. We demonstrate its application to transient absorption spectroscopy and microscopy, lowering the noise floor to ~17 dB above the shot noise limit. Furthermore, we demonstrate a dramatic improvement in data acquisition time from ~6 h to ~5 min in a real-time imaging scenario.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Surface-Defect-Passivation-Enabled Near-Unity Charge Collection Efficiency in Bromide-Based Perovskite Gamma-Ray Spectrum Devices

Hybrid lead halide perovskites have superior charge transport properties to all-inorganic perovskites, but high-resolution spectroscopic radiation detectors have not been realized. Here we show that surface deep traps severely limit charge collection in formamidinium lead bromide (FAPbBr3) single-crystal devices, despite having a good bulk transport property. Three types of defect on the crystal surface, namely, FA vacancies, uncoordinated lead and Pb-Pb dimers caused by bromide loss, are found to form deep traps, resulting in non-radiative charge recombinations at the metal/perovskite interface. By tailoring the passivation functional groups, we find that ammonium bromide can passivate all these three deep traps on FAPbBr3 surfaces, improving the charge collection efficiency to near unity. The comparable bulk and surface recombination lifetimes indicate that all the surface defects are effectively passivated. Surface passivation also reduces the dark current by 10 times and decreases the dark counts by ~60 times. The energy resolution of the 137Cs spectra acquired using the FAPbBr3 detectors is improved from 5.7% to 1.7% when all the surface defects are passivated without changing the bulk properties, which is the best among solution-grown semiconductor detectors. Surface passivation is stable for more than six months, and FAPbBr3 spectroscopic detectors can operate at unprecedented high temperatures of more than 130 degrees C.

gamma ray↗
DOE OSTI2023

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-purity germanium semiconductor modeling in the detector response function toolkit

In this study, we have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60 Co, 133 Ba, and 137 Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

De-noising drift chambers in CLAS12 using convolutional auto encoders

Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Biomass pyrolysis devolatilization kinetics of herbaceous and woody feedstocks

Devolatilization kinetics were determined using a modified micropyrolyzer reactor for several biomass feedstocks: switchgrass, corn stover, red oak, and pine. Here, the micropyrolyzer was directly coupled to a flame ionization detector (FID) to track the release of volatiles from the biomass. Time series data from these experiments was analyzed to determine apparent devolatilization rates. Care was taken to assure the experiments were isothermal and kinetically limited calculating a Biot number less than 0.1 and pyrolysis numbers greater than 10, which simplifies the derivation of devolatilization rates. A single, first order reaction was able to model devolatilization rates at temperatures up to 500 °C. No correlation was found between the inorganic content of the biomass and its rate of devolatilization. Apparent activation energies were in the range of 54.9–88.4 kJ mol –1 . The rate coefficient at 500 °C was calculated as 1.90–5.14 s –1 for the four feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2024

Testing the optical components for the National Ignition Facility time-resolved soft x-ray opacity spectrometer (OpSpecTR)

Opacity measurements are being carried out at the Z-facility at Sandia National Laboratories and at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory. The current soft x-ray Opacity Spectrometer (OpSpec) used on the NIF uses two elliptically bent crystals in time-integrated mode on either an image plate or a film. Plans are under way to expand these opacity measurements into a mode of time-resolved detection, called OpSpecTR. Previously, considerations for the available hCMOS detector size and photometrics led to a crystal geometry redesign and the use of a grazing angle x-ray mirror. The mirror acts as a low-pass x-ray energy filter, reducing the contribution of higher energy x rays. The first tests of the mirror and the crystal for OpSpecTR are presented here. The size of the mirror reflection and the reflectivity is tested using a Manson x-ray source. The mirror coupled with the new elliptical crystal shape demonstrates OpSpecTR’s spectral coverage. Finally, the results from the x-ray optics performance testing are shown along with the intended design.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Optimizing the hit finding algorithm for liquid argon TPC neutrino detectors using parallel architectures

Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming even more difficult as the detectors increase in size to reach their physics goals. Liquid argon time projection chamber (LArTPC) neutrino experiments are expected to grow in the next decade to have 100 times more wires than in currently operating experiments, and modernization of LArTPC reconstruction code, including parallelization both at data- and instruction-level, will help to mitigate this challenge. The LArTPC hit finding algorithm is used across multiple experiments through a common software framework. In this paper we discuss a parallel implementation of this algorithm. Using a standalone setup we find speedup factors of two times from vectorization and 30–100 times from multi-threading on Intel architectures. The new version has been incorporated back into the framework so that it can be used by experiments. On a serial execution, the integrated version is about 10 times faster than the previous one and, once parallelization is enabled, more speedups comparable to the standalone program are achieved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗