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NASA NTRS1992

Detection of x ray sources in PROS

The problem of detecting discrete sources in x-ray images has much in common with the problem of automatic source detection at other wavelengths. In all cases, one searches for positive brightness enhancements exceeding a certain threshold, which appear consistent with what one expects for a point source, in the presence of a (possibly) spatially variable background. Multidimensional point spread functions (e.g., dependent on detector position and photon energy) are also common. At the same time, the problem in x-ray astronomy has some unique aspects. For example, for typical x-ray exposures in current or recent observatories, the number of available pixels far exceeds the number of actual x-ray events, so Poisson, rather than Gaussian statistics apply. Further, extended cosmic x-ray sources are common, and one often desires to detect point sources in the vicinity or even within bright, diffuse x-ray emission. Finally, support structures in x-ray detectors often cast sharp shadows in x-ray images making it necessary to detect sources in a region of rapidly varying exposure. We have developed a source detection package within the IRAF/PROS environment which attempts to deal with some of the problems of x-ray source detection. We have patterned our package after the successful Einstein Observatory x-ray source detection programs. However, we have attempted to improve the flexibility and accessibility of the functions and to provide a graphical front-end for the user. Our philosophy has been to use standard IRAF tasks whenever possible for image manipulation and to separate general functions from mission-specific ones. We will report on the current status of the package and discuss future developments, including simulation tasks, to allow the user to assess detection efficiency and source significance, tasks to determine source intensity, and alternative detection algorithms.

Deponte, J.↗

DOE OSTI2024

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗

NASA NTRS1988

Extreme ultraviolet quantum efficiency of opaque alkali halide photocathodes on microchannel plates

Comprehensive measurements are presented for the quantum detection efficiency (QDE) of the microchannel plate materials CsI, KBr, KCl, and MgF2, over the 44-1800 A wavelength range. QDEs in excess of 40 percent are achieved by several materials in specific wavelength regions of the EUV. Structure is noted in the wavelength dependence of the QDE that is directly related to the valence-band/conduction-band gap energy and the onset of atomic-like resonant transitions. A simple photocathode model allows interpretation of these features, together with the QDE efficiency variation, as a function of illumination angle.

Siegmund, O. H. W.↗

DOE OSTI2025

Scintillation light detection in polycrystalline diamond using single photon detectors

Here, this study investigates the scintillation properties of polycrystalline diamond for particle detection applications, particularly in neutron and alpha radiation environments. Polycrystalline diamonds provide a cost-effective alternative to monocrystalline diamonds while retaining essential detection properties. Photoluminescence measurements were performed to analyze emission spectra, revealing distinct characteristics based on impurity content and crystallinity. Scintillation responses were assessed using Silicon Photomultipliers (SiPMs), demonstrating the capability of polycrystalline diamond powders to respond to alpha irradiation, albeit with reduced resolution compared to traditional scintillators. A prototype neutron detector was developed by combining diamond powder with neutron-sensitive 6 LiF, and its performance was evaluated through experimental testing and Geant4 simulations. The findings indicate that polycrystalline diamond-based detectors can achieve significant detection efficiency while remaining insensitive to gamma radiation, offering potential for portable neutron detection applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Gamma-Ray and Cosmic Ray Muon Modalities for Cargo Inspection

Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.

Bae, Junghyun↗

DOE OSTI2024

Single-photon detection using large-scale high-temperature MgB2 sensors at 20 K

Abstract Ultra-fast single-photon detectors with high current density and operating temperature can benefit space and ground applications, including quantum optical communication systems, lightweight cryogenics for space crafts, and medical use. Here we demonstrate magnesium diboride (MgB 2 ) thin-film superconducting microwires capable of single-photon detection at 1.55 μ m optical wavelength. We used helium ions to alter the properties of MgB 2 , resulting in microwire-based detectors exhibiting single-photon sensitivity across a broad temperature range of up to 20 K, and detection efficiency saturation for 1 μ m wide microwires at 3.7 K. Linearity of detection rate vs incident power was preserved up to at least 100 Mcps. Despite the large active area of up to 400 × 400 μ m 2 , the reset time was found to be as low as ~ 1 ns. Our research provides possibilities for breaking the operating temperature limit and maximum single-pixel count rate, expanding the detector area, and raises inquiries about the fundamental mechanisms of single-photon detection in high-critical-temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

A perspective on the device physics of lead halide perovskite semiconducting detector for gamma and x-ray sensing

Metal-halide perovskites are emerging materials for radiation sensing featuring high absorption cross section, high charge mobility, and long carrier lifetime enabling superior detection efficiencies even at room temperature. Perovskite detector technologies are more complex involving different detecting modes and device architectures. Here, to elucidate the working principles, we provide a Perspective on the device structures and the operational principles of halide perovskite direct conversion detectors for radiation sensing. We will first discuss different detection modes and introduce the commonly used device architectures and their working principles. Based on our work and pioneer developments in the field, we will next compare the performances of the reported detectors. Additionally, we will summarize the single crystal detectors and polycrystalline thin film devices and discuss their advantages and disadvantages for different applications. Finally, we provide a future Perspective on the critical problems that must be addressed to commercialize this technology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS2019

Encounter-Based Simulation Architecture for Detect-And-Avoid Modeling

This paper presents an encounter-based simulation architecture developed at NASA to facilitate flexible and efficient Detect and Avoid modeling in parametric or tradespace studies on large data sets. The basic premise of this tool is that large-scale input data can be reduced to a set of `canonical encounters' and that using the reduced data in simulations does not lead to loss of fidelity. A canonical encounter is specified as ownship and intruder flight portions potentially resulting in a loss of well clear along with a set of properties that characterize the encounter. The advantages of using canonical encounters include faster simulations, reduced memory footprint, ability to select encounters based on user-specified criteria, shared encounters across multiple teams, peer-reviewed encounters, and a better understanding of the input data set, to name a few.

MOPS↗

NASA NTRS2019

Encounter-Based Simulation Architecture for Detect and Avoid Modeling

MOPS↗

DOE OSTI2021

Anatomy of Continuous Mars SEIS and Pressure Data from Unsupervised Learning

The seismic noise recorded by the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) seismometer (Seismic Experiment for Interior Structure [SEIS]) has a strong daily quasi-periodicity and numerous transient microevents, associated mostly with an active Martian environment with wind bursts, pressure drops, in addition to thermally induced lander and instrument cracks. That noise is far from the Earth’s microseismic noise. Quantifying the importance of nonstochasticity and identifying these microevents is mandatory for improving continuous data quality and noise analysis techniques, including autocorrelation. Cataloging these events has so far been made with specific algorithms and operator’s visual inspection. We investigate here the continuous data with an unsupervised deep-learning approach built on a deep scattering network. This leads to the successful detection and clustering of these microevents as well as better determination of daily cycles associated with changes in the intensity and color of the background noise. We first provide a description of our approach, and then present the learned clusters followed by a study of their origin and associated physical phenomena. We show that the clustering is robust over several Martian days, showing distinct types of glitches that repeat at a rate of several tens per sol with stable time differences. We show that the clustering and detection efficiency for pressure drops and glitches is comparable to or better than manual or targeted detection techniques proposed to date, noticeably with an unsupervised approach. Finally, here we discuss the origin of other clusters found, especially glitch sequences with stable time offsets that might generate artifacts in autocorrelation analyses. We conclude with presenting the potential of unsupervised learning for long-term space mission operations, in particular, for geophysical and environmental observatories.

58 GEOSCIENCES↗

NASA NTRS1986

An experimental evaluation of the effectiveness of random testing of fault-tolerant software

Results of a fault-tolerant software (FTS) experiment are used to show deficiencies of the simple random testing approach. Testing was performed using randomly generated test cases supplemented with extremal and special value (ESV) cases. Error detection efficiency of the random testing approach, with emphasis on correlated errors, was compared to the error detecting capabilities of the ESV data and found deficient. The use of carefully designed test cases as a supplement to random testing, as well as the use of structure based testing are recommended.

Vouk, Mladen A.↗

DOE OSTI2025

Hardness of Observing Strong-to-Weak Symmetry Breaking

Spontaneous symmetry breaking (SSB) is the cornerstone of our understanding of quantum phases of matter. Recent works have generalized this concept to the domain of mixed states in open quantum systems, where symmetries can be realized in two distinct ways dubbed strong and weak. Novel intrinsically mixed phases of quantum matter can then be defined by the spontaneous breaking of strong symmetry down to weak symmetry. However, proposed order parameters for strong-to-weak SSB (based on mixed-state fidelities or purities) seem to require exponentially many copies of the state, raising the question: Is it possible to efficiently detect strong-to-weak SSB, in general? In this work, we answer this question negatively in the paradigmatic cases of ℤ2 and U(1) symmetries. We construct ensembles of pseudorandom mixed states that do not break the strong symmetry yet are computationally indistinguishable from states that do. This rules out the existence of efficient state-agnostic protocols to detect strong-to-weak SSB.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Observation of Undulator Radiation Generated by a Single Electron Circulating in a Storage Ring and Possible Applications

An experimental study into the undulator radiation, generated by a single electron was carried out at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab. The individual photons were detected by a Single Photon Avalanche Diode (SPAD) at an average rate of 1 detection per 300 revolutions in the ring. The detection events were continuously recorded by a picosecond event timer for as long as 1 minute at a time. The collected data were used to test if there is any deviation from the classically predicted Poissonian photostatistics. It was motivated by the observation * of sub-Poissonian statistics in a similar experiment. The observation * could be an instrumentation effect related to low detection efficiency and long detector dead time. In our experiment, the detector (SPAD) has a much higher efficiency (65%) and a much lower dead time. In addition, we show that the collected data (recorded detection times) can be used to study the synchrotron motion of a single electron and infer some parameters of the ring. For example, by comparing the results of simulation and measurement for the synchrotron motion we were able to estimate the magnitude of the RF phase jitter.

43 PARTICLE ACCELERATORS↗

NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

DOE OSTI2020

Modeling the Transmission of Optical Lightning Signals Through Complex 3‐D Cloud Scenes

Abstract Space‐based lightning imagers have shown that complex cloud scenes consisting of multiple tall convective features, anvil clouds, and warm boundary cloud layers are illuminated by lightning in many different ways depending on where the lightning occurs and how energetic it is. Modifications to the optical lightning signals from radiative transfer in the cloud medium can lead to reductions in detection efficiency and location accuracy for these instruments and can also cause some of the optical signals that are detected to have unexpected spatial energy distributions. In this study, we perform Monte Carlo radiative transfer simulations of optical lightning emissions in clouds with complex 3‐D geometries to shed some light on the origins of certain irregular radiance patterns that have been recorded from orbit. We show that diffuse reflections off nearby cloud faces can explain lightning signals in nonelectrified clouds, tall clouds can result in poor optical transmission and suppressed radiances that could lead to missed events and that particularly favorable viewing conditions can cause otherwise normal lightning to produce a superbolt that is orders of magnitude brighter than the same flash seen from a different angle.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Absolute and angular efficiencies of a microchannel-plate position-sensitive detector

This paper presents a characterization of a commercially available position-sensitive detector of energetic ions and neutrals. The detector consists of two microchannel plates followed by a resistive position-encoding anode. The work includes measurement of absolute efficiencies of H(+), He(+), and O(+) ions in the energy range between 250 and 5000 eV, measurement of relative detection efficiencies as a function of particle impact angle, and a simple method for accurate measurement of the time at which a particle strikes the detector.

Gao, R. S.↗

NASA NTRS1991

Heterodyne Doppler 1-micron lidar measurement of reduced effective telescope aperture due to atmospheric turbulence

A pulsed Nd:YAG bistatic focused-beam lidar allowing simultaneous heterodyne and direct detection of the same lidar returns has been experimentally employed to ascertain the effect of atmospheric turbulence on heterodyne and direct-detection lidar at 1 micron, by measuring the average carrier-to-noise ratio and statistical fluctuation level in the return signals under various experimental and atmospheric conditions. Atmospheric turbulence is found capable of reducing the lidar receiver's effective telescope aperture and heterodyne detection efficiency. This observed effective-aperture limitation functionally resembles predictions based on the Clifford and Wandzura (1981) heterodyne wavefront detection theory.

Chan, Kin Pui↗