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At least 55 records · Page 3

A compact, low-power epithermal neutron counter for lunar water detection

The detection and characterization of lunar water are critical for enabling sustainable human and robotic exploration of the Moon. Orbital neutron spectrometers, such as instruments on Lunar Prospector and the Lunar Reconnaissance Orbiter, have revealed hydrogen-rich regions near the poles but are limited by coarse spatial resolution and low counting efficiency. We present a compact, lightweight, and low-power epithermal neutron detector based on boron-coated silicon imagers, designed to probe subsurface hydrogen at decimeter scales from mobile platforms such as lunar rovers. This instrument leverages the high neutron capture cross-section of 10 B to convert epithermal neutrons into detectable α and 7 Li ions in a fully-depleted silicon imager, providing a unique event topology to identify neutrons while suppressing backgrounds. Monte Carlo simulations demonstrate that a 3 μm boron layer achieves optimal neutron detection efficiency, further enhanced with polyethylene moderation to improve sensitivity to the 0.4 eV–500 keV epithermal energy range. For a 10 cm 2 active area, the detector achieves sensitivity to H 2 O weight fractions as low as 0.01 wt% in a 15 minute measurement. This scalable, portable, low-mass design is well-suited for integration into upcoming Artemis and commercial lunar rovers, providing a transformative capability for in-situ resource prospecting and ground-truth validation of orbital measurements.

Detector modelling and simulations I (interaction

Refined Sensitivity Estimates for Single-Molecule Magnet Dark Matter Detectors

We revisit the sensitivity of Single Molecule Magnet (SMM) crystals as detectors for low-mass dark matter. In previous work, we established the concept of the ``magnetic bubble chamber'', where energy deposited by dark matter triggers a magnetic avalanche in a metastable crystal. The original sensitivity estimates relied on a conservative criterion requiring the spin relaxation time to be strictly shorter than the thermal diffusion time. Here, we demonstrate that this criterion effectively ignores the stochastic nature of spin relaxation. We derive a refined analytic estimate which accounts for the fraction of spins that relax even when diffusion is fast. We show that the Zeeman energy released by this fraction contributes to local heating, significantly lowering the energy threshold for avalanche formation. We present simulation results confirming this effect and report on experimental verification of the assumed low-temperature thermal properties of two representative SMM crystals, Mn$_{12}$-acetate and Mn$_{32}$. Together, these efforts extend this pathfinder program toward the realization of SMM-based detectors with controlled material properties and enhanced dark matter sensitivity.

Eberhardt, Andrew [Tokyo U., IPMU]

Simulations of Ground and Space-Based Oxygen Atom Experiments

Fast, pulsed atomic oxygen sources are a key tool in ground-based investigations of spacecraft contamination and surface erosion effects. These technically challenging ground-based studies provide a before and after picture of materials under low-earth-orbit (LEO) conditions. It would be of great interest to track in real time the pulsed flux from the source to the surface sample target and beyond in order to characterize the population of atoms and molecules that actually impact the surface and those that make it downstream to any coincident detectors. We have performed simulations in order to provide such detailed descriptions of these ground-based measurements and to provide an assessment of their correspondence to the actual LEO environment. Where possible we also make comparisons to measured fluxes and erosion yields. To perform the calculations we use a detailed description of a measurement beam and surface geometry based on the W, pulsed apparatus at Montana State University. In this system, a short pulse (on the order of 10 microseconds) of an O/O2 beam impacts a flat sample about 40 cm downstream and slightly displaced &om the beam s central axis. Past this target, at the end of the beam axis is a quadrupole mass spectrometer that measures the relative in situ flux of 0102 to give an overall normalized erosion yield. In our simulations we use the Direct Simulation Monte Carlo (DSMC) method, and track individual atoms within the atomic oxygen pulse. DSMC techniques are typically used to model rarefied (few collision) gas-flows which occur at altitudes above approximately 110 kilometers. These techniques are well suited for the conditions here, and multi-collision effects that can only be treated by this or a similar technique are included. This simulation includes collisions with the surface and among gas atoms that have scattered from the surface. The simulation also includes descriptions of the velocity spread and spatial profiles of the O/O2 beam obtained from separate measurements. These computations use basic engineering models for the gas-gas and gas-surface scattering and focus on the influence of multi-collision effects. These simulations characterize many important quantities of interest including the actual flux of atoms that reach the surface, the energy distribution of this flux, as well as the direction of the velocity of the flux that strikes the surface. These quantities are important in characterizing the conditions which give rise to measured surface erosion. The calculations also yield time- snapshots of the pulse as it impacts and flows around the surface. These snapshots reveal the local environment of gas near the surface for the duration of the pulse. We are also able to compute the flux of molecules that travel downstream and reach the spectrometer, and we characterize their velocity distribution. The number of atoms that reach the spectrometer can in fact be influenced by the presence of the surface due to gas-gas collisions from atoms scattered h m the surface, and it will generally be less than that with the surface absent. This amounts to an overall normalization factor in computing erosion yields. We discuss these quantities and their relationship to the gas-surf$ce interaction parameters. We have also performed similar calculations corresponding to conditions (number densities, temperatures, and velocities) of low-earth orbit. The steady-state nature and lower overall flux of the actual space environment give rise to differences in the nature of the gas-impacts on the surface from those of the ground-based measurements using a pulsed source.

Minton, T. K.

Preliminary On-Orbit Neutron Dose Equivalent and Energy Spectrum Results from the ISS-RAD Fast Neutron Detector (FND)

The ISS-RAD instrument was activated on ISS on February 1st, 2016. Integrated in ISS-RAD, the Fast Neutron Detector (FND) performs, for the first time on ISS, routine and precise direct neutron measurements between 0.5 and 8 MeV. Preliminary results for neutron dose equivalent and neutron flux energy distributions from online/on-board algorithms and offline ground analyses will be shown, along with comparisons to simulated data and previously measured neutron spectral data. On-orbit data quality and pre-launch analysis validation results will be discussed as well.

Semones, Edward

Analysis of SOFCAL calibration data

Ionization calorimeters determine the total energy of a particle by absorbing, within the mass of the calorimeter, the entire energy of the particle or a significant (and determinable) fraction of it. The JACEE group has used passive ionization calorimetery, which employs photographic emulsions as the detector medium, to measure the charge composition and energy spectrum of cosmic rays up to, and exceeding, 10(exp 14)eV. The SOFIC approach depends similarly on the use of three-dimensional nuclear-electromagnetic shower theory to relate the ionization deposits obtained during a shower to the energy of the particle causing the shower. Bundles of thousands of scintillating optical fibers are read out using image-intensified CCD's. Such an event may be triggered by a fast shower detector placed under the instrument or if only heavy particles are of interest, from a fast primary Cerention detector placed above the calorimeter. In the first study, fast Hammatsu photomultiplier tubes were purchased and tested for possible application for a triggering purpose. In the second study, some refinements have been made to the theoretical treatment of hadronic interactions in the central collision region. These will be helpful in improving the simulations necessary for observations of high energy cosmic ray nuclei with a SOFIC.

Gregory, John C.

Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments

Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational autoencoders, and normalizing flows, have been widely used and studied as efficient alternatives for traditional scientific simulations. However, they have several drawbacks, including training instability and inability to cover the entire data distribution, especially for regions where data are rare. This is particularly challenging for whole-event, full-detector simulations in high-energy heavy-ion experiments, such as sPHENIX at the Relativistic Heavy Ion Collider and Large Hadron Collider experiments, where thousands of particles are produced per event and interact with the detector. This work investigates the effectiveness of denoising diffusion probabilistic models (DDPMs) as an AI-based generative surrogate model for the sPHENIX experiment that includes the heavy-ion event generation and response of the entire calorimeter stack. DDPM performance in sPHENIX simulation data is compared with a popular rival, GANs. Results show that both DDPMs and GANs can reproduce the data distribution where the examples are abundant (low-to-medium calorimeter energies). Nonetheless, DDPMs significantly outperform GANs, especially in high-energy regions where data are rare. Additionally, DDPMs exhibit superior stability compared to GANs. The results are consistent between both central and peripheral centrality heavy-ion collision events. Moreover, DDPMs offer a substantial speedup of approximately a factor of 100 compared to the traditional Geant4 simulation method.

42 ENGINEERING

A Fast Evaluation of PDA Experimental Parameters Using Mie Scattering to Enhance the Measurement Accuracy of Droplet Size Distributions

The Phase Doppler technique (PDA) and its implementation generally relies on a geometric optics formulation for light scattering to estimate drop sizes from the measured phase differences between Doppler signals from two or more detectors. Although this limits experimental PDA scattering geometries to those where only one component of the geometric scatter is dominant, the calculations are relatively simple. This TM describes a fast method to evaluate PDA experimental parameters analytically using Mie scattering that provides a performance estimate of all possible configurations. The best configurations are fully tested using a Monte Carlo simulation to obtain a more accurate capability estimate for each one.

PDA

Real-time diagnostics for a reusable rocket engine

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Guo, T. H.

Use of simulated neural networks of aerial image classification

The utility of one layer neural network in aerial image classification is examined. The network was trained with the delta rule. This method was shown to be useful as a classifier in aerial images with good resolution. It is fast, it is easy to implement, because it is distribution-free, nothing about statistical distribution of the data is needed, and it is very efficient as a boundary detector.

Medina, Frances I.

Fast neutron leakage spectra of the EUCLID experiment

Special nuclear material in sub-critical and critical configurations measured in integral experiments are important for validation and adjustment of nuclear data. Many different evaluations of nuclear data exist, and these different evaluations can provide different values for individual cross sections that vary due to the uncertainties in differential experiments or lack of such data. For integral experiments, differences in these individual cross sections can have compensating errors, which lead to the same answer. One example of this is the Jezebel critical assembly, where k eff of the system is correctly computed by both ENDF/B-VIII.0 and JEFF-3.3, despite having substantially different underlying evaluated values for specific reactions (such as elastic and inelastic cross sections). To reduce compensating errors in nuclear data, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project has utilized machine learning to design a set of sub-critical and critical experiments. These experiments include slab- and cube-like configurations of 239 Pu in the form of the ZPPR plates. Six different responses were measured on a total of thirteen different configurations. One of these responses, the neutron leakage spectrum, was measured using an EJ301D detector. Finally, the results of the neutron leakage spectra show good agreement (within 1–2 σ ) with the expected spectrum from simulations and will be used in the subsequent nuclear data adjustment done by the EUCLID team.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Status of the Mu2e experiment

The Mu2e experiment at Fermilab searches for the coherent, neutrino-less conversion of a μ − to e − in the Coulomb field of Al nuclei, that represents one of the cleanest Charged Lepton Flavor Violating (CLFV) processes for exploring Beyond the Standard Model (BSM) physics. Mu2e aims to improve previous sensitivity by four orders of magnitude, with a distinctive signature provided by identifying mono-energetic electrons with energy slightly below the muon rest mass. To reach this goal, the experiment will use the highest intensity pulsed muon beam in the world, with up to 6 × 1 0 9 stopped muons/sec. This is achieved using the Fermilab proton beam and the design and realization of a unique 25 m long superconducting solenoidal system. The high beam intensity relies upon minimizing beam losses in the slow extraction region, indicating an opportunity of using bent crystals for shadowing. A high-resolution straw tracker and a fast CsI crystal calorimeter identify the conversion electron. Both detectors are inserted behind the Stopping Target in the last solenoid section. A Cosmic Ray Veto covers a large part of the solenoids to suppress background produced by cosmic rays. In this paper, we report the details of the experimental layout, the construction status of the magnetic system and detectors, and a short description of the simulation and realization of the bent crystals. Performing crystal channeling in front of the first slow extraction septa will allow beam shadowing and largely reduce beam losses. •Charge Lepton Flavor Violation processes: μ − → e − conversion.•Large Superconducting Solenoid system.•High-Intensity beams•High precision detectors.•Crystal channeling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Solid, structured composite neutron detectors with high dynamic range capability

Neutron detectors are essential across disciplines such as fundamental science, nuclear security, safeguards, and civilian applications. While 3 He-filled gas proportional counters have long been revered for their efficacy in detecting thermal neutrons and praised for their efficiency, neutron/gamma discrimination, and stability, the scarcity of 3He has spurred a search for alternatives. Here, we explore a solid structured scintillating particle composite (SPC) consisting of 6 Li-containing scintillating glass particles within an acrylic matrix as a neutron detector for high dynamic range applications. We show for the first time that an SPC neutron detector can boast an intrinsic detection efficiency of 0.261% for pure 252 Cf fission neutrons and an overall neutron detection efficiency of (0.546 ± 0.003)% at the Neutron Free-in-Air facility while being able to function in an intense gamma-ray environment. We also show that the SPC neutron detector supports fast neutron capture times and enables a dual-readout scheme that extends the detector dynamic range to high incident neutron fluxes. A scalable fabrication process allows for tailoring the SPC detector properties to the requirements of specific applications. Good agreement is found between the experimental results taken with a National Institute of Standards and Technology traceable 252 Cf source and the coupled MCNP6 and optical-ray-tracing simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

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

A Fast Framework for Generating Radioactive Mixture Spectra and Its Application to Remote High-Performance Mixture Identification

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

GADRAS

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model

Submillisecond measurements of system optical modulation functions in mosaic focal plane arrays

Measurements of system optical modulation functions (MTF, SWR) may be distorted by time-dependent environmental effects (thermal, vibration, flexure) and by electronics drift. Fast data collection may therefore be advantageous by minimizing drift time. The problem of fast data collection is accentuated when modulation data must be taken on a large number of detectors in a focal plane array. A method has been developed for the generation and storage of knife edge data from focal plane arrays, where data collection time per detector is in the submillisecond range. Once knife edge collects are completed, MTF response is found using conventional convolution techniques. SWR is obtained directly from knife edge response using a computerized simulation algorithm which bypasses use of MTF harmonics. Requirements for detector electronics speed, damping, and dynamic range are considered.

Thurlow, P. E.

Progress on the Development of a Simulation Environment for Optical Communications

Deep space laser communications require extremely accurate beam pointing to take advantage of the narrow beams achievable at optical wavelengths. This pointing accuracy must be achieved in the presence of spacecraft basebody motion which may exceed laser pointing requirements by orders of magnitude.In this paper a model of an optical band transceiver pointing control system is developed that can be used to predict performance under various operating scenarios. The transceiver model consists of an electro-mechanical model of the telescope platform and isolator. A novel photon counting detector array is used in the simulation as the focal plane detector. In the simulation we are able to inject various cases of spacecraft basebody motion based on both flight data and future mission spacecraft jitter requirements. Various models of uplink beacon flux levels and atmospheric scintillation are also available for analysis.Using these models, detector processing and control functions are implemented in the simulation. A complete acquisition sequence is demonstrated with blind acquisition and tracking of the modulated uplink beam and positioning of the downlink beam on the focal plane array. These simulations predict that pointing requirements will be met with representative disturbance models and uplink beam scintillation.

pointing control