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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Real-Time Anomaly Detection for Beyond Standard Model Searches in ProtoDUNE Horizontal Drift

This paper summarizes work conducted throughout a SULI internship at Fermi National Accelerator Laboratory focused on building an unsupervised machine learning model for real-time anomaly detection in ProtoDUNE Horizontal Drift. Using simulated data, we trained an autoencoder model on a pure cosmic dataset, and evaluated it on both cosmic and neutrino events---making the model an anomaly detector. The goal was to make a model which matches or exceeds the current ADC Simple Window trigger algorithm so that our model can perform at the same rate but provide sensitivity to potential beyond-the-Standard-Model (BSM) signatures. In the end, we were able to construct a model which slightly exceeds the capabilities of the ADC Simple Window while remaining completely unsupervised, achieving $31.9 \pm 0.2$\% ($26.6 \pm 0.2$\%) $\nu$ efficiency at 5 Hz (2 Hz), a 3.6 (3.2) percentage point increase. Additionally, $17.5 \pm 0.3$\% ($18.3 \pm 0.3$\%) of the events that passed the autoencoder at 5 Hz (2 Hz) were missed by the current trigger algorithm. Future work will investigate alternative normalization methods, including quantile transformation, and evaluate the model on ProtoDUNE-HD detector-glitch data if that data becomes available.

Wilson, Cameron C. [Cincinnati U., RWC]↗
DOE OSTI2024

Improving the performance of cryogenic calorimeters with nonlinear multivariate noise cancellation algorithms

Abstract State-of-the-art physics experiments require high-resolution, low-noise, and low-threshold detectors to achieve competitive scientific results. However, experimental environments invariably introduce sources of noise, such as electrical interference or microphonics. The sources of this environmental noise can often be monitored by adding specially designed “auxiliary devices” (e.g. microphones, accelerometers, seismometers, magnetometers, and antennae). A model can then be constructed to predict the detector noise based on the auxiliary device information, which can then be subtracted from the true detector signal. Here, we present a multivariate noise cancellation algorithm which can be used in a variety of settings to improve the performance of detectors using multiple auxiliary devices. To validate this approach, we apply it to simulated data to remove noise due to electromagnetic interference and microphonic vibrations. We then employ the algorithm to a cryogenic light detector in the laboratory and show an improvement in the detector performance. Finally, we motivate the use of nonlinear terms to better model vibrational contributions to the noise in thermal detectors. We show a further improvement in the performance of a particular channel of the CUORE detector when using the nonlinear algorithm in combination with optimal filtering techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Forward Analytic Model of Neutron Time-of-Flight Signals for Inferring Ion Temperatures from MagLIF Experiments

A forward analytic model is required to rapidly simulate the neutron time-of-flight (nToF) signals that result from magnetized liner inertial fusion (MagLIF) experiments at Sandia’s Z Pulsed Power Facility. Various experimental parameters, such as the burn-weighted fuel-ion temperature and liner areal density, determine the shape of the nToF signal and are important for characterizing any given MagLIF experiment. Extracting these parameters from measured nToF signals requires an appropriate analytic model that includes the primary deuterium-deuterium neutron peak, once-scattered neutrons in the beryllium liner of the MagLIF target, and direct beamline attenuation. Here, mathematical expressions for this model were derived from the general-geometry time- and energy-dependent neutron transport equation with anisotropic scattering. Assumptions consistent with the time-of-flight technique were used to simplify this linear Boltzmann transport equation into a more tractable form. Models of the uncollided and once-collided neutron scalar fluxes were developed for one of the five nToF detector locations at the Z-Machine. Numerical results from these models were produced for a representative MagLIF problem and found to be in good agreement with similar neutron transport simulations. Twenty experimental MagLIF data sets were analyzed using the forward models, which were determined to only be significantly sensitive to the ion temperature. The results of this work were also found to agree with values obtained separately using a zero scatter analytic model and a high-fidelity Monte Carlo simulation. Finally, inherent difficulties in this and similar techniques are identified, and a new approach forward is suggested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

AI-assisted object condensation clustering for calorimeter shower reconstruction at CLAS12

Several nuclear physics studies using the CLAS12 detector rely on the accurate reconstruction of neutrons and photons from its forward angle calorimeter system. These studies often place restrictive cuts when measuring neutral particles due to an overabundance of false clusters created by the existing calorimeter reconstruction software. In this work, we present a new AI approach to clustering CLAS12 calorimeter hits based on the object condensation framework. The model learns a latent representation of the full detector topology using GravNet layers, serving as the positional encoding for an event’s calorimeter hits which are processed by a Transformer encoder. This unique structure allows the model to contextualize local and long range information, improving its performance. Evaluated on one million simulated $e^-$ $+$ $p$ collision events, our method significantly improves cluster trustworthiness: the fraction of reliable neutron clusters, increasing from 8.88% to 30.73%, and photon clusters, increasing from 51.07% to 64.73%. In conclusion, our study also marks the first application of AI clustering techniques for hodoscopic detectors, showing potential for usage in many other experiments.

Calorimeters↗
DOE OSTI2026

pyFLANK, a graph neural network based null distribution inference model for F ST outlier detection

Detecting genomic regions under selection is essential for understanding how populations adapt to different environments, yet it remains challenging due to the confounding effects of demographic history and linkage disequilibrium (LD). Fixation index (F ST ) is a widely used statistic to identify genomic regions under adaptation. However, identifying genes under selection by defining F ST outliers often remains challenging, owing to confounding effects of underlying demographic history. Traditional methods assume independence among loci and rely on simple demographic models, while newer models perform much better but are computationally expensive and not easily scalable. Here, we present pyFLANK, an open-source and automated Python implementation which detects F ST outliers using a null distribution inferred from quasi-independent loci. Our tool integrates three approaches to identify loci obeying a null distribution: graph neural network (GNN) inference, linkage disequilibrium (LD)-based inference, and user-defined input. Because pyFLANK uses GNN-based inference of quasi-independent loci, it yields a more accurate null model with less need for user parameter input. In simulation experiments, pyFLANK achieved lower false positive rates than current methods while maintaining comparable detection power, indicating that its refined null model better distinguishes true adaptive loci from background variation. The GNN-based model, in particular, detected additional loci associated with phenotypic variance that were not identified by existing methods. Assessments of simulation and real data from different species demonstrate that pyFLANK achieves lower false positive rates compared with other commonly used F ST outlier detectors, while maintaining comparable detection power and excellent computational performance, providing a robust and user-friendly tool for identifying loci under divergent selection. It extends existing F ST outlier frameworks by incorporating explicit LD-aware strategies for null model calibration. The method is intended as a practical and scalable complement to existing genome scan approaches.

FST↗
DOE OSTI2026

Neutron detector response modeling in NOvA

Neutrons can present a significant challenge for neutrino experiments in which energy reconstruction is critical. With the ability to escape detection completely and with a weak correlation between their kinetic energy and any eventual energy deposition, it is difficult to fully account for neutrons produced in neutrino interactions. This in turn leads to significant model dependence when evaluating neutron-related systematic uncertainties. The NOvA experiment is a long-baseline neutrino oscillation experiment with a high-statistics sample of antineutrino data collected by its near detector. We report an excess relative to data of simulated neutron candidates with low energy depositions when using standard Geant4 physics lists. The simulation excess is traced to an overabundance of secondary photons produced from interactions of neutrons with kinetic energy greater than \SI{20}{\mega\eV}. Improved agreement with data is obtained by applying the data-driven neutron-on-carbon \menate model for neutrons between \SI{20}{\mega\eV} and ${\sim}$\SI{100}{\mega\eV}. With \menate, the residual oversimulation is more uniform across the calorimetric neutron energy spectrum, suggesting possible overproduction of primary neutrons by the GENIE neutrino interaction generator. These results motivate the adoption of \menate-supplemented Geant4 simulation as the nominal simulation in the production of future \nova simulation.

Abubakar, S.↗
DOE OSTI2021

Thermonuclear neutron emission from a sheared-flow stabilized Z-pinch

We report the fusion Z-pinch experiment (FuZE) is a sheared-flow stabilized Z-pinch designed to study the effects of flow stabilization on deuterium plasmas with densities and temperatures high enough to drive nuclear fusion reactions. Results from FuZE show high pinch currents and neutron emission durations thousands of times longer than instability growth times. While these results are consistent with thermonuclear neutron emission, energetically resolved neutron measurements are a stronger constraint on the origin of the fusion production. This stems from the strong anisotropy in energy created in beam-target fusion, compared to the relatively isotropic emission in thermonuclear fusion. In dense Z-pinch plasmas, a potential and undesirable cause of beam-target fusion reactions is the presence of fast-growing, “sausage” instabilities. This work introduces a new method for characterizing beam instabilities by recording individual neutron interactions in plastic scintillator detectors positioned at two different angles around the device chamber. Histograms of the pulse-integral spectra from the two locations are compared using detailed Monte Carlo simulations. These models infer the deuteron beam energy based on differences in the measured neutron spectra at the two angles, thereby discriminating beam-target from thermonuclear production. An analysis of neutron emission profiles from FuZE precludes the presence of deuteron beams with energies greater than 4.65 keV with a statistical uncertainty of 4.15 keV and a systematic uncertainty of 0.53 keV. This analysis demonstrates that axial, beam-target fusion reactions are not the dominant source of neutron emission from FuZE. These data are promising for scaling FuZE up to fusion reactor conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

KamNet: An integrated spatiotemporal deep neural network for rare event searches in KamLAND-Zen

Rare event searches allow us to search for new physics at energy scales inaccessible with other means by leveraging specialized large-mass detectors. Machine learning provides a new tool to maximize the information provided by these detectors. The information is sparse, which forces these algorithms to start from the lowest level data and exploit all symmetries in the detector to produce results. In this work we present KamNet, which harnesses breakthroughs in geometric deep learning and spatiotemporal data analysis to maximize the physics reach of KamLAND-Zen, a kiloton scale spherical liquid scintillator detector searching for 0⁢νβ⁢β. Using a simplified background model for KamLAND, we show that KamNet outperforms a conventional convolutional neural network (CNN) on benchmarking Monte Carlo simulations with an increasing level of robustness. Using simulated data, we then demonstrate KamNet's ability to increase KamLAND-Zen's sensitivity to 0ν⁢ββ and 2⁢ν⁢β⁢β decay to excited states. A key component of this work is the addition of an attention mechanism to elucidate the underlying physics KamNet is using for the background rejection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Simulation of gallium nitride vertical fin-shaped field effect transistor for use as thermal neutron detector

Through the use of a radiation detection system simulation framework, a gallium nitride vertical fin-shaped field effect transistor (FinFET) was studied for output response when utilized as a thermal neutron detector. The FinFET was assumed to had been backfilled with boron carbide, reactive to thermal neutrons. The GaN FinFET was modeled with radiation transport from MCNP, and the electronic transport from COMSOL Multiphysics. Fabricated FinFET devices (not neutron reactive) were tested to aid in the tuning of the COMSOL FinFET model. Through time-depenent studies, the drain current response pulse to simulated ionization due to single events lead to building of a database of device responses to radiation. By integrating the current pulses over time, the induced charge was calculated. Using the results of the radiation transport PTRAC file in combination with the induced charge database, an integrated charge spectrum was calculated.

Davidson, Bryce L.↗
DOE OSTI2020

AWCC Simulations

Neutron well counters provide a means to measure fissile mass by detecting coincident neutrons, which is a unique signature to fission. For coincidence counting, mass is determined using a calibration curve established with items that have the same material characteristics. Multiplicity analysis solves the point model equations for mass using known detector parameters. In both cases, mass measurements may exhibit a bias due to item characteristics and should be corrected for. Experiments can be done to estimate bias and material effects, but they require having both the well counter and the material well defined. In pursuit of estimating measurement bias and uncertainty in a High Efficiency Neutron Counter (HENC), an MCNP simulation was matched to measurements performed with an Active Well Coincidence Counter (AWCC) to de ne a neutron source term. The neutron source term will be used to predict measurement performance of similar material types in a HENC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

SNEWPY: A Data Pipeline from Supernova Simulations to Neutrino Signals

Current neutrino detectors will observe hundreds to thousands of neutrinos from a Galactic supernovae, and future detectors will increase this yield by an order of magnitude or more. With such a data set comes the potential for a huge increase in our understanding of the explosions of massive stars, nuclear physics under extreme conditions, and the properties of the neutrino. However, there is currently a large gap between supernova simulations and the corresponding signals in neutrino detectors, which will make any comparison between theory and observation very difficult. SNEWPY is an open-source software package which bridges this gap. The SNEWPY code can interface with supernova simulation data to generate from the model either a time series of neutrino spectral fluences at Earth, or the total time-integrated spectral fluence. Data from several hundred simulations of core-collapse, thermonuclear, and pair-instability supernovae is included in the package. This output may then be used by an event generator such as sntools or an event rate calculator such as SNOwGLoBES. Additional routines in the SNEWPY package automate the processing of the generated data through the SNOwGLoBES software and collate its output into the observable channels of each detector. In this paper we describe the contents of the package, the physics behind SNEWPY, the organization of the code, and provide examples of how to make use of its capabilities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modeling and Simulation of MC-Small Design

In order to design a lightweight, highly portable neutron multiplicity counter for use in higher risk regions by mobile field teams, a redesign of the MC-15 is being performed, with the goal of producing a detector below 30 lbs for ease of transport. To achieve this, multiple MCNP® simulations were run, evaluating the number and positioning of the He-3 tubes in the detector as well as the amount of high-density polyethylene (HDPE) surrounding the tubes. Based on these simulations, the proposed redesign of the MC-15 (aka MC-Small) possesses 11 tubes and is 13 in wide, 3.21 in thick and 13 in tall. Including the changes to the positioning of the tubes and the removal of HDPE from less sensitive regions of the detectors (i.e. bases of tubes, back of detector), this resulted in an efficiency of 0.56% when measuring a bare Cf-252 source 19.69 in away, only 28% less efficient (relatively) than the MC-15 while weighing 18 lbs, 12 lbs less than the weight of the MC-15.

42 ENGINEERING↗
DOE OSTI2021

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Real-space inversion and super-resolution of ultrafast scattering

Ultrafast scattering using x-rays or electrons is an emerging method to obtain structure dynamics at the atomic lengthscales and timescales. However, directly resolving in real-space atomic motions is inherently limited by the finite detector range and the probe energy. So, as a result, the time-resolved signal interpretation is mostly done in reciprocal space and relies on modeling and simulations of specific structures and processes. Here, we introduce a model-free approach to directly resolve scattering signals in real space, surpassing the diffraction limit, using scattering kernels and signal priors that naturally arise from the measurement constraints. We demonstrate the approach on simulated and experimental data, recover multiple atomic motions at sub-angstrom resolutions, and discuss the recovery accuracy and resolution limits versus signal fidelity. The approach offers a robust path to obtain high-resolution real-space information of atomic-scale structure dynamics using current time-resolved x-ray or electron scattering sources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Determining g A / g V with High-Resolution Spectral Measurements Using a LiInSe 2 Bolometer

Neutrinoless double beta decay (0νββ) processes sample a wide range of intermediate forbidden nuclear transitions, which may be impacted by quenching of the axial vector coupling constant (g A /g V ), the uncertainty of which plays a pivotal role in determining the sensitivity reach of 0νββ experiments. Here we present measurements performed on a high-resolution LiInSe 2 bolometer in a “source = detector” configuration to measure the spectral shape of the fourfold forbidden β decay of 115 In . The value of g A /g V is determined by comparing the spectral shape of theoretical predictions to the experimental β spectrum taking into account various simulated background components as well as a variety of detector effects. We find evidence of quenching of g A /g V at >5 σ with a model-dependent quenching factor of 0.655 ± 0.002 as compared to the free-nucleon value for the interacting shell model. We also measured the 115 In half-life to be [5.18 ± 0.06(stat) $^{+0.005}_{- 0.015}$(sys)] x 10 14 yr within the interacting shell model framework. This Letter demonstrates the power of the bolometeric technique to perform precision nuclear physics single-β decay measurements, which along with improved nuclear modeling can help reduce the uncertainties in the calculation of several decay nuclear matrix elements including those used in 0νββ sensitivity calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

GeV-scale neutrinos: interactions with mesons and DUNE sensitivity

The simplest extension of the SM to account for the observed neutrino masses and mixings is the addition of at least two singlet fermions (or right-handed neutrinos). If their masses lie at or below the GeV scale, such new fermions would be produced in meson decays. Similarly, provided they are sufficiently heavy, their decay channels may involve mesons in the final state. Although the couplings between mesons and heavy neutrinos have been computed previously, significant discrepancies can be found in the literature. The aim of this paper is to clarify such discrepancies and provide consistent expressions for all relevant effective operators involving mesons with masses up to 2 GeV. Moreover, the effective Lagrangians obtained for both the Dirac and Majorana scenarios are made publicly available as FeynRules models so that fully differential event distributions can be easily simulated. As an application of our setup, we numerically compute the expected sensitivity of the DUNE near detector to these heavy neutral leptons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Geant4 HEP Examples

Geant4 is a widely used simulation toolkit in high-energy physics (HEP), enabling precise modeling of particle interactions with matter. It plays a crucial role in the development and optimization of detector concepts for future HEP programs. With a structured set of examples ranging from basic to advanced, Geant4 provides a comprehensive set of concrete examples for users at different expertise levels. As a critical tool for the HEP community, Geant4 continues to evolve, adapting to emerging computational paradigms and experimental requirements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗