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DOE OSTI2024

Scintillating Bubble Chambers for Direct Dark Matter Detection, and an Update on SBC-LAr10

The Scintillating Bubble Chamber (SBC) Collaboration aims to use the liquid-noble bubble chamber technology as a low-threshold detector for dark matter particles of 1-10 GeV/c2. The detector combines the remarkable electron recoil (ER) discrimination of the bubble chamber with the event-by-event energy resolution provided by liquid argon (LAr) scintillation, with the crucial added benefit that ER discrimination in liquid-noble bubble chambers extends to much lower thresholds than in past freon-filled bubble chambers, with the potential for quasi-background-free operation at thresholds of 100 eV in nuclear recoil (NR) energy. SBC has developed two functionally identical 10 kg detectors: SBC-LAr10 at Fermilab will calibrate low-threshold performance, while the radio-pure SBC-SNOLAB chamber will execute SBC s first deep-underground dark matter search. SBC-LAr10 at Fermilab was recently installed in the MINOS tunnel 100 meters underground, and the first bubbles are expected this fall. I will present the current status of SBC-LAr10 and describe the suite of gamma and neutron calibrations we will execute. The calibrations will confirm the physics reach of this new technology, motivating not just the SBC-SNOLAB chamber now being assembled but also future searches into the solar neutrino fog at 1 GeV/c2.

Sheng, Zhiheng↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

Identifying unseen electromagnetic waveforms is critical for many applications, like interference management, electronic warfare and spectrum management. Traditionally this is done using statistical methods for anomaly detection, which has evolved to deep learning models for identifying the unseen data, formally termed as open set recognition. Some prior methods use a generative model to emulate open set data, which face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. To alleviate this issue, we propose a discriminative model that effectively combines time and frequency domain features of communication signals for accurate predictions. We further introduce a cosine similarity loss that makes the domain specific features unique to enhance the prediction rate. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Reaching For New Physics With MeV-scale Reconstruction In The MicroBooNE LArTPC Neutrino Detector

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing MeV-Scale energy depositions, or blips, in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV scale using reconstructed blips in MicroBooNE LArTPC data at Fermilab. A concentration of low-energy ($<$3 MeV) blips is observed around fiberglass mechanical support struts along the TPC edges, with spectral features consistent with the Compton edge of the 2.614 MeV $^{208}$Tl decay $\gamma$ ray. With these features we perform the electron energy scale calibration to few-percent precision and yield the specific activity of $^{208}$Tl in the struts, $(11.7 \pm 0.2 \text{(stat)} \pm 2.8 \text{(syst)})$ Bq/kg. Using cosmogenic blips above 3 MeV, we demonstrate the ability of large LArTPCs to discriminate low-energy proton and electron depositions. An enriched low-energy proton sample selected with this technique is smaller in data than in dedicated CORSIKA simulations, pointing to possible mismodeling in CORSIKA incident cosmic fluxes or Geant4 particle transport. These methods are applied to MicroBooNE's inclusive single-photon search, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons. By identifying and classifying blips near single-photon events selected by the WireCell reconstruction framework, a more comprehensive labeling of nearby hadronic activity is established: blips upstream of the shower axis indicate previously unidentified final-state protons, while elevated blip counts at wide angles signal final-state neutrons. Taken together with MiniBooNE's long-standing low-energy excess (LEE) and MicroBooNE electron-like and sterile neutrino searches disfavored as possible explanations of the MiniBooNE anomaly, this analysis motivates an expanded exploration of the single-photon channel in Fermilab's short-baseline LArTPC program. This thesis documents the current status of this enhanced analysis, which will form a key part of MicroBooNE's final low-energy-excess results.

Andrade Aldana, Diego Armando [IIT, Chicago (main)↗
DOE OSTI2025

Using Boosted Decision Trees to Select High Quality Measurements in the Mu2e Experiment at Fermilab

This thesis presents the implementation and evaluation of a Boosted Decision Tree (BDT) model to improve the selection of high-quality track measurements in the Mu2e experiment at Fermilab. The Mu2e experiment is a high-energy physics experiments seeking to observe a rare theoretical physics process known as Charged Lepton Flavor Violation. A significant challenge faced by the Mu2e experiment are so-called background events, which are events whose data mimics that of the rare physics process the experiment seeks to observe. Without a mechanism to reduce background, it would be impossible to know whether Charged Lepton Flavor Violation occurred or not. To this end, high-quality track measurements must be distinguished from low-quality track measurements. A track can be conceived of as the reconstructed path of a particle that traveled through the Mu2e detector. In addition to other data, data about such tracks is stored using a C++-based framework, specific to the domain of high-energy physics, known as ROOT. A boosted decision tree model was trained using ROOT’s Toolkit For Multivariate Analysis by leveraging variables ancillary to track quality. In evaluation, the BDT achieves a ROC-AUC of 0.927 in discriminating good-quality tracks from poor-quality tracks. Such a score is indicative of both strong discrimination and strong generalization. Subsequently, it is shown that applying a BDT-based quality cut to the distribution of particle momenta significantly enhances the signal-to-background distinction for signal electrons, paving the way for improved sensitivity to Charged Lepton Flavor Violation.

Mullany, Brendan T. [Drew U.] (ORCID:0009000818888↗
DOE OSTI2014

Neutron response characterization for an EJ299-33 plastic scintillation detector

Organic scintillation detectors have shown promise as neutron detectors for characterizing special nuclear materials in various arms-control and homeland security applications. Recent advances have yielded a new plastic scintillator - EJ299-33 - with pulse-shape-discrimination (PSD) capability. Plastic scintillators would have a much expanded range of deployment relative to liquids and crystals. Here in this paper, we present a full characterization of pulse height response to fission-energy neutrons for an EJ299-33 detector with 7.62-by-7.62-cm cylindrical active volume, and compare with an EJ309 liquid scintillator in the same assembly. Scintillation light output relations, energy resolutions, and response matrices are presented for both detectors. A Continuous spectrum neutron source, obtained via the bombardment of 27 Al with 7.44-MeV deuterons at the Edwards Accelerator Facility at Ohio University, was used for the measurement. A new procedure for evaluating and comparing PSD performance is presented which accounts for the effect of the light output relation on the ability to detect low energy neutrons. The EJ299-33 is shown to have considerable deficit in matrix condition, and in PSD figure of merit when compared to EJ309, especially when neutron energy is taken into account. Furthermore the EJ299 is likely to bring a modest PSD capability into a array of held applications that are not accessible to liquids or crystals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Spatio-temporal heterogeneity in soil water stable isotopic composition and its ecohydrologic implications in semiarid ecosystems

Spatio-temporal heterogeneity in soil water content is recognized as a common phenomenon, but heterogeneity in the hydrogen and oxygen isotope composition of soil water, which can reveal processes of water cycling within soils, has not been well studied. New advances are being driven by measurement approaches allowing sampling with high density in both space and time. Using in situ soil water vapour probe techniques, combined with conventional soil and plant water vacuum distillation extraction, we monitored the hydrogen and oxygen stable isotopic composition of soil and plant waters at paired sites dominated by grasses and Gambel's oak ( Quercus gambelii ) within a semiarid montane ecosystem over the course of a growing season. We found that sites spaced only 20 m apart had profoundly different soil water isotopic and volumetric conditions. We document patterns of depth- and time-explicit variation in soil water isotopic conditions at these sites and consider mechanisms for the observed heterogeneity. We found that soil water content and isotopic variability were damped under Q. gambelii , perhaps due in part to hydraulic redistribution of deep soil water or groundwater by Q. gambelii in these soils relative to the grass-dominated site. We also found some support for H isotope discrimination effects during water uptake by Q. gambelii . In this ecosystem, the soil water content was higher than that at the neighbouring Grass site, and thus, 25% more water was available for transpiration by Q. gambelii compared with the Grass site. This work highlights the role of plants in governing soil water variation and demonstrates that they can also strongly influence the isotope ratios of soil water. The resulting fine-scale heterogeneity has implications for the use of isotope tracers to study soil hydrology and evaporation and transpiration fluxes to improve understanding of water cycling through the soil–plant–atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Use of neural networks to analyze pulse shape data in low-background detectors

Pacific Northwest National Laboratory has accumulated years of data with ultra-low-background proportional counters collected in an on-site shallow underground laboratory. This large dataset of events is exploited to study the impact of using neural networks for data analysis compared to simple pulse shape discrimination (PSD). The PSD method can introduce false positives for overlapping event distributions; however, a neural network can separate and correctly classify these events. Here, this paper describes the training, testing, and validation of a neutral network, analysis of challenge datasets, and a comparison between the standard PSD approach and a dense, fully-connected neural network.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Emergence of the polydeterminant in QCD

A generalization of the determinant appears in particle physics in effective Lagrangian interaction terms that model the chiral anomaly in quantum chromodynamics (Giacosa et al. in Phys Rev D 97(9):091901, 2018, Phys Rev D 109(7):L071502, 2024), in particular in connection to mesons. This polydeterminant function, known in the mathematical literature as a mixed discriminant, associates N distinct N x N complex matrices into a complex number and reduces to the usual determinant when all matrices are taken as equal. Here, we explore the main properties of the polydeterminant applied to (quantum) fields by using a formalism and a language close to high-energy physics approaches. We discuss its use as a tool to write down novel chiral anomalous Lagrangian terms and present an explicit illustrative model for mesons. Finally, the extension of the polydeterminant as a function of tensors is shown.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

High dimensional binary classification under label shift: phase transition and regularization

Label Shift has been widely believed to be harmful to the generalization performance of machine learning models. Researchers have proposed many approaches to mitigate the impact of the label shift, e.g., balancing the training data. However, these methods often consider the underparametrized regime, where the sample size is much larger than the data dimension. The research under the overparametrized regime is very limited. Here, to bridge this gap, we propose a new asymptotic analysis of the Fisher Linear Discriminant classifier for binary classification with label shift. Specifically, we prove that there exists a phase transition phenomenon: Under certain overparametrized regime, the classifier trained using imbalanced data outperforms the counterpart with reduced balanced data. Moreover, we investigate the impact of regularization to the label shift: The aforementioned phase transition vanishes as the regularization becomes strong.

binary classification↗
DOE OSTI2023

Accurate activity determination of a californium neutron source

Accurately counting analog events requires constructing an electronics chain that produces one count for each input pulse. Here, in this work, we review the use of Nuclear Instrumentation Module electronic units for counting neutron capture events in a 3He tube. We identify two unique types of false trigger events in a leading-edge discriminator and show how a dual timer module can be used to produce a veto window to exclude these events. We use the constructed electronics chain to build an apparatus to measure neutron pulses from a 252 Cf neutron source. We compare the measurements with a Monte Carlo N-Particle (MCNP) model to determine the activity of the neutron source. Furthermore, by making additional measurements with borated polyethylene attenuators between the source and detector, we are able to determine the boron concentration of the polyethylene. This technique provides accurate determination of the source activity to a precision of 2.8% at the k=1 level. The method used is simple, inexpensive, and requires no additional calibrated instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Comparison of four learning-based methods for predicting groundwater redox status

Knowing the location where groundwater denitrification occurs, or by proxy the groundwater redox status (oxic, mixed, and anoxic), is valuable information for assessing and managing potential agricultural land-use impacts on freshwater quality. We compare the efficacy of supervised (Linear Discriminant Analysis LDA; Boosted Regression Trees, BRT; and Random Forest, RF) and unsupervised (Modified Self-Organizing Map, MSOM) learning-based methods to predict groundwater redox status in the agriculturally dominated Tasman, Waikato, and Wellington regions of New Zealand. Thresholds applied to regional groundwater-quality samples provide redox status variables and learn heuristics constrained by these variables and applied to spatial factors (climate, elevation, geologic, hydrology soils, and well depth) identify optimal sets of regional predictor variables. A split-sample approach is used to train and test the learning methods ability to predict redox status using the optimal predictor variables. Overall, the supervised methods demonstrate a prediction bias toward oxic conditions and inability to perform statistically well when using independent regional data; for example, consider kappa statistics for BRT (Tasman: 0.42, Waikato: 0.38, Wellington: 0.17), RF (Tasman: 0.42, Waikato: 0.47, Wellington: 0.17 and LDA (Tasman: 0.46, Waikato: 0.32, Wellington: 0.17). By contrast, the unsupervised method performs statistically well when predicting oxic, mixed, and anoxic conditions and corresponding depths when using independent regional data; for example, consider MSOM kappa statistics for Tasman: 0.78, Waikato: 0.80, Wellington: 0.76. The unsupervised learning method provides the added benefits of being (1) able to combine predictions into 3D regional anoxic probability plots for interpreting the spatial influence of paleosols and groundwater flowpaths on redox status, and (2) readily extended to map 3D redox status across New Zealand and other countries despite data bias and sparsity.

machine learning algorithms, Random Forest, booste↗
DOE OSTI2015

Scintillation properties of solution-grown trans -stilbene single crystals

The scintillation properties of trans-stilbene crystals grown for the first time by application of the solution growth technique to the scale of 10 cm are reported. Measurements of the scintillation light output, pulse shape discrimination, and neutron detection efficiency were made with sets of crystals cut as 50 cm diameter cylinders of different lengths from 0.3 to 10 cm. Comparison to liquid scintillators and traditional melt-grown stilbene showed that at increasing sizes new solution-grown crystals exhibit better scintillation performance that makes them promising for use in large scale neutron detectors. Results are discussed in relation to structural imperfections attributed to different methods of growth.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Neutron detection in a high-gamma field using solution-grown stilbene

We present that a solution-based technique for growing large-volume stilbene scintillators was developed in 2013; crystals up to diameters of 10 cm, or larger, have been grown while preserving excellent pulse shape discrimination (PSD) properties. The goal of this study is to evaluate the PSD capabilities of 5.08 by 5.08-cm stilbene crystals grown by Lawrence Livermore National Laboratory and Inrad Optics when exposed to a 1000 to 1 gamma ray-neutron ratio and operating at a 100-kHz count rate. Results were compared to an equivalent EJ-309 liquid scintillation detector. 252 Cf neutron pulses were recorded in two experiments where 60 Co and 137 Cs sources created the high-gamma field. The high count rate created numerous double pulses that were cleaned using fractional and template approaches designed to remove double pulses while preserving neutron counts. PSD was performed at a threshold of 42 keVee (440-keV proton) for stilbene and 60 keVee (610-keV proton) for EJ-309 liquid. The lower threshold in stilbene resulted in a neutron intrinsic efficiency of approximately 14.5%, 10% higher than EJ-309 liquid, for bare 252 Cf and 13% for 252 Cf in the high-gamma field. Despite the lower threshold, the gamma misclassification rate in stilbene was approximately 3×10 $-$6 , nearly a factor-of-five lower than what we found with the EJ-309 liquid.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Melt-cast organic glasses as high-efficiency fast neutron scintillators

In this work we report a new class of organic-based scintillators that combines several of the desirable attributes of existing crystalline, liquid, and plastic organic scintillators. The prepared materials may be isolated in single crystalline form or melt-cast to produce highly transparent glasses that have been shown to provide high light yields of up to 16,000 photons/MeVee, as evaluated against EJ-200 plastic scintillators and solution-grown trans -stilbene crystals. The prepared organic glasses exhibit neutron/gamma pulse-shape discrimination (PSD) and are compatible with wavelength shifters to reduce optical self-absorption effects that are intrinsic to pure materials such as crystalline organics. In conclusion, the combination of high scintillation efficiency, PSD capabilities, and facile scale-up via melt-casting distinguishes this new class of amorphous materials from existing alternatives.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Measuring the scintillation decay time for different energy deposited by γ-rays and neutrons in a Cs 2 LiYCl 6 :Ce 3+ detector

In nuclear safeguards and homeland security applications, it is greatly beneficial to simultaneously detect γ-rays, thermal neutrons, and fast neutrons using a single detector with reasonable pulse shape discrimination capability, energy resolution comparable with or even better than NaI(Tl) detectors, and high detection efficiency. Cs 2 LiYCl 6 :Ce 3+ detector (CLYC) scintillation detectors have been proven to be one promising candidate to meet these requirements. In this work, the decay time and fraction of each scintillation component for different energy deposition and incident particle type (γ-ray, thermal neutron, and fast neutron) were investigated based on fitting the PMT anode output with exponential functions. For γ-rays, four components were determined with ultrafast decay time of less than one nanosecond and slow time in the order of magnitude of microsecond. It was found that the dependence on the energy deposited by γ-rays of the fraction as well as the decay time of the three slow components was small. However, significant dependence was observed for the ultrafast component. Two or three components were determined for thermal neutrons and fast neutrons without observing a component with fast decay time. To verify the approach used it was first applied to scintillation pulses induced by γ-rays in a NaI(Tl) detector. We found the results were consistent with well-known data already published in the literature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Applications of C 7 LYC scintillators in fast neutron spectroscopy

Here, the capabilities of 7 Li-enriched Cs 2 7 LiYCl 6 (C 7 LYC) scintillation detectors for fast neutron spectroscopy are explored in benchmark experiments that exploit its excellent pulse-shape discrimination between neutrons and γ rays, and its unprecedented ≈10% energy resolution for fast neutrons in the few MeV range, obtained through the 35 Cl(n,p) reaction. Energy- and angle-resolved elastic and inelastic neutron scattering cross-section measurements of 56 Fe(n,n’) were performed at Los Alamos National Laboratory with a pulsed white neutron source and an array of 1" x 1" C 7 LYC crystals. The results convincingly establish the utility of this dual n/γ scintillator for fast neutron spectroscopy. Intrinsic efficiency measurements of both 1" x 1" and the first ever 3" x 3" C 7 LYC crystal have been initiated, using mono-energetic fast neutron beams at UMass Lowell generated via the 7 Li(p,n) reaction. Finally, the spectroscopic capabilities and potential of C 7 LYC are discussed in the context of developing this emerging scintillator for targeted science applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Conceptual design and first results for a neutron detector with interaction localization capabilities

In this study, a new high-precision detector for studying neutrons from beta-delayed neutron emission and direct reaction studies is proposed. The Neutron dEtector with multi-neutron (denoted Xn) Tracking (NEXT) array is designed to maintain high intrinsic neutron detection efficiency while reducing uncertainties in neutron energy measurements. A single NEXT module is composed of thin segments of plastic scintillator, each optically separated, capable of neutron-gamma discrimination. Each segmented module is coupled to position sensitive photodetectors enabling the high-precision determination of neutron time of arrival and interaction position within the active volume. A design study has been conducted based on simulations and experimental tests leading to the construction of prototype units. First results from measurements using a 252 Cf neutron source and accelerator-produced monoenergetic neutrons are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗