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Evaluating the Effects of Detector Modeling Uncertainties on Sterile Neutrino Oscillation Analysis with the ICARUS Detector

he ICARUS T600 LArTPC detector was refurbished after an initial run at the underground LNGS labs and is currently taking data within its experimental hall at Fermilab after full commissioning. Regular data taking began in May 2021 with neutrinos from the Booster Neutrino Beam (BNB) and the Neutrinos at the Main Injector (NuMI) off-axis beam. As the far detector of the Short-Baseline Neutrino (SBN) Program, the ICARUS detector's capability in searching for both muon neutrino disappearance and electron neutrino appearance will allow for unprecedented sensitivity to light sterile neutrinos with eV-scale mass. The ultimate sensitivity of the detector to sterile neutrino oscillations depends on the understanding of the detector response and the uncertainties remaining after calibrating the detector model. This poster will review how detector-model-related uncertainties are quantified, evaluated and their impact on expected sterile neutrino oscillation sensitivities using the existing ICARUS data. The work pursued here is broadly applicable to other ICARUS analysis pathways such as neutrino-argon cross-sections and Beyond the Standard Model physics searches. It will finally discuss improvement pathways to reduce the systematic uncertainties to the level needed for the joint sterile neutrino oscillation analysis with the Short Baseline Near Detector (SBND) within the SBN Program.

43 PARTICLE ACCELERATORS↗

DRiFT - Release 2.1.0: Organic Scintillators and Gas Detectors

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that post-processes output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. The focus of this release is on organic scintillator, gas detector, and associated capabilities, while semiconductor features are still under development. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. DRiFT also has several diagnostic and detector physics features relevant to neutron gas detector simulations including: gas detector wall effects, inactive areas at the end of detector tubes, and effects of a preamplifier. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DRiFT - Release 1.1.1: Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator, gas, and semiconductor features, the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis with the ORIGEN Module of PNAR Spent Fuel Measurements for Nuclear Safeguards Applications

This report documents the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements for 23 boiling water reactor spent fuel assemblies that were performed in Finland under Action Sheet 65, which is an international collaboration on spent fuel safeguards verification methods in the context of the Finnish spent fuel encapsulation/repository system. PNAR measures the passive neutron and gamma emission rates from each of the spent fuel assemblies like a Fork detector, and it also measures the PNAR ratio, which is expected to correlate with the net neutron multiplication of the measured fuel assembly. The analysis was performed with the Oak Ridge Isotope Generation and Depletion (ORIGEN) Data Analysis Module, which was originally developed for predicting Fork detector spent fuel measurement signals in real time and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the International Atomic Energy Agency. The module includes the ORIGEN burnup analysis code and integrates detector response functions pregenerated using the MCNP Monte Carlo transport code to predict the detector signals in several seconds per assembly. In this study, new response functions specific to the analyzed PNAR measurements were generated for the ORIGEN Module. The study also analyzes the impact of using detailed fuel design and operation information vs. standard safeguards information on the results calculated with the ORIGEN Module. Using detailed information reduced the standard deviation of the relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. An uncertainty assessment of the calculations was also performed to estimate the potential impact of the accuracy and the completeness of declaration information on the calculated results for the count rates and net neutron multiplications. The ORIGEN Module predictions for PNAR signals and net neutron multiplication are expected to directly support the safeguards inspectors’ efforts to verify operator declarations of a spent fuel assembly in real time in safeguards practices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Reducing systematic bias in machine learning applications to J/ψ signal extraction in high-energy nuclear physics

Machine learning techniques are increasingly used in high-energy nuclear physics because they can exploit multivariate correlations more efficiently than conventional cut-based analyses. A central challenge is the construction of training samples that faithfully reproduce the detector response observed in data. Signal samples are usually derived from detector simulations; therefore, mismatches between simulation and data can degrade classifier performance and introduce systematic biases. This work presents two practical correction procedures, namely cumulative distribution function (CDF) mapping and a shift-and-scale transformation, to align simulated signal features with those measured in data. Their performance is demonstrated with $J$/$\psi$ yield measurements in $\sqrt{s_{nn}}$ = 200 GeV Ru+Ru and Zr+Zr collisions recorded by STAR. A set of self-consistency tests shows that these procedures substantially suppress the systematic bias associated with data-simulation discrepancies in machine-learning-based signal extraction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The NuMI Flux Prediction at ICARUS

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment seeking to probe fundamental symmetries within the structure of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix, and perform precision measurements its parameters including the neutrino mass ordering via the sign of $\Delta m^2_{31}$, and the charge-parity violating phase, $\delta_{CP}$. To make these measurements with high precision, DUNE will require external $\nu$-Ar scattering cross section data as a crucial input to the oscillation fit. Imaging Cosmic And Rare Underground Signals (ICARUS) is a 476 t liquid argon neutrino detector located at Fermi National Accelerator Laboratory (FNAL) where it is serving as the far detector for the Short-Baseline Neutrino (SBN) program along the Booster Neutrino Beam (BNB) axis. ICARUS additionally lies 795 m downstream and 100.1 mrad off-axis of the Neutrinos at the Main Injector (NuMI) neutrino beam. From this position, ICARUS is exposed to a large flux of NuMI (anti-)electron and (anti-)muon neutrinos, and poses a unique opportunity to provide high-statistics measurements of quasi-elastic and single pion-production cross sections for four neutrino flavors ($\nu_{\mu}$, $\nu_{e}$, $\bar{\nu}_{\mu}$, $\bar{\nu}_{e}$). This dissertation is centered around accurately characterizing the models and estimating their precision for use in making these measurements. This includes identifying major sources of uncertainty in the models such that they can be properly propagated to the cross section measurements. Specifically, this work focused on the model of the NuMI beamline and its impact on the neutrino fluxes, but also delved into the detector response model and its impact on reconstructed observables in the detector. Significant efforts were made to improve the characterization to enhance precision and thus reduce the level of propagated uncertainty. In particular, the NuMI flux was determined to be composed of 57% $\nu_{\mu}$, 38% $\bar{\nu}_{\mu}$, 3% $\nu_{e}$, and 2% $\bar{\nu}_{e}$ while the horns are operating in the positive-particle focusing configuration. The total uncertainty on the $\nu_{\mu} + \bar{\nu}_{\mu}$ ($\nu_{e} + \bar{\nu}_{e}$) flux while operating in the forward horn operating mode was determined to be 10.84% (9.04%). Compared to the on-axis flux, mesons that eventually decay to neutrinos more frequently reinteract within the NuMI structure, resulting in elevated uncertainty as these processes are not well-constrained by existing hadron interaction cross section measurements. Covariance matrices were calculated to propagate the flux uncertainty characterization to NuMI analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A study of events with photoelectric emission in the DarkSide-50 liquid argon Time Projection Chamber

Finding unequivocal evidence of dark matter interactions in a particle detector is a major goal of research in physics. Liquid argon time projection chambers offer a path to probe Weakly Interacting Massive Particles scattering cross sections on nuclei down to the so-called neutrino floor, in a mass range from a few GeV to hundreds of TeV. Based on the successful operation of the DarkSide-50 detector at LNGS, a new and more sensitive experiment, DarkSide-20k, has been designed and is now under construction. A thorough understanding of the DarkSide-50 detector response and, therefore, of all types of events observed in the detector, is essential for the optimal design of the new experiment. In this article, we report on a specific set of events, namely, standard two-pulse scintillation–ionization signals with a third small amplitude pulse, occurring within the 440 μ s data acquisition window of standard events. Some of these events are due to the photoionization of the TPC cathode. We compare our results with those published by collaborations using liquid xenon time projection chambers, which observed a similar phenomenon, and, in particular, with a recent paper by the LUX Collaboration (D.S. Akerib et al. Phys.Rev.D 102, 092004 (2020)) From the measured rate of these events, we estimate for the first time the quantum efficiency of the tetraphenyl butadiene deposited on the DarkSide-50 cathode at wavelengths of around 128 nm, in liquid argon. Also, both experiments observe events likely related to the photoionization of impurities in the liquid. The probability of photoelectron emission per unit length turns out to be an order of magnitude lower in DarkSide-50 than in LUX.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spectra-to-exposure conversion using polynomial response models for gamma-ray field characterization

Accurate measurement of exposure rate from gamma-ray spectral data remains a critical challenge during radiological emergency response operations. Conventional methods rely on pre-defined static conversion factors derived from fixed geometries and isotopic compositions, which often fail to capture real-world environmental variability. This study presents a generalized approach as a "next-step" for converting gamma-ray spectral data into exposure rate using polynomial response models. The method introduces a flexible weighting scheme based on the in-situ detector response to distributed sources, enabling a pathway towards improved correspondence between measured spectra and "ground-truth" exposure rates. Experimental data from sodium iodide NaI(Tl) detectors were used to validate the approach as, at least equivalent to the current count-to-exposure method employed in emergency response CONOPS. Results show that the polynomial weighting model is sufficiently equal to the count-to-exposure method and may help improve accuracy given its adaptability to real-world conditions.

61 RADIATION PROTECTION AND DOSIMETRY↗

The scintillator surface detector of the Pierre Auger observatory

Data collected so far by the Pierre Auger Observatory have enabled major advances in ultra-high energy cosmic ray physics and demonstrated that improved determination of masses of primary cosmic-ray particles, preferably on an event-by-event basis, is necessary for understanding their origin and nature. Improvement in primary mass measurements was the main motivation for the upgrade of the Pierre Auger Observatory, called AugerPrime. As part of this upgrade, scintillator detectors are added to the existing water-Cherenkov surface detector stations. By making use of the differences in detector response to the electromagnetic particles and muons between scintillator and water-Cherenkov detectors, the electromagnetic and muonic components of cosmic-ray air showers can be disentangled. Since the muonic component is sensitive to the primary mass, such combination of detectors provides a powerful way to improve primary mass composition measurements over the original Auger surface detector design. In this paper, the so-called Scintillator Surface Detectors are discussed, including their design characteristics, production process, testing procedure and deployment in the field.

Detector design and construction technologies and ↗

Threat Sources for Creating Synthetic Urban Search Data

Equivalent point source energy emission distributions were computed for various threat sources for use in simulating the detector responses for urban search scenarios. The sources include standard isotopic sources used in detector testing, medical and industrial sources occasionally encountered in urban searches, and several types of special nuclear materials. Most of the equivalent point source distributions represent small sources inside some amount of shielding, but the special nuclear material sources represent volumetrically distributed sources in spheres of metal. Text-based inputs for emission distributions are available for the Monte Carlo transport codes Monte Carlo N-Particle, SCALE/MAVRIC, and Omnibus/Shift, any of which can easily be converted to other formats. These sources were developed for use in the Radiological Anomaly Detection and Identification (RADAI) project and the follow-on project, the RADAI-Extended project, sponsored by the National Nuclear Security Administration Office of Defense Nuclear Nonproliferation Research and Development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Toward Trustworthy Detectors Detector Characterization for SuperCDMS SNOLAB Commissioning

SuperCDMS SNOLAB is a next generation direct detection experiment searching for low mass dark matter using cryogenic germanium and silicon detectors operated at millikelvin temperatures. As commissioning begins, establishing stable, predictable detector response to energy deposits is a prerequisite for future physics analysis. This work studies detector stability and calibration for four SuperCDMS SNOLAB detectors, det 7 and det 15 (germanium) and det 11 and det 14 (silicon), using Barium-133 calibration data (356 keV gamma ray reference) and low background data (ambient radiation, no external source). The Ba-133 data show no distinct line at the expected energy, and the low background data show a baseline that drifts and oscillates rather than remaining flat, consistently across multiple channels, suggesting a shared, detector wide cause. These observations point to the cryogenic support system as the likely source, since small temperature fluctuations could couple into the temperature sensitive detectors, informing the ongoing commissioning effort.

O'Hanlon, Vika [Skidmore Coll.]↗

Energy resolution of the LZ detector for high-energy electronic recoils

The LUX-ZEPLIN (LZ) detector is a dual-phase liquid xenon time projection chamber (TPC) installed at the Sanford Underground Research Facility (Lead, South Dakota) at a depth of 1478 meters. Although the main objective of LZ is the direct detection of dark matter, its low background environment allows for the search of other rare processes, such as the neutrinoless double beta decay of xenon isotopes 134 Xe and 136 Xe with the respective Q-values of 826 keV and 2458 keV. The sensitivity of the detector to these decays is directly determined by the energy resolution, which, in turn, is degraded by non-uniformities in detector response. In this work, we present a novel method to correct, in the data, the non-uniformity of the light collected by an array of photosensors in a scintillation detector. This method is based on the knowledge of the light response functions of individual photosensors. With these techniques, we report, at a very early phase of the detector operations, a state-of-the-art energy resolution (σ/μ) of (0.67 ± 0.01)% at 2614 keV for the fiducial volume of 5.6 tonnes of liquid xenon.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Charge response and energy calibration of ProtoDUNE-

ProtoDUNE-SP is a test bed liquid argon time projection chamber (LArTPC) for the far detector of the Deep Underground Neutrino Experiment (DUNE). This LArTPC was calibrated using cosmic-ray cathode-crossing muons, electric field maps, and purity-monitor data to correct for nonuniformities in the detector response and cosmic-ray stopping muons to perform the absolute energy scale calibration for further physics analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A comprehensive final summary of the MCNP calculations performed concerning the UW 137 Cs release event

This document combines and supersedes earlier reports (e.g. LA-UR-19-32358 and LA-UR-20- 22216) that discussed MCNP-calculated conversion factors (count rate per unit activity per unit area) for collimated 2”x2” NaI detectors (Ludlum model 44-10 and Thermo model SPA3) in contact with various surfaces of interest to the University of Washington 137 Cs release event. These surfaces include: Exterior surface of round and rectangular ducts, Exterior surface of outdoor brick work, Exterior surface of cast iron pipes, Exterior surface of an O 2 filter assembly For each surface, the calculated conversion factors allowed inferences on 137 Cs activity on interior surfaces based on exterior contact measurements of the 662 keV photopeak count rate. The MCNP calculations included the effect of attached collimators (i.e. either a Pb/Sb-based Ludlum or a W-based “Rees” model) on detector response. As a consequence, the conversion factors only apply to the appropriate collimated 2”x2” NaI detector operated in pulse height analysis (PHA) mode. Other assumptions affecting the calculations and valid application of the conversion factors will be outlined below.

54 ENVIRONMENTAL SCIENCES↗

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗

DRiFT Current Mode, Trigger Settings and Flexible Detector Specifications Applied to Scintillator Arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Constraining the impact of chlorine as a neutron absorber in next-gen fast reactor designs

The role of chlorine as a neutron poison and as a seed for producing radioactive waste in nuclear systems has driven a renewed interest to improve its nuclear data uncertainties. Additionally, basic and applied science programs that use CLYC (Cs 2 LiYCl 6 :Ce) detectors for neutron spectroscopy and monitoring are also very sensitive to any change in chlorine nuclear data for simulations of the detector response. In this work, sensitivities relevant for these different applications are addressed through simulations of the efficiency of CLYC detectors in a fast fission spectrum when applying new chlorine nuclear data as input. These simulations are validated by an experimental measurement using CLYC detectors coupled to an ionization chamber loaded with a 252 Cf spontaneous fission source. The results are then used to obtain the first reliable direct measurement of the 35 Cl(n,p 0 ) and summed Cl(n,p+n,α) fission spectrum average cross sections, found to be 54.7(32) and 105.0(98) mb, respectively. The results are within uncertainty of calculated fission spectrum averaged cross sections based on recently re-evaluated chlorine nuclear data, which confirm recent impact studies performed for the Molten Chloride Reactor Experiment. Meanwhile, there currently exists only one published criticality benchmark experiment that is sufficiently sensitive to chlorine nuclear data. Discrepancies are found with this set of criticality safety benchmarks, which are more sensitive to thermal and epithermal neutron energies than the energies, above 100 keV, tested in this current work. Hence, there is still a need to re-evaluate the chlorine nuclear data at lower energies to assess these discrepancies. Interpretation of the data from future “faster” criticality benchmarks, which are needed for next-gen fast reactor designs, benefit from the improved constraints on the chlorine nuclear data validated in this work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutrino Beam Monitoring

Accelerator facilities produce neutrino beams from meson decays in a decay volume. Experiments measure event rates that depend on flux, cross sections, and detector response, so the flux is predicted using hadron production and beamline modeling and constrained by beam instrumentation, since near detectors alone cannot separate flux from cross section. Proton, hadron, and muon monitors can track the parent particle distributions and beam conditions, providing the inputs needed for flux predictions in long-baseline experiments such as NOvA, T2K, and DUNE. This talk reviews how beam monitors are used in practice to understand neutrino flux. Proton beam monitors tell where the beam hits the target and how stable it is. Farther downstream, hadron and muon monitors sample particles produced in meson decays. Because those muons come from the same parents as the neutrinos, their profiles reveal focusing, alignment shifts, and other changes in the beam, and they are routinely used to detect problems and guide flux predictions. The muon information can be used more quantitatively; for example, to infer the parent meson phase space, and fast radiation-hard timing detectors can add sensitivity to the momentum dependence of the focusing. These developments show both how tightly beam measurements can constrain the flux and where the current limits still lie. These approaches complement monitored-beam concepts, in which the decay region is instrumented to detect charged leptons from meson decays and to measure the neutrino flux directly.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗