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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enhancing Neutrino Event Simulation through Overlays at the ICARUS Experiment on the Short-Baseline Neutrino Program

In the pursuit of precise neutrino event simulation, the ICARUS experiment within the Short-Baseline Neutrino (SBN) program at Fermilab uses an overlay technique to closely align simulations with experimental data. This technique consists of taking signals from data from each of the each of the three subsystems (TPC, PMT, CRT) and overlaying a simulated neutrino interaction onto the event. The overlay procedure includes superimposing simulated waveforms from neutrino interactions from both Time Projection Chambers (TPC) and Photomultiplier Tubes (PMTs) onto their respective data counterparts. Furthermore, the Cosmic Ray Tagger (CRT) hits from both data and simulations are combined to form the overlay event. By combining signals in this manner, we can obtain a data-driven modeling of cosmic backgrounds as well as the detector response enabling a more precise handling of noise sources when using neutrino simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1985

High energy neutrino astronomy with MACRO

A large area underground detector with accurate muon tracking and directionality can be used for the search of extraterrestrial sources of high energy neutrinos. The sensitivity of the MACRO detector to possible sources of neutrinos was evaluated with a Monte-Carlo simulation of the neutrino interaction in the rock and and of the detection in the real apparatus. Two categories of possible neutrino sources are discussed in comparison with the detector sensitivity. Promising candidate objects for this search appear to be the two binary X-ray sources in the southern key Vela X1 and LMC X4, which are known to emit gamma rays up to the 10,000 TeV region.

Auriemma, G.↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗
DOE OSTI2020

Dynamic focusing of laser driven positron jets by self-generated fields

Abstract Focusing effect of laser-driven positron jets by self-generated target sheath fields has been observed for the first time experimentally and the results are supported by the computational studies. In the experiment, OMEGA EP short-pulse (0.7 ps, 500 J) irradiates mm-size gold targets with a concave back surface and reference flat-surface targets. Both targets exhibited positrons with quasi-monoenergetic energy peaks while targets with concave curvature also showed increased number of positrons at the detector. The data is consistent with hybrid-PIC simulations confirming that the time-varying electric fields driven by electrons escaping from the target significantly change the trajectories of positrons. These simulations show a small radius of curvature on the rear side increases the relative focusing effect and the positrons to electrons ratio in the escaping plasma. For the smallest radius of curvature, positron jets that are up to 10 times denser can be achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Neutrino-nucleus cross section impacts on neutrino oscillation measurements

The challenges in neutrino-nucleus cross section modeling and its impact on neutrino oscillation experiments are widely recognized. However, a comprehensive and theoretically robust estimation of cross section uncertainties has been lacking, and few studies have quantitatively examined their impact on oscillation measurements. In this work, we evaluate the effect of cross section uncertainties on oscillation parameters using setups inspired by NOvA and DUNE. To characterize these uncertainties, we adopt multiple neutrino-nucleus event generators and simulate a realistic experimental procedure that incorporates near-detector data and near-to-far-detector extrapolation. Our results confirm that cross section uncertainties cannot significantly bias oscillation results in current statistics-dominated experiments like NOvA. However, they could lead to substantial bias for future systematics-dominated experiments like DUNE, even when near-detector data are employed to mitigate uncertainties. These findings underscore the need for further studies on the quantitative impacts of cross section modeling, improved strategies to utilize near-detector data and the PRISM concept, and more robust cross section models to optimize the success of future experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

New opportunities for rare charm from $Z\rightarrow c\bar{c}$ decays

We analyze the potential of rare charm decays as probes of new physics at a high-luminosity flavor facility operating at the Z pole, such as the FCC-ee or CEPC. In particular, we identify clean null-test observables in $D^0 → π^+ π^- v\bar{v}$ and in polarized $Λ^+_c → p ℓ^+ ℓ^-$ decays with $ℓ = e, μ$. Complementarity with the LHC and HL-LHC flavor programs arises from the characteristic features of a Tera-Z environment: the capability to study missing-energy modes and charm production with significant polarization. We improve the theoretical description of $D^0 → π^+ π^- v\bar{v}$ decays and work out the phenomenology of polarization-induced null-test observables in $Λ^+_c → p ℓ^+ ℓ^-$ decays. In regions of dilepton mass near the φ resonance, polarization asymmetries can reach $O$(5%) for muons and $O$(14%) for electrons times the $Λ^+_c$ polarization. We also point out synergies between the dineutrino and the dilepton modes using the SMEFT framework of heavy new physics. Using the IDEA detector concept at FCC-ee, we find in simulation studies that dineutrino branching fractions as low as ~ 2 x 10 -7 can be probed, which reaches well into the parameter space of new physics, and also allows for discrimination of lepton flavor structures. Furthermore, the measurement of asymmetries in $Λ^+_c → p ℓ^+ ℓ^-$ at $O$(1%) will be possible. Similar sensitivities are expected for dielectron final states, although robust predictions will require further dedicated studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Time Shifted Transport Tallies

When modeling experiments on platforms such as the National Ignition Facility (NIF), several different calculations are strung together to calculate the final diagnostic response of the detectors on the machine. For example, a highly detailed simulation may be performed of capsule implosion on NIF, where one of the key diagnostics is the history of the thermal radiation emission from the capsule. This simulation domain can be a few centimeters in size. The NIF target chamber is much larger, so a second calculation can be done to transport the energy from the capsule out to the diagnostics. Typically, the results from the first calculation are used as a point source in the second, since all the fine detail is not needed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measuring Light Yield with Isolated Protons in MicroBooNE

Liquid Argon Time Projection Chambers (LArTPCs) are precision detectors used extensively in neutrino physics. The MicroBooNE experiment at Fermilab is one of the experiments employing this technique and has collected 5 years of data from 2015-2021. The primary signal in LArTPCs is ionisation, but argon also emits large quantities of scintillation light, which can be used for calorimetry, timing and background rejection. Prompt scintillation light in MicroBooNE is recorded with an array of 32 PhotoMultiplier Tubes (PMTs). To enable the full use of scintillation light in the experiment, it is important to characterize the efficiency of light collection in the detector, i.e. the light yield. We present a new method of measuring the light yield using isolated proton interactions, which enables a position-dependent light yield measurement to map the response of the detector across its volume. This method can be used to calibrate the light response in large-scale LArTPC detectors as well as to test assumptions used in simulating scintillation light.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurement of Triple-Differential Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report the first measurement of the differential cross section $d^2σ(E_ν)/dcos(θ_µ)dP_µ$for inclusive muon neutrino charged-current scattering on argon. This measurement utilizes data from6.5×10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located on-axis in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. In this note, the mapping from reconstructed kinematics to truth quantities, particularly from reconstructed to true neutrino energy, is validated by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after conditional constraint from the muon momentum distribution in data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled within its uncertainties in simulation, enabling the unfolding to an energy-dependent triple-differential measurement over muon momentum, muon scattering angle, and neutrino energy. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future LArTPC experiments measuring neutrino oscillations. Comparisons with model predictions show the best agreement with Neut 5.4.0.1 at low energy, and with NuWro 19.02.01 at higher energies, particularly at forward muon scattering angles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

First Observation of Neutrino Candidates in ProtoDUNE

The Neutrino Platform at CERN hosts two massive prototypes for the DUNE Far Detector to test the technology for the coming Horizontal Drift and Vertical Drift designs, almost perfectly on axis with the direction of the SPS beamline pointed towards the North Area. The 400 GeV/c SPS protons impacting on the T2 target area may produce exotic particles that could travel ~700 meters to the detectors, in addition to a substantial flux of neutrinos. Simulations of the neutrino flux demonstrate that thousands of neutrino interactions are expected per week in the active volume of NP04 spanning energies from a few GeV up to 180 GeV, constituting the main background for such search. The first step towards establishing a BSM physics program at the Neutrino Platform is therefore to observe neutrinos originating from the SPS beam. A sample of high-energy neutrino events in a DUNE FD-like LArTPC may also be of broader use to the DUNE collaboration. For example, by testing the performance of reconstruction algorithms on highly-energetic neutrino interactions with large hadronic showers. An initial neutrino search was performed by developing filters to remove cosmic events. After filtering, the remaining events were eye-scanned to identify neutrino candidates amongst the residual cosmic background. Over two of the available NP04 runs, 29 neutrino candidates were identified. A separate run taken with the SPS beam off yielded no neutrino candidates. An analysis is now under development that will use all available data, large Monte Carlo samples and full event reconstruction, with the aim of confirming whether NP04 is capable of observing feebly interacting particles originating from the SPS beam.

Pullia, Dario [CERN]↗
DOE OSTI2026

Track Matching in the DUNE Near Detectors

The Deep Underground Neutrino Experiment (DUNE) is an international particle physics experiment looking answer some of the largest unanswered questions in neutrino physics. DUNE uses a high power neutrino beam produced at Fermi National Accelerator Laboratory (Fermilab), and consists of a near detector (ND) also located at Fermilab and a far detector (FD) 1300 km away at the Sanford Underground Research Facility (SURF) in South Dakota. In the first phase of the experiment, the ND complex will contain a modular liquid argon TPC (ND-LAr) and a solid scintillator-based muon spectrometer (TMS), in addition to a beam monitoring detector (SAND) and systems for moving ND-LAr and TMS away from the neutrino beam axis (PRISM). A prototype of ND-LAr, the 2x2 demonstrator, alongside a solid scintillator muon tagger provided by repurposed MINERvA planes, has been built and taken data at Fermilab. For analyses with the ND, connecting particle tracks (such as muons) that exit the liquid argon active volume into the solid scintillator muon detector can improve particle identification and energy reconstruction, and alleviate pileup due to the intense beam. To match tracks between detectors during reconstruction, we have explored using Graph Neural Networks (GNNs) to connect tracks segments between the liquid argon detector region and the solid scintillator detector planes. We have trained a GNN on reconstructed simulated data from the 2×2 demonstrator and repurposed MINERvA planes. We will evaluate its performance and then train a similar network on reconstructed ND-LAr and TMS simulations.

Xing, Daniel [U. Colorado, Boulder]↗
DOE OSTI2021

Neural Network Approaches for Mobile Spectroscopic Gamma-Ray Source Detection

Artificial neural networks (ANNs) for performing spectroscopic gamma-ray source identification have been previously introduced, primarily for applications in controlled laboratory settings. To understand the utility of these methods in scenarios and environments more relevant to nuclear safety and security, this work examines the use of ANNs for mobile detection, which involves highly variable gamma-ray background, low signal-to-noise ratio measurements, and low false alarm rates. Simulated data from a 2” × 4” × 16” NaI(Tl) detector are used in this work for demonstrating these concepts, and the minimum detectable activity (MDA) is used as a performance metric in assessing model performance.In addition to examining simultaneous detection and identification, binary spectral anomaly detection using autoencoders is introduced in this work, and benchmarked using detection methods based on Non-negative Matrix Factorization (NMF) and Principal Component Analysis (PCA). On average, the autoencoder provides a 12% and 23% improvement over NMF- and PCA-based detection methods, respectively. Additionally, source identification using ANNs is extended to leverage temporal dynamics by means of recurrent neural networks, and these time-dependent models outperform their time-independent counterparts by 17% for the analysis examined here. The paper concludes with a discussion on tradeoffs between the ANN-based approaches and the benchmark methods examined here.

Bilton, Kyle J. (ORCID:0000000184553689)↗
DOE OSTI2026

Pulsed-Neutron Experiments at the Inherently Safe Subcritical Assembly

The pulsed neutron technique is a powerful, dynamic method to assay the reactivity of a multiplying system. This work presents the novel application of the pulsed neutron technique to the Inherently Safe Subcritical Assembly, an experimental configuration accepted by the International Criticality Safety Benchmark Evaluation Project Handbook. The experiments were replicated with COG11.3, a continuous-energy Monte Carlo code. The pulsed neutron data were analyzed using the Sjöstrand and Gozani area-ratio methods and by extracting the prompt neutron decay constant. Subsequent static k-eigenvalue and 𝛼-eigenvalue simulations were also performed for the same configurations. Neutron detector dead-time effects from the experiments were corrected using the Backwards Extrapolation Method and shown to have a negligible impact on the estimated reactivities. The results highlight that capturing time-dependent effects like delayed neutron precursor buildup are essential to accurately reproduce experimental results. They also highlight the importance of shielding the detectors from generator source neutrons in deeply subcritical configurations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2017

Lessons Learned from Radiative Transfer Simulations of the Venus Atmosphere

The Venus atmosphere is extremely complex, and because of this the spectrum of Earths sister planet is likewise intricate and a challenge to model accurately. However, accurate modeling of Venus spectrum opens up multiple opportunities to better understand the planet next door, and even for understanding Venus-like planets beyond our solar system. Near-infrared (1-2.5 um, NIR) spectral windows observable on the Venus nigthside present the opportunity to probe beneath the Venusian cloud deck and measure thermal emission from the surface and lower atmosphere remotely from Earth or from orbit. These nigthside spectral windows were discovered by Allen and Crawford (1984) and have since been used measure trace gas abundances in the Venus lower atmosphere (less than 45 km), map surface emissivity varisions, and measure properties of the lower cloud deck. These windows sample radiation from below the cloud base at roughly 45 km, and pressures in this region range from roughly Earthlike (approx. 1 bar) up to 90 bars at the surface. Temperatures in this region are high: they range from about 400 K at the base of the cloud deck up to about 740 K at the surface. This high temperature and pressure presents several challenges to modelers attempting radiative transfer simulations of this region of the atmosphere, which we will review. Venus is also important to spectrally model to predict the remote observables of Venus-like exoplanets in anticipation of data from future observatories. Venus-like planets are likely one of the most common types of terrestrial planets and so simulations of them are valuable for planning observatory and detector properties of future telescopes being designed, as well as predicting the types of observations required to characterize them.

Arney, G.↗
DOE OSTI2025

Searches for New Physics With Muon Conversion at Fermilab and Triboson Production at the LHC

We report on several efforts to search for physics beyond the standard model of particle physics at broad energy scales. The Mu2e experiment at Fermilab will search for charged lepton flavor violation via the muon to electron conversion process, which is suppressed in the Standard Model. Mu2e will be operated at a low energy, yet can probe New Physics at very high mass scales (O(1e3 - 1e4 ) TeV). At high energies, the CMS experiment at the CERN LHC continues to deliver an impressive suite of Standard Model measurements and limits on a variety of New Physics signatures. Mu2e is under construction and slated to collect its first physics data in the coming years. This thesis describes work done during the construction phase of Mu2e and focuses on two critical areas: magnetic field modeling and statistical analysis. We describe a novel method for field modeling which we validate using a simulated dataset representing the expected magnetic field in the Detector Solenoid. This method blends a standard least-squares fitting technique that utilizes physically motivated analytical model functions with a novel physics informed network that is constructed to obey Maxwell’s equations. We show the technique can model the field with an accuracy of 10−7 despite the presence of injected noise in the pseudo-measurements at the 10−5 level. We then present preliminary results of the calibration of 3D Hall probes at the sub-10−4 level. These probes will be used to directly measure the Mu2e Detector Solenoid magnetic field on a sparse grid; these measurements serve as the input to the field model fitting. Finally, we describe the first implementation of both an unbinned shape analysis and a Bayesian interpretation applied to Mu2e pseudo-data. Up to 20% tighter limits can be set by the shape analysis compared to a standard cut & count analysis. The AlCap experiment collected data at PSI in 2015 to measure several important quantities related to nuclear muon capture on an aluminum target, which is a significant background process for Mu2e. The neutron emission from muon capture can introduce background hits in the Mu2e detectors and can increase radiation damage in various elements of the apparatus. We present measurements of the neutron group fluence and mean neutron multiplicity for muon capture on aluminum nuclei. Finally, we discuss an analysis of triboson production at CMS using an Effective Field Theory framework. Standard Model triboson production, which was first observed at CMS in 2020, has a relatively small cross section and provides direct access to both anomalous triple gauge couplings and quartic gauge couplings. These couplings, interpreted in the Standard Model Effective Field Theory, are studied in the present work. We target the boosted regime where the background rate is low and yields are enhanced when dimension-6 and dimension-8 Wilson coefficients are non-zero. We do not observe an excess in the data and therefore set bounds on the Wilson coefficients. For dimension-6 coefficients the tightest observed (expected) bounds are set on cW /Λ2 where Λ is the mass scale of new physics; the bounds are [−0.13, 0.12] TeV−2 ([−0.12, 0.12] TeV−2 ) at 95% CL. The tightest bounds in dimension-8 are set on fT,0 / Λ4 ; the observed (expected) bounds at 95% CL are [−0.63, 0.69] TeV−4 ([−0.54, 0.62] TeV−4 ). Additional results are presented which include scenarios where multiple Wilson coefficients are non-zero, the application of signal model clipping to address unitarity violation in Effective Field Theories, and a novel template fit developed for easier reinterpretation of our results.

Kampa, Cole Erik [Northwestern U. (main)] (ORCID:0↗
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 OSTI2022

Deeply learning deep inelastic scattering kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q 2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗