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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ASCENT: a balloon-borne hard x-ray imaging spectroscopy telescope using transition edge sensor microcalorimeter detectors

Core collapse supernovae are thought to be one of the main sources in the galaxy of elements heavier than iron. Understanding the origin of the elements is thus tightly linked to our understanding of the explosion mechanism of supernovae and supernova nucleosynthesis. X-ray and gamma-ray observations of young supernova remnants, combined with improved theoretical modeling, have resulted in enormous improvements in our knowledge of these events. Here, the isotope Ti44 is one of the most sensitive probes of the innermost regions of the core collapse engine, and its spatial and velocity distribution are key observables. Hard x-ray imaging spectroscopy with the Nuclear Spectroscopic Telescope Array (NuSTAR) has provided new insights into the structure of the supernova remnant Cassiopeia A (Cas A), establishing the convective nature of the supernova engine. However, many questions about the details of this engine remain. We present here the concept for a balloon-borne follow-up mission called A SuperConducting ENergetic x-ray Telescope (ASCENT). ASCENT uses transition edge sensor gamma-ray microcalorimeter detectors with a demonstrated 55-eV full-width half maximum energy resolution at 97 keV. This 8- to 16-fold improvement in energy resolution over NuSTAR will allow for high-resolution imaging and spectroscopy of the Ti44 emission. This will allow for a detailed reconstruction of gamma-ray line redshifts, widths, and shapes, allowing us to address questions such as, What is the source of the neutron star kicks? What is the dominant production pathway for Ti44? Is the engine of Cas A unique?

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

East Antarctic Ice Sheet variability in the central Transantarctic Mountains since the mid Miocene

The response of the East Antarctic Ice Sheet to warmer-than-present climate conditions has direct implications for projections of future sea level, ocean circulation, and global radiative forcing. Nonetheless, it remains uncertain whether the ice sheet is likely to undergo net loss due to amplified melting coupled with dynamic instabilities or whether such losses will be balanced, or even offset, by enhanced accumulation under a higher-precipitation regime. The glacial depositional record from the central Transantarctic Mountains (TAM) provides a robust geologic means to reconstruct the past behaviour of the East Antarctic Ice Sheet, including during periods thought to have been warmer than today, such as the mid-Pliocene Warm Period (~3.3–3.0 Ma). This study describes a new surface-exposure-dated moraine record from Otway Massif in the central TAM spanning the last ~9 Myr and synthesises these data in the context of previously published moraine chronologies constrained with cosmogenic nuclides. The resulting record, although fragmentary, represents the majority of direct and unambiguous terrestrial evidence for the existence and size of the East Antarctic Ice Sheet during the last 14 Myr, and it thus provides new insight into the long-term relationship between the ice sheet and global climate. At face value, the existing TAM moraine record does not exhibit a clear signature of the mid-Pliocene Warm Period, thus precluding a definitive verdict on the East Antarctic Ice Sheet's response to this event. In contrast, an apparent hiatus in moraine deposition both at Otway Massif and the neighbouring Roberts Massif suggests that the ice sheet surface in the central TAM was potentially lower than present during the late Miocene and earliest Pliocene.

58 GEOSCIENCES↗
DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Ocean circulation and climate variability in the northern South China Sea during the Greek Minimum derived from coral Δ 14 C and Sr/Ca records

Ocean circulation transports heat, salt and nutrients, and has profound impacts on the marine environment and climate change. However, the seasonal to centennial variations of the paleocirculation of the South China Sea (SCS) and their driving forces are still unclear due to limited records. Here we reconstructed a high-resolution Δ 14 C record of a coral from Sanya to investigate the seasonal variations of the SCS ocean circulation around 2300 cal yr BP during a grand solar minimum (GSM) period. The seasonal Δ 14 C variability shows the influence of coastal upwelling caused by the East Asian Summer Monsoon (EASM) in summer and the effect of water intrusion from the western Pacific Ocean driven by the Kuroshio Intrusion (KI) in winter. Here we compiled the marine radiocarbon reservoir correction (ΔR) records since 2500 cal yr BP, which indicate a gradual decrease of upwelling significantly correlated with the EASM. Comparisons with other climate records suggest that both the EASM and KI may regulate the ocean circulation variability on centennial time scales. As a good index of the sea surface temperature (SST), our Sr/Ca record and spectral analysis results show a low temperature and a low frequency of El Niño-Southern Oscillation (ENSO) events around 2300 cal yr BP. Moreover, the composite coral Sr/Ca-SST and ENSO index records since 2500 cal yr BP show relatively low SST and weak ENSO during GSMs, supporting the modulation of tropical SST and ENSO by solar activity. Our study has provided high-resolution proxy data and revealed the driving forces of ocean circulation and climate change in the SCS at multiple time scales, which should be considered in further modeling work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Combining In-situ Diagnostics and Data Analytics for Discovery of Process-Structure-Property Relationships in AM parts – A Step Toward Digital Twins

In-situ additive manufacturing (AM) diagnostic tools (e.g., optical/infrared imaging, acoustic, etc.) already exist to correlate process anomalies to printed part defects. This current work aimed to augment existing capabilities by: 1) Incorporating in-situ imaging w/ machine learning (ML) image processing software (ORNL- developed "Peregrine") for AM process anomaly detection 2) Synchronizing multiple in-situ sensors for simultaneous analysis of AM build events 3) Correlating in-situ AM process data, generated part defects and part mechanical properties The key R&D question investigated was to determine if these new combined hardware/software tools could be used to successfully quantify defect distributions for parts build via SNL laser powder bed fusion (LPBF) machines, aiming to better understand data-driven process-structure-property- performance relationships. High resolution optical cameras and acoustic microphones were successfully integrated in two LPBF machines and linked to the Peregrine ML software. The software was successfully calibrated on both machines and used to image hundreds of layers of multiple builds to train the ML software in identifying printed part vs powder. The software's validation accuracy to identify this aspect increased from 56% to 98.8% over three builds. Lighting conditions inside the chamber were found to significantly impact ML algorithm predictions from in-situ sensors, so these were tailored to each machine's internal framework. Finally, 3D part reconstructions were successfully generated for a build from the compressed stack of layer-wise images. Resolution differences nearest and furthest from the optical camera were discussed. Future work aims to improve optical resolution, increase process anomalies identified, and integrate more sensor modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SYMBA: An end-to-end VLBI synthetic data generation pipeline

Realistic synthetic observations of theoretical source models are essential for our understanding of real observational data. In using synthetic data, one can verify the extent to which source parameters can be recovered and evaluate how various data corruption effects can be calibrated. These studies are the most important when proposing observations of new sources, in the characterization of the capabilities of new or upgraded instruments, and when verifying model-based theoretical predictions in a direct comparison with observational data. We present the SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations. SYMBA takes into account several realistic atmospheric, instrumental, and calibration effects. Here, we used SYMBA to create synthetic observations for the Event Horizon Telescope (EHT), a millimetre VLBI array, which has recently captured the first image of a black hole shadow. After testing SYMBA with simple source and corruption models, we study the importance of including all corruption and calibration effects, compared to the addition of thermal noise only. Using synthetic data based on two example general relativistic magnetohydrodynamics (GRMHD) model images of M 87, we performed case studies to assess the image quality that can be obtained with the current and future EHT array for different weather conditions. Our synthetic observations show that the effects of atmospheric and instrumental corruptions on the measured visibilities are significant. Despite these effects, we demonstrate how the overall structure of our GRMHD source models can be recovered robustly with the EHT2017 array after performing calibration steps, which include fringe fitting, a priori amplitude and network calibration, and self-calibration. With the planned addition of new stations to the EHT array in the coming years, images could be reconstructed with higher angular resolution and dynamic range. In our case study, these improvements allowed for a distinction between a thermal and a non-thermal GRMHD model based on salient features in reconstructed images.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Measurement of the Higgs boson production in association with top quarks in multilepton final states in pp collisions at s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair with the Higgs boson (tt¯H$$ t\overline{t}H $$) in multilepton final states is presented. The analysis is based on a data sample of proton-proton collisions at s=13$$ \sqrt{s}=13 $$ TeV recorded with the ATLAS detector at the CERN Large Hadron Collider and corresponding to an integrated luminosity of 140 fb−1. Six final states defined by the number and flavour of reconstructed charged leptons are combined in a simultaneous likelihood fit to extract the tt¯H$$ t\overline{t}H $$ signal and constrain the most relevant backgrounds. The measured tt¯H$$ t\overline{t}H $$ cross-section normalised to Standard Model (SM) prediction is σtt¯H/σSM=0.63−0.19+0.20$$ {\sigma}_{t\overline{t}H}/{\sigma}^{\mathrm{SM}}=0.{63}_{-0.19}^{+0.20} $$. This result corresponds to an observed (expected) significance of 3.3σ (5.3σ). Additionally, two other fits are used to measure the tt¯H$$ t\overline{t}H $$ cross-section differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, and to extract the associated production cross-section of a single top-quark with the Higgs boson (tH) together with the tt¯H$$ t\overline{t}H $$ one. The CP structure of the top quark-Higgs boson Yukawa coupling is probed through an analysis of tt¯H$$ t\overline{t}H $$ and tH events. The results are compatible with the SM hypothesis, and values of the mixing angle between CP-even and CP-odd top-Higgs Yukawa couplings of |α| > 62° are excluded at 68% confidence level.

Aad, G↗
DOE OSTI2025

Spatiotemporal forecasting of the edge localized modes in tokamak plasmas using neural networks

Artificial intelligence techniques have been increasingly adopted by the plasma and fusion science to address problems like plasma reconstruction, surrogate modeling, and tokamak/stellarator optimization. A key focus in sustained fusion research is the prediction and mitigation of edge-localized-modes (ELMs), instabilities that occur in short, periodic bursts and can cause erosion to the tokamak vessel wall. Recent research has demonstrated the power of neural networks in approximating continuous functions. In this work, we build spatiotemporal forecasting models that can predict the onset of ELMs and their evolution at early stages. We leverage recent advances in generative modeling, sequence-to-sequence modeling, and Fourier neural operators to propose architectures and training strategies that can learn to forecast short to long term dynamics of the noisy signals due to ELMs. We benchmark the developed model against a state-of-the-art foundation model using the beam emission spectroscopy (BES) data that captures the plasma fluctuations due to ELMs over a 8 x 8 spatial grid. Our models demonstrate high accuracy, outperforming the baselines, in predicting the evolution of BES signals during ELM events. Furthermore, the developed models exhibit high accuracy in predicting the rapid rise and relaxation of the signals due to ELMs within 30–80 µs.

edge localized modes↗
DOE OSTI2023

Generative adversarial networks for scintillation signal simulation in EXO-200

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network — a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. Furthermore, the network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

New techniques for jet calibration with the ATLAS detector

A determination of the jet energy scale is presented using proton–proton collision data with a centre-of-mass energy of $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 140 fb -1 collected using the ATLAS detector at the LHC. Jets are reconstructed using the ATLAS particle-flow method that combines charged-particle tracks and topo-clusters formed from energy deposits in the calorimeter cells. The anti-k t jet algorithm with radius parameter R = 0.4 is used to define the jet. Novel jet energy scale calibration strategies developed for the LHC Run 2 are reported that lay the foundation for the jet calibration in Run 3. Jets are calibrated with a series of simulation-based corrections, including state-of-the-art techniques in jet calibration such as machine learning methods and novel in situ calibrations to achieve better performance than the baseline calibration derived using up to 81 fb -1 of Run 2 data. The performance of these new techniques is then examined in the in situ measurements by exploiting the transverse momentum balance between a jet and a reference object. The b -quark jet energy scale using particle flow jets is measured for the first time with around 1% precision using $\gamma$+jet events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Neutron Cross Section Measurement In The Protodune-SP Experiment

Understanding the detector response to neutrons will be critical for performing neutrino oscillation analyses in the next-generation Deep Underground Neutrino Experiment (DUNE). The DUNE physics program is centered around measuring the neutrino flavor composition as a function of their energy both at the near and the far detector. Neutrinos in the DUNE beam will have energies ranging between 100~MeV and 10~GeV, which is significant, because individual neutrino energies will not be known beforehand and will have to be reconstructed. Neutrino interactions in DUNE will produce leptons and hadrons -- including protons, pions, and neutrons. Neutrons can transport energy away from their origin and sometimes go undetected. In addition to the primary neutrons produced by the neutrino, subsequent interactions of the charged hadrons can result in secondary neutrons. Neutrons are a source of missing energy and will bias the neutrino energy measurement. Currently, there is also a 20\% energy scale uncertainty and a 40\% uncertainty on the energy resolution for neutrons in DUNE, which must be addressed. ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton prototype for the DUNE far detector and was designed to both validate the technology that will be employed in DUNE and to measure cross sections for the charged hadrons (pions, protons, and kaons) at the relevant energies for DUNE. The ProtoDUNE-SP experiment, therefore, is in a unique position to characterize the secondary neutron component for DUNE. This is achieved by searching for candidate neutron interactions in ProtoDUNE-SP events and using these to facilitate a measurement of the neutron inelastic cross section as well as an estimate of the neutron energy and number. The cross section measurement presented here is based on neutrons produced in 1~GeV, $\pi^+$ events captured in 2018 by ProtoDUNE-SP in accordance with the production and cross section models in the GEANT4 simulation toolkit, version 4.1 0.6p1. T he best-fit neutron inelastic cross section, in the kinetic energy range of 114 to 314~MeV, is $1.24_{-0.08}^{+0.10}$~(stat.~$\oplus$~syst.)~barns.

Rivera, David Orlando↗
DOE OSTI2022

Nanoscale trace-element zoning in pyrite framboids and implications for paleoproxy applications

Pyrite framboids (spherical masses of nanoscale pyrite) are among the earliest textures of pyrite to form in sediments. It has been proposed that their trace-element (TE) contents can be used to track the TE composition of the water column in which they formed. However, it is not clear how these TEs are associated with the framboidal pyrite grains. For instance, it is important to know whether they are incorporated uniformly or are enriched in different regions of the framboid. Here, we used high-resolution scanning transmission electron microscopy to identify chemical zoning within pyrite framboids. We found that initial, nanoscale pyrite euhedral crystals, which make up the volumetric majority of the framboids, are covered/infilled by later pyrite that templates on the earlier pyrite. Further, this later pyrite is enriched in TEs, suggesting that many TEs are incorporated in pyrite relatively late (during early diagenesis; not in the water column). This observation suggests that although chemical analyses of pyrite framboids may provide ocean-water chemistry trends through time, the details are complex. Specifically, the TEs found in pyrite may be linked to adsorption onto organic matter, detrital material, and authigenic minerals such as Fe- and Mn-oxide phases followed by desorption in the sediments or release via dissolution and incorporation into pyrite as overgrowths on the initial nanoscale euhedral crystals that make up framboids. While the use of pyrite chemistry to understand past ocean conditions remains promising, and even diagenetic additions may not preclude the utility of pyrite for reconstructing ancient ocean conditions, care must be taken in interpretations because the end concentration may be influenced by diagenesis.

58 GEOSCIENCES↗
DOE OSTI2023

Λ Baryon Production in ν¯µ Interactions in the MicroBooNE Detector

The Cabibbo suppressed production of $\Lambda$ baryons in anti-neutrino interactions with nuclei is a rare process that is yet to be measured with a modern neutrino detector with automated reconstruction. The cross section for this process is sensitive to a number of unique nuclear effects, most notably the secondary interactions of the produced hyperon while attempting to escape from the nucleus. Other interactions within the nuclear remnant can impact the estimation of neutrino energy in oscillation measurements, and thus an accurate description of the nuclear environment is required. The strangeness violating hyperon production process is only available to anti-neutrinos. The model of this interaction is implemented into the NuWro neutrino interaction Monte Carlo simulation, and some predictions are presented, focusing on the role of nuclear effects. This model introduces a hyperon-nucleus potential, which calculations from hypernuclear theory permit to be strongly repulsive in th e case of $\Sigma$ baryons. The presence of this potential is found to sculpt the shape of the differential cross section in some variables. The MicroBooNE detector will be described, followed by a description of a measurement of the flux averaged, restricted phase space cross section of Cabibbo suppressed $\Lambda$ baryon production. A sophisticated event selection is employed, as a very large quantity of background neutrino interactions must be removed to perform the measurement with any sensitivity. This selection introduces some novel techniques such as the island finding method, and achieves a background reduction of $\sim 10^6$, with an efficiency of around 7\%. The calculation of the systematic uncertainties will be explained, including two procedures explored to handle sources of background with extremely poor simulation statistics: an in-situ constraint using data from sidebands, and a visual inspection of the data and simulation to remove the troublesome background events. The sensitivity to the $\Lambda$ baryon production cross section is calculated in the form of Bayesian posterior probability distributions, combining the systematic uncertainties with data and simulation statistical uncertainties. As a rare process, the statistical uncertainties are highly non-Gaussian, and the Bayesian approach is applied to include the full shapes of these uncertainties. Data corresponding to $2.2 \times 10^{20}$ protons on target of neutrino mode running and $4.9 \times 10^{20}$ protons on target of anti-neutrino running is analysed. When the data was unblinded, five $\Lambda$ production candidates were selected from the data, consistent with the MC simulation prediction of $5.3 \pm 1.1$ events. The final estimated cross section is $1.8^{+2.0}_{-1.6} \times 10^{-40}$cm$^2/$Ar when employing the sideband constraint procedure. A similar result of $2.0^{+2.2}_{-1.8} \times 10^{-40}$cm$^2/$Ar is obtained when performing the visual scan instead. The methods used in t his analysis are intended to be easily exported to other LArTPC detectors such as the Short Baseline Near Detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Towards a neutron multiplicity measurement with the Accelerator Neutrino Neutron Interaction Experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26 ton Gadolinium (Gd)-loaded water Cherenkov detector located on the Booster Neutrino Beam line at Fermilab. Its main goals are the measurement of the neutron multiplicity in neutrino-nucleus interactions as well as the cross-section of Charged Current Quasi-Elastic (CCQE) neutrino interactions on water. Besides the physics goals, the experiment also aims to be a testbed for new technologies such as Large Area Picosecond Photodetectors (LAPPDs) and Water-based Liquid Scintillators (WbLS). This thesis presents a preliminary measurement of the neutron multiplicity with {ANNIE}, using an analysis conducted on a fraction of the 2021 beam year. As preparatory measures, the efficiency of ANNIE's Front Muon Veto (FMV) was determined to be {$\bar{\varepsilon}_{\mathrm{FMV}} = (95.6 \pm 1.6)\%$} while the average efficiency for active scintillator paddles in the Muon Range Detector (MRD) was found to be {$\bar{\varepsilon}_ {\mathrm{MRD}} = (92.1 \pm 7.9)\%$}. Furthermore, the simulation framework used for ANNIE was validated and adapted to reproduce the experimental data by comparing the detector response for samples of Michel electrons, Americium Beryllium neutrons, and through-going muons. The analysis finds average neutron yields of {$\bar{n}_{\mathrm{data}} (\mathrm{beam}) = (0.272 \pm 0.010_{\mathrm{stat}})$} for an inclusive set of all identified muon neutrino candidates and {$\bar{n}_{\mathrm{data}} (\mathrm{beam,FV}) = (0.287 \pm 0.044_{\mathrm{stat}})$ for interactions which happened inside of the Fiducial Volume of ANNIE, which was optimized to increase the neutron detection acceptance. The presented neutron multiplicity values represent the number of detected neutrons after all event selection cuts and are not yet corrected for the neutron detection efficiency. An equivalent analysis on a simulated beam sample predicts neutron yields of $\bar{n}_{\mathrm{MC}}(\mathrm{beam}) = (0.515 \pm 0.0 07_{\mathrm{stat}})$ and $\bar{n}_{\mathrm{MC}}(\mathrm{beam,FV}) = (0.627 \pm 0.031_{\mathrm{stat}})$, indicating that the models tend to overpredict the number of neutrons produced in such interactions. Systematic errors have been briefly considered to contribute {$\sigma_{\mathrm{sys,FMV}} \sim 0.01\,$neutrons/$\nu$-interaction} due to the slight FMV inefficiency and {$\sigma_{\mathrm{sys,n}} \sim 0.05\,$neutrons/$\nu$-interaction} due to the neutron detection efficiency. Simulation studies further highlighted the importance of neutron detection in Diffuse Supernova Background (DSNB) searches. A combination of neutron tagging and Convolutional Neural Networks was found to reduce the most relevant Neutral Current Quasi-Elastic (NCQE) interaction background below the signal level, achieving a Signal-to-Background ratio of 4:1. In a further study, we investigated the positive impact of a deployment of a WbLS target on the energy reconstruction in ANNIE. WbLS provides a scintillation signal from hadronic recoils in addition to the charged lepton that can be included in neutrino energy reconstruction. It was found that a deployed WbLS volume in ANNIE improves the neutrino energy reconstruction from 14\% to 12\%, with the potential of going beyond this if more sophisticated reconstruction algorithms are developed in the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Cosmic-ray anisotropies in right ascension measured by the Pierre Auger Observatory

We present measurements of the large-scale cosmic-ray anisotropies in right ascension, using data collected by the surface detector array of the Pierre Auger Observatory over more than 14 years. We determine the equatorial dipole component, $\vec{d}_\perp$, through a Fourier analysis in right ascension that includes weights for each event so as to account for the main detector-induced systematic effects. For the energies at which the trigger efficiency of the array is small, the ``East-West'' method is employed. Besides using the data from the array with detectors separated by 1500 m, we also include data from the smaller but denser sub-array of detectors with 750 m separation, which allows us to extend the analysis down to $\sim 0.03$ EeV. The most significant equatorial dipole amplitude obtained is that in the cumulative bin above 8~EeV, $d_\perp=6.0^{+1.0}_{-0.9}$%, which is inconsistent with isotropy at the 6$\sigma$ level. In the bins below 8 EeV, we obtain 99% CL upper-bounds on $d_\perp$ at the level of 1 to 3 percent. At energies below 1 EeV, even though the amplitudes are not significant, the phases determined in most of the bins are not far from the right ascension of the Galactic center, at $\alpha_{\rm GC}=-94^\circ$, suggesting a predominantly Galactic origin for anisotropies at these energies. The reconstructed dipole phases in the energy bins above 4 EeV point instead to right ascensions that are almost opposite to the Galactic center one, indicative of an extragalactic cosmic ray origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Search for heavy resonances and quantum black holes in eμ, eτ, and μτ final states in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search is reported for heavy resonances and quantum black holes decaying into eμ, eτ, and μτ final states in proton-proton collision data recorded by the CMS experiment at the CERN LHC during 2016–2018 at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb -1 . The eμ, eτ, and μτ invariant mass spectra are reconstructed, and no evidence is found for physics beyond the standard model. Upper limits are set at 95% confidence level on the product of the cross section and branching fraction for lepton flavor violating signals. Three benchmark signals are studied: resonant τ sneutrino production in R parity violating supersymmetric models, heavy Z' gauge bosons with lepton flavor violating decays, and nonresonant quantum black hole production in models with extra spatial dimensions. Resonant τ sneutrinos are excluded for masses up to 4.2TeV in the eμ channel, 3.7TeV in the eτ channel, and 3.6TeV in the μτ channel. A Z' boson with lepton flavor violating couplings is excluded up to a mass of 5.0TeV in the eμ channel, up to 4.3Te V in the eτ channel, and up to 4.1TeV in the μτ channel. Quantum black holes in the benchmark model are excluded up to the threshold mass of 5.6TeV in the eμ channel, 5.2TeV in the eτ channel, and 5.0TeV in the μτ channel. In addition, model-independent limits are extracted to allow comparisons with other models for the same final states and similar event selection requirements. The results of these searches provide the most stringent limits available from collider experiments for heavy particles that undergo lepton flavor violating decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A pion-argon cross section measurement in the ProtoDUNE-SP experiment with cosmogenic muon

Neutrinos are tiny mysterious fundamental particles with small cross sections. Through neutrino physics, scientists across the world are trying to answer many intriguing questions about nature such as the dominance of matter over antimatter, CP violation in the lepton sector, number of supernovas in the early universe, etc. Detection of neutrinos requires massive particle detectors and intense neutrino beam owing to their small cross section. Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that is planned to start taking data beginning in 2026. DUNE will consist of 4 massive detectors, the first of which will be using single-phase liquid argon time projection chamber (LArTPC) technology. The ProtoDUNE-SP experiment is a prototype of the DUNE built at the CERN neutrino platform and uses the same detector technology that will be used in DUNE first module. The ProtoDUNE-SP experiment collected months of test beam and cosmic ray data beginning in September 2018. It was built to provide a testbed for the installation of detector parts for DUNE, showing long-term stability of the detector, understanding detector response for different test beam particles (including protons, pions, electrons, kaons, muons), and measurement of hadron-argon cross sections. When a particle passes through LArTPC electron-ion pairs are produced. To reconstruct the position and energy of a particle passing through the medium knowledge of ionization electron drift velocity is essential. The electron drift velocity is distorted by an excess positive charge built up in the detector, known as space charge. This study discusses a novel technique for measuring the ionization electron drift velocity using cosmic-ray muons. The technique uses tracks that travel the entire drift distance of the TPC for drift velocity determination. Secondly, the study discusses a method for converting the charge deposited into energy. The method is carried out in two step s. In th e first step detector response for energetic cosmic ray muons crossing the entire the TPC is used to make the charge deposition uniform throughout the TPC, and in the second step stopping cosmic-ray muons are used for determining the energy scale. Finally, the study discusses a pion-argon cross section measurement based on reweighting of Monte Carlo simulations using J. Calcutt's Geant4Reweight framework. Neutrinos cannot be directly detected; they are identified based on the interaction products. Pions are a common interaction product in a neutrino interaction. For precise modeling of neutrino event generators, it is essential to understand the pion-argon interaction. Pion-argon cross section measurement serves as an important input for neutrino interaction models. The results of the pion-argon total reaction cross section using the Geant4 reweighting technique are found to be in good agreement with Geant4 predictions. The many studies carried out in the ProtoDUNE-SP experi ment wil l be useful for current and future neutrino experiments using LArTPC technology including ICARUS, MicroBooNE, DUNE

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗