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Correcting the PFNS for more consistent fission modeling

For FY20, we had a deliverable to write a report detailing efforts to simultaneously evaluate both the prompt neutron multiplicity, $\overline{ν}$, and the prompt neutron fission neutron spectrum, PFNS, using CGMF. CGMF is the LANL-developed fission fragment decay code that consistently evaporates prompt neutrons and γ rays using the Hauser-Feshbach statistical theory of compound reactions. The decay begins by constructing the initial conditions of the fission fragments, then decaying each one from the excited state by neutrons and γ rays, conserving energy, momentum, spin, and parity in each step of the emission. The initial conditions of the fragments, along with the multiplicity, energy, and direction of each emitted neutron or γ ray, are recorded, allowing for the full reconstruction of the fission event. These event histories allow us to reconstruct average quantities, as well as correlations between observables, that can be compared with experimental or evaluated data. In that initial report, although there was already a favorable comparison between $\overline{ν}$ from CGMF, experiment, and the current ENDF/B-VIII.0 evaluation, we showed that there was still significant work to be done to improve the PFNS from CGMF. Historically, the PFNS is calculated too soft by Hauser-Feshbach fission models, and CGMF is no exception. The incorrect shape presents a significant challenge in fission modeling, including for our understanding of the fission process and for our ability to consistently calculate and predict a variety of prompt fission observables (such as fission fragment initial conditions, neutron and γ-ray multiplicities and energies, and the correlations between all observables). In our companion report, we detail our success in using CGMF to evaluate $\overline{ν}$. Although not included in the optimization explicitly, we also keep the initial conditions of the fission fragments physical, along with reproducing reasonably well the neutron multiplicity distribution. As we would expect from the sensitivities calculations from, the average neutron energies change very little from the $\overline{ν}$ optimization along with the PFNS (as will be shown in Sec. 2.6). The conclusion was that the global and statistical models would have to be investigated instead of just the fission fragment initial conditions (as is sufficient for $\overline{ν}$). This report details those efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗

Particle flow reconstruction for the CMS Phase-II Level-1 Trigger

The upgrade of the CMS detector for the high-luminosity LHC will include trackfinding for the first time in the Level-1 trigger, enabling Particle Flow reconstruction of every event in addition to comprehensive pileup mitigation. The Correlator trigger will reconstruct isolated leptons and photons, hadronic jets, and energy sums, assisted in many cases by machine learning to benefit from the complete particle-level event record. Here, we present the logic of these algorithms, possible implementations using large FPGAs and their demonstration in prototype hardware, in addition to the expected physics performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Physics potential of the IceCube Upgrade for atmospheric neutrino oscillations

The IceCube Upgrade is an extension of the existing IceCube Neutrino Observatory and will be deployed in the 2025–2026 austral summer. It will significantly improve the sensitivity of the detector to atmospheric neutrino oscillations. The existing 86-string IceCube array contains a dense in-fill known as DeepCore which is optimized to measure neutrinos with energies down to a few GeV. The IceCube Upgrade will consist of seven new densely instrumented strings placed within the DeepCore volume to further enhance the performance in the GeV energy range. The additional strings will feature new optical modules, each containing multiple photomultiplier tubes (PMTs), in contrast to the existing modules that each contain a single PMT. This will more than triple the number of PMT channels with respect to the current IceCube configuration, allowing for improved detection efficiency and reconstruction performance at GeV energies. We describe necessary updates to simulation, event selection, and reconstruction to accommodate the higher data rates observed by the upgraded detector and the addition of multi-PMT modules. We determine the expected sensitivity of the IceCube Upgrade to the atmospheric neutrino oscillation parameters sin 2 ⁡𝜃 23 and Δ⁢𝑚$^{2}_{32}$, the appearance of tau neutrinos and the neutrino mass ordering. The IceCube Upgrade will provide neutrino oscillation measurements that are of similar precision to those from accelerator experiments, while providing complementarity by probing higher energies and longer baselines, and with different sources of systematic uncertainties.

artificial neural networks↗

Rocks, resolution, and the record at the terrestrial K/T boundary, eastern Montana and western North Dakota

Reconstructions of mass extinction events are based upon faunal patterns, reconstructed from numerical and diversity data ultimately derived from rocks. It follows that geological complexity must not be subsumed in the desire to establish patterns. This is exemplified at the Terrestrial Cretaceous-Tertiary (K/T) boundary in eastern Montana and western North Dakota, where there are represented all of the major indicators of the terrestrial K/T transition: dinosaurian and non-dinosaurian vertebrate faunas, pollen, a megaflora, iridium, and shocked quartz. It is the patterns of these indicators that shape ideas about the terrestrial K/T transition. In eastern Montana and western North Dakota, the K/T transition is represented lithostratigraphically by the Cretaceous Hell Creek Formation, and the Tertiary Tullock Formation. Both of these are the result of aggrading, meandering, fluvial systems, a fact that has important consequences for interpretations of fossils they contain. Direct consequences of the fluvial depositional environments are: facies are lenticular, interfingering, and laterally discontinuous; the occurrence of fossils in the Hell Creek and Tullock formations is facies-dependent; and the K/T sequence in eastern Montana and western North Dakota is incomplete, as indicated by repetitive erosional contacts and soil successions. The significance for faunal patterns of lenticular facies, facies-dependent preservation, and incompleteness is discussed. A project attempting to reconstruct vertebrate evolution in a reproducible manner in Hell Creek-type sediments must be based upon a reliable scale of correlations, given the lenticular nature of the deposits, and a recognition of the fact that disparate facies are not comparable in terms of either numbers of preserved vertebrates or depositional rates.

Fastovsky, D. E.↗

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

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

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

Neutron-antineutron oscillation search with MicroBooNE and DUNE

The Deep Underground Neutrino Experiment (DUNE) is an international project aiming at neutrino physics and astrophysics and a search for phenomena predicted by theories beyond the standard model (BSM). The excellent imaging capability of Liquid Argon Time Projection Chamber (LArTPC) technology, particle tracking and identification utilized in the Far Detector, as well as the Far Detector size and underground placement, allow the experiment to achieve high sensitivity to various rare processes. BSM theories predict the existence of baryon number non-conservation effects, in particular when the baryon number changes by 2. Here we discuss the sensitivity of DUNE to neutron-antineutron oscillation. With full event simulation and reconstruction using the LArSoft package, we have investigated the background to potential signal events from atmospheric neutrino interactions and particle misidentification, and utilized machine learning techniques to enhance the discrimination between signal and background. The methodologies being developed for a high-sensitivity search for neutron-antineutron oscillation in DUNE can also be demonstrated with the currently running MicroBooNE LArTPC. We discuss progress on demonstrating the developed techniques with the first-ever search for neutron-antineutron oscillation in a LArTPC using MicroBooNE data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High performance FPGA embedded system for machine learning based tracking and trigger in sPhenix and EIC

We present a comprehensive end-to-end pipeline to classify triggers versus background events in this paper. This pipeline makes online decisions to select signal data and enables the intelligent trigger system for efficient data collection in the Data Acquisition System (DAQ) of the upcoming sPHENIX and future EIC (Electron-Ion Collider) experiments. Starting from the coordinates of pixel hits that are lightened by passing particles in the detector, the pipeline applies three-stage of event processing (hits clustering, track reconstruction, and trigger detection) and labels all processed events with the binary tag of trigger versus background events. The pipeline consists of deterministic algorithms such as clustering pixels to reduce event size, tracking reconstruction to predict candidate edges, and advanced graph neural network-based models for recognizing the entire jet pattern. In particular, we apply the message-passing graph neural network to predict links between hits and reconstruct tracks and a hierarchical pooling algorithm (DiffPool) to make the graph-level trigger detection. We obtain an impressive performance (≥70% accuracy) for trigger detection with only 3200 neuron weights in the end-to-end pipeline. We deploy the end-to-end pipeline into a field-programmable gate array (FPGA) and accelerate the three stages with speedup factors of 1152, 280, and 21, respectively.

Instruments & Instrumentation↗

Solar neutrino measurements using the full data period of Super-Kamiokande-IV

An analysis of solar neutrino data from the fourth phase of Super-Kamiokande (SK-IV) from October 2008 to May 2018 is performed and the results are presented. The observation time of the dataset of SK-IV corresponds to 2970 days and the total live time for all four phases is 5805 days. For more precise solar neutrino measurements, several improvements are applied in this analysis: lowering the data acquisition threshold in May 2015, further reduction of the spallation background using neutron clustering events, precise energy reconstruction considering the time variation of the PMT gain. The observed number of solar neutrino events in 3.49–19.49 MeV electron kinetic energy region during SK-IV is 65,443 − 388 + 390 ( stat . ) ± 925 ( syst . ) events. Corresponding B 8 solar neutrino flux is ( 2.314 ± 0.014 ( stat . ) ± 0.040 ( syst . ) ) × 10 6 cm − 2 s − 1 , assuming a pure electron-neutrino flavor component without neutrino oscillations. The flux combined with all SK phases up to SK-IV is ( 2.336 ± 0.011 ( stat . ) ± 0.043 ( syst . ) ) × 10 6 cm − 2 s − 1 . Based on the neutrino oscillation analysis from all solar experiments, including the SK 5805 days dataset, the best-fit neutrino oscillation parameters are sin 2 θ 12 , solar = 0.306 ± 0.013 and Δ m 21 , solar 2 = ( 6.1 0 − 0.81 + 0.95 ) × 10 − 5 eV 2 , with a deviation of about 1.5 σ from the Δ m 21 2 parameter obtained by KamLAND. The best-fit neutrino oscillation parameters obtained from all solar experiments and KamLAND are sin 2 θ 12 , global = 0.307 ± 0.012 and Δ m 21 , global 2 = ( 7.5 0 − 0.18 + 0.19 ) × 10 − 5 eV 2 . Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

MLPF: efficient machine-learned particle-flow reconstruction using graph neural networks

In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the detector resolution for jets and the missing transverse momentum. In view of the planned high-luminosity upgrade of the CERN Large Hadron Collider (LHC), it is necessary to revisit existing reconstruction algorithms and ensure that both the physics and computational performance are sufficient in an environment with many simultaneous proton–proton interactions (pileup). Machine learning may offer a prospect for computationally efficient event reconstruction that is well-suited to heterogeneous computing platforms, while significantly improving the reconstruction quality over rule-based algorithms for granular detectors. We introduce MLPF, a novel, end-to-end trainable, machine-learned particle-flow algorithm based on parallelizable, computationally efficient, and scalable graph neural network optimized using a multi-task objective on simulated events. We report the physics and computational performance of the MLPF algorithm on a Monte Carlo dataset of top quark–antiquark pairs produced in proton–proton collisions in conditions similar to those expected for the high-luminosity LHC. The MLPF algorithm improves the physics response with respect to a rule-based benchmark algorithm and demonstrates computationally scalable particle-flow reconstruction in a high-pileup environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields

Compressive sensing is a mathematical technique for simultaneous data acquisition and compression. In this work, we show a CS based architecture for acquiring and reconstructing transient stellar events. This architecture recon-structs a differenced image itself, eliminating the need for any sparse domain transforms, otherwise required for traditional CS reconstruction. The resulting reconstructed differenced image is of critical importance as the information required for generating a time-series photometric light curve is obtained only from a differenced image. Hence, reconstructing a crowded star spatial image, followed by differencing is wasteful. This architecture eliminates the need to 1.) transform an image to a sparse domain, 2.) Reconstruct a dense field, and then apply differencing on the image to obtain the image of critical value. We study the case of microlensing to depict a star source experiencing magnification in time. Our results show that this architecture is able to reconstruct star source magnitudes with magnification factors greater than 1 for clean images with error less than 2% using only 10% of the Nyquist rate samples.

Compressive Sensing, Data acquisition, Image diffe↗

Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields

Compressive sensing is a mathematical technique for simultaneous data acquisition and compression. In this work, we show a CS based architecture for acquiring and reconstructing transient stellar events. This architecture recon-structs a differenced image itself, eliminating the need for any sparse domain transforms, otherwise required for traditional CS reconstruction. The resulting reconstructed differenced image is of critical importance as the information required for generating a time-series photometric light curve is obtained only from a differenced image. Hence, reconstructing a crowded star spatial image, followed by differencing is wasteful. This architecture eliminates the need to 1.) transform an image to a sparse domain, 2.) Reconstruct a dense field, and then apply differencing on the image to obtain the image of critical value. We study the case of microlensing to depict a star source experiencing magnification in time. Our results show that this architecture is able to reconstruct star source magnitudes with magnification factors greater than 1 for clean images with error less than 2% using only 10% of the Nyquist rate samples.

Asmita Korde-patel↗

Improving neutrino oscillation measurements through event classification

Precise neutrino energy reconstruction is essential for next-generation long-baseline oscillation experiments, yet current methods remain limited by large uncertainties in neutrino-nucleus interaction modeling. Even so, it is well established that different interaction channels produce systematically varying amounts of missing energy and therefore yield different reconstruction performance–information that standard calorimetric approaches do not exploit. We introduce a strategy that incorporates this structure by classifying events according to their underlying interaction type prior to energy reconstruction. Using supervised machine-learning techniques trained on labeled generator events, we leverage intrinsic kinematic differences among quasielastic scattering, meson-exchange current, resonance production, and deep-inelastic scattering processes. A cross-generator testing framework demonstrates that this classification approach is robust to microphysics mismodeling and, when applied to a simulated DUNE 𝜈 𝜇 disappearance analysis, yields improved accuracy and sensitivity at the 10%–20% level. These results highlight a practical path toward reducing reconstruction-driven systematics in future oscillation measurements.

Ellis, Sebastian A. R. [King's College, London (Un↗

Improving MicroBooNE's Inclusive Single-Photon Search with Low-Energy Hadronic Identification

This analysis aims to further investigate MicroBooNE’s inclusive single-photon search results, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons using roughly half of MicroBooNE's dataset. Taken together with MiniBooNE’s long-standing low-energy excess and MicroBooNE’s recent electron-like search results showing no observable excess with respect to Standard Model predictions, this result provides strong impetus for expanded exploration of the single-photon channel in Fermilab’s short-baseline liquid-argon time projection chamber (LArTPC) experiments. By identifying and classifying isolated MeV-scale energy depositions, or blips, in the vicinity of single-photon events selected by the Wire-Cell reconstruction framework, we establish a more comprehensive labeling scheme for nearby hadronic content. In particular, blips found backwards along the shower axis indicate the presence of previously-unidentified final-state protons, while elevated blip counts at wide angles signal the presence of final-state neutrons. By applying this new technique to its full dataset, MicroBooNE will perform a purer and higher-statistics test of the truly isolated nature of its modest photon-like excess, furthering its hunt for the presence of unexpected new physics beyond the Standard Model.

Andrade Aldana, Diego [Los Alamos; IIT, Chicago (m↗

Study of Unboosted Higgs Pair Production with HH to bbWW Decay with the CMS experiment at the LHC

Measurement of the Higgs boson self-interaction through the production of Higgs boson (H) pairs is critical for understanding the shape of the Higgs potential and the stability of the universe. Higgs pair production (HH) where one H decays to b quarks (H to bb) and the other to hadronically decaying W bosons (H to WW*→qqqq) has a large branching fraction with the cost of high background from jets produced through quantum chromodynamics (QCD). While previous all-hadronic HH→bbWW analyses focused on the few percent of highly energetic HH events with collimated decay products, this first study of its kind targets the more challenging 95$\%$ of HH to bbWW* in which decay products can be reconstructed as separate jets providing sensitivity to a complementary region of phase space. This poster focuses on generator level measurements of the fractions of HH to bbWW* signal events are fully or partially reconstructed and what fraction are impacted by contamination from high momentum jets from initial or final state radiation. Partially reconstructed events are further classified according to whether the H to bb, H to WW*, or W to qq are fully reconstructed

Gillespie, Emma [U. Louisville]↗

The May 17, 2012 Solar Event: Back-Tracing Analysis and Flux Reconstruction with PAMELA

The PAMELA space experiment is providing first direct observations of Solar Energetic Particles (SEPs) with energies from about 80 MeV to several GeV in near-Earth orbit, bridging the low energy measurements by other spacecrafts and the Ground Level Enhancement (GLE) data by the worldwide network of neutron monitors. Its unique observational capabilities include the possibility of measuring the flux angular distribution and thus investigating possible anisotropies associated to SEP events. The analysis is supported by an accurate back-tracing simulation based on a realistic description of the Earth's magnetosphere, which is exploited to estimate the SEP energy spectra as a function of the asymptotic direction of arrival with respect to the Interplanetary Magnetic Field (IMF). In this work we report the results for the May 17, 2012 event.

Bruno, A.↗

Search for HH → bbτ⁺τ⁻ Using Run 3 Scouting Data Analyze b-tagging and tau-tagging Performance with Unified Particle Transformer

B-tagging and tau-tagging performances play an important role in the search for the rare event HH → bbτ⁺τ⁻. A transformer-based neural network, Unified Particle Transformer, is applied for both tagging tasks, and Run 3 proton–proton collision scouting data at center-of-mass energy of 13.6 TeV is used. The scouting data stream accepts events at a much higher rate compared to traditional triggers, but stores only the objects reconstructed in the trigger, no low-level detector information. Therefore, existing taggers trained for the offline event reconstruction cannot be used. Analysis of the SoftMax plots, ROC/AUC curves, confusion matrix, accuracy and losses are used to evaluate model performance. Specifically, the tagging efficiency of the signal and misidentification probability across multiple background processes are compared for varying working points. Different training samples with distinct distributions of jet flavors are utilized and related model performances are analyzed. Interpretability methods, such as Integrated Gradients, may further be applied to study the input features’ influence on the model’s decisions, providing insights into potential improvements.

Chen, Blair [Purdue U., West Lafayette; Fermilab]↗

Test of lepton flavor universality with measurements of 𝑅⁡(𝐷 + ) and 𝑅⁡(𝐷* + ) using semileptonic 𝐵 tagging at the Belle II experiment

We report measurements of the ratios of branching fractions ℛ⁡(𝐷 (*)+ ) = ℬ⁡($\bar{𝐵}$ 0 → 𝐷 (*)+ ⁢𝜏 −⁢ $\bar{𝜈}$ 𝜏 )/ℬ⁡($\bar{𝐵}$ 0 → 𝐷 (*)+ ⁢ℓ − $\bar{𝜈}$ ℓ ), where ℓ denotes either an electron or a muon. These ratios test the universality of the charged-current weak interaction. The results are based on a 365 fb −1 data sample collected with the Belle II detector at the SuperKEKB 𝑒 + ⁢𝑒 − collider, which operates at a center-of-mass energy corresponding to the ϒ⁡(4⁢𝑆) resonance, just above the threshold for $𝐵\bar{𝐵}$ production. Signal candidates are reconstructed by selecting events in which the companion 𝐵 meson from the ϒ⁡(4⁢𝑆) → $𝐵\bar{𝐵}$ decay is identified in semileptonic modes. The 𝜏 lepton is reconstructed via its leptonic decays. We obtain ℛ⁡(𝐷 + ) = 0.418$^{+0.075}_{−0.073}$⁢(stat)$^{+0.049}_{−0.056}$⁢(syst) and ℛ⁡(𝐷 *+ ) = 0.306$^{+0.035}_{−0.033}$⁢(stat)$^{+0.016}_{−0.018⁢}$(syst), which are consistent with world average values. Accounting for the correlation between them, these values differ from the Standard Model expectation by a collective significance of 1.7 standard deviations.

bottom quark↗