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At least 127 records · Page 7

Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. This effort is pursuing the co-design development of high-performance readout smart pixel ASICs for a future Phase III High Luminosity upgrade of the Large Hadron Collider. A 1.6mm2 ASIC prototype was designed by Fermilab in CMOS 28 nm bulk process and submitted for manufacturing in February 2024. It leverages the analog front-end pixel design of a previous prototype fabricated and tested in 2023, which achieved a simulated detection level of ~400e- with 30fF input capacitance. The ROIC consists of two matrices of 16×16 smart pixels, each 25×25 μm2 in size. Each smart pixel contains a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. There is digital space for the integration of our fully combinatorial AI that performs momentum classification at the bunch crossing rate. The total power consumption is ∼6μW per pixel, which corresponds to ~1mW/cm2. The ASIC incorporates programmable front-end charge injection circuitry to generate pixel cluster charges during characterization. The cluster profile will be generated to duplicate hit characteristics of various momentum (pT). We will present early results from chip testing.

Parpillon, Benjamin

Beyond Classical Searches: Enabling New Discovery Potential at the LHC (Final Technical Report)

The major goals of this project are: • 1. Employ Machine Learning to solve combinatorial problems in searches for new physics phenomena, with a focus on multijet signatures. • 2. Enable high-precision tracking for CMS at the HL-LHC by carrying out the Outer Tracker project for the Phase-II detector upgrade. Compared to the original proposal, the scope is reduced due to reduced resources in final award. In particular, the program of long-lived particle searches was descoped at that time due to lack of resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Research in Neutrino Physics (Final Technical Report)

The goal of the experimental neutrino efforts at Louisiana State University is to measure the properties of neutrinos and to improve our understanding of neutrino interactions. In pursuit of this goal, the group will continue its Intensity Frontier work on the DUNE experiment at Fermilab and the T2K experiment at J-PARC, Japan. The current work is focused on understanding how neutrinos change flavor and on the possibility for asymmetry between neutrinos and anti-neutrinos. The effort on T2K includes physics measurements using the collected T2K data and preparation for the second phase T2K-II data with an increased beam power and the newly upgraded ND280 detector, featuring a novel 3D fine grained scintillation tracker with 4π acceptance and 3D readout. T2K is in a position to improve our understanding of neutrino nucleus interactions which continue to be one of the largest systematic uncertainties for neutrino oscillation measurements. On DUNE, the effort is on analyzing the data collected by the ProtoDUNE-SP prototype at CERN and on the design, installation, and commissioning of ProtoDUNE-II and later the DUNE Far Detector cold electronics. The final DUNE Module-1 components will be fully characterized by ProtoDUNE-II and the collected data will be used to improve and tune simulation and reconstruction algorithms, and to measure hadron scattering cross section, used to improve the modeling of neutrino final state interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Stress Testing the Standard Model of Particle Physics at the Large Hadron Collider

Final technical report for the DOE grant "Stress Testing the Standard Model of Particle Physics at the Large Hadron Collider", awarded to Prof. Aram Apyan at Brandeis University. The work focused on the ATLAS experiment at LHC. During the award period the group worked on ATLAS physics analyses, all-silicon Inner Tracker (ITk) detector upgrade, and reconstruction and calibration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Search for the Muon EDM at Muon $g-2$

After 6 years of taking data, the Muon $g-2$ Experiment measured the anomalous magnetic moment of the muon $a_μ$ to a final precision of 127 ppb. In parallel to this analysis, it is possible to perform a measurement of the muon electric dipole moment (EDM) using the straw tracker detectors. In the Standard Model (SM) EDMs are predicted to be vanishingly small. A non-zero muon EDM would constitute physics beyond the SM (BSM) and be a source of charge-parity violation. The current limit on the muon EDM was set at the predecessor experiment at Brookhaven National Laboratory, giving $|d_\mu|<1.8\times10^{-19}\ e\cdot$cm Fermilab aims to improve this by an order of magnitude, which will help to constrain BSM theories. This poster will cover the importance, methodology, and status of this measurement.

Bailey, Lucy [University Coll. London]

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE

Searches for New Long-Lived Particles and Upgrade to the ATLAS Inner Detector (Final Technical Report)

The search for new fundamental particles is one of the defining goals of the Large Hadron Collider (LHC). The discovery of the Higgs Boson by the ATLAS and CMS collaborations provided the capstone of the Standard Model of particle physics, but outstanding questions remain. Why does the Higgs boson have a mass of 125 GeV when its natural mass would be many orders of magnitude larger? Is there a universal symmetry which unites all three forces described by the Standard Model? Can that symmetry be extended to include gravity? Is dark matter, evidenced by astronomical observations, made of a particle that interacts via Standard Model forces with the rest of matter? Together, these motivations provide compelling arguments that new physical processes await discovery. This project addressed some outstanding questions about the fundamental particles and their interactions with the ATLAS experiment at the Large Hadron Collider. In particular, the project improved the discovery potential for new, long- lived particles produced via electroweak processes in proton-proton collisions and set world-leading limits on their existence for certain values of their potential mass and lifetime. To achieve this, the project developed new data analysis methods, developed new triggers to select events with new long-lived particles during data-taking of the ATLAS experiment, and analyzed the largest proton–proton collision dataset ever produced. The project also supported significant development of the data acquisition software for the upgrade to the ATLAS inner detector, the Inner TracKer (ITk). The upgrade of the ATLAS inner detector is essential to the success of the entire Phase II physics program on ATLAS. Personnel supported by the project provided support for integration, assembly, and testing of the inner two layers of the ITk pixel system during its prototype and pre-production phase. Four PhD students and two post-doctoral scholars were supported by the grant and received invaluable scientific training as part of the research endeavor. The students and postdocs gained essential professional skills in the areas of advanced data analysis techniques, statistical analysis of data and simulation, programming in C++ and Python, hardware and instrumentation development, and presentation and collaboration skills. Additionally, approximately ten undergraduate students supported through other funding sources participated in research activities synergistic with the goals of this project, receiving essential mentorship from the personnel supported by this project.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Hazard Detection Detector Cards

This report presents a comprehensive summary of five advanced anomaly detection tools developed and deployed by Oak Ridge National Laboratory in support of the VA’s Health Information Technology modernization. These detectors—Order Path Tracker, Trend Watcher, Pain Pointer, Performance Monitor, and Patient Record Flag Detector—leverage statistical and machine learning methods to monitor workflow disruptions, detect anomalies in care sequences and volumes, identify bottlenecks, and track system-level performance metrics across VistA and Millennium systems. All detectors have been integrated into the Health Data Analytics Platform (HDAP), with most having completed deployment and testing using live data from targeted stations in cardiology and oncology domains. This work enhances VA’s capacity for proactive system surveillance, promotes patient safety, and informs data-driven operational improvements across the EHR ecosystem.

97 MATHEMATICS AND COMPUTING

The SAND detector for the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation project aiming to study several neutrino properties. It will feature two experimental setups: a near detector that will be installed at Fermilab, in proximity of the neutrino-production point, and a far detector at a distance of 1300 km and 1500 m underground, at the SURF laboratory. The DUNE design and configuration will allow the study of neutrino oscillation, astrophysical neutrinos, and beyond standard model physics. The near detector complex foresees three detectors to be installed. Among these, the System for on-Axis Neutrino Detection (SAND) will serve as on-axis beam monitor, reduce the systematic uncertainties for the oscillation analysis, and search for physics beyond the standard model. SAND will be composed of three sub-detectors, surrounded by a 0.6 T superconducting magnet. The outermost detector will be a lead/scintillating-fiber electromagnetic calorimeter while the inner volume will include a 1-ton liquid argon active target placed upstream followed by a target tracker system. The SAND detector and its goals will be shown in this poster.

Alemanno, Francesca [Salento U.; INFN, Lecce]

Precision Timing in CMS at the HL-LHC: Current Progress on Validation and Production

During the High Luminosity phase of LHC, up to 200 proton-proton collisions per bunch crossing will bring severe challenges for event reconstruction. To mitigate pileup effects, an extended upgrade program of the CMS experiment is expected. Among which, a new timing layer, the MIP Timing Detector (MTD), will be integrated between the tracker and the calorimeters. With a time resolution of 30-60 ps, the MTD will enable 4D vertexing, bringing significant improvements in track-to-vertex association and object identification. The MTD is composed of two subsystems based on different technologies: the Barrel Timing Layer (BTL) consists of LYSO:Ce scintillating crystals readout by SiPMs, and the Endcap Timing Layer (ETL) is made of Low-Gain Avalanche Diodes. The BTL is currently under production, while ETL sensor prototyping and validation are ongoing. Recent system tests have confirmed the performance of the full acquisition chain. This talk will provide an overview of the MTD design, along with the physics motivation, and the current status of BTL construction and ETL development.

Safdari, Murtaza [Fermilab] (ORCID:000000018323731

Electric Utility Distribution Costs: Scoping Study on Trends, Drivers, and Possible Response Strategies [Slides]

This scoping study synthesizes information that will help stakeholders understand the scope, scale, and drivers of recent increases in investor-owned utility (IOU) expenditures on local distribution power grids, while providing regulators and other decision-makers with potential strategies to keep electricity bills down. The study includes five distinct components. Drawing first on data from FERC Form 1, it summarizes key trends in past and recent IOU distribution costs. Next, through a review of a sample of distribution-system plans, it characterizes material drivers of planned distribution expenditures. Ultimately, regulators must approve cost recovery for IOU expenditures, including those for the distribution system. The study therefore also: examines trends in utility requests and regulatory approvals related to changes in retail rates and return on equity; identifies areas where utility shareholder and customer incentives may be misaligned; and develops a menu of options that state regulators might consider to optimize distribution system expenditures. Some of the key findings include: - IOU distribution spending at a national level has grown by 6%/yr since 2014 in real dollar terms, 4x faster than in the prior 20 years and consisting mostly of capital (not operating) expenditure. - On a per-kWh basis, increases in IOU distribution costs since 2014 represent over 30% of the overall national-average increase in retail electricity rates. - Regional spending growth has ranged from 2-8%/yr, with larger estimated rate impacts in CAISO, then NYISO & ISO-NE, and then the Southeast, MISO & PJM (see figure). - Some utilities are planning for significantly increased distribution system spending. Planned spending on managing the existing system (asset replacement, safety & reliability, and resilience are all important drivers) exceeds that for capacity expansion. - IOU rate increase requests ($18 billion in 2025) and public utility commission (PUC) approval levels (average of 64% of requested amounts from 2021-2025) have recently hit multi-decadal highs. - PUCs in New England and the Southeast have recently approved a greater fraction of rate requests (>75%, on average) than in ther regions, while PUCs in California and the Southeast have generally authorized higher equity returns than in other regions. - Regulators have many tools to tackle potential misalignments between utility and customer interests and, more specifically, to optimize and reduce distribution costs. Shorter-term options include those related to return on equity, capital structure, depreciation, trackers, construction work in progress, and securitization. Longer-term options include performance-based regulation and a wide variety of planning-related requirements. All options embed important tradeoffs.

24 POWER TRANSMISSION AND DISTRIBUTION

FERC order 2222 & DER policy and implementation report - January 2026

The January 2026 FERC 2222 Tracker Report provides an overview of the progress and challenges in the implementation of FERC Order 2222, emphasizing the critical need for state-level action to address gaps in DERA/EDC communication protocols. The report highlights the importance of reliable communication between electric distribution companies (EDCs) and DER aggregators (DERAs) for seamless market operations, noting the absence of specific directives from FERC and RTO/ISO compliance filings. Key discussions include the operational coordination required to manage DER operations within aggregated markets, the potential use of tools like DER Registries for efficient data exchange, and the implications of non-performance due to communication issues. While steps are being taken at the state level, such as ongoing policy development and bi-monthly webinars for stakeholder education, no states have fully developed coordination frameworks as of early 2026. The report underscores the growing role of states and local regulators in defining these protocols and ensuring effective coordination amidst the complex dynamics of distributed energy resources (DERs) integration into wholesale markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Automating Detection and Diagnosis of Faults, Failures, and Underperformance in PV Plants

The project developed hybrid physics-based and machine-learning methods for near-real-time detection of balance-of-system faults (e.g., string, combiner, and tracker outages) in utility-scale Photovoltaic plants, achieving over 50% true positive rates with under 10% false positives and significantly reducing engineering setup time. In the extended phase, the scope expanded to plant-level underperformance analysis and industry benchmarking through the SUPER.epri.com platform. SUPER standardizes data processing and performance metrics across more than 9 GWac and 120+ plants, enabling robust comparisons and insights into loss rates, inverter downtime, and capacity degradation.

14 SOLAR ENERGY

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Calorimeter calibration and performance for the Mu2e experiment

The Mu2e experiment at Fermilab will search for the charged lepton flavour-violating conversion of a muon into an electron, aiming to reach a sensitivity of $R_{\mu e} \sim 10^{-17}$, an improvement of four orders of magnitude over previous limits. To reach this goal, Mu2e will use an intense pulsed muon beam and a detector system composed of a high-precision straw tube tracker and a pure CsI crystal calorimeter. The calorimeter plays a crucial role in the experiment, as it provides particle identification capabilities that are necessary for background suppression. To perform its tasks, the detector must achieve an energy resolution better than 10% and a timing resolution below 500 ps for 100 MeV electrons. Cosmic-ray data and laser pulses are used to equalize the response of each channel, to calibrate the energy scale and to monitor the system's stability over time. This poster reports on the calibration and analysis techniques developed to ensure that the calorimeter requirements for precise energy and time measurements are met. Results for the calorimeter performance obtained during the commissioning phase will be discussed, and an overview of the current status in the Mu2e experimental hall will be presented.

Salamino, Sabrina [Frascati]

Integration of a real-time orientation measurement system for a real-time evaluator (RTE) to measure the position and orientation of crane-lifted components

Prefabrication of building components holds the potential to revolutionize the construction industry. Prefabrication consists of manufacturing building components, modules, and other elements in a factory to be shipped and installed on a construction site. Prefabricated components have been produced for various applications including precast concrete panels for new construction and exterior wall retrofits. The manufacturing process has seen much innovation in recent years; however, the installation process has seen minimal advancements. A real-time evaluator (RTE) was developed to reduce the installation cost of prefabricated components by reducing installation time, decreasing rework, and improving accuracy. The RTE uses off-the-shelf hardware and novel algorithms to assist erectors with component installation by measuring the real-time positions of connections and prefabricated components, providing installation guidance through a graphical user interface, and monitoring the accumulated installation errors. An overview of the RTE and the proposed workflow is presented. Previous on-site demonstrations provided valuable feedback from users on the potential areas for improvement of the system. One common request was real-time measurement of component orientation during lifting, a process that previously required that the component remain stationary while the laser tracker cycled through target prisms. This paper will present the incorporation and testing of a real-time orientation measurement system as it was implemented into the RTE, allowing for measurement of component orientation during movement.

Selvakumar, Balaji [ORNL]