From Jupiter Laser Facility to National Ignition Facility: An overview of High-Power Laser Experiments at LLNL
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Physics - Plasma physics↗
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Reconstruction of 6D Phase Space
A ‘Phase Space’ is a mathematical representation of all possible physical states of matter of a physical volume or system. Particle beams at Fermilab exist in a six-dimensional phase space: three position dimensions, and three momentum dimensions. To ‘reconstruct’ that space means to take measurement data from virtual detectors along those beams and map out where particles are and how they’re moving, using computational methods. In this experiment, we simulated a particle beam (Fig 1) and used the position distribution of each particle at each detector to map out the magnitude of the beam’s initial momentum.
Shirlee, Jermaine [DuPage Coll.]↗
Performance Validation of Endcap Timing Layer Detector Modules for CMS Phase-2 Upgrade
The High-Luminosity Large Hadron Collider (HL-LHC) will operate up to 200 simultaneous collisions per bunch crossing, which is a significant jump from the current value of about 30 collisions per bunch crossing, producing significant pileup that challenges accurate event reconstruction. To address this, the Compact Muon Solenoid (CMS) experiment is implementing the Endcap Timing Layer (ETL), a precision timing detector designed to provide timing measurements with a resolution of approximately 50 ps per hit and 35 ps per reconstructed track. This project focuses on the characterization and validation of ETL detector modules using laboratory laser test data. ETL performance is evaluated by analyzing key quantities such as Bunch Crossing Identification (BCID), Time-of-Arrival (TOA), Time-over-Threshold (TOT), Noise Stability etc. The resulting analysis provides insight into the timing performance and operational stability of ETL modules, contributing to the quality assurance process req uired before their installation in the CMS experiment and ensure that the modules can meet the long-term reliability requirements of approximately 10 years of operation without replacement.
Chipara, Munashe [Fermilab]↗
Accelerating lattice gauge theory studies with Agentic AI
Lattice gauge theory research, with its computationally intensive simulations and complex multi‑stage workflows, is well positioned to benefit from agentic AI systems. We demonstrate how such tools can support key components of lattice gauge theory research, including novel simulation code development using standard LQCD frameworks, HPC job orchestration, simulation data analysis, and expert‑guided tuning of algorithmic parameters such as Hasenbusch mass preconditioning and multigrid solvers. Our results show that agentic AI can reduce manual effort, improve productivity, and accelerate the research cycle while maintaining essential human oversight.
Ayyar, Venkitesh [Fermilab]↗
Atmospheric Modeling and Denoising for Millimeter-Wave Line Intensity Mapping
Line-intensity mapping (LIM) offers a promising approach to mapping large-scale cosmic structure, and the greatest obstacle for ground-based observations at millimeter wavelengths is foreground contamination from atmospheric emission. In this work, we present a simulation and denoising framework designed to isolate and subtract atmospheric fluctuations from LIM data, modeled after the instrument parameters of the South Pole Telescope Summertime Line Intensity Mapper (SPT-SLIM). We generate mock observations spanning 125-175 GHz containing cosmic signals, precipitable water vapor screens, ice crystal fluctuations, and photon noise. We then implement a spatial-spectral atmospheric removal pipeline combining per-pixel linear template regression with a two-dimensional Fourier-domain filter. The framework is evaluated under simulated conditions in the South Pole and the Atacama Desert across three key metrics: cosmic signal preservation, foreground subtraction efficiency, and instrument noise injection. Our pipeline achieves atmospheric suppression at large spatial scales, and these results establish a physically grounded foundation for atmosphere removal in ground-based LIM data collection.
Saye, Laney [UC, Berkeley (main)] (ORCID:000900078↗
Pre-Equilibrium De-Excitations in Neutrino-Nucleus Interactions
Pre-equilibrium de-excitation is a well-established stage of nucleon-induced nuclear reactions but has not previously been incorporated into neutrino event generators. This work implements the Koning-Duijvestijn exciton model within the MARLEY neutrino event generator to simulate energy redistribution and particle emission before compound nucleus equilibrium. The implementation includes modular calculations of particle-hole state densities, internal transition rates, emission rates, and Monte Carlo cascade sampling, and is validated against the TALYS-2.2 nuclear reaction code. A new event record is also proposed to enable future uncertainty reweighting studies. This work establishes the first framework for studying pre-equilibrium effects in neutrino-induced reactions, with the goal of improving predictions of particle multiplicities, γ-ray production, and MeV-scale detector signals relevant to experiments such as DUNE.
Visser, Erin [Michigan State U., East Lansing (mai↗
Towards Anomaly Detection at the CMS High-Level Trigger System
Traditional trigger strategies in CMS typically rely on model-dependent selections or rigid kinematic cuts, risking the omission of unexpected exotic signatures. To address this, we propose a novel anomaly detection (AD) algorithm for the High-Level Trigger (HLT), designed to serve as a complementary second layer of filtering to the Level-1 AXOL1TL AD algorithm. We employ a transformer-based foundation model trained on a diverse ensemble of Standard Model processes. By combining a joint contrastive and classification objective, and using particle kinematics as inputs, the model learns to map events to a physics-informed latent space where anomalous events are isolated from dominant backgrounds. Preliminary results show that this strategy enhances the signal-to-background ratio across a range of rare SM and BSM scenarios. Furthermore, this work constitutes foundational R&D for the potential implementation of an analogous AD algorithm in the Level-1 trigger system for Phase-2.
Cruz, Roy [U. Wisconsin, Madison (main)] (ORCID:00↗
A New Era for Bubble Chamber Technology
Neutrino experiments like DUNE are limited by how well we understand the way neutrinos actually interact with atoms. The best way to fix that is to measure interactions on hydrogen, since a hydrogen nucleus is just a single free proton with largely none of the nuclear effects that heavier targets like argon have. The catch is that no one has built a hydrogen bubble chamber for a neutrino beam since the 1980s, mostly because the old chambers had too low of an active time. MAMBA is a project focused on bringing that technology back but built to cycle continuously at 1 Hz. I spent my summer internship on two of the subsystems that make that kind of speed possible. First, I helped install and test a new solid copper thermal link that replaced the old flexible braided cooling path, and it brought the coldhead down to 21.3 K, right at the target temperature. Second, I built and tested a Raspberry Pi based PLC control system, and across 20,000 trials it answered in a median of 0.64 ms, with only 0.66\% of trials running past 1 ms. Both results point the same direction: that inexpensive, off the shelf hardware can perform fast and reliable enough to eventually run a bubble chamber the way MAMBA needs it to run.
Williams, Nicholas [DuPage Coll.]↗
Detector architecture and data flow of the CMS HGCAL Phase-2 Endcap Calorimeter Upgrade
The CMS High Granularity Calorimeter (HGCAL) is the Phase-2 endcap calorimeter upgrade for the High-Luminosity Large Hadron Collider, designed to provide precise spatial, energy, and timing measurements in a high-radiation, high-pileup environment. This work presents an overview of the HGCAL assembly process, detector architecture, and end-to-end data flow. The data flow goes from signal generation in silicon sensors and scintillator tiles through front-end electronics, optical transmission, and back-end data acquisition. The study highlights how the integrated detector, electronics, and readout systems enable efficient event reconstruction and support the physics objectives of the HL-LHC.
Osei Boakye, Prince [Grambling State U.]↗
Captan+X Data Converter Integration
Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.
Espinoza, David [Illinois U., Urbana (main)]↗
Hardware Implementation of Grover's Search Algorithm
Grover's algorithm searches through an unstructured database, offering a quadratic speedup over classical search algorithms. We implement it, as well as two deterministic variants, on IBM (Kingston) and IQM (Garnet) hardware. Additionally, we test dynamical decoupling as an error mitigation technique. We compare our results to a classical, brute force approach to evaluate current hardware capabilities.
Pressman, Daniel [Fermilab]↗
Characterization of High-Entropy Alloys for Accelerator Beam Window Applications
Particle production targets and accelerator beam windows receive millions of high-energy/intensity beam pulses throughout their service lifetime. For next-generation multi-MW accelerators, it is necessary for beam windows to be able to withstand higher levels of thermal shock and radiation damage, while also having good high-temperature mechanical properties. Novel High-Entropy Alloys (HEAs) that form a single-phase microstructure, have nanoscale precipitates, and are made from low-Z elements are good candidates for beam window materials. This is due to their high-temperature strength and high resistance to radiation-induced swelling and hardening, as well as their beam transparency, allowing for maximized particle production and a longer service lifetime.
Kidwell, Tristan [U. Chicago (main)] (ORCID:000900↗
Development and implementation of high-throughput proteomic and metabolomics assays by using advanced chromatographic and mass spectrometric systems (CRADA Final Report)
The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOFMS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Overall, the project advanced rapid metabolomics by combining liquid chromatography, ion mobility spectrometry, and data-independent mass spectrometry with machine learning. This multidimensional approach uses retention time, collision cross-section, precursor mass, and fragment-ion information to distinguish chemically similar metabolites that can be difficult to resolve using conventional liquid- or gas-chromatography methods. The resulting workflow also provided automated metabolite-identification error estimates, addressing a recognized need for statistical confidence measures in metabolomics.
Petzold, Christopher [Lawrence Berkeley National L↗
Distributed Wind Certification Best Practices Guideline: January 16, 2023-January 15, 2026
This Distributed Wind (DW) Certification Best Practices Guideline describes the typical approach for certification of distributed wind turbines above and below 150 kilowatts (kW) in size based on the conformity assessment requirements in the United States. The purpose of the guideline is to clarify and consistently describe the complex path to certification for various systems and components. This is done via clarification of both the required turbine type certification elements, as well as third-party electrical safety listing of turbine system components and subassemblies.
17 WIND ENERGY↗
Magnetic Mapping of MAGIS-100 Tubes to Guide Experimental Redesign
The MAGIS-100 atom interferometer requires an exceptionally uniform, low-magnetic-field environment along its 100-meter baseline. While characterization of the raw structural tubes established a clean baseline, the original surrounding experimental design proved overly complex, ultimately introducing complications that degraded data precision. To resolve these systemic issues, a comprehensive redesign of the surrounding apparatus is underway. This poster details our magnetometry data collection efforts on the baseline tubes and highlights how these measurements are being used to guide a streamlined external design. By leveraging this background data, the new configuration aims to eliminate the complexities of the initial setup and ensure the environmental stability required for high-precision quantum sensing.
Savoia Cooley, Patricia [North Central Coll.]↗
Finite Element Analysis and Measurement of Coefficients of Thermal Expansion on HEAs
This poster covers the introducing why Finite Element Analysis is essential in understanding HiRadMat. It also covers on the experimental procedures and obtained result of the measurement of Coefficient of thermal expansion (CTE) of High Entropy Alloys, and the relevance of these results in application of selecting beam intercepting devices
Itemba, Leo [U. Chicago (main)]↗
Longitudinal Phase Space Tomography for the Booster Synchrotron
Efforts in the study of the longitudinal behavior of charged particles in the Fermilab Booster can be catalyzed with an image of the two-dimensional phase space distribution. In the past, tomography has been extensively employed in the reconstruction of the phase space in accelerators such as the Recycler at Fermilab and the Proton Synchrotron Booster at CERN. However, such a capability had yet to realize for the Fermilab Booster synchrotron. In this work, the first successful tomographic phase space reconstruction of a low-energy Booster bunch is presented along with validation metrics. A numerical turn-by-turn model of the longitudinal particle dynamics in the Booster has been implemented, which utilizes a fast, map-based particle transport algorithm. Using a sinogram generated from the Wall Current Monitor, the iterative reconstruction algorithm recovers a discretized image of the original phase space distribution at variable resolution. The reconstruction result shows low root-mean-square error and a rapid convergence toward the solution, providing strong evidence of accuracy. Future and ongoing work includes modeling high-energy bunches above transition and using tomography to infer certain machine parameters such as synchronous phase, peak gap voltage, and synchronous energy in addition to the phase space distribution.
Ebeid, Safi [Unlisted]↗
Data for EMSL Project 61093 from August 2026
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Toyoda, Jason [Environmental Molecular Sciences La↗