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At least 163 records · Page 9

Exploring baryon resonances with transition generalized parton distributions: status and perspectives

QCD gives rise to a rich spectrum of excited baryon states. Understanding their internal structure is important for many areas of nuclear physics, such as nuclear forces, dense matter, and neutrino-nucleus interactions. Generalized parton distributions (GPDs) are an established tool for characterizing the QCD structure of the ground-state nucleon. They are used to create 3D tomographic images of the quark/gluon structure and quantify the mechanical properties such as the distribution of mass, angular momentum, and forces in the system. Transition GPDs extend these concepts to N → N* transitions and can be used to characterize the 3D structure and mechanical properties of baryon resonances. They can be probed in high-momentum-transfer exclusive electroproduction processes with resonance transitions e + N → e' + M + N*, such as deeply-virtual Compton scattering (M = γ) or meson production (M = π, K, etc.), and in related photon/hadron-induced processes. This White Paper describes a research program aiming to explore baryon resonance structure with transition GPDs. This includes the properties and interpretation of the transition GPDs, theoretical methods for structures and processes, first experimental results from JLab 12 GeV, future measurements with existing and planned facilities (JLab detector and energy upgrades, COMPASS/AMBER, EIC, EicC, J-PARC, LHC ultraperipheral collisions), and the theoretical and experimental developments needed to realize this program.

Experimental Nuclear Physics↗

Exploring Resonance Structures in the Partial-Wave Analysis of ¿p0 Photoproduction at GlueX

This thesis studies what happens when a photon (¿) collides with a proton (p) and produces a neutral omega (¿) and pion (p0) pair, with a recoiling proton (p'), expressed as ¿p ¿ ¿p0p'. We study this and other reactions to better understand the strong nuclear force; one of the four fundamental forces that govern all the physics of the universe. This force is specifically responsible for the binding and decay of subatomic particles, such as the ones here. While we understand the ¿ and p0, what we are actually interested in is a short-lived unknown particle X that decays via X ¿ ¿p0. There are a multitude of possible particles X can be, and so our focus in this work is to find out what X is by determining its properties from the particles we measure. We do this via an intricate analysis procedure known as “partial-wave analysis”. By analogy, one can think of our particle detector as a buoy, and the particles we want to analyze (X) as pebbles hitting a pond. The waves created by the pebble will move our buoy, giving us information about the pebble that produced the wave. However, when multiple pebbles hit our pond, the waves overlap and interfere with each other. Our buoy only can measure the complicated interfering result of all the waves. To disentangle this, our partial-wave analysis works by modeling this interference pattern so that we may infer the properties of the pebbles (particles) we produced. In this thesis, we review the relevant experimental history in photoproduction and related production mechanisms, as well as the theoretical foundations that motivate our measurement. We describe the methods used to collect our data at the GlueX experiment stationed at the Jefferson Lab accelerator facility in Newport News, Virginia. We then detail the selections we apply to ensure our events are almost exclusively ¿p ¿ ¿p0p'. We cover the intensity model, how we verify its capabilities, and finally present our results together with systematic studies. Our primary result is the detection of a b1(1235) meson interfering with a wide JPC = 1-- vector state, measured via a mass-independent partial-wave analysis. It provides precise experimental results that can be used as input for theoretical models of the reaction, yielding conclusions about the procedures responsible for how our universe behaves at its most basic level.

Scheuer, Kevin [College of William and Mary, Willi↗

Multi-Beam-Energy Control Unit Based on Triple-Bend Achromats

X-ray free electron lasers (XFELs) are the new generation of particle accelerator-based light sources, capable of producing tunable, high-power X-ray pulses that are increasingly vital across various scientific disciplines. Recently, continuous-wave (CW) XFELs driven by superconducting linear accelerators have garnered significant attention due to their ability to enhance availability by supporting multiple undulator lines simultaneously. In this paper, we introduce a novel delay system comprising four triple-bend achromats (TBAs). This delay system was combined with fast kickers and can be employed to generate electron beams on a bunch-to-bunch basis in a CW-XFEL facility. Based on the parameters of the Shanghai High-Repetition-Rate XFEL and Extreme Light Facility, start-to-end simulations demonstrate that the TBA-based delay system achieves excellent electron beam qualities while providing a wide beam-energy-tuning range from 1.39 to 8 GeV.

43 PARTICLE ACCELERATORS↗

Integration of a new Cryogenic Liquefier into the IB-1 Cryogenic Test Facility

The increase over the last years of the testing activities related to quantum systems, SRF cavities for the PIP-II and the LCLS-II projects, as well as superconducting magnets for the HL-LHC project and Fusion research activities, has required the addition of a new Helium cryogenic plant into the existing IB-1 Industrial Cryogenic Test Facility. The new cryogenic plant is composed of a cryogenic liquefier (Cold Box) able to provide up to 340 L/h, a 4 kL Dewar and two Mycom ® compressors providing up to 120 g/s. AL-AT (Air Liquide Advanced Technologies) has taken part of this project by designing and manufacturing the cryogenic liquefier. This new cryogenic plant is connected through a cryogenic distribution system to a 10 kL Dewar, which is part of the existing cryogenic test facility, itself composed of another Cold Box and a Sullair ® compressor. The new cryogenic plant has two main operating modes: one allows to transfer liquid helium at 1.7 bar between the two Dewars, the other allows to transfer supercritical Helium at 2 bar or more between the new Cold Box and the 10 kL Dewar. The entire industrial cryogenic facility is handled by a common Inventory Control System, composed of three control valves, and 9 tanks giving a total buffer volume of more than 1000 m3. This paper presents the technical features of the new Helium cryogenic plant, as well as the main results of the liquefier commissioning phase and details of the helium transfer between the two Dewars, making the connection between the cryogenic plants at the IB-1 Industrial Cryogenic Test Facility.

43 PARTICLE ACCELERATORS↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗

Blending as an In-Tank Waste Processing Strategy: Year 1 Progress Report

The Hanford Site stores approximately 56 million gallons of radioactive legacy defense waste in underground tanks. Direct feed of southeast quadrant tank waste to a high-level waste treatment facility is currently being explored to accelerate tank treatment activities. This study seeks to de-risk waste transfers by favorably altering the resuspension and critical velocities of wastes through strategic waste blending. Wastes rich in aluminum- and zirconium-bearing solids pose significant risks due to their high settled strength and density. A series of tests explores how solid phase particle size and suspending phase chemistry alter waste transport properties, quantified through the just-suspended mixing speed (NJS), for pure and blended aluminum- and zirconium-bearing waste solid simulants. The study utilizes a range of gibbsites (three sizes spanning 10 to 90 µm) and zirconia solids (three sizes spanning 10 to 100 µm). As expected, the NJS of pure solids largely follows predictions based on literature correlations; blends of gibbsite and zirconium-bearing solids of differing particle sizes exhibit NJS maxima attributed to dense packing of the mixed-size settled solids. The findings of this study will assist in developing strategies to optimize the transport of waste solids for the safe and efficient delivery of tank waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision

Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape cosmic evolution. This whitepaper presents a vision for how Artificial Intelligence (AI) can accelerate discovery in this field. We outline grand challenges that must be addressed to enable transformative breakthroughs and describe how current and planned experimental facilities can implement this vision to advance our understanding of the vast and complex physical world from the smallest to the largest scales. We show how facilities currently under construction, such as the HL-LHC, DUNE and soon EIC, can both benefit from and serve as proving grounds for this vision, while also enabling a longer-term goal for how future experiments -- like FCC-ee at CERN, IceCube-Gen2, a Muon Collider in the U.S., and smaller to mid-scale projects -- can be fully AI-native. We describe how a truly national-scale collaboration, jointly managed across large funding partners, and involving both DOE laboratories and universities, can make this happen.

Aarrestad, Thea Klaeboe [ETH, Zurich (main)]↗

Horizontal 1 K refrigerator with novel loading mechanism for polarized solid targets

We describe a helium evaporation refrigerator used to cool dynamically polarized proton and deuteron targets for electron-scattering experiments using the CEBAF Large Acceptance Spectrometer CLAS12 at Jefferson Lab. The geometry of the CLAS12 detector systems places severe design and construction constraints on the refrigerator and its ancillary equipment, resulting in a horizontal cryostat with a length of 4 m. The 16 cm 3 target samples, consisting of frozen ammonia (NH 3 or ND 3 ), are loaded at the upstream end of the cryostat and moved to the beam-interaction region using a novel transport mechanism. At this location they are cooled with superfluid helium and polarized via dynamic nuclear polarization at 1 K and 5 T. In this manner samples can be replaced and cooled to 1 K in about 30 minutes without disturbing any elements of the electron beam line or particle detection system. In conclusion, we estimate that this method saved 18 days of valuable beam time over the course of a recent, 88-day long experiment.

Evaporation refrigerator↗

Nonlocal nucleon matrix elements in the rest frame

Extracting parton structure from lattice quantum chromodynamics (QCD) calculations requires studying the coordinate scale 𝑧 3 dependence of the matrix elements of bilocal operators. The most significant contribution comes from the 𝑧 3 dependence induced by ultraviolet (UV) renormalization of the Wilson line. We demonstrate that the next-to-leading order perturbative calculations of the renormalization factor can describe, to a few percent accuracy, the logarithm of the lattice QCD rest frame matrix elements with separations up to distances of 0.6 fm on multiple lattice spacings. The residual discrepancies can be modeled by a leading effect from the structure of the nucleon.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Business Plan for a Domestic Supply of Superconducting Radiofrequency Cavities

Superconducting radiofrequency (SRF) cavities are critical components of modern particle accelerators. The industrialization of SRF technology in the U.S. has a long history, with several companies becoming interested in the technology in the past 30 years. However, there is currently no U.S. manufacturer with the capability to produce fully assembled, ready-to-test SRF cavities. A majority of these companies have either left the field or shut their doors. As a result, government-sponsored SRF accelerator projects in the U.S. largely rely on European vendors for the cavity supply. This presents not only a supply chain risk for scientific use cases, but also severely limits the commercialization of accelerator-based technologies. SRF accelerators have a range of strategic applications, including environmental remediation, semiconductor lithography, medical isotope production, and irradiation/sterilization. The nurturing of a domestic SRF industry is critical to maintaining U.S. economic competitiveness.

43 PARTICLE ACCELERATORS↗

Electron-Ion Collider (EIC) Hadron Storage Ring (HSR) Injection Transport Beamline (Y-Line Ext.) Lattice Design and Magnet Parameters

The preliminary design of the Electron-Ion Collider (EIC) Hadron Storage Ring (HSR) Normal Conducting Injection Beamline ( Y-Line Ext. ) lattice is discussed. The preliminary design includes the periodic cells, matching sections, state of the art Twiss parameters at the HSR injection, the magnet parameters and first order instrumentation placement. Furthermore, the beamline parameters, element coordinates, and other information are discussed. The names of the HSR Injection Beamline elements used in this technical report ( i.e. HD1, HQ1 ) are preliminary and not the official site wide names.

43 PARTICLE ACCELERATORS↗

F2D2 Targetry Overview and Conceptual Design Updates

F2D2 is a proposed 2.5 MW beam dump facility using PIP-II beam to serve dark sector physics experiments, and potentially other users. Further updates to the conceptual design are presented, along with targetry theory informing the design.

43 PARTICLE ACCELERATORS↗

Neutrino Beam Monitoring

Accelerator facilities produce neutrino beams from meson decays in a decay volume. Experiments measure event rates that depend on flux, cross sections, and detector response, so the flux is predicted using hadron production and beamline modeling and constrained by beam instrumentation, since near detectors alone cannot separate flux from cross section. Proton, hadron, and muon monitors can track the parent particle distributions and beam conditions, providing the inputs needed for flux predictions in long-baseline experiments such as NOvA, T2K, and DUNE. This talk reviews how beam monitors are used in practice to understand neutrino flux. Proton beam monitors tell where the beam hits the target and how stable it is. Farther downstream, hadron and muon monitors sample particles produced in meson decays. Because those muons come from the same parents as the neutrinos, their profiles reveal focusing, alignment shifts, and other changes in the beam, and they are routinely used to detect problems and guide flux predictions. The muon information can be used more quantitatively; for example, to infer the parent meson phase space, and fast radiation-hard timing detectors can add sensitivity to the momentum dependence of the focusing. These developments show both how tightly beam measurements can constrain the flux and where the current limits still lie. These approaches complement monitored-beam concepts, in which the decay region is instrumented to detect charged leptons from meson decays and to measure the neutrino flux directly.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Neutrino Beam Monitoring

Accelerator facilities produce neutrino beams from meson decays in a decay volume. Experiments measure event rates that depend on flux, cross sections, and detector response, so the flux is predicted using hadron production and beamline modeling and constrained by beam instrumentation, since near detectors alone cannot separate flux from cross section. Proton, hadron, and muon monitors can track the parent particle distributions and beam conditions, providing the inputs needed for flux predictions in long-baseline experiments such as NOvA, T2K, and DUNE. This talk reviews how beam monitors are used in practice to understand neutrino flux. Proton beam monitors tell where the beam hits the target and how stable it is. Farther downstream, hadron and muon monitors sample particles produced in meson decays. Because those muons come from the same parents as the neutrinos, their profiles reveal focusing, alignment shifts, and other changes in the beam, and they are routinely used to detect problems and guide flux predictions. The muon information can be used more quantitatively; for example, to infer the parent meson phase space, and fast radiation-hard timing detectors can add sensitivity to the momentum dependence of the focusing. These developments show both how tightly beam measurements can constrain the flux and where the current limits still lie. These approaches complement monitored-beam concepts, in which the decay region is instrumented to detect charged leptons from meson decays and to measure the neutrino flux directly.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Virtual to Physical: Reinforcement Learning to Optimize SNS Particle Accelerator Controls

Complex accelerators must have control systems that can handle dynamic nonlinear environments. This makes traditional control methods unsuitable as they can struggle to adapt to these uncertainties. This provides an ideal environment for reinforcement learning algorithms as they are adaptable and generalizable. We present a reinforcement learning pipeline that can effectively handle the dynamics of a complex accelerator. We test and prove our pipelines capabilities on multiple environments including the Spallation Neutron Source (SNS) and the Beam Test Facility (BTF) at Oakridge National Lab (ORNL). Due to the limited time available to train an online algorithm like reinforcement learning on a real accelerator, we utilize a virtual twin accelerator (VIRAC) developed by ORNL to pretrain the policy and show its ability to converge in the virtual environment. We then test the adaptability of the pretrained RL model by applying it on the real accelerator and comparing the results. Utilizing our Scientific Optimization and Controls Toolkit (SOCT) and open-source standards such as Gymnasium we create and solve for a MEBT orbit correction problem in the SNS and an emittance maximization problem in the BTF. We show how Twin Delayed Deep Deterministic Policy Gradient (TD3) can solve this optimization environment in the virtual accelerator and transfer this policy onto the real accelerator for inference and model retraining. We show how reinforcement learning can be utilized as a control system for complex accelerators and provide a model pipeline for how an implementation performs and can be adapted to new accelerator control problems.

Kasparian, Armen [Thomas Jefferson National Accele↗

Polarized positrons at Ce\(^+\)BAF

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab [1]. This concept is based on positron beam generation by a high current polarized electron beam (1 mA, 120 MeV, >85% polarization) irradiating a 4 mm thick rotating water-cooled tungsten target or liquid metal target. The update on the development of the Ce+BAF injector concept including the polarized electron source, the development of high power targets, simulations of positron capture, the design of the transport line from the positron injector to the CEBAF North Linac and the planned experiment to measure the upper limits of transverse and longitudinal emittances accepted by the 12 GeV CEBAF optics are presented. [1] J. Grames et al., "Positron beams at Ce+BAF", in Proc. 14th Int. Particle Accelerator Conf. (IPAC’23), Venice, Italy, MOPL152, pp. 896–899 (2023). doi:10.18429/JACoW-IPAC2023-MOPL152

Ushakov, Andriy↗

Development of a half-meter scale Traveling-Wave (TW) SRF cavity

Traveling-wave technology can push the accelerator field gradient of niobium SRF cavity to 70MV/m or higher beyond the fundamental limit of 50~60MV/m in Standing-Wave regime. The 1st demonstration of TW resonance excitation in a proof-of-principle 3-cell SRF cavity in 2K liquid helium was successfully carried out at Fermilab in collaboration with Euclid Techlabs. In parallel with that, the RF design process of 0.5~1 meter scale TW cavity was begun at Fermilab for advancing TW technologies necessary more for future accelerator-scale one. Considering the physical dimensions of existing SRF facilities (for fabrication, processing, and cryogenic testing) and the lessons learned from the 3-cell, Fermilab has proposed a preliminary RF design of a half-meter scale TW SRF cavity. It consists of a 7-cell structure and a power feedback waveguide (WG) loop with new RF configurations to control TW resonance. Here we report a preliminary RF design, development plans, and activities.

43 PARTICLE ACCELERATORS↗