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At least 55 records · Page 3

Laser wavelength dependence of particle acceleration mechanisms in high intensity laser–solid density plasma interactions

We investigate the generation of relativistic electrons and the subsequent ion acceleration due to target-normal sheath acceleration when ultra-intense (⁠ I > 10 18 W/cm 2 ⁠) short pulse (⁠ τ L < 10ps⁠) lasers are incident onto solid density targets as laser wavelength is varied. Scaling laws for the hot electron temperature, T hot ⁠, and the maximum ion energy, E max ⁠, are recast as a function of laser wavelength. These predictions are compared to results from particle-in-cell computer simulations in a variety of geometries, including cases where realistic plasma density profiles as determined by a radiation hydrodynamics code are used. It is found that the wavelength dependence observed in simulation is less pronounced than what is predicted from the well-established scaling laws. An assessment of how switching to longer laser wavelengths, specifically 2 μm Tm:YLF technology, would impact current high energy density science applications and diagnostics is made.

Electromagnetism

Conditional guided generative diffusion for particle accelerator beam diagnostics

Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exceeds that of traditional synchrotron-based light sources by orders of magnitude. FEL operation requires precise control of the shape and energy of the extremely short electron bunches whose characteristics directly translate into the properties of the produced light. Control of short intense beams is difficult due to beam characteristics drifting with time and complex collective effects such as space charge and coherent synchrotron radiation. Detailed diagnostics of beam properties are therefore essential for precise beam control. Such measurements typically rely on a destructive approach based on a combination of a transverse deflecting resonant cavity followed by a dipole magnet in order to measure a beam’s 2D time vs energy longitudinal phase-space distribution. In this paper, we develop a non-invasive virtual diagnostic of an electron beam’s longitudinal phase space at megapixel resolution (1024 × 1024) based on a generative conditional diffusion model. We demonstrate the model’s generative ability on experimental data from the European X-ray FEL.

43 PARTICLE ACCELERATORS

Assessment and Improvement Proposals for High-Pressure Rinsing Processes during Cleanroom Preparation of Superconducting Radio-Frequency Cavities for Particle Accelerators

The goal of this internship is to develop a fluid dynamics characterization of the high-pressure flow used for cleaning the internal surface of the SRF cavities. Initially, the High Pressure Rinsing (HPR) process is introduced, focusing on the problems of the SRF cavities and how this method can be used to increase their acceleration efficiency and performance. The characterization of the problem is then presented, including an introduction to the multiphase flow modeling and the analysis of the Fermilab facility for the HPR. To accomplish the goal, a preliminary estimation of the variables was performed using MATLAB. Then, multiple 2D simulations were developed with Ansys Fluent, and the influence of the main parameter was investigated. The simulation results are then presented and analysed, with a focus on the possible future developments of the HPR process fluid dynamic characterization.

43 PARTICLE ACCELERATORS

Investigation of new superconducting materials for the next generation high-performance RF superconducting cavities for particle accelerators

In this DOE-funded project DE-SC0010081-020 Old Dominion University (ODU) in collaboration with University of Wisconsin (UW) and Jefferson Laboratory have investigated both experimentally and theoretically electromagnetic response and losses in multilayered superconducting structures made of new SRF materials which can push the field and Q performance limits of accelerating cavities.

43 PARTICLE ACCELERATORS

Low-energy H- beam injectors for particle accelerators: upgrade requirements, challenges and future plans [Slides]

High brightness, negative hydrogen ion sources are used extensively in large, accelerator-based, user facilities operating worldwide. Negative hydrogen beams have become the preferred means of filling circular accelerators and storage rings as well as enabling efficient extraction from cyclotrons. Much larger beams of H- ions are also utilized for neutral beams injection into fusion machines and will be discussed in a separate companion presentation. Some of the accelerator facilities include the US Spallation Neutron Source (SNS), Japan Proton Accelerator Research Complex (J-PARC), Rutherford Appleton Laboratory (RAL-ISIS), Los Alamos Neutron Science Center (LANSCE), Fermi National Accelerator Laboratory (FNAL), Brookhaven National Laboratory (BNL), the CERN LHC injector, the Chinese Spallation Neutron Source (CSNS) as well as numerous installations of D-Pace (licenced by TRIUMF) ion sources used mainly with cyclotrons. Many facilities are currently working on various improvement / upgrade projects, both in the near and long term, which are driving further development of their ion source and LEBT (Low Energy Beam Transport) and, in some cases, their overall front end injector system. This report will first provide a simple description of each facilities existing ion source and LEBT and summarize the operational parameters which are currently being routinely injected into their accelerators. Next, the parametric goals of each of the facilities upgrade projects are specified as well as development efforts currently underway to meet these requirement and improvement goals. It is hoped that that this work will not only capture the current state-of-the-art of worldwide H- beam injectors and clarify the research goals and efforts of the community in general but will also encourage further inter laboratory collaborations.

43 PARTICLE ACCELERATORS

Transition to Petschek Reconnection in Subrelativistic Pair Plasmas: Implications for Particle Acceleration

While relativistic magnetic reconnection in pair plasmas has emerged in recent years as a candidate for the origin of radiation from extreme astrophysical environments, the corresponding subrelativistic pair-plasma regime has remained less explored, leaving open the question of how relativistic physics affects reconnection. In this paper, we investigate the differences between these regimes by contrasting two-dimensional particle-in-cell simulations of reconnection in pair plasmas with relativistic magnetization (σ ≫ 1) and subrelativistic magnetization (σ < 1). By utilizing unprecedentedly large domain sizes and outflow boundary conditions, we demonstrate that lowering the magnetization results in a change in the reconnection geometry from a plasmoid chain to a Petschek geometry, where laminar exhausts bounded by slow-mode shocks emanate from a single diffusion region. We attribute this change to the reduced plasmoid production rate in the low-σ case: When the secondary tearing rate is sufficiently low, plasmoids are too few in number to prevent the system from relaxing into a stable Petschek configuration. This geometric change also affects particle energization: We show that while high-σ plasmoid chains generate power-law energy spectra, low-σ Petschek exhausts merely heat incoming plasma and yield negligible nonthermal acceleration. These results have implications for predicting the global current sheet geometry and the resulting energy spectra in a variety of systems.

Plasma astrophysics

Particle acceleration during classical phase transitions on a spherical lattice

Abstract When compressed, certain lattices undergo phase transitions that may allow nuclei to gain significant kinetic energy. To explore the dynamics of this phenomenon, we develop a methodology to study Coulomb coupled N -body systems constrained to a sphere, as in the Thomson problem. We initialize N total Boron nuclei as point particles on the surface of the sphere, allowing them to equilibrate via Coulomb scattering with a viscous damping term. To simulate a phase transition, we remove N rm particles, forcing the system to rearrange into a new equilibrium. With this model, we consider the Thomson problem as a dynamical system, providing a framework to explore how non-zero temperature affects structural imperfections in Thomson minima. We develop a scaling relation for the average peak kinetic energy attained by a single particle as a function of N and N rm . For certain values of N , we find an order of magnitude energy gain when increasing N rm from 1 to 6. The model may help to design a lattice that maximizes the energy output.

Bachmann, Aidan M. (ORCID:0000000294706404)

Transversely pumped laser driven particle accelerator

We present a novel acceleration scheme capable of accelerating electrons and ions in an underdense plasma. Transversely Pumped Acceleration (TPA) uses multiple arrays of counter-propagating laser beamlets that focus onto a central acceleration axis. Tuning the injection timing and the spacing between the adjacent beamlets allows for precise control over the position and velocity of the intersection point of the counter-propagating beam arrays. This results in an accelerating structure that propagates orthogonal to the direction of laser propagation. We present the theory that sets the injection timing of the incoming pulses to accelerate electrons and ions with a tunable phase velocity plasma wave. Simulation results are also presented which demonstrate 1.12 GeV proton beams accelerated in 3.6 mm of plasma and electron acceleration gradients on the order of 1 TeV/m in a scheme that circumvents dephasing. This work has potential applications as a compact accelerator for medical physics and high energy physics colliders.

Laser-produced plasmas

Towards continual machine learning for particle accelerators

This talk covers our work on errant beam prognostics at the Spallation Neutron Source (SNS), focusing on the end-to-end process from data collection to the development and deployment of predictive models in specific. A short overview of AIML work done for accelerators and current trends will be presented. We will walk through key steps involved in creating robust Machine Learning (ML) models, including model training, validation, and deployment in an operational setting. In addition to presenting our technical approach, we will share valuable lessons learned, emphasizing the importance of infrastructure to support the continuous adaptation of models to evolving data and system behaviors. This talk will provide insights into the challenges and solutions involved in applying ML to real-world operational environments, with a particular focus on managing data drift and changes in accelerator setup while ensuring model resilience over time.

Accelerator Physics

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

Digital Twin Industry Standards and Opportunities from the Particle Accelerator Community

Digital twins (DTs) are predictive models of a physical system that dynamically update to reflect any changes. This concept was first conceived as early as 1993 by David Gelernter in his speculative non-fiction Mirror Worlds. DTs were coined in 2002 by Michael Grieves and applied to Product Lifecycle Management for manufacturing. Since then, industry has been developing tools to simplify the creation, deployment, and use of digital twins for manufacturing, fleet management, and biological systems. We will recommend industry standard technology and interfaces that we should adopt in the accelerator community. We further identify gaps in this technology to which we can add new capabilities and solutions, which can be expanded for our use cases.

Miceli, Tia [Fermilab] (ORCID:0000000265577789)

Ultra-High Vacuum Outgassing Characterization of Thermally Processed Low-Carbon Steel for Advanced Particle Accelerator and Gravitational Wave Detector Applications

This dissertation investigated AISI 1020 low-carbon steel as an alternative vacuum chamber material to conventional stainless steel for ultra-high vacuum (UHV) and extreme-high vacuum (XHV) applications. After a 400 °C/48 h bake, AISI 1020 tube chambers achieved a hydrogen outgassing rate of 2.4 × 10¿¹6 Torr·L·s¿¹·cm¿², approximately 2,300 times lower than the prebaked 316L stainless-steel comparator, among the lowest hydrogen outgassing rates ever reported for an uncoated metallic vacuum chamber. Bare and magnetite-coated AISI 1020 chambers were then compared using throughput and rate-of-rise methods. The magnetite coating yielded 5× lower water outgassing at room temperature, but this advantage disappeared after 80 °C baking. After full thermal conditioning (400 °C/48 h prebake followed by 150 °C/96 h and 200 °C/110 h), bare steel achieved 25× lower hydrogen outgassing than the magnetite-coated chamber (9.6 × 10¿¹6 Torr·L·s¿¹·cm¿²) and >99% H2 purity with carbon species below RGA detection. Monte Carlo molecular flow simulations of a CEBAF photogun beamline (96 scenarios) showed that replacing 304L stainless steel with AISI 1020 reduces equilibrium H2 pressure by a factor of 833; a single 304L electrode contributes 98.8% of the gas load despite occupying only 9.1% of the internal surface area. A 500-m Einstein Telescope beampipe screening showed that corrugated bellows contribute 18% of the gas load from only 0.7% of the surface area. A five-model adsorption isotherm framework applied to 22 pumpdown datasets (164 fits with AR(1)-GLS correction) established that the experimental protocol, not the material, controls isotherm identifiability: Dubinin–Radushkevich wins isothermal pipe pumpdowns; Langmuir wins thermally dominated chamber bakes. Cross-dataset joint fitting of the AISI 1020 pipe pumpdowns yielded an H2 diffusion activation energy Ed = 7.24 ± 1.28 kcal·mol¿¹, consistent with trap dominated diffusion in commercial low-carbon steels. Two companion innovations were developed: a Variable Conductance Device (VCD, patent pending IDF-00723) for XHV outgassing measurement, and VacuumDesignerPro (VDP), a MATLAB-based design tool validated against LIGO benchmarks.

Al-Allaq, Aiman H [Old Dominion University]

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Accelerator control systems often represent relatively complex and safety-sensitive human-machine interfaces within process control industries. These systems are technically robust and reflect the cumulative integration of solutions built and adapted across decades. One of the regular, unfortunate casualties of provisional accelerator control system updates is their human-system interfaces (HSIs) which often lag behind modern usability and design standards. An additional challenge is that although there is a multitude of established human factors (HF), and user experience (UX) principles for everyday digital applications, there are very few (if any) established principles for complex and safety-critical applications for an accelerator. This paper argues for the importance of established HF and UX principles (herein referred to as human-centered design principles) into the development of accelerator HSIs, emphasizing the need for clarity, consistency, responsiveness, and cognitive accessibility. Drawing from HF/UX best practices and human-centered design, this paper discusses how these approaches can enhance operator performance, reduce human error, and improve accelerator personnel collaboration. Case studies from Accelerator Control Operations Research Network (ACORN) at Fermilab are explored to demonstrate how interfaces built with human-centered design principles can scale with system complexity while remaining intuitive and efficient for diverse user roles including operators, machine experts, and engineers. By bridging the gap between traditional control system design and modern human-centered design methods, this paper provides a roadmap for evolving accelerator HSIs into more usable, maintainable, and effective tools.

Hill, Rachael [Idaho Natl. Lab.]