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At least 19 records

Using kernel-based statistical distance to study the dynamics of charged particle beams in particle-based simulation codes

Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as numerical diagnostics for simulations involving charged-particle beams. Related measures of statistical dependence are also described. The resulting diagnostics provide sensitive measures of dynamical processes important for beams in nonlinear or high-intensity systems, which are otherwise difficult to characterize. Here, the focus is on kernel-based methods such as maximum mean discrepancy, which have a well-developed mathematical foundation and reasonable computational complexity. Several benchmark problems and examples involving intense beams are discussed. While the focus is on charged-particle beams, these methods may also be applied to other many-body systems such as plasmas or gravitational systems.

47 OTHER INSTRUMENTATION↗

Beam particle identification and tagging of incompletely stripped heavy beams with HEIST

A challenge preventing successful inverse kinematics measurements with heavy nuclei that are not fully stripped is identifying and tagging the beam particles. For this purpose, the HEavy ISotope Tagger (HEIST) has been developed. HEIST utilizes two micro-channel plate timing detectors to measure the time-of-flight, a multi-sampling ion chamber to measure energy loss, and a high-purity germanium detector to identify isomer decays and calibrate the isotope identification system. HEIST has successfully identified 198 Pb and other nearby nuclei at energies of about 75 MeV/A. In the experiment discussed, a typical cut containing 89% of all 198 Pb 80+ in the beam had a purity of 86%. We examine the issues of charge state contamination. Here, the observed charge state populations of these ions are presented and, using an adjusted beam energy, are well described by the charge state model GLOBAL.

47 OTHER INSTRUMENTATION↗

Methods and systems for evaluating a target using pulsed, energetic particle beams

A method for evaluating a target, the target having a surface, includes pulsing a defined, energetic particle beam through the surface and into the target such that particle energy deposition from the particle beam is concentrated in a subsurface target volume within a target medium of the target. The deposited particle energy induces a thermoelastic expansion of the target medium in the target volume that generates a corresponding acoustic wave. The method further includes detecting the acoustic wave from the target medium.

Hunt, Sean Matthew↗

Mutually guided light and particle beam propagation

The polarizability of atoms and molecules gives rise to optical forces that trap particles and a refractive index that guides light beams, potentially leading to a self-guided laser and particle beam propagation. In this paper, the mutual interactions between an expanding particle beam and a diffracting light beam are investigated using an axisymmetric particle-light coupled simulation. The nonlinear coupling between particles and photons is dependent on the particle beam radius, particle density, particle velocity and temperature, polarizability, light beam waist, light frequency (with respect to the resonance frequency), and light intensity. The computational results show that the maximum propagation distance is achieved when the waveguiding effect is optimized to single-mode operation. The application of the coupled beam propagation as a space propulsion system is discussed.

42 ENGINEERING↗

PyEmittance: A General Python Package for Particle Beam Emittance Measurements With Adaptive Quadrupole Scans [Poster]

We present PyEmittance: a new Python package for general particle beam emittance measurements that offers adaptive quadrupole scans and is designed for robust and flexible integration with Python-based software, with online accelerators, and with simulation software. It is open source software, and can be installed via the command pip install pyemittance.

43 PARTICLE ACCELERATORS↗

Neutrino Hunting: Looking through a UV Lens Scintillation Photon Detection in a Large-Volume Liquid Argon Time Projection Chamber, Exposed to a Multi-GeV Charged Particle Beam

The Deep Underground Neutrino Experiment (DUNE) will be a world-class neutrino observatory and nucleon decay detector designed to answer fundamental questions about elementary particles and their role in the universe. The DUNE experiment will consist of a a Near Detector, located at Fermilab, and a Far Detector, approximately 1.5~km underground at the Sanford Underground Research Facility in South Dakota, located $\sim$1300~km away. The accelerator complex at Fermilab will host an intense beam of neutrinos directed toward the two detectors. My dissertation centers on the implementation of technologies used to detect scintillation photon signals in liquid argon in the context of the DUNE's Far Detector Single-Phase (SP) module design, and features direct contributions to the Photon Detection System (PDS) deployed in the ProtoDUNE-SP Large-Volume Liquid Argon Time Projection Chamber (LArTPC) prototype. The PDS is needed for non-beam event timing, such as atmospheric neutrinos, proton d ecay, and supernova detection. The PDS provides a prompt signal ($t_{0}$ information) for micro-second event time determination, which improves the TPC's spatial localization along drift direction, enables accurate ionization-signal-attenuation determination, and even provides calorimetry. My dissertation will discuss an overview of the DUNE and ProtoDUNE-SP experiment and how we detect neutrinos in LAr, via charge and scintillation light. It will discuss my core experimental and analysis work, in regards to the Photon Detection System; including my contributions in establishing procedures for the commissioning and integration for the Photon Detector System that will be valuable during the construction, installation, commissioning, and operations of the DUNE Far Detector. In addition, it will comprehensively discuss the capability of three different photon detection technologies, and their characteristics and responses to muon and electron beam particles over a range of beam momenta , from 0.3~GeV/$c$ - 7~GeV/$c$. Further, the overall progress detailed in this thesis will help pave the way toward understanding the physical properties of these detectors, which will contribute to the success of the sensitivity measurements required for determining the neutrino mass hierarchy and $\delta_{CP}$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Phase-space tailoring and cooling of charged-particle beams for energy- and intensity-frontier applications

This project addressed accelerator science & technology researches relevant to the Intensity and Energy frontiers by investigating generic techniques to tailor and cool the phase-space distributions of charged-particle beams. Specifically, the project had two main research thrusts: (i) the development of phase-space tailoring techniques using externally-applied electromagnetic fields and (ii) the investigation of phase-space control using the beam’s self-field such as the optical-stochastic cooling (OSC). The work related to the development of phase-space-tailoring techniques leveraged on the research performed under our previous grant DE-SC0011831 where new temporal-shaping methods were proposed and some experimentally demonstrated. The work related to the concept of beam manipulation using self fields, and especially OSC, built on the achievements supported by grant DE-SC0013761 which focused on a OSC proof-of-principle experiment at the Fermilab’s IOTA ring.

43 PARTICLE ACCELERATORS↗

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Particle Beam Acceleration Using 3 Petawatt Laser Pulses

The Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) is presently operational at the Gerard Mourou Center for Ultrafast Optical Science (CUOS) at the University of Michigan. ZEUS is a significant upgrade of the previous high power laser systems at CUOS and consists of two beamlines thatoperate in perfect synchronization. The 500 TW beamline became operational in 2023, 2 PW operation started in 2025 and full 3 PW power levels will be available in 2026. It is presently the highest power laser system in the US. In this grant the high field science group at CUOS has leveraged this unique high power laser facility to investigate laser wake field acceleration (LWFA) in ultra-high power laser plasma interactions and have shown how this can scale for future electron–positron colliders at high energy. The dual beam experimental configuration enables flexibility for many frontier experiments in laser-driven acceleration research, in particular, enabling extended channelling/acceleration experiments, positron generation/acceleration experiments and proof-of-principle transverse pumping “dephasingless” electron acceleration experiment and theory. LWFA may be able to miniaturize particle accelerators for high energy physics and also enable new sources of ultrafast, extreme brightness and precise x-rays for a wide variety of applications. In laser wake field acceleration, an electron bunch “surfs” on the electron plasma wave (the “wake field”) generated by the ponderomotive force of an intense laser. The plasma wave has a strong longitudinal electric field that stays in phase with the relativistic driver. A relativistic charged particle may, therefore, remain in phase with the accelerating field over long distances and gain ultra-relativistic energies. The accelerating electric field strength that the plasma wave can support can be many orders of magnitude higher than that of conventional accelerators, which makes laser wakefield acceleration an exciting prospect as an advanced accelerator concept. In this research project we have investigated the scaling of this mechanism to laser powers of 2 PW and have measured the x-ray emission and radio frequency emission resulting from the acceleration process. We have also performed theoretical investigation of mechanisms to scale laser driven accelerators to much higher energy using dephasingless acceleration processes.

43 PARTICLE ACCELERATORS↗

Radiation Response of Ga 2 O 3 MOSFETs Probed via Focused Particle Beams

Gallium Oxide (Ga 2 O 3 ), particularly in its β-phase, is attracting lots of interest for high-power and high-voltage electronics due to its wide bandgap, high breakdown field, and thermal stability. This study investigates the radiation response of Ga 2 O 3 Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) under Total Ionizing Dose (TID) and Displacement Damage (DD) conditions, which are critical for applications in radiation environments. Utilizing a dual-beam Focused Ion Beam and Scanning Electron Microscope setup, microscale analysis of radiation effects on individual devices is performed. The findings reveal distinct behaviors under TID and DD + TID conditions, with TID leading to threshold voltage shifts due to trapped charges, while DD results in decreased drive current attributed to increased carrier scattering from lattice defects. Notably, it is demonstrated that the TID effect can be mitigated through dynamic threshold voltage adjustments and that the predicted TID from ions calculated by Monte Carlo simulations overestimates actual TID due to unaccounted charge yield effects. In conclusion, this research enhances the understanding of Ga2O3 MOSFETs' performance in harsh radiation environments, providing insights for the design of robust electronic devices for space and nuclear applications.

MOSFET↗

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗