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At least 1,027 records · Page 57

Multi-messenger dynamic imaging of laser-driven shocks in water using a plasma wakefield accelerator

Understanding dense matter hydrodynamics is critical for predicting plasma behavior in environments relevant to laser-driven inertial confinement fusion. Traditional diagnostic sources face limitations in brightness, spatiotemporal resolution, and in their ability to detect relevant electromagnetic fields. In this work, we present a dual-probe, multi-messenger laser wakefield accelerator platform combining ultrafast X-rays and relativistic electron beams at 1 Hz, to interrogate a free-flowing water target in vacuum, heated by an intense 200 ps laser pulse. This scheme enables high-repetition-rate tracking the evolution of the interaction using both particle types. Betatron X-rays reveal a cylindrically symmetric shock compression morphology assisted by low-density vapor, resembling foam-layer-assisted fusion targets. The synchronized electron beam detects time-evolving electromagnetic fields, uncovering charge separation and ion species differentiation during plasma expansion – phenomena not captured by photons or hydrodynamic simulations. We show that combining both probes provides complementary insights spanning kinetic to hydrodynamic regimes, highlighting the need for hybrid physics models to accurately predict fusion-relevant plasma behavior.

imaging techniques↗

Microcoulomb (0.7 ± $$\frac{0.4}{0.2}$$ μC) laser plasma accelerator on OMEGA EP

Abstract Laser-plasma accelerators (LPAs) driven by picosecond-scale, kilojoule-class lasers can generate particle beams and x-ray sources that could be utilized in experiments driven by multi-kilojoule, high-energy-density science (HEDS) drivers such as the OMEGA laser at the Laboratory for Laser Energetics (LLE) or the National Ignition Facility at Lawrence Livermore National Laboratory. This paper reports on the development of the first LPA driven by a short-pulse, kilojoule-class laser (OMEGA EP) connected to a multi-kilojoule HEDS driver (OMEGA). In experiments, electron beams were produced with electron energies greater than 200 MeV, divergences as low as 32 mrad, charge greater than 700 nC, and conversion efficiencies from laser energy to electron energy up to 11%. The electron beam charge scales with both the normalized vector potential and plasma density. These electron beams show promise as a method to generate MeV-class radiography sources and improved-flux broadband x-ray sources at HEDS drivers.

43 PARTICLE ACCELERATORS↗

Photon acceleration of high-intensity vector vortex beams into the extreme ultraviolet

Extreme ultraviolet (XUV) light sources allow for the probing of bound electron dynamics on attosecond scales, interrogation of high-energy-density matter, and access to novel regimes of strong-field quantum electrodynamics. Despite the importance of these applications, coherent XUV sources remain relatively rare, and those that do exist are limited in their peak intensity and spatio-polarization structure. Here, we demonstrate that photon acceleration of an optical vector vortex pulse in the moving density gradient of an electron beam–driven plasma wave can produce a high-intensity, tunable-wavelength XUV pulse with the same vector vortex structure as the original pulse. Quasi-3D, boosted-frame particlein- cell simulations show the transition of optical vector vortex pulses with 800-nm wavelengths and intensities below 10 18 W/cm 2 to XUV vector vortex pulses with 36-nm wavelengths and intensities exceeding 10 20 W/cm 2 over a distance of 1.2 cm. The XUV pulses have sub-femtosecond durations and nearly flat phase fronts. The production of such high-quality, high-intensity XUV vector vortex pulses could expand the utility of XUV light as a diagnostic and driver of novel light–matter interactions.

43 PARTICLE ACCELERATORS↗

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

The growing demand for energy-efficient processes to support a sustainable future drives the need for research to rapidly explore chemical and material space through accelerated catalyst discovery initiatives. Recent breakthroughs in high-throughput experimental and computational methods are transforming the catalysis field, surpassing traditional approaches to manipulating variables in catalytic processes. Key advancements in innovation include the integration of machine learning for efficient catalyst screening, high-throughput experimentation, data-driven methodologies employing comprehensive databases, and in situ and in operando techniques for realistic observations. This progress has undoubtedly been intertwined with a collaborative framework across disciplines, reshaping catalyst discovery methods in both industry and academia. This Opinion article presents a multifaceted perspective from coauthors with expertise spanning various stages of the Technology Readiness Level spectrum, highlighting both opportunities and persistent challenges in integrating computational and experimental approaches in catalysis. These challenges span from obtaining high-quality experimental data, scaling simulations to industrially relevant materials and process conditions to navigating the complexity and predictive accuracy of computational models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proton acceleration in an overdense hydrogen plasma by intense CO 2 laser pulses with nonlinear propagation effects in the underdense pre-plasma

We report on proton acceleration from intense CO 2 laser-irradiated hydrogen plasmas at near-critical densities, with the density gradient steepened by Nd:YAG laser ablation-driven hydrodynamic shocks. While the experimental results, such as the quasi-monoenergetic proton spectra and their scaling with respect to the laser energy, are generally in agreement with the simulations, certain laser shots produced significantly higher proton energies than anticipated during the experiment. The increased proton energy may be linked to nonlinear propagation effects in the steepened plasma density ramp before the critical surface, including relativistic self-focusing and, for the case of temporally-structured laser pulses observed in the experiment, focusing of the trailing pulse through the plasma channel formed by the leading pulse 25 ps ahead. The occurrence of channel focusing in the underdense hydrogen plasma is supported by a subsequent pump-probe experiment with a dark-field imaging technique, where the formation of ion channels was observed after the passage of an intense CO 2 laser pulse

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental characterization of discharge plasma dynamics in a square capillary for prospective applications in laser wakefield acceleration

Research on plasma generated by electrical discharge in gas-filled capillaries plays an important role in advancing laser wakefield accelerators. We present a comprehensive study of the temporal and spatial distribution of plasma density within a short, 1 cm long, square-shaped capillary filled with hydrogen gas. Two transverse capillary sizes, 500 μm and 300 μm, were investigated achieving peak plasma densities of 0.9 × 10 18 cm −3 and 2.5 × 10 18 cm −3 , respectively, at the capillary center. In addition, we explore how these distributions depend on discharge parameters, specifically discharge current and gas flow through the capillary. Plasma density was determined by analyzing the Stark broadening of the hydrogen Balmer-alpha line. The results obtained were compared with the theoretical models and simulations. The comparison between the model predictions and the experimental data at the transient ionization stage of the discharge reveals a discrepancy of a factor of ∼1.3–2.1, depending on the capillary size, which is thoroughly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Strong interplay between superluminosity and radiation friction during direct laser acceleration

Using a test-particle model, we examine direct laser acceleration of electrons within a magnetic filament that has been shown to form inside a laser-irradiated plasma. We focus on ultra-high intensity interactions where the force of radiation friction caused by electron emission of electromagnetic radiation must be taken into account. It is shown that even relatively weak superluminosity of laser wave fronts—the feature that has been previously neglected—qualitatively changes the electron dynamics, leading to a so-called attractor effect. As a result of this effect, electrons with various initial energies reach roughly the same maximum energy and emit roughly the same power in the form of x-rays and gamma-rays. Our analysis implies that the primary cause of the superluminosity is the laser-heated plasma. The discovered strong interplay between superluminosity and radiation friction is of direct relevance to laser-plasma interactions at high-intensity multi-PW laser facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Design of a compact, cryogen-free superconducting solenoid for the electron lens of the Fermilab Integrable Optics Test Accelerator (IOTA)

The proposed electron lens for Fermilab's Integrable Optics Test Accelerator (IOTA) will broaden its capabilities by enabling new research in nonlinear integrable optics, space-charge compensation, proton beam cooling, and more. The electron lens is based on a 5–10 keV, 1–2 A electron beam, shaped using a 0.7 m long, 0.8 T solenoidal magnetic field. A cryogen-free superconducting solenoid has been designed to provide this solenoidal field, taking into consideration the constraints on space, utilities, and infrastructure in the IOTA experimental hall. The solenoid is made of copper stabilized niobium-titanium conductor, conduction-cooled using 4 K closed-cycle cryocoolers. This paper describes the overall design of the solenoid encompassing its mechanical construction, current leads optimization, cryogenic thermal modeling that provides estimates of cooldown time and static/dynamic heat loads, and quench analysis.

43 PARTICLE ACCELERATORS↗

Modeling of advanced accelerator concepts

Computer modeling is essential to research on Advanced Accelerator Concepts (AAC), as well as to their design and operation. This paper summarizes the current status and future needs of AAC systems and reports on several key aspects of (i) high-performance computing (including performance, portability, scalability, advanced algorithms, scalable I/Os and In-Situ analysis), (ii) the benefits of ecosystems with integrated workflows based on standardized input and output and with integrated frameworks developed as a community, and (iii) sustainability and reliability (including code robustness and usability).

47 OTHER INSTRUMENTATION↗

Positron sources: from conventional to advanced accelerator concepts-based colliders

Positron sources are the key elements for the future and current lepton collider projects such as ILC, CLIC, SuperKEKB, FCC-ee, Muon Collider/LEMMA, etc., introducing challenging critical requirements for high intensity and low emittance beams in order to achieve high luminosity. In fact, due to their large production emittance and constraints given by the target thermal load, the main collider parameters such as the peak and average current, the emittances, the damping time, the repetition frequency and consequently the luminosity are determined by the positron beam characteristics. In this work, the conventional positron sources and their main properties are explored for giving an indication to the challenges that apply during the design of the advanced accelerator concepts. The photon-driven positron sources as the novel approach proposed, primarily for the future linear colliders, are described highlighting their variety and problematic.

47 OTHER INSTRUMENTATION↗

A smart alarm for particle accelerator beamline operations

We present the initial results of a proof-of-concept 'smart alarm' for the Continuous Electron Beam Accelerator Facility injector beamline at Jefferson Lab. To minimize machine downtime and improve operational efficiency, an autonomous alarm system able to identify and diagnose unusual machine states is needed. Our approach leverages a trained neural network capable of alerting operators (a) when an anomalous condition exists in the beamline and (b) identifying the element setting that is the root cause. The tool is based on an inverse model that maps beamline readings (diagnostic readbacks) to settings (beamline attributes operators can modify). The model takes as input readings from the machine and computes machine settings which are compared to control setpoints. Instances where predictions differ from setpoints by a user-defined threshold are flagged as anomalous. Given data corresponding to 354 anomalous injector configurations, the model can narrow the root cause of an anomalous condition to three potential candidates with 94.6% accuracy. Furthermore, compared to the current method of identifying anomalous conditions which raises an alarm when machine parameters drift outside their normal tolerances, the data-driven model can identify 83% more anomalous conditions.

43 PARTICLE ACCELERATORS↗

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗

Nanometer-scale prebunched electron beams generated from all-optical plasma-based acceleration

High-quality and prebunched electron beams can produce coherent x-rays with high intensity and narrow bandwidth, which are essential for modern light sources. An all-optical scheme based on plasma-based acceleration for producing bright electron beams that are prebunched on the nanometer scale is proposed. By using a density modulation created by two low intensity counterpropagating lasers, the phase velocity of the plasma wake excited by an intense driver laser in a uniform plasma can be modulated at a frequency twice that of the colliding lasers, thus turning the injection on and off. The injected electrons are microbunched at the Doppler-shifted modulated wavelength, corresponding to the phase velocity of the gradually expanding wakefield. It is demonstrated that by controlling the properties of the drive and colliding lasers, beams with exotic prebunched structures can be produced, which may have critical applications in ultrafast high power x-rays. This extremely compact, all-optical scheme for producing ultrabright prebunched electron beams may therefore enable novel applications for ultrafast x-ray users and arouse general interest in various fields.

Beam injection, extraction & transport↗

Overcoming timestep limitations in boosted-frame particle-in-cell simulations of plasma-based acceleration

Explicit electromagnetic Particle-In-Cell (PIC) codes are typically limited by the Courant- Friedrichs-Lewy (CFL) condition, which implies that the timestep multiplied by the speed of light must be smaller than the smallest cell size. In the case of boosted-frame PIC simulations of plasma-based acceleration, this limitation can be a major hinderance as the cells are often very elongated along the longitudinal direction and the timestep is thus limited by the small, transverse cell size. This entails many small-timestep PIC iterations, and can limit the potential speed-up of the boosted-frame technique. Here, by using a CFL-free analytical spectral solver, and by mitigating additional numerical instabilities that arise at large timestep, we show that it is possible to overcome traditional limitations on the timestep and thereby realize the full potential of the boosted-frame technique over a much wider range of parameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fabrication of the Fermilab Pre-Series Cold Mass for the HL-LHC Accelerator Upgrade Project

Fermilab is fabricating ten full length cold masses for the high-luminosity Large Hadron Collider Accelerator Upgrade Project (HL-LHC AUP). One practice assembly and one pre-series assembly have been completed. Here this paper summarizes the construction details. Topics include incoming inspection, bus assembly, component machining, shell forming, beam tube insertion, bus expansion loop installation, instrumentation installation, electrical testing, heat exchanger installation and final assembly welding. In-process surveys, alignment measurements and testing are presented and explained. Problems encountered during construction and their solutions are discussed.

43 PARTICLE ACCELERATORS↗

Performance of an optical TPC Geant4 simulation with opticks GPU-accelerated photon propagation

We investigate the performance of Opticks, a NVIDIA OptiX API 7.5 GPU-accelerated photon propagation tool compared with a single-threaded Geant4 simulation. We compare the simulations using an improved model of the NEXT-CRAB-0 gaseous time projection chamber. Performance results suggest that Opticks improves simulation speeds by between 58.47 ± 0.02 and 181.39 ± 0.28 times relative to a CPU-only Geant4 simulation and these results vary between different types of GPU and CPU. A detailed comparison shows that the number of detected photons, along with their times and wavelengths, are in good agreement between Opticks and Geant4.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Toward particle accelerator machine state embeddings as a modality for large language models

Understanding and diagnosing the state of a particle accelerator requires navigating high-dimensional control system data, often involving hundreds of interdependent parameters. We propose a novel multimodal embedding framework that jointly learns representations of machine states from both numerical control system readouts and natural language descriptions. This enables the translation of complex machine conditions into human-readable summaries while maintaining fidelity to the underlying physical system. The obtained embeddings are subsequently adapted to an open-weights large language model via cross-attention conditioning. We demonstrate a first implementation trained on European XFEL machine state data. This work covers the embedding model architecture, training methodology, and presents initial examples demonstrating the model's capabilities in action. Due to the general concept of machine state, the model can be easily adapted to other facilities and control system environments.

Accelerator Physics↗