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At least 271 records · Page 15

Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements

Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing the reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities.

Kim, Seongyeol [Pohang Univ. of Science and Techno↗

RF Sources for Electron Accelerators With a focus on high-duty-factor, low-to-moderate energy architectures

A charged particle, such as an electron or a proton, is accelerated through its interaction with either a static (DC) or time-varying (RF) electric field. The magnitude of the accelerating field, or gradient, is typically given in units of volts per meter; in charged-particle accelerators, fields are usually expressed as kV/m or MV/m. The energy of the accelerated particle is usually expressed in terms of electron volts, or eV. An electron starting at rest at ground potential, and accelerated to an electrode with a potential of 1 kV, will have an energy of 1 keV.

43 PARTICLE ACCELERATORS↗

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗

Machine learning at the Spallation Neutron Source accelerator and target

We describe the ongoing efforts to apply Machine Learning techniques to improve the performance of our accelerator and target. Specially, we are looking to minimize halo beam losses in the absence of a proper physics model, automatically detect and log anomalies in the target support systems such as cooling, and detect and prevent errant beam pulses in the linac. We also describe the infrastructure we use to acquire and stream data to the GPU cluster for training, our code development cycle, and edge computing for model inference. To minimize halo beam losses, we use a Reinforcement Learning technique tested on a virtual accelerator. The target anomaly detection is trained on archived data using incomplete physics models and is made part of the existing target reporting system. The errant beam prevention analyzes beam current and beam phase waveforms as well as accelerator configuration data to predict errant pulses. We also develop continual learning to adapt to changes in the accelerator.

Accelerator Physics↗

Simulation study of high-current 7 Li 3+ beam acceleration with laser ion source and RFQ linac using direct plasma injection

Accelerator-based neutron sources (ABNS) utilizing the 7 Li(p,n) 7 Be reaction in inverse kinematics offer strong forward-directed neutron emission, making them attractive for compact and clean neutron source with low background neutrons and unwanted radiation. However, practical use of such systems requires lithium ion beam currents that exceed the capability of conventional ion accelerators by two orders of magnitude. In this study, we numerically designed and evaluated a high-current acceleration system based on a direct plasma injection scheme (DPIS), combining a laser ion source (LIS) and a radio-frequency quadrupole (RFQ) linac. The ion extraction optics and RFQ entrance were optimized using IGUN, OPERA, and GPT, demonstrating that over 1.2 A-class beam current can be injected into the RFQ. The RFQ structure was designed under realistic engineering constraints including surface field strength (Kilpatrick factor) and RF power. GPT simulations showed that a 370 mA 7 Li 3+ beam can be successfully accelerated within a ±10 % energy spread. To validate downstream compatibility, we also designed a simplified medium-energy beam transport (MEBT) section and an interdigital H-type (IH) linac, confirming successful acceleration of a 320 mA beam to the total energy of 14 MeV. These results support the feasibility of the DPIS and RFQ approach as a promising solution for compact neutron sources and other high-intensity ion beam applications.

43 PARTICLE ACCELERATORS↗

Accelerated oxidation of epoxy thermosets with increased O 2 pressure

Polymer oxidation is usually accelerated with temperature, which is therefore applied in nearly every experimental approach dealing with predictive materials aging. Because of this simple approach, we may tend to neglect that the effective concentration of oxygen also acts as a rate multiplier for oxidation. Increasing the oxygen partial pressure in an aging environment accelerates oxidation, and while there is often a near proportional increase initially, the effect of additional oxygen usually transitions to a saturation level at some elevated pressure. This has been theoretically described in the general autoxidation scheme and is well recognized. However, for many materials the exact rate behavior under moderately increased oxygen concentration remains to be established. We therefore review epoxy oxidation and offer a broader overview of its behavior under increased O 2 partial pressure. Experimental data are given for a few thermoset materials demonstrating their rate behavior under O 2 partial pressure up to 4 atm, meaning approximately 20 times more than under standard atmospheric conditions. Confirmative evidence suggests that epoxy materials will reach saturation oxidation rates only at significantly higher O 2 partial pressure. In such a high-pressure regime it is theoretically possible to not only accelerate oxidation, but to transition into a condition where O 2 diffusion can be increased without further accelerating the oxidation rate. Finally, this can reduce diffusion limited oxidation effects under specific accelerated aging conditions as a combination of temperature and O 2 partial pressure.

36 MATERIALS SCIENCE↗

Multi-beam operation of LANSCE accelerator facility

The Los Alamos Neutron Science Center (LANSCE) accelerator facility has been in operation for 50 years performing important scientific support for national security. The unique feature of the LANSCE accelerator facility is multi-beam operation, delivering beams to five experimental areas. The near-term plans are to replace obsolete and almost end-of-life systems of the LANSCE linear accelerator with a modern 100-MeV Front End with significant improvement in beam quality. This paper summarizes experimental results obtained during the operation of the LANSCE accelerator facility and considers plans to expand the performance of the accelerator for near- and long-term operations.

47 OTHER INSTRUMENTATION↗

Extending JuTrack’s capabilities to the FRIB accelerator to enhance online modeling

JuTrack is a Julia-based accelerator modeling and tracking package that utilizes compiler-level automatic differentiation (AD) to enable fast and accurate derivative calculations. While JuTrack provides a solid foundation for beam dynamics simulations, its capabilities must be extended to support the Facility for Rare Isotopes (FRIB) linac. This includes modeling heavy-ion linac accelerator components such as the liquid-lithium charge stripper, which facilitates efficient acceleration by remove electrons from heavy isotopes, and incorporating multi-charge state acceleration tracking, which allows for charge-dependent beam dynamics. These extensions address challenges such as the beam matching and optimization of multi charge state through various accelerating structures and beam-material interaction modeling while maintaining the auto differentiation capability. This work focuses on adapting JuTrack to incorporate these elements, enhancing its online modeling abilities. We present modifications to JuTrack’s framework and demonstrate their performance in FRIB simulations.

Accelerator Physics↗

High-Power Targetry R&D for Next-Generation Accelerator Target Facilities

Beam-intercepting devices such as beam windows and particle-production targets are critical components of accelerator target facilities for High Energy Physics (HEP) experiments. The high-power, pulsed structure of the particle beams used for these experiments leads to thermal shock and high-cycle fatigue in addition to radiation damage resulting from the accumulated particle fluence. This can lead to degradation of the target system s mechanical and thermal properties; considerably reducing their lifetimes and presenting substantial challenges to reliable operation of multi-MW class facilities. Recently several major accelerator facilities have been forced to operate at reduced power levels due to target survivability concerns. Furthermore, at Fermilab it is planned to increase the neutrino production beam power up to 2.4 MW in coming years. Therefore, timely R&D on the irradiated behavior of target system materials is critical to efficient operation of accelerator facilities and full utilization of recent accelerator power upgrades for HEP research. This talk will begin with an overview of high-power targetry, and the significant challenges presented by beam power increases expected for future HEP experiments. We will then cover several past materials irradiation studies that have been completed by the High-Power Targetry R&D group at Fermilab and its collaborators on common accelerator and target materials such as graphite, beryllium, titanium, and tungsten. Finally, we will conclude with a discussion of two novel materials investigations under way within the group; high-entropy alloys for beam window applications, and electrospun nanofibers to serve as particle production targets.

43 PARTICLE ACCELERATORS↗

A Scalable, High-Efficiency, Low-Energy-Spread Laser Wakefield Accelerator Using a Tri-Plateau Plasma Channel

The emergence of multi-petawatt laser facilities is expected to push forward the maximum energy gain that can be achieved in a single stage of a laser wakefield acceleration (LWFA) to tens of giga-electron volts, which begs the question—is it likely to impact particle physics by providing a truly compact particle collider? Colliders have very stringent requirements on beam energy, acceleration efficiency, and beam quality. In this article, we propose an LWFA scheme that can for the first time simultaneously achieve hitherto unrealized acceleration efficiency from the laser to the electron beam of >20% and a sub-1% energy spread using a stepwise plasma structure and a nonlinearly chirped laser pulse. Three-dimensional high-fidelity simulations show that the nonlinear chirp can effectively mitigate the laser waveform distortion and lengthen the acceleration distance. This, combined with an interstage rephasing process in the stepwise plasma, can triple the beam energy gain compared to that in a uniform plasma for a fixed laser energy, thereby dramatically increasing the efficiency. A dynamic beam loading effect can almost perfectly cancel the energy chirp that arises during the acceleration, leading to the sub-percent energy spread. This scheme is highly scalable and can be applied to petawatt LWFA scenarios. Scaling laws are obtained, which suggest that electron beams with parameters relevant for a Higgs factory could be reached with the proposed high-efficiency, low-energy-spread scheme.

43 PARTICLE ACCELERATORS↗

Spatiotemporal processing of linear acceleration: primary afferent and central vestibular neuron responses

Spatiotemporal convergence and two-dimensional (2-D) neural tuning have been proposed as a major neural mechanism in the signal processing of linear acceleration. To examine this hypothesis, we studied the firing properties of primary otolith afferents and central otolith neurons that respond exclusively to horizontal linear accelerations of the head (0.16-10 Hz) in alert rhesus monkeys. Unlike primary afferents, the majority of central otolith neurons exhibited 2-D spatial tuning to linear acceleration. As a result, central otolith dynamics vary as a function of movement direction. During movement along the maximum sensitivity direction, the dynamics of all central otolith neurons differed significantly from those observed for the primary afferent population. Specifically at low frequencies (</=0.5 Hz), the firing rate of the majority of central otolith neurons peaked in phase with linear velocity, in contrast to primary afferents that peaked in phase with linear acceleration. At least three different groups of central response dynamics were described according to the properties observed for motion along the maximum sensitivity direction. "High-pass" neurons exhibited increasing gains and phase values as a function of frequency. "Flat" neurons were characterized by relatively flat gains and constant phase lags (approximately 20-55 degrees ). A few neurons ("low-pass") were characterized by decreasing gain and phase as a function of frequency. The response dynamics of central otolith neurons suggest that the approximately 90 degrees phase lags observed at low frequencies are not the result of a neural integration but rather the effect of nonminimum phase behavior, which could arise at least partly through spatiotemporal convergence. Neither afferent nor central otolith neurons discriminated between gravitational and inertial components of linear acceleration. Thus response sensitivity was indistinguishable during 0.5-Hz pitch oscillations and fore-aft movements. The fact that otolith-only central neurons with "high-pass" filter properties exhibit semicircular canal-like dynamics during head tilts might have important consequences for the conclusions of previous studies of sensory convergence and sensorimotor transformations in central vestibular neurons.

NASA Discipline Neuroscience↗

Horizontal vestibuloocular reflex evoked by high-acceleration rotations in the squirrel monkey. III. Responses after labyrinthectomy

The horizontal angular vestibuloocular reflex (VOR) evoked by high-frequency, high-acceleration rotations was studied in four squirrel monkeys after unilateral labyrinthectomy. Spontaneous nystagmus was measured at the beginning and end of each testing session. During the period that animals were kept in darkness (4 days), the nystagmus at each of these times measured approximately 20 degrees /s. Within 18-24 h after return to the light, the nystagmus (measured in darkness) decreased to 2.8 +/- 1.5 degrees /s (mean +/- SD) when recorded at the beginning but was 20.3 +/- 3.9 degrees /s at the end of the testing session. The latency of the VOR measured from responses to steps of acceleration (3,000 degrees /s(2) reaching a velocity of 150 degrees /s) was 8.4 +/- 0.3 ms for responses to ipsilesional rotations and 7.7 +/- 0.4 ms for contralesional rotations. During the period that animals were kept in darkness after the labyrinthectomy, the gain of the VOR measured during the steps of acceleration was 0.67 +/- 0.12 for contralesional rotations and 0.39 +/- 0.04 for ipsilesional rotations. Within 18-24 h after return to light, the VOR gain for contralesional rotations increased to 0.87 +/- 0.08, whereas there was only a slight increase for ipsilesional rotations to 0.41 +/- 0. 06. A symmetrical increase in the gain measured at the plateau of head velocity was noted after the animals were returned to light. The VOR evoked by sinusoidal rotations of 2-15 Hz, +/-20 degrees /s, showed a better recovery of gain at lower (2-4 Hz) than at higher (6-15 Hz) frequencies. At 0.5 Hz, gain decreased symmetrically when the peak amplitude was increased from 20 to 100 degrees /s. At 10 Hz, gain was decreased for ipsilesional half-cycles and increased for contralesional half-cycles when velocity was raised from 20 to 50 degrees /s. A model incorporating linear and nonlinear pathways was used to simulate the data. Selective increases in the gain for the linear pathway accounted for the recovery in VOR gain for responses at the velocity plateau of the steps of acceleration and for the sinusoidal rotations at lower peak velocities. The increase in gain for contralesional responses to steps of acceleration and sinusoidal rotations at higher frequencies and velocities was due to an increase in the contribution of the nonlinear pathway. This pathway was driven into cutoff and therefore did not affect responses for rotations toward the lesioned side.

NASA Discipline Neuroscience↗

Towards Agentic AI on Particle Accelerators

As particle accelerators grow in complexity, traditional control methods face increasing challenges in achieving optimal performance. This paper envisions a paradigm shift: a decentralized multi-agent framework for accelerator control, powered by Large Language Models (LLMs) and distributed among autonomous agents. We present a proposition of a self-improving decentralized system where intelligent agents handle high-level tasks and communication and each agent is specialized control individual accelerator components. This approach raises some questions: What are the future applications of AI in particle accelerators? How can we implement an autonomous complex system such as a particle accelerator where agents gradually improve through experience and human feedback? What are the implications of integrating a human-in-the-loop component for labeling operational data and providing expert guidance? We show two examples, where we demonstrate viability of such architecture.

43 PARTICLE ACCELERATORS↗

A compact low-level RF control system for advanced concept compact electron linear accelerator

A compact low-level RF (LLRF) control system based on RF system-on-chip (RFSoC) technology has been designed for the Advanced Concept Compact Electron Linear-accelerator (ACCEL) program, which has challenging requirements in both RF performance and size, weight, and power consumption (SWaP). The compact LLRF solution employs the direct RF sampling technique of RFSoC, which samples the RF signals directly without any analog upconversion and downconversion. Compared with the conventional heterodyne based architecture used for the LLRF system of a linear accelerator (LINAC), the elimination of analog mixers can significantly reduce the size and weight of the system, especially with LINAC requiring a larger number of RF channels. Based on the requirements of ACCEL, a prototype LLRF platform has been developed, and the control schemes have been proposed. The prototype LLRF system demonstrated magnitude and phase fluctuation levels below 1% and 1° on the flattop of a 2 μs RF pulse. The LLRF control schemes proposed for ACCEL are implemented with a prototype hardware platform. In conclusion, this paper will introduce the new compact LLRF solution and summarize a selection of experimental test results of the prototype itself and with the accelerating structure cavities designed for ACCEL.

Liu, C. [SLAC National Accelerator Laboratory (SLA↗

Small scale electron linear accelerators for industrial applications

Linear accelerators (linacs), producing electron or X-ray radiation in the MeV range, are critical tools for industrial irradiation, medical device sterilization, food pasteurization, non-destructive testing, security, medical, and many other applications. Many of these applications require compact and flexible radiation sources. In this paper, we present new technologies for small-scale electron linear accelerators and examples of their practical implementations. Furthermore, these developments include low energy accelerators with self-shielding options and form factors, ranging from cabinet-size to hand-portable generators; medium-energy accelerators for novel radiotherapy and security applications; and high-energy 10 MeV linacs capable of reaching 20–35 kW beam power for emerging industrial and phytosanitary applications

43 PARTICLE ACCELERATORS↗

Data Science Shows that Entropy Correlates with Accelerated Zeolite Crystallization in Monte Carlo Simulations

We have performed a data science study of Monte Carlo simulation trajectories to understand factors that can accelerate formation of zeolite nanoporous crystals, a process that can take days or even weeks. In previous work, Monte Carlo simulations predicted and experiments confirmed that using a secondary organic structure-directing agent (OSDA) accelerates crystallization of all-silica LTA zeolite, with experiments finding a three-fold speedup [PCCP 24, 142-148 (2022)]. However, it remains unclear what physical factors cause the speed-up. Here, we apply data science to analyze the simulation trajectories to discover what drives accelerated zeolite crystallization in Monte Carlo going from a one-OSDA synthesis (1OSDA) to a two-OSDA version (2OSDA). We encoded simulation snapshots using the Smooth Overlap of Atomic Positions approach, which represents all 2- and 3-body correlations within a given cutoff distance. Principal component analyses failed to discriminate datasets of structures from 1OSDA and 2OSDA simulations, while the Support Vector Machine (SVM) approach succeeded at classifying such structures with an area-under-curve (AUC) score of 0.99 (where AUC = 1 is a perfect classification) with all 3-body correlations, and as high as 0.94 with only 2-body correlations. SVM decision functions reveal relatively broad / narrow histograms for 1OSDA / 2OSDA datasets, suggesting that the two simulations differ strongly in information heterogeneity. Informed by these results, we performed pair (2-body) entropy calculations during crystallization, resulting in entropy differences that semi-quantitatively account for the speedup observed in the previous Monte Carlo simulations. We conclude that altering synthesis conditions in ways that substantially changes the entropy of labile silica networks may accelerate zeolite crystallization, and we discuss possible approaches for achieving such acceleration.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Experimental demonstration of accelerating a beam with a large transverse emittance ratio in the relativistic heavy ion collider for the electron-ion collider

The electron-ion collider (EIC), to be constructed at Brookhaven National Laboratory, will collide polarized high-energy electron beams with hadron beams, achieving luminosities of up to 1.0 × 10 34 cm −2 s −1 in the center-of-mass energy range of 20–140 GeV. To reach such high luminosity, the EIC will employ small, flat beams at the interaction point. According to the design of the EIC hadron storage ring (HSR), hadron beams with a large transverse emittance ratio of 11:1 will be generated at the injection energy using an electron cooling technique and then accelerated to high energies for collisions. Accelerating hadron beams with such a large emittance ratio had never been demonstrated elsewhere—until our recent beam experiment at the relativistic heavy ion collider (RHIC). In this experiment, we successfully generated a large transverse emittance ratio of 13:1 with a gold-ion beam at 31 GeV/nucleon using stochastic cooling. We then accelerated this beam, with a transverse emittance ratio of 11:1, from 31 to 100 GeV/nucleon. Thanks to RHIC’s high-performance orbit, tune, and decoupling feedback systems, the large emittance ratio was well maintained throughout the 5-min-long acceleration process. This experiment fully validated the EIC/HSR design assumptions—namely, that large-emittance-ratio hadron beams can be generated at injection energy and then accelerated to high energies for collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗