A5055560315- Particle accelerators and beam dynamics
- Particle Accelerators and Free-Electron Lasers
- Particle Detector Development and Performance
- Laser-Plasma Interactions and Diagnostics
- Advanced Multi-Objective Optimization Algorithms
- Magnetic confinement fusion research
- Gyrotron and Vacuum Electronics Research
- Magnetic Properties and Applications
- Advanced X-ray Imaging Techniques
- Plasma Diagnostics and Applications
- Scientific Computing and Data Management
- Pulsed Power Technology Applications
- Gaussian Processes and Bayesian Inference
- Advancements in Photolithography Techniques
- Radiation Detection and Scintillator Technologies
- Electron and X-Ray Spectroscopy Techniques
- Nuclear Physics and Applications
- Microfluidic and Capillary Electrophoresis Applications
- Vacuum and Plasma Arcs
- Electric Motor Design and Analysis
- Superconducting Materials and Applications
- Photocathodes and Microchannel Plates
- Radiation Effects in Electronics
- Nuclear reactor physics and engineering
- Parallel Computing and Optimization Techniques
SLAC National Accelerator Laboratory
2022-2025
University of California, Los Angeles
2016-2021
University of Chicago
2021
Characterizing the phase space distribution of particle beams in accelerators is a central part understanding beam dynamics and improving accelerator performance. However, conventional analysis methods either use simplifying assumptions or require specialized diagnostics to infer high-dimensional (>2D) properties. In this Letter, we introduce general-purpose algorithm that combines neural networks with differentiable tracking efficiently reconstruct distributions without using manipulations....
Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design model calibration simulations. The effectiveness of discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. community has recognized advantages Bayesian algorithms, which leverage statistical surrogate models objective functions effectively address challenges,...
Next-generation accelerator concepts, which hinge on the precise shaping of beam distributions, demand equally diagnostic methods capable reconstructing distributions within six-dimensional position-momentum spaces. However, characterization intricate features using current techniques necessitates a substantial number measurements, many hours valuable time. Novel phase space reconstruction are needed to reduce measurements required reconstruct detailed, high-dimensional in order resolve...
Recent studies of the performance radio-frequency (rf) copper cavities operated at cryogenic temperatures have shown a dramatic increase in maximum achievable surface electric field. We propose to exploit this development enable new generation photoinjectors that may attain, through enhancement launch field photocathode, significant five-dimensional electron beam brightness. present detailed dynamics associated with such system, by examining an S-band photoinjector $250\text{ }\text{...
Particle accelerators require constant tuning during operation to meet beam quality, total charge and particle energy requirements for use in a wide variety of physics, chemistry biology experiments. Maximizing the performance an accelerator facility often necessitates multiobjective optimization, where operators must balance trade-offs between multiple competing objectives simultaneously, using limited, temporally expensive observations. Usually, optimization problems are solved off-line,...
Beams with cross-plane coupling or extreme asymmetries between the two transverse phase spaces are often encountered in particle accelerators. Flat beams large transverse-emittance ratios critical for future linear colliders. Similarly, magnetized significant expected to enhance performance of electron cooling hadron beams. Preparing these requires precise control and characterization four-dimensional space. In this study, we employ generative phase-space reconstruction techniques rapidly...
Ultrafast electron diffraction using MeV energy beams(MeV-UED) has enabled unprecedented scientific opportunities in the study of ultrafast structural dynamics a variety gas, liquid and solid state systems. Broad applications usually pose different requirements for probe properties. Due to complex, nonlinear correlated nature accelerator systems, beam property optimization is time-taking process often relies on extensive hand-tuning by experienced human operators. Algorithm based efficient...
Abstract Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-Objective Optimization (MOO) is particularly challenging due to trade-offs between the Evolutionary algorithms, such as genetic algorithm (GA), have been leveraged for many problems, however, they do not apply complex control problems by design. This paper demonstrates power differentiability solving MOO using a Deep Differentiable Reinforcement Learning (DDRL) in particle accelerators....
Tuning particle accelerators is a challenging and time-consuming task that can be automated carried out efficiently using suitable optimization algorithms, such as model-based Bayesian techniques. One of the major advantages algorithms ability to incorporate prior information about beam physics historical behavior into model used make control decisions. In this work, we examine incorporating accelerator by utilizing fast executing, neural network models trained on simulated or datasets mean...
Plasma wakefields can enable very high accelerating gradients for frontier energy particle accelerators, in excess of 10 GeV/m. To overcome limits on total acceleration achievable, specially shaped drive beams be used both linear and nonlinear plasma wakefield accelerators (PWFA), to increase the transformer ratio, implying that beam deceleration is minimized relative obtained wake. In this Letter, we report results a PWFA, ratio experiment using high-charge, longitudinally asymmetric cell....
Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects magnetic, mechanical, and material components accelerators often neglected models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis not negligible high precision In this Letter, we combine the classical Preisach model with machine learning techniques efficiently create nonparametric,...
Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of accelerated beam response to accelerator input parameters is of-ten first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical extended higher dimensional spaces, complicated measurement constraints present, or prior information known about scarce. In this...
Abstract Ultrafast electron diffraction using MeV energy beams(MeV-UED) has enabled unprecedented scientific opportunities in the study of ultrafast structural dynamics a variety gas, liquid and solid state systems. Broad applications usually pose different requirements for probe properties. Due to complex, nonlinear correlated nature accelerator systems, beam property optimization is time-taking process often relies on extensive hand-tuning by experienced human operators. Algorithm based...
Recent studies of the performance radio-frequency (RF) copper cavities operated at cryogenic temperatures have shown a dramatic increase in maximum achievable surface electric field. We propose to exploit this development enable new generation photoinjectors that may attain, through enhancement launch field photocathode, significant five-dimensional electron beam brightness. present detailed dynamics associated with such system, by examining an S-band photoinjector 250 MV/m peak reaches...
We report the development of a multileaf collimator (MLC) for charged particle beams, based on independently actuated tungsten strips that can selectively scatter unwanted particles. The MLC is used in conjunction with an emittance exchange beamline to rapidly generate highly variable longitudinal bunch profiles. developed consists 40 independent leaves are 2 mm wide and move up 10 operates ultrahigh vacuum environment, enabled by novel features such as magnetically coupled actuation. An...
Tuning particle accelerators is a challenging and time-consuming task, but can be automated carried out efficiently through the use of suitable optimization algorithms. With successful applications at various facilities, Bayesian using Gaussian process modeling has proven to particularly powerful tool address these challenges in practice. One its major benefits that it allows incorporating prior information, such as knowledge about shape objective function or predictions based on archived...
Transverse beam emittance plays a key role in the performance of high-brightness accelerators. Characterizing is often carried out using quadrupole scan, which fits matrix elements to experimental measurements first-order dynamics. Despite its simplicity at face value, this procedure difficult automate due practical limitations. Key issues that must be addressed include maintaining size measurement validity by keeping beams within radius diagnostic screens, ensuring fitting produces...
In this article we examine recent developments in the research area concerning creation of end-to-end models for complete optimization measuring instruments. The consider rely on differentiable programming methods and specification a software pipeline including all factors impacting performance -- from data-generating processes to their reconstruction extraction inference parameters interest instrument along with careful utility function well aligned end goals experiment. Building previous...
Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design model calibration simulations. The effectiveness of discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. community has recognized advantages Bayesian algorithms, which leverage statistical surrogate models objective functions effectively address challenges,...
Bayesian optimization has been shown to be a powerful tool for solving black box problems during online accelerator optimization. The major advantage of based techniques is the ability include prior information about problem speed up optimization, even if that not perfectly correlated with experimental measurements. In parallel, neural network surrogate system models facilities are increasingly being made available, but at present they widely used in this work, we demonstrate use an...
Present-day and next-generation accelerators, particularly for applications in driving wakefield-based schemes, require longitudinal beam shaping attendant characterization experimental optimization. Here we present a diagnostic method which reconstructs the profile at location of wakefield-generating source. The methods presented derive charged particle solely from measurement time-resolved centroid energy change due to wakefield effects. reconstruction technique is based on deconvolution...