A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
Particle accelerators are complex systems that focus, guide, and accelerate intense charged
particle beams to high energy. Beam diagnostics present a challenging problem due to …
particle beams to high energy. Beam diagnostics present a challenging problem due to …
[HTML][HTML] Structural biology in the age of X-ray free-electron lasers and exascale computing
Serial femtosecond X-ray crystallography has emerged as a powerful method for
investigating biomolecular structure and dynamics. With the new generation of X-ray free …
investigating biomolecular structure and dynamics. With the new generation of X-ray free …
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 …
energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model …
Multiple-core-hole resonance spectroscopy with ultraintense X-ray pulses
Understanding the interaction of intense, femtosecond X-ray pulses with heavy atoms is
crucial for gaining insights into the structure and dynamics of matter. One key aspect of …
crucial for gaining insights into the structure and dynamics of matter. One key aspect of …
X-ray-induced atomic transitions via machine learning: A computational investigation
Intense x-ray free-electron laser pulses can induce multiple sequences of one-photon
ionization and accompanying decay processes in atoms, producing highly charged atomic …
ionization and accompanying decay processes in atoms, producing highly charged atomic …
Phenomenological model of a free-electron laser using machine learning
AM Kalitenko - Physica Scripta, 2023 - iopscience.iop.org
Free electron lasers (FELs) are used in various fields of scientific research. Programs and
methods are created for their design and calibration. The development of machine learning …
methods are created for their design and calibration. The development of machine learning …
Electronic Population Reconstruction from Strong-Field-Modified Absorption Spectra with a Convolutional Neural Network
D Richter, A Magunia, M Rebholz, C Ott, T Pfeifer - Optics, 2024 - mdpi.com
We simulate ultrafast electronic transitions in an atom and corresponding absorption line
changes with a numerical, few-level model, similar to previous work. In addition, a …
changes with a numerical, few-level model, similar to previous work. In addition, a …
Applying Machine‐Learning Methods to Laser Acceleration of Protons: Lessons Learned From Synthetic Data
R Desai, T Zhang, JJ Felice, R Oropeza… - … to Plasma Physics, 2024 - Wiley Online Library
In this study, we consider three different machine‐learning methods—a three‐hidden‐layer
neural network, support vector regression, and Gaussian process regression—and compare …
neural network, support vector regression, and Gaussian process regression—and compare …
[PDF][PDF] Structural Biology in the age of X-ray Free Electron Lasers and Exascale Computing Sandra Mous, Frédéric Poitevin, Mark S. Hunter, Dilipkumar N. Asthagiri
TL Beck - newswise.com
Serial femtosecond X-ray crystallography has emerged as a powerful method for
investigating biomolecular structure and dynamics. With the new generation of X-ray free …
investigating biomolecular structure and dynamics. With the new generation of X-ray free …