High‐repetition‐rate operation of a double‐discharge electron beam generator

1996 ◽  
Vol 35 (5) ◽  
pp. 1330 ◽  
Author(s):  
Mircea Udrea
Keyword(s):  
Electron Beam ◽  
Repetition Rate ◽  
High Repetition Rate ◽  
High Repetition ◽  
Double Discharge

Electron-beam-pumped high-repetition-rate KrF laser system

2000 ◽  
Author(s):  
Eiichi Takahashi ◽  
Isao Okuda ◽  
Yuji Matsumoto ◽  
Isao Matsushima ◽  
Susumu Kato ◽  
...  
Keyword(s):  
Electron Beam ◽  
Repetition Rate ◽  
Laser System ◽  
High Repetition Rate ◽  
High Repetition ◽  
Krf Laser

High-Repetition-Rate Electron-Beam-Pumped KrF Laser Technology for Inertial-Fusion-Energy Drivers

2001 ◽  
Vol 40 (Part 1, No. 2B) ◽  
pp. 1152-1155 ◽  
Author(s):  
Isao Okuda ◽  
Eiichi Takahashi ◽  
Isao Matsushima ◽  
Yuji Matsumoto ◽  
Susumu Kato ◽  
...  
Keyword(s):  
Electron Beam ◽  
Repetition Rate ◽  
Fusion Energy ◽  
High Repetition Rate ◽  
Inertial Fusion ◽  
Inertial Fusion Energy ◽  
Laser Technology ◽  
High Repetition ◽  
Krf Laser

scholarly journals Accurate prediction of mega-electron-volt electron beam properties from UED using machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhe Zhang ◽  
Xi Yang ◽  
Xiaobiao Huang ◽  
Junjie Li ◽  
Timur Shaftan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Electron Beam ◽  
Real Time ◽  
Repetition Rate ◽  
High Repetition Rate ◽  
Detailed Knowledge ◽  
Full Potential ◽  
Single Shot ◽  
Noninvasive Diagnostics ◽  
High Repetition

AbstractTo harness the full potential of the ultrafast electron diffraction (UED) and microscopy (UEM), we must know accurately the electron beam properties, such as emittance, energy spread, spatial-pointing jitter, and shot-to-shot energy fluctuation. Owing to the inherent fluctuations in UED/UEM instruments, obtaining such detailed knowledge requires real-time characterization of the beam properties for each electron bunch. While diagnostics of these properties exist, they are often invasive, and many of them cannot operate at a high repetition rate. Here, we present a technique to overcome such limitations. Employing a machine learning (ML) strategy, we can accurately predict electron beam properties for every shot using only parameters that are easily recorded at high repetition rate by the detector while the experiments are ongoing, by training a model on a small set of fully diagnosed bunches. Applying ML as real-time noninvasive diagnostics could enable some new capabilities, e.g., online optimization of the long-term stability and fine single-shot quality of the electron beam, filtering the events and making online corrections of the data for time-resolved UED, otherwise impossible. This opens the possibility of fully realizing the potential of high repetition rate UED and UEM for life science and condensed matter physics applications.

Initial testing of a high-repetition-rate electron-beam-pumped KrF laser amplifier

2001 ◽  
Vol 72 (5) ◽  
pp. 623-626 ◽  
Author(s):  
I. Okuda ◽  
J. Ma ◽  
E. Takahashi ◽  
I. Matsushima ◽  
Y. Matsumoto ◽  
...  
Keyword(s):  
Electron Beam ◽  
Repetition Rate ◽  
High Repetition Rate ◽  
Laser Amplifier ◽  
Initial Testing ◽  
High Repetition ◽  
Krf Laser
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