Fabrication and Testing of the Transition Section Between Modules of a Wakefield Accelerator
PHYSICAL REVIEW ACCELERATORS AND BEAMS(2024)
Argonne Natl Lab
Abstract
The fabrication process is presented for a typical transition section located between each cylindrical corrugated waveguide structure comprising the wakefield accelerator module. The transition section includes couplers for extracting the 180 GHz TM01 accelerating mode and separate couplers for extracting the 190 GHz HE11 dipole mode, both modes induced by the electron bunch traversing the cylindrical corrugated waveguide structure. Extraction of the high-power accelerating mode reduces the heat load due to the subterahertz wave power dissipation within the corrugated accelerating structure. Extraction of the low-power dipole mode serves the purpose of detecting the electron bunch transverse oscillations within the wakefield accelerator and identifying the onset of beam breakup instability. Comprehensive testing of the fully functional transition section with an electron beam was done at the Accelerator Test Facility in Brookhaven National Laboratory which verified the functionality of the transition section.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined