WeChat Mini Program
Old Version Features
Activate VIP¥0.73/day
Master AI Research

Beam Loss Monitoring System for the SKIF Synchrotron Light Source

JOURNAL OF INSTRUMENTATION(2022)

Russian Acad Sci

Cited 1|Views17
Abstract
The Siberian ring source of photons (SKIF) is a new 3 GeV fourth-generation synchrotronlight source being developed by the Budker Institute of Nuclear Physics (BINP). A beam lossmonitoring system is necessary to ensure its reliable commissioning and operation. Two typesof beam loss monitors will be installed in the SKIF: 5 fiber-based Cherenkov beam loss monitors(CBLMs) for the linac and transfer lines and 128 scintillator-based beam loss monitors (SBLMs) forthe storage ring. Sophisticated electronic equipment is employed to use these monitors in differentmodes of SKIF operation. The paper describes the design of the SKIF beam loss monitoring systembased on numerical simulations and experimental studies
More
Translated text
Key words
Instrumentation for particle accelerators and storage rings- high energy (linear acceler-ators,synchrotrons),Photon detectors for UV,visible and IR photons (vacuum) (photomultipliers,HPDs,others),Cherenkov and transition radiation,Scintillators,scintillation and light emissionprocesses (solid,gas and liquid scintillators)
上传PDF
Bibtex
收藏
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