Home > Publications database > The application of encoder–decoder neural networks in high accuracy and efficiency slit-scan emittance measurements > print

001     599968
005     20250715173521.0
024 7 _ |a 10.1016/j.nima.2023.168125
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024 7 _ |a 0167-5087
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024 7 _ |a 1872-9576
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024 7 _ |a arXiv:2207.09144
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088 _ _ |a arXiv:2207.09144
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100 1 _ |a Ma, S.
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245 _ _ |a The application of encoder–decoder neural networks in high accuracy and efficiency slit-scan emittance measurements
260 _ _ |a Amsterdam
|c 2023
|b North-Holland Publ. Co.
336 7 _ |a article
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520 _ _ |a A superconducting radio-frequency (SRF) photo injector is in operation at the electron linac for beams with high brilliance and low emittance (ELBE) radiation center and generates continuous wave (CW) electron beams with high average current and high brightness for user operation since 2018. The speed of emittance measurement at the SRF gun beamline can be increased by improving the slit-scan system, thus the measurement time for one phase space mapping can be shortened from about 15 min to 90 s. The convolution neural networks are applied to improve the efficiency and accuracy of beamlet images processing. In order to estimate the uncertainty in the calculation of normalized emittance, we analyze the main error contributions.
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650 _ 7 |a SRF photo injectors
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650 _ 7 |a Beam emittance
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650 _ 7 |a Slit-scan
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650 _ 7 |a Machine learning
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700 1 _ |a Arnold, A.
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700 1 _ |a Michel, P.
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700 1 _ |a Murcek, P.
|b 3
700 1 _ |a Ryzhov, A.
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700 1 _ |a Schaber, J.
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700 1 _ |a Steinbrück, R.
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700 1 _ |a Evtushenko, P.
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700 1 _ |a Teichert, J.
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700 1 _ |a Hillert, W.
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700 1 _ |a Xiang, R.
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700 1 _ |a Zhu, J.
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773 _ _ |a 10.1016/j.nima.2023.168125
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787 0 _ |a Ma, S. et.al.
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|t The application of machine learning in high accuracy and efficiency slit-scan emittance measurements
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