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[n] D. Wang, A. DeSimone, and G. Ha, “Enabling arbitrary correlations in beam phase space via curve matching”, in Proc. IPAC'25, Taipei, Taiwan, Jun. 2025, pp. 3166-3169. doi:10.18429/JACoW-IPAC2025-THPS098
[n] R. Robles, A. Edelen, W. Lou, C. Mayes, and R. Roussel, “Efficient computation of two-dimensional coherent synchrotron radiation with neural networks”, in Proc. IPAC'23, Venice, Italy, May 2023, pp. 2892-2895. doi:10.18429/JACoW-IPAC2023-WEPA105
[n] C. Leon, A. Scheinker, N. Yampolsky, and P. Anisimov, “Generalization ability of convolutional neural networks trained for coherent synchrotron radiation computations”, in Proc. LINAC'24, Chicago, IL, USA, Aug. 2024, pp. 219-222. doi:10.18429/JACoW-LINAC2024-MOPB081
[n] K. Shipman, D. Patrick, M. Sanchez Barrueta, Q. Marksteiner, R. Hemphill, and H. Xu, “Magnetic focusing architecture for a compact electron buncher”, in Proc. IPAC'24, Nashville, TN, USA, May 2024, pp. 153-155. doi:10.18429/JACoW-IPAC2024-MOPC41
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References
- D. Wang, A. DeSimone, and G. Ha, “Enabling arbitrary correlations in beam phase space via curve matching”, in Proc. 16th Int. Particle Accelerator Conf. (IPAC'25), Taipei, Taiwan, Jun. 2025, paper THPS098, pp. 3166-3169.
- R. Robles, A. Edelen, W. Lou, C. Mayes, and R. Roussel, “Efficient computation of two-dimensional coherent synchrotron radiation with neural networks”, in Proc. 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper WEPA105, pp. 2892-2895.
- C. Leon, A. Scheinker, N. Yampolsky, and P. Anisimov, “Generalization ability of convolutional neural networks trained for coherent synchrotron radiation computations”, in Proc. 32nd Linear Accelerator Conf. (LINAC'24), Chicago, IL, USA, Aug. 2024, pp. 219-222.
- K. Shipman, D. Patrick, M. Sanchez Barrueta, Q. Marksteiner, R. Hemphill, and H. Xu, “Magnetic focusing architecture for a compact electron buncher”, in Proc. 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper MOPC41, pp. 153-155.
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