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Author: M. Palmer


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Reference
J. Kim et al., “In Situ SEY Measurements at CesrTA”, in Proc. 49th ICFA Advanced Beam Dynamics Workshop on Electron Cloud Physics (ECLOUD'10), Ithaca, NY, USA, Oct. 2010, paper PST12, pp. 140-146.
J. O'Meara and M. Palmer, “Mechanical Design Features of the NAL 200 MeV Linac Injector”, in Proc. 1968 Proton Linear Accelerator Conf. (LINAC'68), Long Island, NY, USA, May 1968, paper A-3, pp. 30-40.
J. Walton, R. Andrews, H. Edwards, and M. Palmer, “An Improved Design for the Fermilab SEPTA”, in Proc. 6th Particle Accelerator Conf. (PAC'75), Washington D.C., USA, Mar. 1975, pp. 1091-1094.
J. Kidd et al., “A High Intensity Beam Dump for the Tevatron Beam Abort System”, in Proc. 9th Particle Accelerator Conf. (PAC'81), Washington D.C., USA, Mar. 1981, pp. 2774-2777.
D. L. Rubin et al., “CESR Status and Performance”, in Proc. 19th Particle Accelerator Conf. (PAC'01), Chicago, IL, USA, Jun. 2001, paper RPPH122, pp. 3520-3522.
M. Palmer, J. Dobbins, D. Hartill, and C. Strohman, “An Upgrade for the Beam Position Monitoring System at the Cornell Electron Storage Ring”, in Proc. 19th Particle Accelerator Conf. (PAC'01), Chicago, IL, USA, Jun. 2001, paper TPAH064, pp. 1360-1362.
D. Sagan, M. G. Billing, and M. Palmer, “Effect on Luminosity from Bunch-to-Bunch Orbit Displacements at CESR”, in Proc. 19th Particle Accelerator Conf. (PAC'01), Chicago, IL, USA, Jun. 2001, paper WOAB004, pp. 347-349.
T. Bolin et al., “Data analysis and control of an MeV ultrafast electron diffraction system and a photocathode laser and gun system using machine learning”, in Proc. 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper MOPA081, pp. 222-225.
X. Chang, J. Hirshfield, M. Palmer, M. Fedurin, and Y. Jiang, “Cyclotron resonance accelerator for electron beams”, in Proc. 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper TUPA062, pp. 1472-1475.
M. Fedurin et al., “Operation the Accelerator Test Facility linac transport beamline by using Artificial Intelegence and Machine Learning Methods”, presented at the 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper THPL016, unpublished.


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