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Author: J. P. Gonzalez-Aguilera


References



Reference
A. Edelen et al., “Detailed Phase Space Reconstruction from Accelerator Beam Measurements Using Differentiable Simulations”, presented at the 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper THPL165, unpublished.
A. Edelen et al., “Progress on combining digital twins and machine learning based control for accelerators at SLAC”, presented at the 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper TUPS72, this conference.
J. P. Gonzalez-Aguilera et al., “Beam Diagnostics for Multi-Objective Bayesian Optimization at the Argonne Wakefield Accelerator Facility”, in Proc. 12th Int. Particle Accelerator Conf. (IPAC'21), Campinas, Brazil, May 2021, pp. 960-962.
J. P. Gonzalez-Aguilera, R. Roussel, A. Edelen, and Y.-K. Kim, “Detailed characterization of coherent synchrotron radiation effects using generative phase space reconstruction”, presented at the 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper WEPG94, this conference.
J. P. Gonzalez-Aguilera, Y.-K. Kim, R. Roussel, A. Edelen, and C. Mayes, “Towards fully differentiable accelerator modeling”, in Proc. 14th Int. Particle Accelerator Conf. (IPAC'23), Venice, Italy, May 2023, paper WEPA065, pp. 2797-2800.
R. Roussel et al., “Efficient 6-dimensional phase space reconstructions from experimental measurements using generative machine learning”, presented at the 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper TUPS73, this conference.
S. Kim et al., “Demonstrations of the 4D phase space reconstruction of flat and magnetized beams using neural-networks and differentiable simulations”, presented at the 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper MOPS77, this conference.


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