Speaker
Description
One of the greatest challenges for the EIC’s proposed Rapid Cycling Synchrotron will be to achieve high polarization transmission to 18 GeV. While SVD based orbit smoothing should be sufficient to achieve over 99% polarization transmission up to 10 GeV, the growth in the strength of residual imperfection spin resonances make achieving polarization transmission of 90% and above to 18 GeV more difficult when base vertical quadrupole misalignments grow larger than 100 microns. One promising approach is to deploy estimates of the vertical quadrupole misalignments using simple misalignment to BPM response matrices. Using this, the stronger imperfection spin resonances from 10 to 18 GeV can be estimated and corrected using vertical correctors. With this approach, base quadrupole misalignments of up to 200 microns can now be tolerated. However, the existence of dipole rolls limits the effectiveness of this approach since their effect on the orbit as registered at the BPMs is very similar. Here we describe a new approach which leverages machine learning methods to guide perturbations to the lattice that maximize the net Fisher’s Information and thus help increase the accuracy of imperfection spin resonance corrections.
Funding Agency
Work supported by URA., Inc., under contract DE-AC02-76CH03000 with the U.S. Dept. of Energy.
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