19–24 May 2024
Music City Center
US/Central timezone

Differentiable modeling of Siberian Snakes in BNL’s AGS: nonlinear maps, symplectic tracking, and optical compensation

MOPS03
20 May 2024, 16:00
2h
Blues (MCC Exhibit Hall A)

Blues

MCC Exhibit Hall A

Poster Presentation MC5.D03 Calculations of EM fields Theory and Code Developments Monday Poster Session

Speaker

Eiad Hamwi (Cornell University (CLASSE))

Description

Meaningful prediction and enhancement of spin-polarization in the RHIC and EIC accelerators relies on accurate modeling of each sub-component. While nonlinear beam propagation and symplectic tracking is well established for common accelerator components, it has hitherto not been established for Siberian Snakes, which are essential for the acceleration of polarized protons in storage rings. Here we describe the first differentiable model, applied to both snakes of the AGS, which injects polarized beam into RHIC and the HSR of the EIC. This enables the full power of nonlinear maps to be applied to the AGS, including normal form theory and symplectic tracking. We show how important this is for long-term beam motion in the AGS: without the symplectic representations, simulated particle motion destabilizes during about 1000 turns spent close to injection energy. Including the new snake representations, the Bmad toolkit was used to optimize the closed orbit and the optics between injection and extraction, including corrections to the coupling and to the vertical dispersion that the snakes currently create. Finally, we use simulation results to compare randomly generated lattice misalignments with surveying data measurements.

Funding Agency

Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy, No. DE SC-0024287, and DE-SC0018008.

Region represented North America
Paper preparation format LaTeX

Primary author

Eiad Hamwi (Cornell University (CLASSE))

Co-authors

Georg Hoffstaetter (Cornell University (CLASSE)) Vincent Schoefer (Brookhaven National Laboratory) Weijian Lin (Cornell University (CLASSE))

Presentation materials

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