Abstract
Future machines such as the electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations which require millions of turns. Until recently, most of the methods used linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a symplectic way up to an arbitrary order and colliding them at each turn. The code is called GHOST for GPU-accelerated High-Order Symplectic Tracking. As of now, there is no other code in existence that can accurately model the single-particle non-linear dynamics and the beam-beam effect at the same time for a large enough number of turns required to verify the long-term stability of a collider. Our approach relies on a matrix-based, arbitrary-order, symplectic particle tracking for beam transport and the Bassetti-Erskine approximation for the beam-beam interaction.
| Original language | English |
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| Title of host publication | IPAC 2017 - Proceedings of the 8th International Particle Accelerator Conference |
| Publisher | Joint Accelerator Conferences Website - JACoW |
| Pages | 3918-3920 |
| Number of pages | 3 |
| ISBN (Electronic) | 9783954501823 |
| State | Published - Jul 2017 |
| Externally published | Yes |
| Event | 8th International Particle Accelerator Conference, IPAC 2017 - Bella Conference Center, Denmark Duration: May 14 2017 → May 19 2017 |
Publication series
| Name | IPAC 2017 - Proceedings of the 8th International Particle Accelerator Conference |
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Conference
| Conference | 8th International Particle Accelerator Conference, IPAC 2017 |
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| Country/Territory | Denmark |
| City | Bella Conference Center |
| Period | 05/14/17 → 05/19/17 |
Funding
∗ We are thankful for the generous support of the Old Dominion University Research Foundation through the Research Seed Funding Program 15-492. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 GPU used for this research. We acknowledge the support of Jefferson Lab grant to Old Dominion University 16-347. Authored by Jefferson Science Associates, LLC under U.S. DOE Contract No. DE-AC05-06OR23177 and DE-AC02-06CH11357. † [email protected]