1 / 6

GPT - Introduction

GPT - Introduction. ASTRA. ASTRA. GPT. GPT. Gun beamline design has been modelled in GPT, and compared to original ASTRA model Analysis shows that ASTRA and GPT agree very well Differences mainly due to space-charge meshes, as well as small differences between different versions

selina
Download Presentation

GPT - Introduction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GPT - Introduction ASTRA ASTRA GPT GPT • Gun beamline design has been modelled in GPT, and compared to original ASTRA model • Analysis shows that ASTRA and GPT agree very well • Differences mainly due to space-charge meshes, as well as small differences between different versions • GPT model also includes full injector (cathode to linac) • Comparisons between GPT and MAD/Elegant show “relatively” good agreement without space-charge • Re-matched injector (in GPT) with space-charge also shows good agreement • GPT model post-linac has issues • Analysis of focusing in dipoles does not agree between MAD and GPT • Comparison between “Real” machine settings and GPT model agree reasonably well in the injector • Slight tweaks to post-booster matching quadrupoles improve agreement • Low gun voltage (230kV) and gun beamline steering suspected to account for most of the differences

  2. GPT - Modelling • Gun beamline taken from ASTRA model • Machine design mapped automatically from MAD model • Dipole fringe-field parameters taken from fitting 2D field maps • Dipole magnetic lengths optimised to minimise steering effects from fringe fields • Quadrupole fields can be taken directly from the machine • Based on measured calibration curves of Field vs. current

  3. GPT – Modelling • GPT linac model different to MAD model • Post-linac extraction chicane dipoles differ between MAD/GPT • Re-match in MAD post-extraction chicane: FEL Bunch-length vs. Linac Phase Energy Spread vs. Linac Phase

  4. R56 & Dispersion Calculations • Using the data from the previous slides:

  5. Fix dispersion in ST1 • ST1DIP02: 9.5°  8.9°

  6. Fix Dispersion in ST2 • ST2DIP02/03: 21.5°  13.76° !

More Related