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This content will become publicly available on October 15, 2015

Title: Adaptive method for electron bunch profile prediction

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. Thus, the simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. Finally, the main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.
Authors:
 [1] ;  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States)
Publication Date:
OSTI Identifier:
1223578
Report Number(s):
SLAC-PUB-16310; LA-UR-15-24596
Journal ID: ISSN 1098-4402; PRABFM
Grant/Contract Number:
AC02-76SF00515; AC52-06NA25396
Type:
Published Article
Journal Name:
Physical Review Special Topics. Accelerators and Beams
Additional Journal Information:
Journal Volume: 18; Journal Issue: 10; Journal ID: ISSN 1098-4402
Publisher:
American Physical Society (APS)
Research Org:
SLAC National Accelerator Lab., Menlo Park, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; ACCPHY; bunch profiles; 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING