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Title: RF Gun Optimization Study

Abstract

Injector gun design is an iterative process where the designer optimizes a few nonlinearly interdependent beam parameters to achieve the required beam quality for a particle accelerator. Few tools exist to automate the optimization process and thoroughly explore the parameter space. The challenging beam requirements of new accelerator applications such as light sources and electron cooling devices drive the development of RF and SRF photo injectors. A genetic algorithm (GA) has been successfully used to optimize DC photo injector designs at Cornell University [1] and Jefferson Lab [2]. We propose to apply GA techniques to the design of RF and SRF gun injectors. In this paper, we report on the initial phase of the study where we model and optimize a system that has been benchmarked with beam measurements and simulation.

Authors:
;
Publication Date:
Research Org.:
Thomas Jefferson National Accelerator Facility, Newport News, VA
Sponsoring Org.:
USDOE - Office of Energy Research (ER)
OSTI Identifier:
909377
Report Number(s):
JLAB-ACP-07-669; DOE/OR/23177-0080
TRN: US0703886
DOE Contract Number:  
AC05-06OR23177
Resource Type:
Conference
Resource Relation:
Conference: 2007 IEEE Particle Accelerator Conference, Albuquerque, NM, 25-30 June 2007
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; ACCELERATORS; ALGORITHMS; DESIGN; ELECTRON COOLING; GENETICS; LIGHT SOURCES; OPTIMIZATION; SIMULATION

Citation Formats

Alicia Hofler, and Pavel Evtushenko. RF Gun Optimization Study. United States: N. p., 2007. Web.
Alicia Hofler, & Pavel Evtushenko. RF Gun Optimization Study. United States.
Alicia Hofler, and Pavel Evtushenko. Tue . "RF Gun Optimization Study". United States. https://www.osti.gov/servlets/purl/909377.
@article{osti_909377,
title = {RF Gun Optimization Study},
author = {Alicia Hofler and Pavel Evtushenko},
abstractNote = {Injector gun design is an iterative process where the designer optimizes a few nonlinearly interdependent beam parameters to achieve the required beam quality for a particle accelerator. Few tools exist to automate the optimization process and thoroughly explore the parameter space. The challenging beam requirements of new accelerator applications such as light sources and electron cooling devices drive the development of RF and SRF photo injectors. A genetic algorithm (GA) has been successfully used to optimize DC photo injector designs at Cornell University [1] and Jefferson Lab [2]. We propose to apply GA techniques to the design of RF and SRF gun injectors. In this paper, we report on the initial phase of the study where we model and optimize a system that has been benchmarked with beam measurements and simulation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2007},
month = {7}
}

Conference:
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