Optimization Framework for a Radio Frequency Gun Based Injector

Linear accelerator based light sources are used to produce coherent x-ray beams with unprecedented peak intensity. In these devices, the key parameters of the photon beam such as brilliance and coherence are directly dependent on the electron beam parameters. This leads to stringent beam quality requirements for the electron beam source. Radio frequency (RF) guns are used in such light sources since they accelerate electrons to relativistic energies over a very short distance, thus minimizing the beam quality degradation due to space charge effects within the particle bunch. Designing such sources including optimization of its beam parameters is a complex process where one needs to meet many requirements simultaneously. It is useful to have a tool to automate the design optimization in the context of the injector beam dynamics performance. Evolutionary and genetic algorithms are powerful tools to apply to nonlinear multi-objective optimization problems, and they have been successfully used in injector optimizations where the electric field profiles for the accelerating devices are fixed. Here the genetic algorithm based approach is extended to modify and optimize the electric field profile for an RF gun concurrently with the injector performance. Two field modification methods are used. This dissertation presents an overview of the optimization system and examples of its application to a state of the art RF gun. Results indicate improved injector performance is possible with unbalanced electric field profiles where the peak field in the cathode cell is larger than in subsequent cells

Common Graphics Library (CGL). Volume 1: LEZ user's guide

Users are introduced to and instructed in the use of the Langley Easy (LEZ) routines of the Common Graphics Library (CGL). The LEZ routines form an application independent graphics package which enables the user community to view data quickly and easily, while providing a means of generating scientific charts conforming to the publication and/or viewgraph process. A distinct advantage for using the LEZ routines is that the underlying graphics package may be replaced or modified without requiring the users to change their application programs. The library is written in ANSI FORTRAN 77, and currently uses a CORE-based underlying graphics package, and is therefore machine independent, providing support for centralized and/or distributed computer systems

Transferable Output ASCII Data (TOAD) editor version 1.0 user's guide

The Transferable Output ASCII Data (TOAD) editor is an interactive software tool for manipulating the contents of TOAD files. The TOAD editor is specifically designed to work with tabular data. Selected subsets of data may be displayed to the user's screen, sorted, exchanged, duplicated, removed, replaced, inserted, or transferred to and from external files. It also offers a number of useful features including on-line help, macros, a command history, an 'undo' option, variables, and a full compliment of mathematical functions and conversion factors. Written in ANSI FORTRAN 77 and completely self-contained, the TOAD editor is very portable and has already been installed on SUN, SGI/IRIS, and CONVEX hosts

Narrow-Band Emission in Thomson Sources Operating in the High-Field Regime

We present a novel and quite general analysis of the interaction of a high-field chirped laser pulse and a relativistic electron, in which exquisite control of the spectral brilliance of the up-shifted Thomson-scattered photon is shown to be possible. Normally, when Thomson scattering occurs at high field strengths, there is ponderomotive line broadening in the scattered radiation. This effect makes the bandwidth too large for some applications and reduces the spectral brilliance. We show that such broadening can be corrected and eliminated by suitable frequency modulation of the incident laser pulse. Furthermore, we suggest a practical realization of this compensation idea in terms of a chirped-beam-driven free electron laser oscillator configuration and show that significant compensation can occur, even with the imperfect matching to be expected in these conditions

Innovative Applications of Genetic Algorithms to Problems in Accelerator Physics

The genetic algorithm (GA) is a powerful technique that implements the principles nature uses in biological evolution to optimize a multidimensional nonlinear problem. The GA works especially well for problems with a large number of local extrema, where traditional methods (such as conjugate gradient, steepest descent, and others) fail or, at best, underperform. The field of accelerator physics, among others, abounds with problems which lend themselves to optimization via GAs. In this paper, we report on the successful application of GAs in several problems related to the existing Continuous Electron Beam Accelerator Facility nuclear physics machine, the proposed Medium-energy Electron-Ion Collider at Jefferson Lab, and a radio frequency gun-based injector. These encouraging results are a step forward in optimizing accelerator design and provide an impetus for application of GAs to other problems in the field. To that end, we discuss the details of the GAs used, include a newly devised enhancement which leads to improved convergence to the optimum, and make recommendations for future GA developments and accelerator applications

Simultaneous Optimization of the Cavity Heat Load and Trip Rates in Linacs Using a Genetic Algorithm

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab\u27s Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines

Beam Dynamics Studies for Transverse Electromagnetic Mode Type rf Deflectors

We have performed three-dimensional simulations of beam dynamics for transverse electromagnetic mode (TEM) type rf deflectors: normal and superconducting. The compact size of these cavities as compared to the conventional TM110 type structures is more attractive particularly at low frequency. Highly concentrated electromagnetic fields between the parallel bars provide strong electrical stability to the beam for any mechanical disturbance. An array of six 2-cell normal conducting cavities or a single cell superconducting structure is enough to produce the required vertical displacement at the target point. Both the normal and superconducting structures show very small emittance dilution due to the vertical kick of the beam

Genetic algorithms and their applications in accelerator physics

Multi-objective optimization techniques are widely used in an extremely broad range of fields. Genetic optimization for multi-objective optimization was introduced in the accelerator community in relatively recent times and quickly spread becoming a fundamental tool in multi-dimensional optimization problems. This discussion introduces the basics of the technique and reviews applications in accelerator problems

OPTIMIZING RF GUN CAVITY GEOMETRY WITHIN AN AUTOMATED INJECTOR DESIGN SYSTEM*

Abstract RF guns play an integral role in the success of several light sources around the world, and properly designed and optimized cw superconducting RF (SRF) guns can provide a path to higher average brightness. As the need for these guns grows, it is important to have automated optimization software tools that vary the geometry of the gun cavity as part of the injector design process. This will allow designers to improve existing designs for present installations, extend the utility of these guns to other applications, and develop new designs. An evolutionary algorithm (EA) based system can provide this capability because EAs can search in parallel a large parameter space (often non-linear) and in a relatively short time identify promising regions of the space for more careful consideration. The injector designer can then evaluate more cavity design parameters during the injector optimization process against the beam performance requirements of the injector. This paper describes an extension to the APISA software that allows the cavity geometry to be modified as part of the injector optimization

Optimizing SRF Gun Cavity Profiles in a Genetic Algorithm Framework

Automation of DC photoinjector designs using a genetic algorithm (GA) based optimization is an accepted practice in accelerator physics. Allowing the gun cavity field profile shape to be varied can extend the utility of this optimization methodology to superconducting and normal conducting radio frequency (SRF/RF) gun based injectors. Finding optimal field and cavity geometry configurations can provide guidance for cavity design choices and verify existing designs. We have considered two approaches for varying the electric field profile. The first is to determine the optimal field profile shape that should be used independent of the cavity geometry, and the other is to vary the geometry of the gun cavity structure to produce an optimal field profile. The first method can provide a theoretical optimal and can illuminate where possible gains can be made in field shaping. The second method can produce more realistically achievable designs that can be compared to existing designs. In this paper, we discuss the design and implementation for these two methods for generating field profiles for SRF/RF guns in a GA based injector optimization scheme and provide preliminary results