Kernel Density Estimators for Axisymmetric Particle Beams

Author:

Pierce Christopher M.1,Kim Young-Kee1

Affiliation:

1. Enrico Fermi Institute, University of Chicago, Chicago, IL 60637, USA

Abstract

Bright beams are commonly represented by sampled data in the numerical algorithms used to simulate their properties. However, in these calculations and the analyses of their outputs, the beam’s density is sometimes required and must be calculated from the samples. Axisymmetric beams, which possess a rotational symmetry and are naturally expressed in polar coordinates, pose a particular challenge to density estimators. The area element in polar coordinates shrinks as the radius becomes small, and weighting the samples to account for their reduced frequency may cause unwelcome artifacts. In this work, we derive analytical expressions for two kernel density estimators, which solve these problems in the spatial coordinates and in the transverse phase space. We show how the kernels can be found by averaging the Gaussian kernel in Cartesian coordinates over the polar angle and demonstrate their use on test problems. These results show that particle beam symmetries can be taken advantage of in density estimation while avoiding artifacts.

Funder

U.S. National Science Foundation

Publisher

MDPI AG

Subject

Instrumentation

Reference22 articles.

1. Hockney, R.W., and Eastwood, J.W. (2021). Computer Simulation Using Particles, CRC Press.

2. GENESIS 1.3: A Fully 3D Time-Dependent FEL Simulation Code;Reiche;Nucl. Instrum. Methods Phys. Res. Sect. Accel. Spectrometers Detect. Assoc. Equip.,1999

3. TDA—A Three-Dimensional Axisymmetric Code for Free-Electron-Laser (FEL) Simulation;Tran;Comput. Phys. Commun.,1989

4. Edelen, A.L., Biedron, S.G., Milton, S.V., and Edelen, J.P. (2016). First Steps toward Incorporating Image Based Diagnostics into Particle Accelerator Control Systems Using Convolutional Neural Networks. arXiv.

5. Artificial Neural Networks for Solving Ordinary and Partial Differential Equations;Lagaris;Comput. Phys.,1997

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3