Supplementary materials: "Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines"

Data archive for stage 3 of manuscript for PASC24. See Readme stage 3.txt for more details. This work was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under U.S. Department of Energy Contract No. DE-AC02-05CH11231 and by LLNL under Contract DE-AC52-07NA27344. This material is based upon work supported by the U.S. Department of Energy, OFfice of Science, Office of High Energy Physics, General Accelerator R&D (GARD), under contract number DE-AC02-05CH11231. This material is based upon work supported by the CAMPA collaboration, a project of the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of High Energy Physics, Scientific Discovery through Advanced Computing (SciDAC) program. This research was supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation's exascale computing imperative.This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award HEP-ERCAP0023719.本数据集存档对应PASC24稿件的第三阶段工作，详细信息请参阅Readme stage 3.txt文件。本研究得到劳伦斯伯克利国家实验室实验室指导研究与发展计划的支持，该计划隶属于美国能源部，合同编号DE-AC02-05CH11231；同时得到劳伦斯利弗莫尔国家实验室（Lawrence Livermore National Laboratory, LLNL）的支持，合同编号DE-AC52-07NA27344。本材料基于美国能源部科学办公室高能物理办公室通用加速器研发（General Accelerator R&D, GARD）项目资助的工作，项目合同编号为DE-AC02-05CH11231。本材料基于CAMPA合作项目的工作成果，该项目隶属于美国能源部科学办公室先进科学计算研究办公室与高能物理办公室的科学发现通过先进计算（Scientific Discovery through Advanced Computing, SciDAC）计划。本研究得到百亿亿次计算计划（Exascale Computing Project, 项目编号17-SC-20-SC）的支持，该计划由美国能源部科学办公室与国家核安全管理局联合发起，旨在构建完备的百亿亿次计算生态，涵盖软件、应用及硬件技术，以支撑国家的百亿亿次计算战略需求。本研究使用了国家能源研究科学计算中心（National Energy Research Scientific Computing Center, NERSC）的计算资源，该中心为美国能源部科学办公室下属的用户设施，依托合同DE-AC02-05CH11231获得资助，本次使用的NERSC项目编号为HEP-ERCAP0023719。