面向低能缪子与离子注入的多层TRIM.SP代码的现代化与统计验证
Modernization and Statistical Validation of a Multilayer TRIM.SP Code for Low-Energy Muon and Ion Implantation
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中文总结 AI 辅助
该研究对多层TRIM.SP代码进行现代化，优化RNG后端以提升运行效率，通过多组模拟验证其可靠性，构建了开源工作台。
中文摘要 AI 辅助
我们描述了本地多层this http URL实现的分阶段现代化工作，该实现被称为this http URL-NL。这项工作包括：保持行为不变的重构、修正局部簿记与初始化缺陷、支持每层超过5种元素、可复现的构建模式，以及运行时可选的随机数生成器（RNG）接口。RANLUX RNG仍为默认参考后端，而PCG32和xoshiro256**则提供了更快的替代方案，且无需更改输入卡格式。代码验证结合了精确回归测试与对13种代表性靶材多层结构的统计比较，每种后端对应143个能量配置点，总计429次模拟。在测试套件中，PCG32和xoshiro256**分别将运行时间缩短了1.98倍和2.01倍。注入、背散射与透射份额，以及平均注入深度、射程歧离和代表性深度分布均未表现出系统的RNG依赖性。结合用于设置、扫描与结果收集的基于this http URL的图形界面，该Fortran引擎构成了开源的this http URL-NL工作台。
英文摘要
We describe the staged modernization of a local multilayer TRIM.SP implementation, denoted TRIM.SP-NL. The work included behavior-preserving refactoring, correction of localized bookkeeping and initialization defects, support for more than five elements per layer, reproducible build modes, and a runtime-selectable random-number-generator (RNG) interface. The RANLUX RNG remains the default reference backend, while PCG32 and xoshiro256** provide faster alternatives without changing the input-deck format. The code validation combined exact regression testing with statistical comparisons over 13 representative target multilayer configurations, comprising 143 energy-configuration points per backend and 429 simulations in total. Across the test suite, PCG32 and xoshiro256** reduced runtime by factors of 1.98 and 2.01, respectively. The implanted, backscattered, and transmitted fractions, as well as the mean implantation depths, range straggling, and representative depth profiles showed no systematic RNG dependence. Together with a Node.js-based graphical interface for setup, scans, and result collection, the Fortran engine forms the open-source TRIM.SP-NL Workbench.
发表机构
- PSI Center for Neutron and Muon Sciences（PSI中子与μ子科学中心）
- TRIUMF
- Department of Physics and Astronomy, University of Victoria（维多利亚大学物理与天文系）
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