This contribution presents a rewritten and expanded version of the Fast Grain Boundary (FGB) program (Eiler et al., 1994) with the motivation of adding to the geochemical tools available for reconstructing temperature-time (T–t) histories that inform studies of tectonics and crustal evolution. Both the original and the new FGB programs model the oxygen-isotope compositional evolution of a rock resulting from diffusive oxygen isotope exchange between minerals. The new FGB program is coded in Python and includes a graphical user interface. Additionally, C-compiled versions of the code are available that provide a 20x speedup of model calculations. The new implementation also allows for inversion of the FGB model to extract unbiased thermal histories from oxygen isotope data. The Levenberg-Marquardt (LM) algorithm is applied to search for cooling histories that maximize agreement between the model output and the measured oxygen isotope data. Tests with synthetic datasets show that the LM algorithm is able to distinguish between simple linear cooling and more complex thermal histories that include reheating events. Inversion of a natural oxygen isotope zoning dataset from titanite shows that, within the resolution of the models and data, the Adirondack Mountains sample location experienced rapid (30–70 °C/m.y.), monotonic cooling from 700 to 500 °C. We develop a heuristic guide to sampling and analytical approaches that improve the resolution of inversion solutions for current SIMS analytical capabilities, and we suggest targets for future improvements of SIMS analysis. Our tests indicate that the current SIMS analytical precision for in situ oxygen isotope measurements is sufficient to allow for temperature-time path recovery with thermal resolution of 25–50 °C and temporal resolution of 2–3 million years.

此文稿提出了快速晶粒边界（FGB）程序的重写版本和扩展版本（Eiler等，1994），其动机是增加了可用于重构温度-时间（T–t）的地球化学工具。）历史，可为构造学和地壳演化研究提供参考。原始和新的FGB程序都模拟了矿物之间扩散的氧同位素交换导致的岩石的氧同位素组成演化。新的FGB程序使用Python编码，并包含图形用户界面。此外，还提供C编译版本的代码，可将模型计算速度提高20倍。新的实现方式还允许对FGB模型进行反演，以从氧同位素数据中提取无偏热历史。Levenberg-Marquardt（LM）算法用于搜索冷却历史，该历史使模型输出与测得的氧同位素数据之间的一致性达到最大。对合成数据集的测试表明，LM算法能够区分简单的线性冷却和更复杂的包括重新加热事件的热历史。从钛矿对天然氧同位素分区数据集的反演表明，在模型和数据的分辨率范围内，阿迪朗达克山脉样品位置经历了从700至500°C的快速（30-70°C / my）单调冷却。我们为采样和分析方法开发了启发式指南，以提高当前SIMS分析功能的反演解决方案的分辨率，并为将来SIMS分析的改进提出目标。