模拟辐射激波流体力学的大型计算机实验的校准
Calibrating a large computer experiment simulating radiative shock hydrodynamics
摘要：
我们考虑适应一个典型的计算机模型校准装置，涉及耦合高斯过程（GP）仿真器，模拟辐射冲击流体力学的计算机实验是数量级大于通常可以容纳。传统的方法需要成千上万的大型矩阵求逆来评估MCMC方案中的似然性。我们的方法取代了昂贵的理想与节俭采取的基本成分，协同仿真，校准和优化的三个现代思想：本地近似GP回归，模块化和网格自适应直接搜索。新的方法是出于必要性-考虑到我们的特殊应用-和最近的趋势，在超级计算机模拟文献。合成数据应用程序使我们能够探索在受控环境中的几种变化的优点，并与我们激励真实数据实验的结果一起，导致对辐射冲击动力学的显着见解以及校准企业的局限性。
英文摘要：
We consider adapting a canonical computer model calibration apparatus, involving coupled Gaussian process (GP) emulators, to a computer experiment simulating radiative shock hydrodynamics that is orders of magnitude larger than what can typically be accommodated. The conventional approach calls for thousands of large matrix inverses to evaluate the likelihood in an MCMC scheme. Our approach replaces that costly ideal with a thrifty take on essential ingredients, synergizing three modern ideas in emulation, calibration and optimization: local approximate GP regression, modularization, and mesh adaptive direct search. The new methodology is motivated both by necessity - considering our particular application - and by recent trends in the supercomputer simulation literature. A synthetic data application allows us to explore the merits of several variations in a controlled environment and, together with results on our motivating real-data experiment, lead to noteworthy insights into the dynamics of radiative shocks as well as the limitations of the calibration enterprise generally.
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