Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes
Multi-Fidelity Emulation for the Matter Power Spectrum using Gaussian Processes
复制标题
使用高斯过程对物质功率谱进行多保真度仿真
DOI：
10.1093/mnras/stab3114
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发表时间：
2021
影响因子：
4.8
通讯作者：
Shelton, Christian R
中科院分区：
文献类型：
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作者：
Ho, Ming-Feng;Bird, Simeon;Shelton, Christian R
我们提出了通过组合来自不同分辨率的宇宙N体模拟的信息来模拟物质功率谱的方法。仿真器允许通过在有限数量的仿真的参数空间内插来估计仿真输出。我们提出了多保真仿真在宇宙学中的第一个实现，其中许多低分辨率的仿真与一些高分辨率的仿真相结合以实现更高的仿真精度。功率谱对宇宙学的依赖是从低分辨率模拟中了解到的，而低分辨率模拟又使用高分辨率模拟进行了校准。我们表明，我们的多保真仿真器在仅使用三个高保真(HF)仿真时预测高保真(HF)对应的相对精度达到百分比级别的相对精度，并且性能优于使用11个仿真的单保真仿真器，尽管我们不试图产生具有高绝对精度的融合仿真器。在固定数量的高频训练模拟中，我们表明我们的多保真仿真器在≃上是单保真仿真器的100倍，在≃上是单保真仿真器的20倍。多保真仿真的训练速度很快，只需对标准高斯过程进行简单的修改。我们提出的仿真器通过融合来自不同保真度的仿真，展示了一种预测非线性尺度的新方法。
We present methods for emulating the matter power spectrum by combining information from cosmologicalN-body simulations at different resolutions. An emulator allows estimation of simulation output by interpolating across the parameter space of a limited number of simulations. We present the first implementation in cosmology of multifidelity emulation, where many low-resolution simulations are combined with a few high-resolution simulations to achieve an increased emulation accuracy. The power spectrum’s dependence on cosmology is learned from the low-resolution simulations, which are in turn calibrated using high-resolution simulations. We show that our multifidelity emulator predicts high-fidelity (HF) counterparts to percent-level relative accuracy when using only three HF simulations and outperforms a single-fidelity emulator that uses 11 simulations, although we do not attempt to produce a converged emulator with high absolute accuracy. With a fixed number of HF training simulations, we show that our multifidelity emulator is ≃100 times better than a single-fidelity emulator at, and ≃20 times better at. Multifidelity emulation is fast to train, using only a simple modification to standard Gaussian processes. Our proposed emulator shows a new way to predict non-linear scales by fusing simulations from different fidelities.