论文标题
部分可观测时空混沌系统的无模型预测
Snowmass2021 Cosmic Frontier Dark Matter Direct Detection to the Neutrino Fog
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
We present a summary of future prospects for direct detection of dark matter within the GeV/c2 to TeV/c2 mass range. This is paired with a new definition of the neutrino fog in order to better quantify the rate of diminishing returns on sensitivity due to irreducible neutrino backgrounds. A survey of dark matter candidates predicted to fall within this mass range demonstrates that fully testing multiple well-motivated theo-ries will require expanding the currently-funded generation of experiments down to and past the neutrino fog. We end with the status and plans for next-generation exper-iments and novel R&D concepts which will get us there.
