论文标题
具有深神经网络的介电轴卤素的仿真：原理证明
Simulation of dielectric axion haloscopes with deep neural networks: a proof-of-principle
论文作者
论文摘要
介电轴卤素（例如Madmax实验）是直接搜索暗物质轴的有希望的概念。可靠的模拟是成功实现实验的基本要求。由于模拟的复杂性，对计算资源的需求很快就会变得过于望而却步。在本文中，我们首次展示了现代深度学习技术可以帮助介电卤素的模拟和优化。
Dielectric axion haloscopes, such as the MADMAX experiment, are promising concepts for the direct search for dark matter axions. A reliable simulation is a fundamental requirement for the successful realisation of the experiments. Due to the complexity of the simulations, the demands on computing resources can quickly become prohibitive. In this paper, we show for the first time that modern deep learning techniques can be applied to aid the simulation and optimisation of dielectric haloscopes.
