arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.00638physics.optics
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利用神经网络实现宽带光的光谱分裂与集中

Spectral splitting and concentration of broadband light using neural networks

Alim Yolalmaz, Emre Yüce

AI总结:

本文提出用神经网络逆向设计并实验验证可分裂和集中宽带光的衍射元件 SpliCons,准确率达96.6 ± 2.3%,2秒内完成设计且性能优于局部搜索。

摘要:

能够同时控制光的衍射和干涉的紧凑型光子元件,可在超紧凑尺寸下提供卓越性能。与传统光学结构不同,这些衍射光学元件能够同时控制光的光谱和空间分布。然而,使用现有算法对这种衍射光学元件进行逆向设计非常耗时,而且设计方案普遍缺乏实验验证。为此,我们开发了一种神经网络模型,用于在实验上设计和验证 SpliCons;这是一种特殊类型的衍射光学元件,能够实现宽带光的光谱分裂和同步集中。我们利用神经网络来挖掘通过相位板进行波前重构所产生的非线性运算。结果表明,与通过局部搜索优化算法优化的相位板相比,该神经网络模型在定量评估下为相位板带来了增强的光谱分裂性能。通过比较输出平面处的强度分布,我们在实验上验证了经神经网络优化的相位板的能力。神经网络一旦完成训练,我们就能在2秒内以96.6 ± 2.3%的准确率设计出 SpliCons,速度比迭代搜索算法快数个数量级。我们公开发布所开发的快速高效框架,以促进衍射光学元件的设计和实现,从而在显微镜、光谱学和太阳能应用中产生变革性影响。

英文摘要:

Compact photonic elements that control both the diffraction and interference of light offer superior performance at ultra-compact dimensions. Unlike conventional optical structures, these diffractive optical elements can provide simultaneous control of spectral and spatial profile of light. However, the inverse-design of such a diffractive optical element is time-consuming with current algorithms, and the designs generally lack experimental validation. Here, we develop a neural network model to experimentally design and validate SpliCons; a special type of diffractive optical element that can achieve spectral splitting and simultaneous concentration of broadband light. We use neural networks to exploit nonlinear operations that result from wavefront reconstruction through a phase plate. Our results show that the neural network model yields enhanced spectral splitting performance for phase plates with quantitative assessment compared to phase plates that are optimized via local search optimization algorithm. The capabilities of the phase plates optimized via neural network are experimentally validated by comparing the intensity distribution at the output plane. Once the neural networks are trained, we manage to design SpliCons with 96.6 $\pm$ 2.3% accuracy within 2 seconds, which is orders of magnitude faster than iterative search algorithms. We openly share the fast and efficient framework that we develop in order to contribute to the design and implementation of diffractive optical elements that can lead to transformative effects in microscopy, spectroscopy, and solar energy applications.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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