Terahertz Time-Domain Spectroscopy (THz-TDS) has been a powerful tool for material characterization. The Fabry–Perot (FP) effect caused by the multiple reflections within the sample exists inherently, which makes the echoes contaminated. In the case of thin samples, different reflection signals may merge together and even the echoes corresponding to the main reflection disappears, making the characterization improper or impossible. To deal with this problem, a novel time-domain optimization method is proposed for removing the FP effect. By introducing a new term which describes the variation of the waveform in time-domain, not only the complex refractive index but also the thickness of material are obtained for a very thin silicon wafer (∼100 μm) whose thickness is less than 2/3 lambda at the central frequency of the THz-TDS system. The accuracy of the algorithm is quite comparable to an iterative method, which is considered to be the most accurate one at the moment, but it is more than 100 times faster, with a better convergence performance. Hence, it is promising for rapid material scenarios such as the in-line quality control and imaging-related applications.

中文翻译：

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使用太赫兹时域光谱法消除材料表征中法布里-珀罗效应的可靠方法

太赫兹时域光谱 (THz-TDS) 已成为材料表征的强大工具。样品内部多次反射引起的法布里-珀罗 (FP) 效应是固有存在的，这使得回声受到污染。在薄样品的情况下，不同的反射信号可能融合在一起，甚至与主反射对应的回波消失，使表征不正确或不可能。为了解决这个问题，提出了一种新的时域优化方法来消除 FP 效应。通过引入一个描述时域波形变化的新术语，对于厚度小于 2/3 的非常薄的硅晶片（~100 μm），不仅可以获得复折射率，还可以获得材料的厚度THz-TDS 系统中心频率处的 lambda。该算法的精度与迭代法相当，被认为是目前最准确的方法，但速度快了100多倍，收敛性能更好。因此，它有望用于快速材料场景，例如在线质量控制和成像相关应用。