Precise and rapid distance measurements by scatterometry

Abstract

We found that the distances between isolated scatterers with similar columnar shapes could be measured by taking a single Fourier transform of their diffraction intensity. If the scatterers have different shapes, the distances between similar shapes can be selected from the distances between all the shapes. The distance from a specific scatterer can be measured with a resolution of 0.8 wavelengths and a precision of 0.01 wavelengths. This technique has the potential to be used in a novel optical memory that has a memory density as high as that of holographic memory, while can be fabricated by simple transfer molding. We used rigorous coupled-wave analysis to calculate the diffraction intensity. Some of the results were verified by nonstandard finite-difference time-domain simulations and experiments.

A columnar model explaining long-term memory

“…To calculate scattering with directional information, a large left scatterer was added. It has a strong scattering intensity, because the scattering intensity increases as the scatterer becomes larger [17]. The result of FT is shown in Fig.…”

“…Itoh et al proposed the model of memory shown in Fig. 1a [17]. This model has the following characteristics.…”

“…developed a new simple method to apply RCWA to an isolated system [17]. This method enables the calculation of distance by a one-time FT of the distribution of scattering and some correction for the shape of scatterers by RCWA.…”

“…This method enables the calculation of distance by a one-time FT of the distribution of scattering and some correction for the shape of scatterers by RCWA. Moreover, it can utilize the effects of size and shape to extract specific distance information [17]. If the sizes and shapes of columnar scatterers are similar, and the distance between scatters ranges from 1 to several 10 wavelengths, the scattering distribution is approximately calculated by FT of the image, and the abovementioned optical memory is possible.…”

“…First, single neurons can store complex information [15], and second, subtle changes in neurons underlie the process of memorization [16]. To address these discrepancies, we present a new model that combines columnar memory [17] and holographic memory. Columnar memory can have various sizes and a complex shape.…”