Single Exposure Imaging of Talbot Carpets and Resolution Characterization of Detectors for Micro- and Nano- Patterns

Abstract

In this paper, we demonstrate a self-imaging technique that can visualize longitudinal interference patterns behind periodically-structured objects, which is often referred to as Talbot carpet. Talbot carpet is of great interest due to ever-decreasing scale of interference features. We demonstrate experimentally that Talbot carpets can be imaged in a single exposure configuration revealing a broad spectrum of multi-scale features. We have performed rigorous diffraction simulations for showing that Talbot carpet print can produce ever-decreasing structures down to limits set by mask feature sizes. This demonstrates that large-scale pattern masks may be used for direct printing of features with substantially smaller scales. This approach is also useful for characterization of image sensors and recording media