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arXiv · 2212.13122

Sparsity for Ultrafast Material Identification

Yurui Qu·Qingyi Zhou·Jin Xiang·Zongfu Yu
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Abstract

Mid-infrared spectroscopy is often used to identify material. Thousands of spectral points are measured in a time-consuming process using expensive table-top instrument. However, material identification is a sparse problem, which in theory could be solved with just a few measurements. Here we exploit the sparsity of the problem and develop an ultra-fast, portable, and inexpensive method to identify materials. In a single-shot, a mid-infrared camera can identify materials based on their spectroscopic signatures. This method does not require prior calibration, making it robust and versatile in handling a broad range of materials.

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Yurui Qu, Qingyi Zhou, Jin Xiang, Zongfu Yu. 2022-11-10. Sparsity for Ultrafast Material Identification. https://arxiv.org/abs/2212.13122

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