We demonstrate an optical machine learning method in the terahertz domain, which allows the recognition of objects within a single measurement. As many materials are transparent in the terahertz spectral region, objects hidden within such materials can be identified. In contrast to typical object recognition methods, our method only requires a single pixel detector instead of a focal plane array. The core of the calculation is performed by a quantum cascade laser generated terahertz beam, which is spatially modulated at a near-infrared encoded silicon wafer. We show that this method is robust against displacements of the objects and noise. Additionally, the method is flexible and, due to the optically performed recognition task, inherently fast.

中文翻译：

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太赫兹光学机器学习用于物体识别

我们在太赫兹域中演示了一种光学机器学习方法，该方法可以在一次测量中识别物体。由于许多材料在太赫兹光谱区域中都是透明的，因此可以识别隐藏在此类材料中的物体。与典型的对象识别方法相比，我们的方法仅需要单个像素检测器，而不需要焦平面阵列。计算的核心是由量子级联激光器产生的太赫兹光束执行的，该太赫兹光束在近红外编码的硅晶片上进行了空间调制。我们证明了这种方法对于物体的位移和噪声是鲁棒的。另外，该方法是灵活的，并且由于光学地执行识别任务，因此固有地快速。