论文标题
图像分类使用一系列纳米层的集体光学模式
Image classification using collective optical modes of an array of nanolasers
论文作者
论文摘要
纳米剂设计和制造业的最新进展在高集成密度和超低功耗方面开辟了前所未有的观点，使这些设备非常适合高性能光学计算系统。在这项工作中，我们利用纳米式阵列的集体模式的对称属性进行二进制图像分类。该实现基于8x8数组，并依赖于在空间调制的泵模式下的阵列的集体光学模式的激活，即所谓的“零模式”。我们证明，一种简单的培训策略使我们能够在二进制图像识别中实现98％的总体成功率。
Recent advancements in nanolaser design and manufacturing open up unprecedented perspectives in terms of high integration densities and ultra-low power consumption, making these devices ideal for high-performance optical computing systems. In this work we exploit the symmetry properties of the collective modes of a nanolaser array for binary image classification. The implementation is based on a 8x8 array, and relies on the activation of a collective optical mode of the array, the so-called "zero mode", under spatially modulated pump patterns. We demonstrate that a simple training strategy allows us to achieve an overall success rate of 98% in binary image recognition.
