Ultrashort laser pulses with femtosecond to attosecond pulse duration are the shortest systematic events humans can currently create. Characterization (amplitude and phase) of these pulses is a crucial ingredient in ultrafast science, e.g., exploring chemical reactions and electronic phase transitions. Here, we propose and demonstrate, numerically and experimentally, what is to the best of our knowledge, the first deep neural network technique to reconstruct ultrashort optical pulses. Employing deep neural networks for reconstruction of ultrashort pulses enables diagnostics of very weak pulses and offers new possibilities, e.g., reconstruction of pulses using measurement devices without knowing in advance the relations between the pulses and the measured signals. Finally, we demonstrate the ability to reconstruct ultrashort pulses from their experimentally measured frequency-resolved optical gating traces via deep networks that have been trained on simulated data.

中文翻译：

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超短脉冲的深度学习重建

飞秒级至阿秒级脉冲持续时间的超短激光脉冲是人类目前可以产生的最短的系统事件。这些脉冲的表征（幅度和相位）是超快科学中的重要组成部分，例如，探索化学反应和电子相变。在这里，我们以数值和实验的方式提出并证明，就我们所知，什么是第一种用于重建超短光脉冲的深度神经网络技术。采用深层神经网络来重建超短脉冲可以诊断非常微弱的脉冲，并提供了新的可能性，例如，使用测量设备重建脉冲，而无需事先知道脉冲与被测信号之间的关系。最后，