Ultrafast lasers, providing the shortest pulses worldwide, have been playing a vital role in the ultrafast imaging technology. The temporal resolution has been increasing rapidly in recent years but finally reaches its limit—the pulse width approaches photoperiods, causing significant broadening of spectral bandwidth. The state-of-the-art high harmonics generation based attosecond lasers, with pulse widths reaching ∼50 attoseconds, present octave-spanning spectra. This brings a major challenge to traditional imaging methods, as they result in unbearable chromatic aberrations. To address this challenge, we propose the neural-network approach for broadband imaging and demonstrate its effectiveness empirically by facilitating rapid coherent diffractive imaging under octave-spanning supercontinuum illumination. The proposed method remains effective when deployed with three-octave-spanning spectra, supporting both continuous and comb-like profiles as indicated by simulations. Such lensless imaging method, applicable to both extreme ultraviolet and soft x-ray sources, potentially provides an approach to attosecond imaging.

中文翻译：

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神经网络支持的倍频程跨度相干衍射成像


超快激光器提供全球最短的脉冲，在超快成像技术中一直发挥着至关重要的作用。近年来，时间分辨率一直在迅速提高，但最终达到了极限——脉冲宽度接近光周期，导致光谱带宽显着拓宽。最先进的基于阿秒高谐波产生的激光器，脉冲宽度达到 ∼50 阿秒，呈现倍频程跨度光谱。这给传统的成像方法带来了重大挑战，因为它们会导致难以忍受的色差。为了应对这一挑战，我们提出了用于宽带成像的神经网络方法，并通过在倍频程跨度超连续照明下促进快速相干衍射成像来实证证明其有效性。所提出的方法在部署三个倍频程跨度的光谱时仍然有效，支持模拟所示的连续和梳状剖面。这种无透镜成像方法适用于极紫外和软 X 射线源，可能提供了一种阿秒成像方法。