Sub-photon accuracy noise reduction of a single shot coherent diffraction pattern with an atomic model trained autoencoder.

Single-shot imaging with femtosecond X-ray lasers is a powerful measurement technique that can achieve both high spatial and temporal resolution. However, its accuracy has been severely limited by the difficulty of applying conventional noise-reduction processing. This study uses deep learning to validate noise reduction techniques, with autoencoders serving as the learning model. Focusing on the diffraction patterns of nanoparticles, we simulated a large dataset treating the nanoparticles as composed of many independent atoms. Three neural network architectures are investigated: neural network, convolutional neural network and U-net, with U-net showing superior performance in noise reduction and subphoton reproduction. We also extended our models to apply to diffraction patterns of particle shapes different from those in the simulated data. We then applied the U-net model to a coherent diffractive imaging study, wherein a nanoparticle in a microfluidic device is exposed to a single X-ray free-electron laser pulse. After noise reduction, the reconstructed nanoparticle image improved significantly even though the nanoparticle shape was different from the training data, highlighting the importance of transfer learning.

(Sub-)Picosecond Surface Correlations of Femtosecond Laser Excited Al-Coated Multilayers Observed by Grazing-Incidence X-ray Scattering.

Femtosecond high-intensity laser pulses at intensities surpassing 1014 W/cm2 can generate a diverse range of functional surface nanostructures. Achieving precise control over the production of these functional structures necessitates a thorough understanding of the surface morphology dynamics with nanometer-scale spatial resolution and picosecond-scale temporal resolution. In this study, we show that single XFEL pulses can elucidate structural changes on surfaces induced by laser-generated plasmas using grazing-incidence small-angle X-ray scattering (GISAXS). Using aluminium-coated multilayer samples we distinguish between sub-picosecond (ps) surface morphology dynamics and subsequent multi-ps subsurface density dynamics with nanometer-depth sensitivity. The observed subsurface density dynamics serve to validate advanced simulation models representing matter under extreme conditions. Our findings promise to open new avenues for laser material-nanoprocessing and high-energy-density science.

Seeded stimulated X-ray emission at 5.9 keV.

X-ray free-electron lasers (XFELs) provide intense pulses that can generate stimulated X-ray emission, a phenomenon that has been observed and studied in materials ranging from neon to copper. Two schemes have been employed: amplified spontaneous emission (ASE) and seeded stimulated emission (SSE), where a second color XFEL pulse provides the seed. Both phenomena are currently explored for coherent X-ray laser sources and spectroscopy. Here, we report measurements of ASE and SSE of the 5.9 keV Mn Kα1 fluorescence line from a 3.9 molar NaMnO4 solution, pumped with 7 femtosecond FWHM XFEL pulses at 6.6 keV. We observed ASE at a pump pulse intensity of 1.7 × 1019 W/cm2, consistent with earlier findings. We observed SSE at dramatically reduced pump pulse intensities down to 1.1 × 1017 W/cm2. These intensities are well within the range of many existing XFEL instruments, which supports the experimental feasibility of SSE as a tool to generate coherent X-ray pulses, spectroscopic studies of transition metal complexes, and other applications.