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Extreme states of matter exist throughout the universe e.g. inside planetary cores, stars or astrophysical jets. Such conditions can be generated in the laboratory in the interaction of powerful lasers with solids. Yet, the measurement of the subsequent plasma dynamics with regard to density, temperature and ionization is a major experimental challenge. However, ultra-short X-ray pulses provided by X-ray free electron lasers (XFELs) allow for dedicated studies, which are highly relevant to study laboratory astrophysics, laser-fusion research or laser-plasma-based particle acceleration. Here, we report on experiments that employ a novel ultrafast method, which allows to simultaneously access temperature, ionization state and nanometer scale expansion dynamics in high-intensity laser-driven solid-density plasmas with a single X-ray detector. Using this method, we gain access to the expansion dynamics of a buried layer in compound samples, and we measure opacity changes arising from bound-bound resonance transitions in highly ionized copper. The presence of highly ionized copper leads to a temperature estimate of at least 2 million Kelvin already after the first 100 femtoseconds following the high-intensity laser irradiation. More specifically, we make use of asymmetries in small-angle X-ray scattering (SAXS) patterns, which arise from different spatial distributions of absorption and scattering cross sections in nanostructured grating samples when we tune an XFEL to atomic resonant energies of copper. Thereby, changes in asymmetry can be connected with the evolution of the plasma expansion and ionization dynamics. The potential of XFEL-based resonant SAXS to obtain three-dimensional ultrafast, nanoscopic information on density and opacity may offer a unique path for the characterization of dynamic processes in High Energy Density plasmas.

SLAC is developing the Lightsource Unified Modeling Environment (LUME) for efficient modeling of X-ray free electron laser (XFEL) performance. This project takes a holistic approach starting with the simulation of the electron beams, to the production of the photon pulses, to their transport through the optical components of the beamline, to their interaction with the samples and the simulation of the detectors, and finally followed by the analysis of simulated data. LUME leverages existing, well-established simulation codes, and provides standard interfaces to these codes via open-source Python packages. Data are exchanged in standard formats based on openPMD and its extensions. The platform is built with an open, well-documented architecture so that science groups around the world can contribute specific experimental designs and software modules, advancing both their scientific interests and a broader knowledge of the opportunities provided by the exceptional capabilities of X-ray FELs., Proceedings of the 12th International Particle Accelerator Conference, IPAC2021, Campinas, SP, Brazil

Resonant Small-angle x-ray scattering raw data obtained in measurements at MEC at LCLS and evalutation of the asymmetry in the scattering patterns. The data set is structured in case 1/Si-Cu-compound targets and case 2/Cu-only-targets as presented in the publication for on- and off-resonant XFEL probe energies.

International audience; Photon and Neutron sources are producing more and more petabytes of scientific data each year. At the same time scientific publishing is evolving to make scientific data part of publications. The Photon and Neutron Open Science Cloud (PaNOSC*) project is a EU financed project to provide scientific data management for enabling Open Science. Data will be managed according to the FAIR principles. This means data will be curated and made available under an Open Data policy, findable, interoperable and reusable. This paper will describe how the European photon and neutron sources on the ESFRI** roadmap envision PaNOSC as part of the European Open Science Cloud***. The paper will address the issues of data policy, metadata, data curation, long term archiving and data sharing in the context of the latest developments in these areas.

Jupyter notebooks are executable documents that are displayed in a web browser. The notebook elements consist of human-authored contextual elements and computer code, and computer-generated output from executing the computer code. Such outputs can include tables and plots. The notebook elements can be executed interactively, and the whole notebook can be saved, re-loaded and re-executed, or converted to read-only formats such as HTML, LaTeX and PDF. Exploiting these characteristics, Jupyter notebooks can be used to improve the effectiveness of computational and data exploration, documentation, communication, reproducibility and re-usability of scientific research results. They also serve as building blocks of remote data access and analysis as is required for facilities hosting large data sets and initiatives such as the European Open Science Cloud (EOSC). In this contribution we report from our experience of using Jupyter notebooks for data analysis at research facilities, and outline opportunities and future plans., Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems, ICALEPCS2019, New York, NY, USA

Sand waves are rhythmic patterns resulted from the interaction between water flow and sandy bed. In this paper the research progress upon the sand wave is introduced from three aspects which include theoretical analysis, numerical simulation and experimental study, based on the available literatures.

Scientific reports 11(1), 17976 (2021). doi:10.1038/s41598-021-97142-5, We present a computational case study of X-ray single-particle imaging of hydrated proteins on an example of 2-Nitrogenase–Iron protein covered with water layers of various thickness, using a start-to-end simulation platform and experimental parameters of the SPB/SFX instrument at the European X-ray Free-Electron Laser facility. The simulations identify an optimal thickness of the water layer at which the effective resolution for imaging the hydrated sample becomes significantly higher than for the non-hydrated sample. This effect is lost when the water layer becomes too thick. Even though the detailed results presented pertain to the specific sample studied, the trends which we identify should also hold in a general case. We expect these findings will guide future single-particle imaging experiments using hydrated proteins., Published by Macmillan Publishers Limited, part of Springer Nature, [London]

Photon and Neutron sources are producing more and more petabytes of scientific data each year. At the same time scientific publishing is evolving to make scientific data part of publications. The Photon and Neutron Open Science Cloud (PaNOSC*) project is a EU financed project to provide scientific data management for enabling Open Science. Data will be managed according to the FAIR principles. This means data will be curated and made available under an Open Data policy, findable, interoperable and reusable. This paper will describe how the European photon and neutron sources on the ESFRI** roadmap envision PaNOSC as part of the European Open Science Cloud***. The paper will address the issues of data policy, metadata, data curation, long term archiving and data sharing in the context of the latest developments in these areas., Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems, ICALEPCS2019, New York, NY, USA