In-Situ Analysis of Convoluted Data at Large-Scale Facilitates

Advances to electron microscopes and X-ray facilities have enabled tremendous leaps in the quality of experimental data over the past decades. This has lead to the development of experimental configurations and techniques that were not possible even five or ten years ago. Simultaneously, improvements in informatics and detectors have dramatically increased the rate of data acquisition. Data processing has in many cases become more challenging due to increased experimental complexity and data throughput despite advances to data quality. In particular, the challenge arises when using novel experimental configurations, as is often the case at X-ray free electron lasers. Successful execution and optimization of the experiment is frequently contingent on in-situ data analysis, and data-processing often becomes a bottleneck for the experiment as a whole. Most critically, as the number of collaborators grows with experimental complexity, the programming knowledge often does not scale in a similar fashion.<br/><br/>This poster will detail our approach to automating data analysis in-situ during an ongoing experiment. We have found that automatic and semi-automatic data processing have enabled faster feedback to guide experiments during an ongoing beamtime at X-ray free electron facilities, and empowered more team members to access convoluted results in an approachable manner. Automated data analysis also reduces the overall workload of the beamtime, allowing for more rest between shifts and less exhaustion. We believe our approach is generally applicable to electron microscopes and scanning probe microscopy in addition to X-ray science.