Investigation of fast and efficient lossless compression algorithms for macromolecular crystallography experiments

Structural biology experiments benefit significantly from state‐of‐the‐art synchrotron data collection. One can acquire macromolecular crystallography (MX) diffraction data on large‐area photon‐counting pixel‐array detectors at framing rates exceeding 1000 frames per second, using 200 Gbps network connectivity, or higher when available. In extreme cases this represents a raw data throughput of about 25 GB s−1, which is nearly impossible to deliver at reasonable cost without compression. Our field has used lossless compression for decades to make such data collection manageable. Many MX beamlines are now fitted with DECTRIS Eiger detectors, all of which are delivered with optimized compression algorithms by default, and they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community. Here one of the latest and most promising lossless compression algorithms is investigated on a variety of diffraction data like those routinely acquired at state‐of‐the‐art MX beamlines. Many macromolecular crystallography beamlines are now fitted with DECTRIS Eiger detectors, which are all delivered with optimized compression algorithms by default; they perform well with current framing rates and typical diffraction data. However, better lossless compression algorithms have been developed and are now available to the research community.