Continued advances in computational power and high-speed networking are enabling a new model of scientific experiment, experiment-in-the-loop computing (EILC). In this model, high-end computing systems are closely coupled to experimental and observational infrastructure, and the two interact to drive a deeper understanding of physical phenomena. At the same time, advances and widespread adoption of machine learning enables new ways to register and use experimental data.<\/p>\n\n\n\n
Several research and development challenges are posed by this multifaceted paradigm, many of which are independent of the particular scientific application domain. New algorithms to integrate simulation outputs and experimental data sets must be developed. High performance
data management and transfer techniques must be developed to manage and manipulate simulated and observed data sets. Workflows must be constructed with high levels of usability and understandability to enable scientific post-analysis and improvement of the computing solution.<\/p>\n\n\n\n
The Workshop on Experiment-in-the-Loop Computing (XLOOP 2026) will be a unique opportunity to promote this cross-cutting, interdisciplinary topic area. We invite papers, presentations, and participants from the physical and computer sciences, and encourage the sharing of
ideas from across these domains to find common solutions and technologies to make rapid progress in EILC, so that many application areas can easily adopt these methods.<\/p>\n\n\n\n
The proceedings of the workshop will be submitted for publishing to the ACM.<\/p>\n\n\n\n
Topics of interest include, but are not limited to:<\/p>\n\n\n\n
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