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.

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.

The Workshop on Experiment-in-the-Loop Computing (XLOOP 2025) 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.

The proceedings of the workshop will be submitted for publishing to IEEE CPS.

Previous years' proceedings may be found here:

2024: https://conferences.computer.org/sc-wpub/#!/toc/0#XLOOP2024:6thAnnualWorkshoponExtreme-ScaleExperiment-in-the-LoopComputing
2023: https://dl.acm.org/doi/proceedings/10.1145/3624062#heading42
2022: https://ieeexplore.ieee.org/xpl/conhome/10024591/proceeding
2021: https://www.computer.org/csdl/proceedings/xloop/2021/1zG2XAuTfyw
2020: https://www.computer.org/csdl/proceedings/xloop/2020/1pZ0UawOMkU
2019: https://ieeexplore.ieee.org/xpl/conhome/8938158/proceeding

== Topics ==

Topics of interest include, but are not limited to:

* Machine learning applications in simulation or experiment control
* Case studies in EILC applications and solutions
* Data transfer techniques and technologies
* In situ analysis methods and tools relevant to experiment data
* Simulation and experiment validation methods and tools
* Workflow technologies to manage computation and experiment couplings
* Advanced systems architecture for EILC applications
* High-performance I/O methods and libraries
* Data integration and assimilation algorithms and technologies
* Performance evaluation in EILC applications and solutions
* Cyberinfrastructure and "big science" planning and reporting
* Portable solutions for reproducible, transferable experiments

== Paper Submission ==

Please submit novel papers of 8 pages in IEEE style via the SC submissions site. Deadlines are:

* Submissions due: August 1, 2025
* Author notification: August 29, 2025
* Reproducibility info (optional): October 3, 2025
* Camera-ready version: September 26, 2025
* Copyright submission: September 26, 2025
* Workshop @ SC: November 16, 2025

Templates may be found at the workshop web site.

Reproducibility: XLOOP participates in the reproducibility initiative.

Reproducibility data does not count against the XLOOP page requirement.

Details about this data are available at the XLOOP web site.

== Organization ==

Chairs:

Justin M Wozniak (Argonne National Laboratory) (woz@anl.gov)
Nicholas Schwarz (Argonne National Laboratory) (nschwarz@anl.gov)

Contact us at xloop-chairs@lists.dsl.anl.gov

Steering committee:

Debbie Bard National Energy Research Scientific Computing Center
Eli Dart ESNet
Mallikarjun (Arjun) Shankar Oak Ridge National Laboratory
Christine Sweeney Los Alamos National Laboratory
Venkatram Vishwanath Argonne National Laboratory

Program committee:

Tekin Bicer (Argonne National Laboratory)
Stuart Campbell (Brookhaven National Laboratory)
Rudolph Dimper (European Synchrotron Radiation Facility)
Kjiersten Fagnan (Lawrence Berkeley National Laboratory)
Rafael Ferreira Da Silva (Oak Ridge National Laboratory)
Geoffrey Fox (Indiana University)
Alex Hexemer (Lawrence Berkeley National Laboratory)
Tony Hey (Rutherford Appleton Laboratory)
Shantenu Jha (Rutgers)
Wiebke Koepp (Lawrence Berkeley National Laboratory)
Olga Kuchar (Oak Ridge National Laboratory)
Jakob Luettgau (University of Tennessee Knoxville)
Kurt H. Maier (Pacific Northwest National Laboratory)
Preeti Malakar (Indian Institute of Technology Kanpur)
Bojan Nikolic (Square Kilometer Array, Cambridge)
Hannah Parraga (Argonne National Laboratory)
Marc F. Paterno (Fermi National Accelerator Laboratory)
Line Pouchard (Brookhaven National Laboratory)
Thomas E. Proffen (Oak Ridge National Laboratory)
Lavanya Ramakrishnan (Lawrence Berkeley National Laboratory)
Tobias Richter (European Spallation Source)
Jana Thayer (SLAC National Accelerator Laboratory)
Thomas Uram (Argonne National Laboratory)