Introduction of the Sirepo-Bluesky interface and its application to the optimization problems

Maksim S. Rakitin; Abigail Giles; Kaleb Swartz; Joshua Lynch; Paul Moeller; Robert Nagler; Daniel B. Allan; Thomas A. Caswell; Lutz Wiegart; Oleg Chubar; Yonghua Du

doi:10.1117/12.2569000

21 August 2020 Introduction of the Sirepo-Bluesky interface and its application to the optimization problems

Maksim S. Rakitin, Abigail Giles, Kaleb Swartz, Joshua Lynch, Paul Moeller, Robert Nagler, Daniel B. Allan, Thomas A. Caswell, Lutz Wiegart, Oleg Chubar, Yonghua Du

Author Affiliations +

Proceedings Volume 11493, Advances in Computational Methods for X-Ray Optics V; 1149311 (2020) https://doi.org/10.1117/12.2569000
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

Simulation of beamlines at light sources is an essential part of their design and commissioning. Such simulations can be performed by the Synchrotron Radiation Workshop (SRW) code, which now has a user-friendly, browser- based interface, Sirepo. The simulations, utilizing a concept of a "virtual" beamline, can aim to optimize the specific aspects of a beamline, such as maximization of the flux, minimization of the beam size, etc. These tasks are also performed at the physical beamlines using various alignment procedures. At NSLS-II these procedures are executed by the Bluesky data collection framework. The Sirepo-Bluesky interface leverages both systems to allow for the multiparameter optimization of the X-ray source and beamline optics with the power of bluesky's plans used for the daily experiments at NSLS-II, and databroker's capabilities to retrieve the captured data and metadata to perform further analysis. Such a "collaboration" between the frameworks can be used to store the simulated results in the same database as for the experimental data, and seamlessly apply the same analysis pipelines, demonstrated in recent publications. In a simulation, multiple parameters can be changed at once and be stored as a snapshot of the "virtual" beamline in time along with the corresponding results of the simulations. A global optimization algorithm (e.g., a genetic algorithm) can then utilize the data to find the best configuration for the desired outcome. Such an optimization procedure can be seamlessly applied to the real hardware by substituting the virtual motors and detectors by the real ones.

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Maksim S. Rakitin, Abigail Giles, Kaleb Swartz, Joshua Lynch, Paul Moeller, Robert Nagler, Daniel B. Allan, Thomas A. Caswell, Lutz Wiegart, Oleg Chubar, and Yonghua Du "Introduction of the Sirepo-Bluesky interface and its application to the optimization problems", Proc. SPIE 11493, Advances in Computational Methods for X-Ray Optics V, 1149311 (21 August 2020); https://doi.org/10.1117/12.2569000

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