JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{nash:napac2022-mopa57,
author = {B. Nash and D.T. Abell and Y. Du and A. Giles and N.B. Goldring and M.V. Keilman and J. Lynch and P. Moeller and T. Morris and I.V. Pogorelov and M.S. Rakitin and A. Walter},
% author = {B. Nash and D.T. Abell and Y. Du and A. Giles and N.B. Goldring and M.V. Keilman and others},
% author = {B. Nash and others},
title = {{Online Models for X-Ray Beamlines}},
& booktitle = {Proc. NAPAC'22},
booktitle = {Proc. 5th Int. Particle Accel. Conf. (NAPAC'22)},
pages = {170--173},
eid = {MOPA57},
language = {english},
keywords = {optics, emittance, synchrotron, radiation, controls},
venue = {Albuquerque, NM, USA},
series = {International Particle Accelerator Conference},
number = {5},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {10},
year = {2022},
issn = {2673-7000},
isbn = {978-3-95450-232-5},
doi = {10.18429/JACoW-NAPAC2022-MOPA57},
url = {https://jacow.org/napac2022/papers/mopa57.pdf},
abstract = {{X-ray beamlines transport synchrotron radiation from the magnetic source to the sample at a synchrotron light source. Alignment of elements such as mirrors and gratings are often done manually and can be quite time consuming. The use of photon beam models during operations is not common in the same way that they are used to great benefit for particle beams in accelerators. Linear and non-linear optics including the effects of coherence may be computed from source properties and augmented with measurements. In collaboration with NSLS-II, we are developing software tools and methods to include the model of the x-ray beam as it passes on its way to the sample. We are integrating the Blue-Sky beamline control toolkit with the Sirepo interface to several x-ray optics codes. Further, we are developing a simplified linear optics approach based on a Gauss-Schell model and linear canonical transforms as well as developing Machine Learning models for use directly from diagnostics data. We present progress on applying these ideas on NSLS-II beamlines and give a future outlook on this rather large and open domain for technological development.}},
}