Advancing AI/ML at the Advanced Photon Source-Reference-Cited by-同舟云学术

Advancing AI/ML at the Advanced Photon Source

Published:2022-07-04 Issue:4 Volume:35 Page:28-35
ISSN:0894-0886
Container-title:Synchrotron Radiation News
language:en
Short-container-title:Synchrotron Radiation News

Author:

Benmore Chris¹^ORCID,Bicer Tekin¹²^ORCID,Chan Maria K. Y.³^ORCID,Di Zichao¹⁴,Gürsoy Dog˘a¹^ORCID,Hwang Inhui¹,Kuklev Nikita⁵^ORCID,Lin Dergan⁴,Liu Zhengchun²,Lobach Ihar⁵^ORCID,Qiao Zhi¹^ORCID,Rebuffi Luca¹^ORCID,Sharma Hemant¹,Shi Xianbo¹^ORCID,Sun Chengjun¹,Yao Yudong¹^ORCID,Zhou Tao³,Sandy Alec¹^ORCID,Miceli Antonino¹,Sun Yine⁵,Schwarz Nicholas¹,Cherukara Mathew J.¹^ORCID

Affiliation:

1. X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, Illinois, USA

2. Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois, USA

3. Center for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois, USA

4. Mathematics and Computer Science, Argonne National Laboratory, Lemont, Illinois, USA

5. Accelerator Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, Illinois, USA

Funder

the U.S. DOE Office of Science-Basic Energy Sciences

the Argonne Leadership Computing Facility,

Publisher

Informa UK Limited

Subject

Nuclear and High Energy Physics,Atomic and Molecular Physics, and Optics

Link

https://www.tandfonline.com/doi/pdf/10.1080/08940886.2022.2112500

Reference31 articles.

1. Adaptive shape control of wavefront-preserving X-ray mirrors with active cooling and heating

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