[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124641-en":3,"doc-seo-124641-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124641,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","Machine Learning Based Alignment For LCLS-II-HE Optics - abstract","Hard X-ray instruments at the Linac Coherent Light Source are being upgraded to exploit the higher repetition rates of LCLS-II-HE. The X-ray Correlation Spectroscopy instrument is converted to Dynamic X-ray Scattering, featuring a meV-scale high-resolution monochromator with unprecedented coherent flux. Long-term drift and vibration sensitivity motivate estimation of angular-drift and vibration tolerances for relevant optics. Simulation results show trained machine learning models can correct misalignments to maintain central energy and optical axis, while Bayesian optimization reduces thermal-deformation and alignment-from-scratch impacts, with ongoing extensions.","arXiv :2308 .07521v1 [physics .acc-ph] 15 Aug 2023  \nMachine Learning Based Alignment For LCLS-II-HE Optics  \nAashwin Mishra, Nicholas Brennan, Tianyu Huang, Jason Jaquith, Hasan Yava¸s, and Matthew  \nSeaberg  \nSLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA  \nABSTRACT  \nThe hard X-ray instruments at the Linac Coherent Light Source are in the design phase for upgrades that will take full advantage of the high repetition rates that will become available with LCLS-II-HE. The current X-ray Correlation Spectroscopy instrument will be converted to the Dynamic X-ray Scattering instrument, and will feature a meV-scale high-resolution monochromator at its front end with unprecedented coherent flux. With the new capability come many engineering and design challenges, not least of which is the sensitivity to long-term drift of the optics. With this in mind, we have estimated the system tolerance to angular drift and vibration for all the relevant optics (∼ 10 components) in terms of how the central energy out of the monochromator will be affected to inform the mechanical design. Additionally, we have started planning for methods to correct for such drifts using available (both invasive and non-invasive) X-ray beam diagnostics. In simulations, we have demonstrated the ability of trained Machine Learning models to correct misalignments to maintain the desired central energy and optical axis within the necessary tolerances. Additionally, we exhibit the use of Bayesian Optimization to minimize the impact of thermal deformations of crystals as well as beam alignment from scratch. The initial results are very promising and efforts to further extend this work are ongoing.  \nKeywords: Linac Coherent Light Source, X-ray beam diagnostics, Machine Learning, Bayesian Optimization  \n1. INTRODUCTION  \nThe Linac Coherent Light Source (LCLS), the first hard X-ray free electron laser in the world, has recently completed the LCLS-II upgrade and is ready to be turned on to deliver high repetition rate at soft X-ray energies. The LCLS-II-HE project is currently in the design phase and will extend LCLS-II to hard X-ray energies, eventually reaching 20 keV. With LCLS-II-HE, we have an opportunity to make measurements that are orders of magnitude more sensitive than what can be made currently at LCLS. This can take many shapes and forms, including high-resolution spectroscopic measurements at the upcoming Dynamic X-ray Scattering (DXS) instrument, all the way to imaging operando systems with high resolution by taking advantage of the unprecedented coherent flux.1  \nAll of these new directions rely on sensitive (and sometimes complex) optical systems that are often spread over many meters and must be aligned properly and efficiently. Furthermore, in order to ensure successful experiments the proper alignment must be maintained within a tight tolerance over the course of hours to days. These are tasks that are increasingly challenging for a human expert to perform without help. Here, we present first steps towards the use of Machine Learning (ML) methods for the alignment and drift correction of a model x-ray optical system. The system chosen for the study is a novel hard X-ray high-resolution monochromator (HRM), designed to preserve the bandwidth-limited XFEL pulse duration. The system is based on the zero dispersion stretcher concept developed for ultrafast lasers, the details of which will be the subject of a forthcoming article and not described here. As the system currently only exists at the conceptual level, all of the results presented in the following sections are based on wave optics simulations rather than physical experiments.  \nFor the purposes of this manuscript, this monochromator design provides a case study of a system with many degrees of freedom and X-ray beam diagnostics, with a photon energy output that is strongly sensitive (relative to the desired ∼meV resolution) to misalignments of a number of the relevant degrees of fr","cbCaibzQU6kxJ7AL","https://ap.wps.com/l/cbCaibzQU6kxJ7AL","pdf",445592,1,7,"English","en",105,"# Introduction\n## Mathematical Details","[{\"question\":\"Why is alignment drift a critical issue for LCLS-II-HE optics?\",\"answer\":\"The upgraded instruments target meV-level energy resolution, making the output strongly sensitive to optical misalignments. Long-term drift and vibration can change the central energy and optical axis beyond tight tolerances during hours to days.\"},{\"question\":\"What optics system is used as the study case?\",\"answer\":\"The study uses a conceptual hard X-ray high-resolution monochromator (HRM) designed to preserve bandwidth-limited XFEL pulse duration, modeled with wave-optics simulations rather than physical experiments.\"},{\"question\":\"How do machine learning and Bayesian optimization contribute to alignment correction?\",\"answer\":\"Trained machine learning models correct simulated misalignments to maintain desired central energy and optical axis. Bayesian optimization is used to mitigate crystal thermal deformation and to perform alignment from scratch, reducing the impact of thermal and alignment uncertainties.\"}]","Machine Learning Based Alignment For LCLS-II-HE Optics - abstract | PDF",1785893483,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-based-alignment-for-lcls-ii-he-optics-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-based-alignment-for-lcls-ii-he-optics-abstract/124641/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is alignment drift a critical issue for LCLS-II-HE optics?","Question",{"text":75,"@type":76},"The upgraded instruments target meV-level energy resolution, making the output strongly sensitive to optical misalignments. Long-term drift and vibration can change the central energy and optical axis beyond tight tolerances during hours to days.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What optics system is used as the study case?",{"text":80,"@type":76},"The study uses a conceptual hard X-ray high-resolution monochromator (HRM) designed to preserve bandwidth-limited XFEL pulse duration, modeled with wave-optics simulations rather than physical experiments.",{"name":82,"@type":73,"acceptedAnswer":83},"How do machine learning and Bayesian optimization contribute to alignment correction?",{"text":84,"@type":76},"Trained machine learning models correct simulated misalignments to maintain desired central energy and optical axis. Bayesian optimization is used to mitigate crystal thermal deformation and to perform alignment from scratch, reducing the impact of thermal and alignment uncertainties.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]