{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/compressed-sensing-of-scanning-transmission","title":"Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) on Non-Rectangular Scans","arxiv_id":"1805.04957","date":"2018-05-13","proceeding":null,"authors":["Xin Li","Ondrej Dyck","Sergei V. Kalinin","Stephen Jesse"],"abstract":"Scanning Transmission Electron Microscopy (STEM) has become the main stay for\nmaterials characterization on atomic level, with applications ranging from\nvisualization of localized and extended defects to mapping order parameter\nfields. In the last several years, attention was attracted by potential of STEM\nto explore beam induced chemical processes and especially manipulating atomic\nmotion, enabling atom-by-atom fabrication. These applications, as well as\ntraditional imaging of beam sensitive materials, necessitate increasing dynamic\nrange of STEM between imaging and manipulation modes, and increasing absolute\nscanning/imaging speeds, that can be achieved by combining sparse sensing\nmethods with non-rectangular scanning trajectories. Here we developed a general\nmethod for real-time reconstruction of sparsely sampled images from high-speed,\nnon-invasive and diverse scanning pathways. This approach is demonstrated on\nboth the synthetic data where ground truth is known and the experimental STEM\ndata. This work lays the foundation for future tasks such as optimal design of\ndose efficient scanning strategies and real-time adaptive inference and control\nof e-beam induced atomic fabrication.","url_abs":"http://arxiv.org/abs/1805.04957v3","url_pdf":"http://arxiv.org/pdf/1805.04957v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"compressed-sensing-of-scanning-transmission","repo_url":"https://github.com/nonmin/RTSSTEM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"compressed-sensing","task_name":"compressed sensing"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}