[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122112-en":3,"doc-seo-122112-105":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":4,"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},122112,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Machine learning driven design and fabrication of photonic devices with engineered dispersion - PhD thesis","A PhD thesis exploring how machine learning can drive the design and fabrication of photonic devices featuring engineered dispersion. The work is authored by Ziheng Guo at the University of St Andrews and includes research acknowledgements, funding information, and declarations about authorship, admission, and scholarly support. It also provides statements regarding permissions for publication, access to research codes via GitHub, and confirmation of research data and digital output deposit requirements. Publication includes clear embargo settings and licensing details.","Machine learning driven design and fabrication of photonic devices with engineered dispersion  \nZiheng Guo  \nA thesis submitted for the degree of PhD  \nat the  \nUniversity of St Andrews  \n2025  \nFull metadata for this thesis is available in St Andrews Research Repository at:  \n[https://research-repository.st-andrews.ac.uk/](https://research-repository.st-andrews.ac.uk/)  \n[Identifier to use to cite or link to this thesis:](Identifier to use to cite or link to this thesis:)[ ](Identifier to use to cite or link to this thesis:)DOI: [https://doi.org/10.17630/sta/1251](https://doi.org/10.17630/sta/1251)  \nThis item is protected by original copyright  \nThis item is licensed under a Creative Commons Licence  \n[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)  \nAcknowledgements  \nI am incredibly grateful to Professor Andrea Di Falco, who guided me through the fascinating world of photonics and successfully mentored me in transitioning from a mathematician to an applied physicist. His expertise and insight have been instrumental in shaping my academic and research path.  \nI also wish to extend my sincere thanks to the Synthetic Optics Group for fostering a warm, supportive, and friendly environment. In particular, I would like to thank Zhongliang Guo from Computer Science for helping me regularize my coding practices and supporting me through my first machine learning project. I am equally grateful to the Associate Professor Sebastian Schulz for his advice on ellipsometry fitting, and to Owen Church, whose camaraderie in the gaming society brought much-needed relaxation. I must also thank the cleanroom technicians for their invaluable assistance in ensuring smooth progress in the lab. My thanks also go to Dr. Jiangmei Liu, Dr. Shaoyang Wang, WeiYe Li, Jiawei You, Yaxiong Lei, Mengfan He, Yuhui Gan, Dr. Jianling Xiao, Jinyi Chen, and Dr. Tomasz Plaskocinski for providing good food and joyful emotional support, which added warmth and balance throughout this journey.  \nAdditionally, I appreciate the support of several investment agencies and individuals who showed interest in my idea of a physics-focused Large Language Model. Their belief in my vision provided me with the strength and direction to explore the future of Artificial Intelligence applications. And I am grateful to all the machines that functioned perfectly when I needed them most.  \nLastly, I would like to express my deepest gratitude to my parents for their unwavering support throughout the difficult times of the pandemic and my four-year journey in pursuing a Ph.D. Their encouragement was invaluable in helping me reach this milestone.  \nFunding  \nThis work was supported by the self-funding first year, and the Chinese Scholarship Council for three years funding [grant number. 202108060233] .  \nResearch Data access statement  \nResearch codes underpinning this thesis are available at  \n[https://github.com/ZooBeasts](https://github.com/ZooBeasts)  \nCandidate's declaration  \nI, Ziheng Guo, do hereby certify that this thesis, submitted for the degree of PhD, which is approximately 44,000 words in length, has been written by me, and that it is the record of work carried out by me, or principally by myself in collaboration with others as acknowledged, and that it has not been submitted in any previous application for any degree. I confirm that any appendices included in my thesis contain only material permitted by the 'Assessment of Postgraduate Research Students' policy.  \nI was admitted as a research student at the University of St Andrews in October 2020.  \nI, Ziheng Guo, received assistance in the writing of this thesis in respect of grammar, which was provided by Andrea Di Falco.  \nI received funding from an organisation or institution and have acknowledged the funder(s) in the full text of my thesis.  \nDate Signature of candidate  \n25/10/24  \nSupervisor's declaration  \nI hereby certify that the candidate has fulfilled the conditions","cbCaiqUOXrijR4sp","https://ap.wps.com/l/cbCaiqUOXrijR4sp","pdf",8911524,1,244,"English","en",105,"# Acknowledgements\n# Funding\n# Research Data access statement\n# Candidate's declaration\n# Supervisor's declaration\n# Permission for publication\n## Printed copy\n## Electronic copy\n# Underpinning Research Data or Digital Outputs\n# Publications","[{\"question\":\"What is the thesis topic and main focus?\",\"answer\":\"The thesis focuses on machine learning driven design and fabrication of photonic devices with engineered dispersion.\"},{\"question\":\"Where can the research codes supporting the thesis be accessed?\",\"answer\":\"The supporting research codes are available at https://github.com/ZooBeasts.\"},{\"question\":\"What publication permissions and embargo settings are included?\",\"answer\":\"The thesis grants permission for use according to the University Library regulations, with no embargo on both the printed copy and the electronic copy.\"}]","Machine learning driven design and fabrication of photonic devices with engineered dispersion - 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