Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms
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| Other Authors: | |
| Format: | Tesis de doctorado |
| Published: |
MX
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.14330/TES01000826874 http://132.248.9.195/ptd2022/junio/0826874/Index.html |
| _version_ | 1832755356939321344 |
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| author | Peralta Ángeles, Jorge Alberto |
| author2 | Reyes Esqueda, Jorge Alejandro |
| author2_role | Asesor |
| author_facet | Reyes Esqueda, Jorge Alejandro Peralta Ángeles, Jorge Alberto |
| author_sort | Peralta Ángeles, Jorge Alberto |
| collection | DSpace |
| degree_department | Instituto de Física |
| degree_department_facet | Instituto de Física |
| degree_grantor | Universidad Nacional Autónoma de México |
| degree_level | Doctorado |
| degree_name | Doctorado en Ciencias (Física) |
| degree_name_facet | Doctorado en Ciencias (Física) |
| format | Tesis de doctorado |
| id | 20.500.14330-TES01000826874 |
| institution | Universidad Nacional Autónoma de México |
| publishDate | 2022 |
| publisher | MX |
| record_format | dspace |
| rights | http://creativecommons.org/licenses/by-nc-nd/4.0 Acceso en línea sin restricciones |
| spelling | 20.500.14330-TES010008268742024-07-24T17:39:16Z Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms Peralta Ángeles, Jorge Alberto Reyes Esqueda, Jorge Alejandro Ciencias Físico - Matemáticas y de las Ingenierías 2022 Tesis de doctorado https://hdl.handle.net/20.500.14330/TES01000826874 http://132.248.9.195/ptd2022/junio/0826874/Index.html http://creativecommons.org/licenses/by-nc-nd/4.0 Acceso en línea sin restricciones MX https://tesiunam.dgb.unam.mx/F?current_base=TES01&func=direct&doc_number=000826874 Doctorado en Ciencias (Física) Universidad Nacional Autónoma de México Instituto de Física Doctorado |
| spellingShingle | Ciencias Físico - Matemáticas y de las Ingenierías Peralta Ángeles, Jorge Alberto Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title | Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title_full | Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title_fullStr | Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title_full_unstemmed | Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title_short | Analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| title_sort | analytically-supported optimal design of hybrid photonic-plasmonic crystals using machine learning algorithms |
| topic | Ciencias Físico - Matemáticas y de las Ingenierías |
| url | https://hdl.handle.net/20.500.14330/TES01000826874 http://132.248.9.195/ptd2022/junio/0826874/Index.html |
| work_keys_str_mv | AT peraltaangelesjorgealberto analyticallysupportedoptimaldesignofhybridphotonicplasmoniccrystalsusingmachinelearningalgorithms |