Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model
In this study, a simplified transformer model is used to predict the beam waist of 1,092 nm light coupled out from SiN-based mixed pitch gratings at various heights. The beam waists data at various heights above the grating is first compiled. Then, we used a sequence of the current beam waist values...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10634767/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849417378202386432 |
|---|---|
| author | Yu Dian Lim Peng Zhao Luca Guidoni Jean-Pierre Likforman Chuan Seng Tan |
| author_facet | Yu Dian Lim Peng Zhao Luca Guidoni Jean-Pierre Likforman Chuan Seng Tan |
| author_sort | Yu Dian Lim |
| collection | DOAJ |
| description | In this study, a simplified transformer model is used to predict the beam waist of 1,092 nm light coupled out from SiN-based mixed pitch gratings at various heights. The beam waists data at various heights above the grating is first compiled. Then, we used a sequence of the current beam waist values, z-positions, and the computed mathematical indicators (features) to predict the next beam waist value (labels). Optimized transformer model yields average percentage error (APE) of 6.6% between the predicted and actual beam waists, which corresponds to 93.4% prediction accuracy. This study provides a pioneering approach to using natural language processing model to perform predictive modelling on photonics data, and possible extrapolation of photonics data using transformer model. |
| format | Article |
| id | doaj-art-44cdfdddd6c54e28b81f34026d82d3b2 |
| institution | Kabale University |
| issn | 1943-0655 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj-art-44cdfdddd6c54e28b81f34026d82d3b22025-08-20T03:32:51ZengIEEEIEEE Photonics Journal1943-06552024-01-011651910.1109/JPHOT.2024.344216910634767Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer ModelYu Dian Lim0https://orcid.org/0000-0003-4188-997XPeng Zhao1https://orcid.org/0000-0002-4850-9354Luca Guidoni2https://orcid.org/0000-0002-7175-8471Jean-Pierre Likforman3https://orcid.org/0000-0002-8879-7813Chuan Seng Tan4https://orcid.org/0000-0003-1250-9165School of Electrical and Electronics Engineering, Nanyang Technological University, SingaporeInteruniversity Microelectronics Centre (IMEC), Leuven, BelgiumLaboratoire Matériaux et Phénomènes Quantiques (MPQ), Université de Paris, Paris, FranceLaboratoire Matériaux et Phénomènes Quantiques (MPQ), Université de Paris, Paris, FranceSchool of Electrical and Electronics Engineering, Nanyang Technological University, SingaporeIn this study, a simplified transformer model is used to predict the beam waist of 1,092 nm light coupled out from SiN-based mixed pitch gratings at various heights. The beam waists data at various heights above the grating is first compiled. Then, we used a sequence of the current beam waist values, z-positions, and the computed mathematical indicators (features) to predict the next beam waist value (labels). Optimized transformer model yields average percentage error (APE) of 6.6% between the predicted and actual beam waists, which corresponds to 93.4% prediction accuracy. This study provides a pioneering approach to using natural language processing model to perform predictive modelling on photonics data, and possible extrapolation of photonics data using transformer model.https://ieeexplore.ieee.org/document/10634767/Attentiongratingsmulti-head attentionphotonics integrated circuitsquantum computingself-attention |
| spellingShingle | Yu Dian Lim Peng Zhao Luca Guidoni Jean-Pierre Likforman Chuan Seng Tan Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model IEEE Photonics Journal Attention gratings multi-head attention photonics integrated circuits quantum computing self-attention |
| title | Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model |
| title_full | Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model |
| title_fullStr | Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model |
| title_full_unstemmed | Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model |
| title_short | Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model |
| title_sort | next value prediction of beam waists from mixed pitch grating using simplified transformer model |
| topic | Attention gratings multi-head attention photonics integrated circuits quantum computing self-attention |
| url | https://ieeexplore.ieee.org/document/10634767/ |
| work_keys_str_mv | AT yudianlim nextvaluepredictionofbeamwaistsfrommixedpitchgratingusingsimplifiedtransformermodel AT pengzhao nextvaluepredictionofbeamwaistsfrommixedpitchgratingusingsimplifiedtransformermodel AT lucaguidoni nextvaluepredictionofbeamwaistsfrommixedpitchgratingusingsimplifiedtransformermodel AT jeanpierrelikforman nextvaluepredictionofbeamwaistsfrommixedpitchgratingusingsimplifiedtransformermodel AT chuansengtan nextvaluepredictionofbeamwaistsfrommixedpitchgratingusingsimplifiedtransformermodel |