A physics-aware neural network for effective refractive index prediction of photonic waveguides: A physics-aware neural network for effective refractive...: H.S. Ünal, A.C. Durgun.
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| Title: | A physics-aware neural network for effective refractive index prediction of photonic waveguides: A physics-aware neural network for effective refractive...: H.S. Ünal, A.C. Durgun. |
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| Authors: | Ünal, Hasan Said1,2 (AUTHOR) hasan.unal@metu.edu.tr, Durgun, Ahmet Cemal1 (AUTHOR) acdurgun@metu.edu.tr |
| Source: | Optical & Quantum Electronics. Jan2025, Vol. 57 Issue 1, p1-13. 13p. |
| Subjects: | Rectangular waveguides, Refractive index, Dynamical systems, Waveguides, Dynamic models |
| Abstract: | Neural network (NN)—based surrogates have been effectively used for modeling dynamic systems, including photonic devices. However, black-box data-driven modeling approaches significantly suffer from performance reduction in high-dimensional spaces.As a remedy, we propose a novel physics-aware NN architecture for the effective index prediction of photonic strip waveguides. The model learns a translation between the strip waveguide and an equivalent infinite slab waveguide by employing physical loss terms in the loss function. The proposed method exhibits significantly lower error, with more than 50 % reduction, compared to a black-box NN and a variational method. Because of its physical basis, the proposed NN can predict field distributions in rectangular waveguides and the effective indices of higher-order modes. [ABSTRACT FROM AUTHOR] |
| Copyright of Optical & Quantum Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 182279775 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A physics-aware neural network for effective refractive index prediction of photonic waveguides: A physics-aware neural network for effective refractive...: H.S. Ünal, A.C. Durgun. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ünal%2C+Hasan+Said%22">Ünal, Hasan Said</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> hasan.unal@metu.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Durgun%2C+Ahmet+Cemal%22">Durgun, Ahmet Cemal</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> acdurgun@metu.edu.tr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Optical+%26+Quantum+Electronics%22">Optical & Quantum Electronics</searchLink>. Jan2025, Vol. 57 Issue 1, p1-13. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Rectangular+waveguides%22">Rectangular waveguides</searchLink><br /><searchLink fieldCode="DE" term="%22Refractive+index%22">Refractive index</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamical+systems%22">Dynamical systems</searchLink><br /><searchLink fieldCode="DE" term="%22Waveguides%22">Waveguides</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+models%22">Dynamic models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Neural network (NN)—based surrogates have been effectively used for modeling dynamic systems, including photonic devices. However, black-box data-driven modeling approaches significantly suffer from performance reduction in high-dimensional spaces.As a remedy, we propose a novel physics-aware NN architecture for the effective index prediction of photonic strip waveguides. The model learns a translation between the strip waveguide and an equivalent infinite slab waveguide by employing physical loss terms in the loss function. The proposed method exhibits significantly lower error, with more than 50 % reduction, compared to a black-box NN and a variational method. Because of its physical basis, the proposed NN can predict field distributions in rectangular waveguides and the effective indices of higher-order modes. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Optical & Quantum Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11082-024-08009-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 1 Subjects: – SubjectFull: Rectangular waveguides Type: general – SubjectFull: Refractive index Type: general – SubjectFull: Dynamical systems Type: general – SubjectFull: Waveguides Type: general – SubjectFull: Dynamic models Type: general Titles: – TitleFull: A physics-aware neural network for effective refractive index prediction of photonic waveguides: A physics-aware neural network for effective refractive...: H.S. Ünal, A.C. Durgun. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ünal, Hasan Said – PersonEntity: Name: NameFull: Durgun, Ahmet Cemal IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 03068919 Numbering: – Type: volume Value: 57 – Type: issue Value: 1 Titles: – TitleFull: Optical & Quantum Electronics Type: main |
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