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Phase-aware free-form inverse design of apodized and chirped fiber Bragg gratings via multi-task U-Net.

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Title: Phase-aware free-form inverse design of apodized and chirped fiber Bragg gratings via multi-task U-Net.
Authors: Lee, Jinho1 (AUTHOR) jinho.lee@mq.edu.au, Kim, Jinchoel2,3 (AUTHOR)
Source: Optics Communications. Oct2026, Vol. 615, pN.PAG-N.PAG. 1p.
Subjects: Fiber Bragg gratings, Apodization, Optical dispersion, Design techniques, Deep learning, Light filters
Abstract: Chirped fiber Bragg gratings (CFBGs) are essential components in optical communications and ultrafast laser systems, providing critical functions such as chromatic dispersion compensation and pulse shaping. Achieving optimal performance requires precise control over two structural parameters, that is the local grating period distribution and the refractive index profile (apodization). While deep learning has recently emerged as a promising tool for inverse design, many existing approaches formulate the task as a parameter retrieval problem, mapping spectral data to a limited set of scalar coefficients based on predefined functions. Here, we present a flexible, data-driven inverse design framework using a multi-task U-Net architecture capable of reconstructing arbitrary, free-form apodization and chirp profiles. A key feature of our approach is the explicit utilization of both reflectivity and group delay spectra as inputs, which enhances the retrieval of phase information essential for accurate dispersion engineering. Furthermore, to ensure that the predicted structures remain smooth and physically realizable without imposing strict geometric constraints, we incorporate a composite loss function with Total Variation (TV) regularization. Numerical verification via the Transfer Matrix Method (TMM) demonstrates that the proposed model successfully reproduces complex target specification, offering a robust and versatile tool for advanced optical filter design. [ABSTRACT FROM AUTHOR]
Copyright of Optics Communications is the property of Elsevier B.V. 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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DbLabel: Engineering Source
An: 193591090
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PubTypeId: academicJournal
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  Data: Phase-aware free-form inverse design of apodized and chirped fiber Bragg gratings via multi-task U-Net.
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  Data: <searchLink fieldCode="AR" term="%22Lee%2C+Jinho%22">Lee, Jinho</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jinho.lee@mq.edu.au</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Jinchoel%22">Kim, Jinchoel</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="DE" term="%22Fiber+Bragg+gratings%22">Fiber Bragg gratings</searchLink><br /><searchLink fieldCode="DE" term="%22Apodization%22">Apodization</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+dispersion%22">Optical dispersion</searchLink><br /><searchLink fieldCode="DE" term="%22Design+techniques%22">Design techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Light+filters%22">Light filters</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Chirped fiber Bragg gratings (CFBGs) are essential components in optical communications and ultrafast laser systems, providing critical functions such as chromatic dispersion compensation and pulse shaping. Achieving optimal performance requires precise control over two structural parameters, that is the local grating period distribution and the refractive index profile (apodization). While deep learning has recently emerged as a promising tool for inverse design, many existing approaches formulate the task as a parameter retrieval problem, mapping spectral data to a limited set of scalar coefficients based on predefined functions. Here, we present a flexible, data-driven inverse design framework using a multi-task U-Net architecture capable of reconstructing arbitrary, free-form apodization and chirp profiles. A key feature of our approach is the explicit utilization of both reflectivity and group delay spectra as inputs, which enhances the retrieval of phase information essential for accurate dispersion engineering. Furthermore, to ensure that the predicted structures remain smooth and physically realizable without imposing strict geometric constraints, we incorporate a composite loss function with Total Variation (TV) regularization. Numerical verification via the Transfer Matrix Method (TMM) demonstrates that the proposed model successfully reproduces complex target specification, offering a robust and versatile tool for advanced optical filter design. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Optics Communications is the property of Elsevier B.V. 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:
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      – Type: doi
        Value: 10.1016/j.optcom.2026.133267
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Fiber Bragg gratings
        Type: general
      – SubjectFull: Apodization
        Type: general
      – SubjectFull: Optical dispersion
        Type: general
      – SubjectFull: Design techniques
        Type: general
      – SubjectFull: Deep learning
        Type: general
      – SubjectFull: Light filters
        Type: general
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      – TitleFull: Phase-aware free-form inverse design of apodized and chirped fiber Bragg gratings via multi-task U-Net.
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              Text: Oct2026
              Type: published
              Y: 2026
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