Advanced Photonics, Volume. 4, Issue 6, 066001(2022)

Physics-informed neural networks for diffraction tomography On the Cover

Amirhossein Saba*, Carlo Gigli1、†, Ahmed B. Ayoub, and Demetri Psaltis
Author Affiliations
  • École Polytechnique Fédérale de Lausanne, Optics Laboratory, Lausanne, Switzerland
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    Equations(8)
    LPh=r1N[2+k02n2(r)]Us+k02[n2(r)n02]Ui2,

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    wwγPhLPhw.

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    LD=i=1L1LUs(Ri{n})Uim2+Reg{n,Us(n)},

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    nnγDLDn.

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    RTV(n)=r|xn(r)|2+|yn(r)|2+|zn(r)|2,(5a)

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    RNN(n)=rmin[n(r)n0,0]2.(5b)

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    Error=UMaxwellNet(r)UCOMSOL(r)2drUCOMSOL(r)2dr,

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    Usx=Us((i+1)Δx,jΔy,kΔz)Us((i1)Δx,jΔy,kΔz)2Δx,

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    Amirhossein Saba, Carlo Gigli, Ahmed B. Ayoub, Demetri Psaltis. Physics-informed neural networks for diffraction tomography[J]. Advanced Photonics, 2022, 4(6): 066001

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    Paper Information

    Category: Research Articles

    Received: Jul. 9, 2022

    Accepted: Oct. 27, 2022

    Posted: Oct. 27, 2022

    Published Online: Nov. 25, 2022

    The Author Email: Saba Amirhossein (amirhossein.sabashirvan@epfl.ch)

    DOI:10.1117/1.AP.4.6.066001

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