Highly-efficient flat-optics inverse design platform via fast trained neural predictors

Maksim Makarenko; A. Burguete-Lopez; Fedor Getman; Andrea Fratalocchi

doi:10.1117/12.2603689

Highly-efficient flat-optics inverse design platform via fast trained neural predictors

Maksim Makarenko, A. Burguete-Lopez, Fedor Getman, Andrea Fratalocchi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We introduce a universal design platform for the development of highly-efficient wavefront engineering structures. To validate this methodology, we fabricated many different optical devices with an experimental efficiency exceeding 99%.

Original language	English (US)
Title of host publication	International Optical Design Conference 2021
Publisher	SPIE
ISBN (Print)	9781510650305
DOIs	https://doi.org/10.1117/12.2603689
State	Published - Nov 19 2021

Bibliographical note

KAUST Repository Item: Exported on 2022-02-11
Acknowledged KAUST grant number(s): OSR-2016-CRG5-2995
Acknowledgements: This research received funding from KAUST (Award OSR-2016-CRG5-2995). Parallel simulations are performed on KAUST’s Shaheen supercomputer.

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10.1117/12.2603689

https://repository.kaust.edu.sa/bitstream/10754/675327/1/osa_2021_daf.pdf

Cite this

@inproceedings{f9add5aa89a84aea93b6535b3d4c335e,

title = "Highly-efficient flat-optics inverse design platform via fast trained neural predictors",

abstract = "We introduce a universal design platform for the development of highly-efficient wavefront engineering structures. To validate this methodology, we fabricated many different optical devices with an experimental efficiency exceeding 99%.",

author = "Maksim Makarenko and A. Burguete-Lopez and Fedor Getman and Andrea Fratalocchi",

note = "KAUST Repository Item: Exported on 2022-02-11 Acknowledged KAUST grant number(s): OSR-2016-CRG5-2995 Acknowledgements: This research received funding from KAUST (Award OSR-2016-CRG5-2995). Parallel simulations are performed on KAUST{\textquoteright}s Shaheen supercomputer.",

year = "2021",

month = nov,

day = "19",

doi = "10.1117/12.2603689",

language = "English (US)",

isbn = "9781510650305",

booktitle = "International Optical Design Conference 2021",

publisher = "SPIE",

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T1 - Highly-efficient flat-optics inverse design platform via fast trained neural predictors

AU - Makarenko, Maksim

AU - Burguete-Lopez, A.

AU - Getman, Fedor

AU - Fratalocchi, Andrea

N1 - KAUST Repository Item: Exported on 2022-02-11 Acknowledged KAUST grant number(s): OSR-2016-CRG5-2995 Acknowledgements: This research received funding from KAUST (Award OSR-2016-CRG5-2995). Parallel simulations are performed on KAUST’s Shaheen supercomputer.

PY - 2021/11/19

Y1 - 2021/11/19

N2 - We introduce a universal design platform for the development of highly-efficient wavefront engineering structures. To validate this methodology, we fabricated many different optical devices with an experimental efficiency exceeding 99%.

AB - We introduce a universal design platform for the development of highly-efficient wavefront engineering structures. To validate this methodology, we fabricated many different optical devices with an experimental efficiency exceeding 99%.

UR - http://hdl.handle.net/10754/675327

UR - http://mr.crossref.org/iPage?doi=10.1117%2F12.2603689

UR - http://www.scopus.com/inward/record.url?scp=85122910042&partnerID=8YFLogxK

U2 - 10.1117/12.2603689

DO - 10.1117/12.2603689

M3 - Conference contribution

SN - 9781510650305

BT - International Optical Design Conference 2021

PB - SPIE

ER -

Highly-efficient flat-optics inverse design platform via fast trained neural predictors

Abstract

Bibliographical note

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