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Deeply subwavelength optical imaging

Deeply subwavelength optical imaging
Deeply subwavelength optical imaging
We report the experimental demonstration of deeply subwavelength far-field
optical imaging of unlabelled samples with resolution better than λ/20. We beat the ~λ/2 diffraction limit of conventional optical microscopy several times over by recording the intensity pattern of coherent light scattered from the object into the far-field. We retrieve information about the object with a deep learning neural network trained on scattering events from a large set of known objects.
2331-8422
Pu, Tanchao
89eb5a37-31bf-469a-ae29-c871d5d25c65
Ou, Jun-Yu
3fb703e3-b222-46d2-b4ee-75f296d9d64d
Papasimakis, Nikitas
f416bfa9-544c-4a3e-8a2d-bc1c11133a51
Zheludev, Nikolai
32fb6af7-97e4-4d11-bca6-805745e40cc6
Pu, Tanchao
89eb5a37-31bf-469a-ae29-c871d5d25c65
Ou, Jun-Yu
3fb703e3-b222-46d2-b4ee-75f296d9d64d
Papasimakis, Nikitas
f416bfa9-544c-4a3e-8a2d-bc1c11133a51
Zheludev, Nikolai
32fb6af7-97e4-4d11-bca6-805745e40cc6

Pu, Tanchao, Ou, Jun-Yu, Papasimakis, Nikitas and Zheludev, Nikolai (2020) Deeply subwavelength optical imaging. arXiv. (Submitted)

Record type: Article

Abstract

We report the experimental demonstration of deeply subwavelength far-field
optical imaging of unlabelled samples with resolution better than λ/20. We beat the ~λ/2 diffraction limit of conventional optical microscopy several times over by recording the intensity pattern of coherent light scattered from the object into the far-field. We retrieve information about the object with a deep learning neural network trained on scattering events from a large set of known objects.

Text
Deeply Subwavelength Optical Imaging - Accepted Manuscript
Available under License University of Southampton Accepted Manuscript Licence.
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More information

Submitted date: 4 January 2020
Related URLs:
Learn more about Zepler Institute for Photonics and Nanoelectronics research Learn more about Institute for Life Sciences research

Identifiers

Local EPrints ID: 450026
URI: http://eprints.soton.ac.uk/id/eprint/450026
ISSN: 2331-8422
PURE UUID: 6ac3298c-185e-4c39-b6c8-4d3bb6554046
ORCID for Tanchao Pu: ORCID iD orcid.org/0000-0002-1782-5653
ORCID for Jun-Yu Ou: ORCID iD orcid.org/0000-0001-8028-6130
ORCID for Nikitas Papasimakis: ORCID iD orcid.org/0000-0002-6347-6466
ORCID for Nikolai Zheludev: ORCID iD orcid.org/0000-0002-1013-6636

Catalogue record

Date deposited: 06 Jul 2021 16:31
Last modified: 17 Mar 2024 04:07

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Contributors

Author: Tanchao Pu ORCID iD
Author: Jun-Yu Ou ORCID iD
Author: Nikitas Papasimakis ORCID iD
Author: Nikolai Zheludev ORCID iD

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