The University of Southampton
University of Southampton Institutional Repository

Deeply subwavelength topological microscopy

Deeply subwavelength topological microscopy
Deeply subwavelength topological microscopy
We demonstrate experimentally label-free far-field imaging of subwavelength objects at resolution greater than λ/20, exceeding the diffraction limit by an order of magnitude. Our imaging approach, termed Deeply Subwavelength Topological Microscopy (DSTM), is based on the combination of illumination with topological structured illumination and artificial intelligence. In DSTM, the imaging target is placed under topological illumination and multiple far-field scattering patterns are recorded for different positions of the imaging target within the illumination light field (see Fig. 1). The diffraction patterns are analyzed by a neural network trained on a large number of scattering events, which allows to reconstruct the object. DSTM promises unprecedented resolution approaching atomic length scales.
Pu, Tanchao
89eb5a37-31bf-469a-ae29-c871d5d25c65
Ou, Jun-Yu
3fb703e3-b222-46d2-b4ee-75f296d9d64d
Yuan, Guanghui
d7af6f06-7da9-41ef-b7f9-cfe09e55fcaa
Rogers, Edward T.F.
b92cc8ab-0d91-4b2e-b5c7-8a2f490a36a2
Papasimakis, Nikitas
f416bfa9-544c-4a3e-8a2d-bc1c11133a51
Smith, Peter J.S.
003de469-9420-4f12-8f0e-8e8d76d28d6c
Zheludev, Nikolai
32fb6af7-97e4-4d11-bca6-805745e40cc6
Pu, Tanchao
89eb5a37-31bf-469a-ae29-c871d5d25c65
Ou, Jun-Yu
3fb703e3-b222-46d2-b4ee-75f296d9d64d
Yuan, Guanghui
d7af6f06-7da9-41ef-b7f9-cfe09e55fcaa
Rogers, Edward T.F.
b92cc8ab-0d91-4b2e-b5c7-8a2f490a36a2
Papasimakis, Nikitas
f416bfa9-544c-4a3e-8a2d-bc1c11133a51
Smith, Peter J.S.
003de469-9420-4f12-8f0e-8e8d76d28d6c
Zheludev, Nikolai
32fb6af7-97e4-4d11-bca6-805745e40cc6

Pu, Tanchao, Ou, Jun-Yu, Yuan, Guanghui, Rogers, Edward T.F., Papasimakis, Nikitas, Smith, Peter J.S. and Zheludev, Nikolai (2021) Deeply subwavelength topological microscopy. CLEO 2021 Virtual Conference, Virtual, United States. 09 - 14 May 2021. (doi:10.1109/CLEO/Europe-EQEC52157.2021.9592653).

Record type: Conference or Workshop Item (Paper)

Abstract

We demonstrate experimentally label-free far-field imaging of subwavelength objects at resolution greater than λ/20, exceeding the diffraction limit by an order of magnitude. Our imaging approach, termed Deeply Subwavelength Topological Microscopy (DSTM), is based on the combination of illumination with topological structured illumination and artificial intelligence. In DSTM, the imaging target is placed under topological illumination and multiple far-field scattering patterns are recorded for different positions of the imaging target within the illumination light field (see Fig. 1). The diffraction patterns are analyzed by a neural network trained on a large number of scattering events, which allows to reconstruct the object. DSTM promises unprecedented resolution approaching atomic length scales.

Text
Deeply Subwavelength Topological Microscopy - Accepted Manuscript
Restricted to Repository staff only
Request a copy

More information

Published date: 21 June 2021
Venue - Dates: CLEO 2021 Virtual Conference, Virtual, United States, 2021-05-09 - 2021-05-14

Identifiers

Local EPrints ID: 446758
URI: http://eprints.soton.ac.uk/id/eprint/446758
PURE UUID: 3f63ceae-3ad2-4ddc-804a-0178e310805c
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 Peter J.S. Smith: ORCID iD orcid.org/0000-0003-4400-6853
ORCID for Nikolai Zheludev: ORCID iD orcid.org/0000-0002-1013-6636

Catalogue record

Date deposited: 22 Feb 2021 17:30
Last modified: 28 Mar 2024 03:01

Export record

Altmetrics

Contributors

Author: Tanchao Pu ORCID iD
Author: Jun-Yu Ou ORCID iD
Author: Guanghui Yuan
Author: Edward T.F. Rogers

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×